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The most intelligent code that 
you would ever find from a 

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politician is from the Rumsfeld,
right? 

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You have known, knowns known, 
unknowns, and unknown unknowns. 

4
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I mean, it is something that you
can use in any scenario anywhere

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and it would be valued. 
Imagine if your child grew up in

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a Suraj barjatya style 
household, where everything was 

7
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sing song and dance and party, 
the chances that an adverse 

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outcome can completely topple 
the child, the chances increase.

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Your job is not related to your 
stock market rate. 

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You think both of them are 
independent but what we do not 

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know inherently is the 
probability of you getting fired

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increases as your stock market 
portfolio, goes down. 

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If imagine that I'm doing dollar
dollar against rupee dollar 

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against China as an e simpler 
example, right now in current 

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benign environment world, you 
would think that China and India

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slightly. 
Yes. 

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They are Emerging Markets. 
Therefore they are correlated, 

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but they are not Not so 
correlated. 

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That is it slightly, you know, 
it's like a dog and a drunkard 

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with a positive 20 percent 
correlation, right? 

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Hello and welcome to data. 
Shatter the podcast on all 

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things data. 
This podcast is a series of 

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conversations with experts and 
Industry leaders in data. 

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And each week. 
We aim to unpack a different 

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compartment of the Just in case 
I am your host, Karthik chassis 

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that I'm a blogger newspaper, 
columnist book author and a 

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former data and strategy 
consultant at currently head 

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analytics and business 
intelligence for delivery. 

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One of India's largest 
logistics. 

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Companies. 
You can follow me on Twitter at 

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Karthik s that is Kar. 
Thi KS and read my blog had no 

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into da.com. 
That is n 0e. 

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N e, hu d a A.com or opinions 
expressed in his podcast, belong

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to me and my podcast guests. 
And it do not reflect the views 

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of any organizations. 
We might be Associated, nothing 

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discussing this podcast, should 
be taken as Financial or legal 

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advice. 
The fundamental principle, 

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underlying all analytics and 
data science is probability and 

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probability was first invented, 
or should I say, discovered to 

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assess the risk? 
So what is the risk? 

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Can we quantify and measure it? 
How do we handle risk in life? 

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And as risk? 
Always back, today's guest on 

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data chatter is below and see 
that over tea. 

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Whoo. 
Co-founder & Investment advisor 

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at Raleigh Asset Management, a 
global Arbitrage fund balance 

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was my classmate at IIT Madras, 
where he studied computer 

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science, but spent most of his 
time gaming, he then went on to 

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IIM Ahmedabad when he continued 
to game heavily and graduated 

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with a gold medal. 
He now runs a hedge fund but 

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still spends most of his time 
gaming. 

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Moreover, he was one of the last
traders to trade on behalf of 

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Lehman Brothers, on 15th, 
September 2008. 

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Who's Gus, you can. 
Imagine is a vast subject. 

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And so, this is a long podcast. 
We talk about measuring risk 

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problems, with too much 
measurement of risk. 

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How risk can be managed and all 
that. 

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We also talked about movies 
games, the differences between 

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poker and Bridge and physics 
Envy. 

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Enjoy. 
Welcome to data chatter. 

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So I will start with a loaded 
question on 15. 

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September 2008. 
You were working for Lehman 

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Brothers. 
You were probably one of the 

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last people to actually trade on
behalf of Lehman Brothers ever. 

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So what's your definition of 
risk? 

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It's funny. 
I mean, I will talk you over. 

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What actually happened on that 
day on Friday. 

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I remember closing. 
Some traits, in Brazil. 

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I was massively long gamma. 
I have seen bear Stearns fall. 

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I position my books, you know, 
saying that there's going to be 

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a lot of volatility but a Lehman
Brothers is not going to 

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collapse. 
So but the markets will be 

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volatile and as position and on 
Sunday night in New York, I was 

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trading and by the time news was
not over there yet and I was 

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treating my gamma first. 
I trade my positions on the 

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machine, then I had to shout it 
over to, you know, my colleagues

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in Singapore saying that, you 
know, by 10 million euros said, 

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until meaning used to trade the 
gamma then initially, what would

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happen was the machine was 
stopped. 

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Then the trader would take 
immediately. 

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Give me the like they shout back
the price, you know, over that 

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line and it was instantaneous. 
Then it would take about a 

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minute and after that it was 
like three minutes and 5 meters 

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like what's happening. 
And you know and are later is 

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like nobody's taking our name 
and that's when I realized that.

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Okay, it's all over and you 
know, so that's like your first 

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it, you know, real. 
Like you join, you join the 

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company which is like one of 
the, you know, top five in us 

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and you know, consider to be 
next to Goldman Sachs and and in

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the way in the trading mentality
and then one fine day and even 

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like a month before, right? 
You see your comes on the floor 

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saying that we will win we will 
do back and you know, a month 

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later that thing doesn't even 
exist and you are out on the 

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road. 
Look, fine. 

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Trying to find a job, right? 
So nothing better introduction 

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to risk mean. 
In fact, When I joined Lehman in

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2007, right on my first day, 
when I was on the trading floor 

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FX Market, that's when the sub, 
you know, mortgage crisis 

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started and my boss. 
Ed who joined, you know, he was 

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the head of Exotics at that 
point of time. 

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He said you should watch these 
markets. 

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You will never see such kind of 
markets ever again. 

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And you know that I don't know 
whether it was an omen or what, 

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but I have seen worse markets 
over the next 56 years. 

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Okay, so let's talk about risk 
from multiple perspectives here,

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right? 
Having, let's just take your 

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situation on the 15th of 
September 2008. 

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One, your company had collapse 
that you were out of a job. 

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They can is that like that's on 
the personal side, s on the 

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market side. 
I think you have seen a bit of a

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rollercoaster ride over the last
one year and a bit when you were

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there with Lehman and so on and 
so you see the markets do lots 

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of funny things and so on and so
you would have one of the things

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you would have had to do as part
of your job. 

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I guess would have been to sort 
of manage risk in whatever. 

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You can we find it. 
It's all. 

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So maybe we can use this to sort
of talk about what risk means in

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a financial sense, what it means
from a personal life, kind of 

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sensing whether the two are 
related. 

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We should think about them in 
different different ways. 

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You know, it's funny you mention
that because the way we think of

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risk in personal world is very 
different from the way you think

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of risk in financial as well as 
even economic sense, right? 

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I mean, when we think about, do 
you want to take that risk? 

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You normally We mean, is the 
downside worth the upside, 

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right? 
For us in real, in English 

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sense. 
English, you know, risk is 

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always to the downside. 
Everything else is about 

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working. 
You don't talk about taking a 

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00:07:24,700 --> 00:07:26,800
risk, when you're buying a 
lottery, you say that, okay, I 

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will lose one rupee or ten 
rupees and then I'm get a crore,

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right? 
So that's the way to think, but 

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00:07:32,800 --> 00:07:36,200
in economic sense and in 
financial world, it's funny. 

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00:07:36,200 --> 00:07:39,900
But risk is essentially any 
deviation from your mean. 

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Whether it's positive, I mean, 
you had an expected outcome of 

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00:07:45,200 --> 00:07:48,700
X. 
The actual outcome is X Plus 1% 

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or x. 
Minus one percent. 

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Both of them are risks and be 
the whole object to being that. 

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You want to narrow the range of 
outcomes, the way the banks or 

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00:07:59,200 --> 00:08:02,000
you know, any person. 
So you want to reach a situation

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where the risk reduction is 
nothing but reducing the scope 

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00:08:06,200 --> 00:08:08,900
of outcomes or narrowing the 
range in which the outcomes can 

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00:08:08,900 --> 00:08:10,700
happen. 
Right. 

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00:08:10,900 --> 00:08:14,200
So that's I think is the 
fundamental difference between 

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00:08:14,400 --> 00:08:17,600
the way we think of risk in the 
normal World versus the way you 

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00:08:17,600 --> 00:08:19,200
think of risk in the financial 
world. 

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00:08:21,400 --> 00:08:24,900
So in in real life, let's say, 
for example, you getting a big 

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00:08:24,900 --> 00:08:28,900
bonus is not a risk, but from 
the bank's perspective, the 

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00:08:28,900 --> 00:08:31,800
likelihood that there's some 
small probability, where you can

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00:08:32,000 --> 00:08:34,900
get significantly more revenues,
for whatever reason. 

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That's a risk, which in some 
sense. 

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00:08:36,600 --> 00:08:39,900
You might be right. 
Yes, you might want. 

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Write your book, you would want 
to, you would want to trade off 

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that small probability of 
getting a bumper profit. 

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00:08:46,700 --> 00:08:50,300
And for let's say, more assured 
smaller number, right? 

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So, that is a risk in some 
sense. 

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00:08:51,700 --> 00:08:53,700
A casino is taking the opposite 
side. 

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00:08:53,900 --> 00:08:58,300
Where you might have to pay out 
a lot of money for one guy, but 

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you are getting in a lot from 
smaller Nichols. 

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00:09:00,800 --> 00:09:02,700
You're picking Nichols from 
everyone. 

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Yeah. 
Okay. 

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Okay. 
So from this perspective, right?

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I mean like I remember reading 
this tweet sometime last week. 

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00:09:10,000 --> 00:09:11,300
I probably sent it to you as 
well. 

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00:09:11,500 --> 00:09:14,900
I think it said that like the 
risk once created can never be 

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destroyed, it can either be 
transferred to somebody else or 

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00:09:18,700 --> 00:09:23,100
it can be managed or it can be 
ridden out at the I'll probably 

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link to that. 
We to the show notes. 

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So can you talk about the 
creation and destruction of 

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risk? 
Is it something like entropy in 

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a sort of thermodynamic sense? 
You know, it's funny that you 

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mention that and I mean not many
people are going to like it when

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I say this, but the whole field 
of finance and economics suffers

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from physics Envy. 
It is a great desire to 

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associate certain principles and
ethics to, you know, the way you

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want that method and Madness, 
like the whole scientific 

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development which happened in 
18th and 19th and early 20th 

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centuries. 
And you had this physics laws 

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00:10:02,500 --> 00:10:05,800
and mats and principles. 
And, you know, the Boyle's law 

179
00:10:05,800 --> 00:10:08,200
is ranging from Newtonian 
mechanics to boys laws and 

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00:10:08,200 --> 00:10:10,700
everything. 
It was some method to that 

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00:10:10,700 --> 00:10:15,800
so-called Madness and we desire 
and economics as Acted and, you 

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00:10:15,800 --> 00:10:19,500
know, ranging from Samson's and 
you know, 1920s and you know, 

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00:10:19,500 --> 00:10:22,000
when you have the micro economic
demand Supply graphs to 

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everything. 
And coming back to your 

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00:10:26,700 --> 00:10:28,800
statement. 
That is actually, I don't think 

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it is true. 
I mean, I remember reading that 

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00:10:30,500 --> 00:10:32,100
and you know, I had a counter to
it. 

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00:10:32,500 --> 00:10:37,600
I lend money to SK, right? 
I have created the risk. 

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00:10:39,000 --> 00:10:41,500
Mauro if s case gives me back 
that money, that risk is 

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00:10:41,500 --> 00:10:43,700
destroyed. 
Right? 

191
00:10:44,200 --> 00:10:47,400
So that it is not like once 
created. 

192
00:10:47,400 --> 00:10:49,400
It can't be destroyed. 
In fact, if you want to look at 

193
00:10:49,400 --> 00:10:52,100
energy, energy is neither 
created nor destroyed. 

194
00:10:52,100 --> 00:10:55,600
You had hold the Big Bang thing 
from energy to Mars and back to 

195
00:10:55,600 --> 00:10:57,400
energy. 
It's like a closed ecosystem, 

196
00:10:58,100 --> 00:11:00,600
right? 
The other thing I should tell 

197
00:11:00,600 --> 00:11:02,000
you, right? 
This is actually Lehman, 

198
00:11:02,000 --> 00:11:05,500
Brothers is a phenomenal example
of what risk. 

199
00:11:05,500 --> 00:11:09,500
He's because, you know, on the 
Monday morning, when I went to 

200
00:11:09,500 --> 00:11:12,200
the office and for one month, I 
just went to the office. 

201
00:11:13,100 --> 00:11:15,300
No Scouting For What is going to
happen? 

202
00:11:15,300 --> 00:11:18,200
We didn't know searching for 
jobs, but we were watching the 

203
00:11:18,200 --> 00:11:21,600
markets but we had nothing to do
and I was very happy that it 

204
00:11:21,600 --> 00:11:27,400
happened because on the other 
side on the weekends at Barclays

205
00:11:27,400 --> 00:11:29,800
and I know people because we 
spoke to dimmit, you know, and 

206
00:11:29,800 --> 00:11:32,400
Credit Suisse and Barclays. 
They were worried because they 

207
00:11:32,400 --> 00:11:34,600
had no clue what to do with 
their positions, with Lehman. 

208
00:11:35,700 --> 00:11:39,300
Right, my risk was done. 
Right job loss and everything, 

209
00:11:39,300 --> 00:11:41,400
but I knew the outcome and it is
done. 

210
00:11:41,400 --> 00:11:45,100
Risk got eliminated outcome has 
happened for those guys. 

211
00:11:45,100 --> 00:11:48,900
They didn't know our dick 
positions long, if they are sold

212
00:11:48,900 --> 00:11:52,200
and options, but they still 
short, or since Lehman got 

213
00:11:52,200 --> 00:11:55,000
eliminated, were they did 
positions vanish and suddenly 

214
00:11:55,000 --> 00:11:58,100
they became long optionality, 
you know, nobody had a clue. 

215
00:11:59,100 --> 00:12:02,500
Right? 
And one of the most I would call

216
00:12:02,500 --> 00:12:05,700
it is like a back-end 
operational Innovation, right? 

217
00:12:05,800 --> 00:12:08,900
Imagine. 
You had three Banks, a b, and c 

218
00:12:09,300 --> 00:12:12,300
and you know that Banks do 
derivatives amongst themselves, 

219
00:12:12,300 --> 00:12:14,900
right? 
And a derivative with b.b. 

220
00:12:15,200 --> 00:12:17,500
Derivative at C and C did with 
a. 

221
00:12:17,800 --> 00:12:21,600
Now effectively, you had three 
units of derivative exposure. 

222
00:12:22,000 --> 00:12:24,100
And for some reason bow, all of 
them off. 

223
00:12:24,100 --> 00:12:27,000
So, let's say a soul to be, be 
sold to sea and sea salt. 

224
00:12:27,000 --> 00:12:30,000
A now. 
There's technically, you know 3 

225
00:12:30,000 --> 00:12:34,900
into 2 6 units on banks balance 
sheets, right now, which also 

226
00:12:34,900 --> 00:12:37,100
means that you have to post, 
mark to Market and all those 

227
00:12:37,100 --> 00:12:39,400
things. 
What banks did is because they 

228
00:12:39,400 --> 00:12:42,900
were worried about this Lehman 
thing, take the inventory, says,

229
00:12:43,000 --> 00:12:45,500
there was a system. 
I mean, we're all the banks 

230
00:12:45,500 --> 00:12:48,400
would post their positions, 
anonymously to have a central 

231
00:12:48,400 --> 00:12:51,400
portal, and the portal would 
basically, then try to endure. 

232
00:12:51,800 --> 00:12:53,700
It will also post their 
valuations for it. 

233
00:12:54,200 --> 00:12:56,100
Right? 
You think it is worth X and some

234
00:12:56,100 --> 00:12:57,400
other bank thinks it's worth. 
Why? 

235
00:12:57,600 --> 00:13:00,600
Right if X is less than y. 
Then you can net off. 

236
00:13:02,100 --> 00:13:04,100
Right, but imagine it is not. 
Then you can. 

237
00:13:04,200 --> 00:13:07,600
So they would basically in men 
do and try to reduce this 

238
00:13:07,600 --> 00:13:12,100
counterparty risk, right? 
It was, it was not their pre, 

239
00:13:12,400 --> 00:13:14,600
you know, or rather. 
It was not into a big way. 

240
00:13:14,600 --> 00:13:18,200
This kind of a reducing your 
risk by sending it to Anonymous 

241
00:13:18,200 --> 00:13:20,600
portals and this thing and some 
banks actually did that very, 

242
00:13:20,600 --> 00:13:22,100
well. 
They actually did funding 

243
00:13:22,100 --> 00:13:26,400
arbitrageurs and all those 
things, you know quite well, but

244
00:13:26,400 --> 00:13:30,200
the point is that was one kind 
of a risk reduction, right risk 

245
00:13:30,200 --> 00:13:33,000
was there one day before? 
This didn't exist the next day. 

246
00:13:33,100 --> 00:13:37,200
So, in that sense, know, I kind 
of disagree with the point that 

247
00:13:37,200 --> 00:13:40,600
risk can neither be created nor 
destroyed, but it is true that 

248
00:13:40,608 --> 00:13:44,400
while alive, and there is no, 
there is always a event which 

249
00:13:44,400 --> 00:13:47,400
might destroy it. 
But while it is alive, you 

250
00:13:47,400 --> 00:13:50,000
cannot, you know, there is 
limited formats. 

251
00:13:50,000 --> 00:13:51,700
You can only more fit and create
it. 

252
00:13:51,700 --> 00:13:55,300
So the usual entropy principals 
who apply as long as it is 

253
00:13:55,300 --> 00:13:58,300
alive. 
Yeah, I think what you mentioned

254
00:13:58,300 --> 00:14:00,800
about economics and finance 
having physics. 

255
00:14:00,800 --> 00:14:02,000
Envy. 
I mean, the first thing I I was 

256
00:14:02,000 --> 00:14:05,200
thinking of was about how pretty
much all of our quantitative 

257
00:14:05,200 --> 00:14:08,600
Finance is it it's based on 
something like a heat equation, 

258
00:14:08,600 --> 00:14:11,900
right? 
It's live in its they try to 

259
00:14:12,000 --> 00:14:15,400
escape physics Concepts in 
pretty much every way possible 

260
00:14:15,700 --> 00:14:17,700
among the other things. 
Do you mean the wonderful thing 

261
00:14:17,700 --> 00:14:20,300
about statistical mechanics? 
If you think of it is that the 

262
00:14:20,300 --> 00:14:24,700
movement of gas is it sort of 
follow it, always not sort of it

263
00:14:24,700 --> 00:14:28,900
follows a normal distribution. 
A lot of physical phenomena, if 

264
00:14:28,900 --> 00:14:32,700
you look at the distribution, 
it's always normal normal as it 

265
00:14:32,700 --> 00:14:38,600
that bell curve distribution. 
What what that does to us, not 

266
00:14:38,600 --> 00:14:41,400
just in finance or economics, 
but all of us in real life is 

267
00:14:41,400 --> 00:14:43,600
that we assume that everything 
in life is normal. 

268
00:14:44,100 --> 00:14:47,000
So, one of my favorite things is
that, like, people think that 

269
00:14:47,000 --> 00:14:50,000
there exists this thing called a
middle class because they think 

270
00:14:50,000 --> 00:14:52,900
wealth is normally distributed. 
And so that everybody in the 

271
00:14:52,900 --> 00:14:56,500
middle is, is the middle class, 
and then you have the Waiting 

272
00:14:56,500 --> 00:14:58,000
for the rich in the lower tail 
for the poor. 

273
00:14:58,200 --> 00:15:01,000
But if you look at any data you 
want that, like, for example, 

274
00:15:01,000 --> 00:15:05,200
wealth is not distributed 
normally or if you or even like 

275
00:15:05,200 --> 00:15:07,900
sort of payoffs from different 
events are not distributed. 

276
00:15:07,900 --> 00:15:11,300
Normally, even though we try to 
sort of suggest pretend that 

277
00:15:11,300 --> 00:15:13,600
they are normal. 
So can you talk about this, 

278
00:15:13,800 --> 00:15:18,100
think of, like, why is it that, 
like, we sort of always think of

279
00:15:18,100 --> 00:15:21,100
things are being normal and 
like, how do you deal with? 

280
00:15:21,700 --> 00:15:24,200
How do you deal with long tailed
distributions in terms of risk, 

281
00:15:24,200 --> 00:15:26,100
and like who are, which is 
risky? 

282
00:15:26,300 --> 00:15:29,900
And how and what are the sort of
some of the mistakes that people

283
00:15:29,900 --> 00:15:33,000
do in terms of assessing 
outcomes? 

284
00:15:33,900 --> 00:15:37,500
Surely that is very interesting 
question in the sense that 

285
00:15:40,100 --> 00:15:44,300
because as humans, I mean we 
came from a long evolutionary 

286
00:15:44,300 --> 00:15:46,800
process, which is Primal right 
at the end. 

287
00:15:46,800 --> 00:15:52,100
We are all monkeys, right? 
So and all nature, as you 

288
00:15:52,100 --> 00:15:56,600
pointed out whether it is near 
normal or normal, I mean, Most 

289
00:15:56,600 --> 00:15:58,500
of the distributions, follow the
bell curve, right? 

290
00:15:58,500 --> 00:16:02,700
Whether it is hides or you know,
and so on and so forth. 

291
00:16:03,900 --> 00:16:11,900
So and secondly, what happens 
is, survival wise, you know, you

292
00:16:11,900 --> 00:16:15,700
prepare for the more you prepare
for the mean, right? 

293
00:16:16,100 --> 00:16:19,300
You don't necessarily prepare 
for the tail and which is why 

294
00:16:19,300 --> 00:16:22,700
human civilizations have, you 
know, you have those Cycles, 

295
00:16:22,900 --> 00:16:25,500
they are big, they grow, then 
they get wiped out because 

296
00:16:25,500 --> 00:16:29,400
you're, you don't Normally, you 
expect things to be status quo, 

297
00:16:29,600 --> 00:16:31,900
right? 
In in mathematical principles. 

298
00:16:31,900 --> 00:16:33,300
You think everything is a 
Martingale? 

299
00:16:34,600 --> 00:16:37,200
Yeah, can you explain articles 
for our business? 

300
00:16:37,200 --> 00:16:38,500
Sorry, not everybody can. 
Yeah. 

301
00:16:38,500 --> 00:16:42,100
So Martingale is a funny 
mathematical process. 

302
00:16:42,100 --> 00:16:48,000
Where the expectation is that 
for your future is you will be 

303
00:16:48,000 --> 00:16:51,500
what you are right now, right? 
Expectation of X in any time in 

304
00:16:51,500 --> 00:16:54,500
future is equal to X of 0 which 
is current time. 

305
00:16:54,800 --> 00:16:57,700
Right? 
It means that and it also is one

306
00:16:57,700 --> 00:17:00,400
of the reasons why you have 
inequalities and all these 

307
00:17:00,400 --> 00:17:03,300
things. 
It's goes very nicely and feeds 

308
00:17:03,300 --> 00:17:06,000
into the situation. 
Because if somebody gets lucky 

309
00:17:06,000 --> 00:17:10,099
and has done, well, it is likely
that that person will remain, 

310
00:17:10,400 --> 00:17:12,700
you know, will continue to stay.
Well, in fact, a certain amount 

311
00:17:12,700 --> 00:17:15,099
of autocorrelation. 
But at least what it means is 

312
00:17:15,099 --> 00:17:18,099
that people who have got lucky, 
right? 

313
00:17:18,500 --> 00:17:21,200
That luck stays with them. 
It doesn't get normalized. 

314
00:17:21,500 --> 00:17:23,900
Right? 
Whereas, overall, you kinda 

315
00:17:23,900 --> 00:17:25,500
expect that things should get 
normalized. 

316
00:17:25,500 --> 00:17:28,400
It doesn't right. 
So this is where that jump from 

317
00:17:28,700 --> 00:17:32,700
the moving from a typical normal
distribution, where we think we 

318
00:17:32,700 --> 00:17:35,900
are in a bell curve to Somewhere
where you are, moving into a 

319
00:17:35,908 --> 00:17:40,500
Martingale, where expectation of
X is a future X is now to you 

320
00:17:40,500 --> 00:17:41,900
have these long tail 
distribution. 

321
00:17:41,900 --> 00:17:47,000
So, where the whole translation 
comes is the more fictitious the

322
00:17:47,000 --> 00:17:50,300
world is away from the nature 
where it's not exogenous 

323
00:17:50,300 --> 00:17:52,200
variables, but it's an 
endogenous variables. 

324
00:17:52,200 --> 00:17:54,400
Right? 
Like I created economics because

325
00:17:54,400 --> 00:17:58,300
humans created a whole bunch of 
laws Way by which we created 

326
00:17:58,300 --> 00:18:01,100
ecosystem, under which we are 
all talking to each other, 

327
00:18:01,100 --> 00:18:04,300
exchanging goods and services 
and all these things right now. 

328
00:18:04,400 --> 00:18:07,800
That creates the phenomena, 
which moves have, it's not 

329
00:18:07,800 --> 00:18:10,700
normal, right? 
There are network effects. 

330
00:18:10,900 --> 00:18:14,200
There are, you know, one thing 
leads to the other, like there 

331
00:18:14,200 --> 00:18:16,700
is a super star in a movie or a 
pop singer. 

332
00:18:16,700 --> 00:18:19,900
Who becomes popular popular 
bream brings in more popularity,

333
00:18:19,900 --> 00:18:22,400
right? 
We know that it's equivalent to 

334
00:18:22,400 --> 00:18:26,900
your old saying, Rolling Stone 
gathers, Mass, kind of a thing. 

335
00:18:28,500 --> 00:18:29,800
Yet. 
I know I said it the other way 

336
00:18:29,800 --> 00:18:34,500
around but the plot makes its 
each other there, the Bible, I 

337
00:18:34,508 --> 00:18:37,800
think that like and also like in
a popular Govinda song. 

338
00:18:37,800 --> 00:18:40,600
I think we're like, if you have 
a lot, you will get more, but if

339
00:18:40,608 --> 00:18:42,400
you don't have anything like, 
you don't get much. 

340
00:18:42,500 --> 00:18:47,600
So, exactly, right. 
So a lot in the ecosystem is 

341
00:18:48,000 --> 00:18:51,100
normalcy happens. 
When there is what you call 

342
00:18:51,300 --> 00:18:53,700
Independent identical 
distribution, right? 

343
00:18:54,000 --> 00:18:56,900
So the future event has to be 
independent of the current 

344
00:18:56,900 --> 00:18:59,000
event. 
Then obviously, You will have 

345
00:18:59,400 --> 00:19:01,600
that, normal distribution is 
coming it. 

346
00:19:01,800 --> 00:19:07,200
But most of these things are, 
you know, it is like what it 

347
00:19:07,200 --> 00:19:10,400
like you're going in the song, 
just go, it's a multiplicative 

348
00:19:10,400 --> 00:19:11,500
effect. 
Right? 

349
00:19:11,700 --> 00:19:14,500
So, people who are rich will get
richer. 

350
00:19:14,600 --> 00:19:17,800
Even if they returns like, 
somebody who has one crore and 

351
00:19:17,800 --> 00:19:21,100
somebody who has let's say 1 
lakh even if the one black guy 

352
00:19:21,100 --> 00:19:24,200
generated hundred percent return
at the end of it, his net worth 

353
00:19:24,200 --> 00:19:26,600
is 2 lakhs. 
And even if the one crore by 

354
00:19:26,600 --> 00:19:30,000
generated, Return. 
It is, file acts. 

355
00:19:30,100 --> 00:19:33,100
The Gap has only widened. 
It did not shrink, right? 

356
00:19:33,100 --> 00:19:37,700
So it is this for, so in 
general, in life in finance is 

357
00:19:37,700 --> 00:19:39,700
obviously slightly different, 
which you can talk later. 

358
00:19:40,000 --> 00:19:44,800
But there is deviation from your
normal distribution because of 

359
00:19:44,800 --> 00:19:48,200
these Auto correlative effects 
because of this endowment 

360
00:19:48,200 --> 00:19:52,000
affects all these things will 
come into picture and then you 

361
00:19:52,000 --> 00:19:55,200
have your typical Network 
effects, which come in, right? 

362
00:19:55,200 --> 00:19:58,200
Your YouTube the popular guys 
will remain in fact, technology.

363
00:19:58,200 --> 00:20:00,300
Elegy. 
If anything is only accentuating

364
00:20:00,300 --> 00:20:02,700
this thing. 
So what it ends up is, you have 

365
00:20:02,700 --> 00:20:06,000
lots of these tail 
distributions, right? 

366
00:20:06,300 --> 00:20:08,200
And in finance, that is also 
true. 

367
00:20:08,400 --> 00:20:11,900
Because what happens is, Imagine
today, stock market is there, 

368
00:20:11,900 --> 00:20:14,600
right? 
Stock market moves down 3% or 

369
00:20:14,600 --> 00:20:19,500
5%, people will not panic, but 
it goes down to 20%, people will

370
00:20:19,500 --> 00:20:21,300
panic. 
And that Panic itself creates 

371
00:20:21,300 --> 00:20:22,800
further Panic. 
Yes. 

372
00:20:23,000 --> 00:20:25,500
Yes, right. 
So there is an acceleration 

373
00:20:25,500 --> 00:20:27,700
effect, which happens Beyond a 
certain threshold. 

374
00:20:28,200 --> 00:20:32,700
Right. 
A, you know, in your olden day 

375
00:20:32,700 --> 00:20:34,900
in physics when we were younger 
and we studied, we had this 

376
00:20:35,200 --> 00:20:38,000
pendulum swing where pendulum is
pulled to the center. 

377
00:20:38,200 --> 00:20:41,500
But imagine that there is a 
pair, a pendulum where it goes 

378
00:20:41,500 --> 00:20:45,000
to an extreme, but that itself 
pushes it further before it 

379
00:20:45,000 --> 00:20:46,200
comes back. 
Yeah. 

380
00:20:46,200 --> 00:20:48,900
I mean, you can actually imagine
that railing sort of like the 

381
00:20:48,900 --> 00:20:52,200
Rope, kind of bending because of
the momentum of the pendulum or 

382
00:20:52,200 --> 00:20:57,100
something great, which should 
opinion, cancer physics book. 

383
00:20:57,200 --> 00:21:01,700
So So that is what creates these
long tails, right? 

384
00:21:01,700 --> 00:21:04,200
I mean whether, you know, and we
have many distributions which 

385
00:21:04,200 --> 00:21:05,900
talked about it, right? 
Ranging from you know, 

386
00:21:05,900 --> 00:21:09,100
exponential's to poisons do all 
sorts of things, which talked 

387
00:21:09,100 --> 00:21:11,500
about this. 
And in fact, one of the first 

388
00:21:11,500 --> 00:21:15,200
things that even when in finance
you have options when they were 

389
00:21:15,200 --> 00:21:18,100
priced, they all assumed or 
normal distribution Brownian 

390
00:21:18,100 --> 00:21:20,500
motion. 
And then you realize that, okay,

391
00:21:20,700 --> 00:21:24,300
if I do it that way, things 
don't work, but you don't adjust

392
00:21:24,300 --> 00:21:27,100
your model. 
What you do is you introduce, 

393
00:21:27,700 --> 00:21:30,000
you know. 
No, workarounds to say that, you

394
00:21:30,000 --> 00:21:33,000
know, that model is becomes 
stops, being a model and starts 

395
00:21:33,000 --> 00:21:36,700
becoming a language, right? 
And then you have in volatility 

396
00:21:36,700 --> 00:21:40,000
the Tails and uh details details
are always more expensive than 

397
00:21:40,300 --> 00:21:42,500
you know, the volatility of the 
Tails is higher. 

398
00:21:42,500 --> 00:21:47,200
So all those things come into 
place and you know, and in the 

399
00:21:47,208 --> 00:21:51,300
true, we all would like to have 
like in general why do people 

400
00:21:51,300 --> 00:21:54,800
now like startups? 
Right startup is nothing but a 

401
00:21:54,800 --> 00:21:58,600
long-tailed outcome where you 
know, you suddenly have Fact, 

402
00:21:58,600 --> 00:22:01,600
even in coming back in finance. 
Like, on one side. 

403
00:22:01,600 --> 00:22:04,200
You have a hedge funds where 
they are trying to make a steady

404
00:22:04,200 --> 00:22:07,000
set of returns, right? 
So what they want is they want a

405
00:22:07,008 --> 00:22:10,500
narrower range of outcomes on a 
consistent basis and they 

406
00:22:10,500 --> 00:22:13,800
believe that that compounding 
will carry on forward in 

407
00:22:13,800 --> 00:22:16,500
contrast. 
If you look at VCS, all they are

408
00:22:16,500 --> 00:22:18,500
doing is that they are betting 
on long tails. 

409
00:22:19,500 --> 00:22:22,600
Right, they will bet on 10 
companies and say that. 

410
00:22:22,700 --> 00:22:26,800
Okay, if one of them works and 
that generates 10x or 20x, 

411
00:22:26,900 --> 00:22:29,800
that's good enough. 
Yeah, actually, I was just 

412
00:22:29,800 --> 00:22:31,700
thinking about it while you're 
explaining now, if you think 

413
00:22:31,700 --> 00:22:36,000
about it in real life, most 
risks are sort of like highly 

414
00:22:36,000 --> 00:22:38,100
skewed risks. 
So for example, there is this 

415
00:22:38,100 --> 00:22:41,100
risk that like, you are driving 
from place a to place B. 

416
00:22:41,100 --> 00:22:44,200
There is a risk that you might 
meet with an accident or there 

417
00:22:44,200 --> 00:22:47,300
is a risk. 
There is a risk that whatever 

418
00:22:47,300 --> 00:22:49,200
happens like there's an 
earthquake at your house. 

419
00:22:49,400 --> 00:22:50,500
Abscess, and you lose your 
house. 

420
00:22:50,700 --> 00:22:53,500
It's always like, sort of the, 
and none of them. 

421
00:22:53,600 --> 00:22:57,200
And in some sense, a lot of 
Life, which and life itself. 

422
00:22:57,200 --> 00:23:01,000
Like you have one life, which 
means that, that, that is like 

423
00:23:01,000 --> 00:23:03,100
sort of fundamentally alleged, 
right? 

424
00:23:03,300 --> 00:23:06,900
So, this is really an issue. 
And also, on the, on the upside,

425
00:23:06,900 --> 00:23:09,700
on the upside, you in a, let's 
say, you start a company. 

426
00:23:10,000 --> 00:23:15,100
That's a, that's a sort of a 
right-tailed, kind of a risk in 

427
00:23:15,100 --> 00:23:16,900
a sense. 
Because like, in the worst case,

428
00:23:16,900 --> 00:23:20,600
you lose what you put in, in the
best case you Make a lot more, 

429
00:23:20,900 --> 00:23:23,000
right? 
So so I think, like, in that 

430
00:23:23,000 --> 00:23:24,500
sense. 
I think the real life 

431
00:23:24,600 --> 00:23:25,200
everywhere. 
You. 

432
00:23:25,200 --> 00:23:30,400
Look, you think you, you look at
all these sort of, it's all long

433
00:23:30,400 --> 00:23:32,400
tail. 
It's all tail risks on either 

434
00:23:32,400 --> 00:23:36,100
side of the tail and that makes 
it fundamentally different from 

435
00:23:36,100 --> 00:23:39,900
Finance where they still is 
exists, but small compared to 

436
00:23:39,900 --> 00:23:44,000
the volatility or standard 
deviation as you call it there. 

437
00:23:44,400 --> 00:23:48,000
And before we Sorry before we go
ahead, I think like a we have 

438
00:23:48,100 --> 00:23:52,600
sort of Digital ahead and so on 
the from so we can we sort of 

439
00:23:52,600 --> 00:23:55,900
like stopped for a little bit 
and they say talk about things 

440
00:23:55,900 --> 00:23:58,400
like tail risk, right? 
A left tail. 

441
00:23:58,600 --> 00:24:01,800
What is volatility? 
What is uncertainty and so on 

442
00:24:01,800 --> 00:24:04,400
and then we can sort of come 
back to come back to this. 

443
00:24:05,700 --> 00:24:09,800
Don't see mean. 
Let me segue into that your 

444
00:24:09,800 --> 00:24:11,600
question that you asked and 
start in this thing, right? 

445
00:24:11,600 --> 00:24:16,000
So, starting with it, is mean 
the most intelligent code that 

446
00:24:16,000 --> 00:24:19,000
you would ever find from a 
politician is from the Rumsfeld,

447
00:24:19,000 --> 00:24:21,800
right? 
You have known, knowns known, 

448
00:24:21,800 --> 00:24:25,100
unknowns, and unknown unknowns. 
I mean, it is something that you

449
00:24:25,100 --> 00:24:31,200
can use in any scenario anywhere
and it would be valued and it is

450
00:24:31,600 --> 00:24:35,300
to understand risk in some 
sense, you know, disrespect. 

451
00:24:35,500 --> 00:24:39,000
Like no knowns will be something
like tomorrow. 

452
00:24:39,600 --> 00:24:41,700
Sun will rise from the East. 
It's a known. 

453
00:24:42,200 --> 00:24:43,900
Nothing is going to change it, 
right? 

454
00:24:43,900 --> 00:24:47,700
Mnsure few billion years later 
that might not, but it's a known

455
00:24:47,700 --> 00:24:51,900
known for is, you know, right. 
A Known Unknown will be that. 

456
00:24:52,200 --> 00:24:54,500
I'm going to go. 
I have to go to my office 

457
00:24:54,500 --> 00:24:58,900
tomorrow, but I don't know 
whether I will reach safely or 

458
00:24:58,900 --> 00:25:01,400
whether I come back right? 
There is a probability right? 

459
00:25:01,400 --> 00:25:04,600
There is a it is an adverse 
outcome can be there or 

460
00:25:04,600 --> 00:25:07,800
something or Or I'm going to a 
casino and I'm playing 

461
00:25:07,800 --> 00:25:10,200
blackjack, right? 
There's a probability of me 

462
00:25:10,200 --> 00:25:12,300
winning or, you know, crafts, 
whichever way it is. 

463
00:25:12,900 --> 00:25:15,500
And then you have things like 
unknown unknown, right? 

464
00:25:15,500 --> 00:25:18,400
Which is what you would call as 
uncertainty. 

465
00:25:18,400 --> 00:25:20,400
So to speak. 
And the reason why you have 

466
00:25:20,400 --> 00:25:22,300
clubbed it as there, as you 
didn't even know that this 

467
00:25:22,300 --> 00:25:25,200
thing. 
I mean, for example, for all of 

468
00:25:25,200 --> 00:25:30,400
us we can say that Source, 
covid-19 unknown unknown right 

469
00:25:30,400 --> 00:25:32,100
now. 
It has become. 

470
00:25:32,100 --> 00:25:35,000
In fact, if anything this kind 
of tells you that all these 

471
00:25:35,000 --> 00:25:37,700
things are Spectrum's. 
Right there is really no 

472
00:25:37,700 --> 00:25:41,500
watertight compartments. 
Covid-19 Known Unknown to all of

473
00:25:41,500 --> 00:25:44,800
us except where, you know, 
except maybe a few people who 

474
00:25:44,800 --> 00:25:49,100
wrote books on pandemics or who 
are doing research on it. 

475
00:25:49,100 --> 00:25:51,700
And so on. 
Similarly financial crisis was 

476
00:25:51,700 --> 00:25:54,900
an unknown unknown. 
For most normal people accepting

477
00:25:54,900 --> 00:25:57,300
to a few people in finance who 
actually watched it. 

478
00:25:57,600 --> 00:25:59,700
So here you can again, see the 
distinction, right? 

479
00:25:59,700 --> 00:26:05,200
So what is risk to one is in 
some sense and uncertain thing, 

480
00:26:05,200 --> 00:26:08,000
too. 
The other, let me stop you 

481
00:26:08,000 --> 00:26:10,200
there. 
You said, what is risk to one? 

482
00:26:10,200 --> 00:26:13,300
Is uncertain two together. 
So, what is the weather? 

483
00:26:13,400 --> 00:26:15,300
Where are you drawing? 
The line between the risk and 

484
00:26:15,300 --> 00:26:17,000
uncertain, or is it a spectrum? 
Again? 

485
00:26:17,800 --> 00:26:21,000
It is a spectrum, but very 
crudely speaking unknown 

486
00:26:21,000 --> 00:26:24,300
unknowns so something which is 
unmeasurable. 

487
00:26:25,600 --> 00:26:31,200
Eight and, and, you know, or 
even not even known. 

488
00:26:31,400 --> 00:26:33,500
Because if you don't know about 
it, you can't even measure it, 

489
00:26:33,900 --> 00:26:36,200
right. 
They follow in, you know, 

490
00:26:36,200 --> 00:26:40,800
uncertain area risk, broadly 
speaks about things that you 

491
00:26:40,800 --> 00:26:45,400
have some ideas, some estimate 
and let again taking the 

492
00:26:45,400 --> 00:26:49,300
example, in December 2000. 
Not December. 

493
00:26:49,300 --> 00:26:55,400
I should say in September 2019. 
Source covid-19 unknown unknown 

494
00:26:55,400 --> 00:27:01,200
for me by December 2019. 
It started moving for me from 

495
00:27:01,200 --> 00:27:05,500
being an unknown unknown to a, 
you know, Known Unknown. 

496
00:27:05,500 --> 00:27:08,800
Like I knew of it, I was 
position for it in January. 

497
00:27:08,800 --> 00:27:12,300
I mean for in on a personal 
level like I started buying the 

498
00:27:12,300 --> 00:27:17,000
sanitizers and Claude Claude 
masks and 95 in January right on

499
00:27:17,000 --> 00:27:20,200
my portfolio in my fund. 
I was positioned saying that, 

500
00:27:20,200 --> 00:27:22,800
okay things are going to be 
blowing up this Thing. 

501
00:27:22,800 --> 00:27:24,700
Because that's when you saw a 
China numbers. 

502
00:27:24,700 --> 00:27:26,800
And, you know, I was, we were 
tracking that on a daily basis 

503
00:27:27,100 --> 00:27:29,300
and it is there. 
But for still most people, it 

504
00:27:29,300 --> 00:27:33,300
was not. 
Yeah, so I mean, I remember, I 

505
00:27:33,300 --> 00:27:35,800
read my first orders and I spoke
to people around. 

506
00:27:35,800 --> 00:27:38,300
I told the family and they were,
like, what crazy thing are you 

507
00:27:38,300 --> 00:27:41,200
talking about? 
Right. 

508
00:27:41,200 --> 00:27:44,400
And by March, obviously 
everybody knew about it, started

509
00:27:44,400 --> 00:27:48,200
impacting our lives and so on. 
So the obviously what I mean is 

510
00:27:48,200 --> 00:27:51,900
I'm trying to draw the line at 
unknown and unmeasurable stuff. 

511
00:27:52,600 --> 00:27:54,600
And that is where I would call 
as uncertainty. 

512
00:27:54,600 --> 00:27:57,100
Because even if you knew about 
it, what the hell, what on Earth

513
00:27:57,100 --> 00:28:00,200
would you do? 
Write it somewhere, it becomes 

514
00:28:00,200 --> 00:28:02,700
measurable where you can take 
actions? 

515
00:28:05,100 --> 00:28:06,900
And it, and it, then it becomes 
risk. 

516
00:28:07,000 --> 00:28:09,200
I mean, to be honest. 
I will be very honest with you, 

517
00:28:09,300 --> 00:28:12,100
but it is risk and uncertainty 
and these things are 

518
00:28:12,100 --> 00:28:15,400
terminologies, like God, you 
know, that elephant in the blind

519
00:28:15,400 --> 00:28:17,200
man story, when things are 
different. 

520
00:28:17,200 --> 00:28:18,800
It's the same thing, but 
different things to different 

521
00:28:18,800 --> 00:28:21,800
people, right, but I'm just 
giving you my perspective of how

522
00:28:21,800 --> 00:28:23,600
I look at it. 
Yeah. 

523
00:28:24,100 --> 00:28:27,800
Okay. 
So you would so that brings us 

524
00:28:27,800 --> 00:28:30,600
to like you were like when you 
can measure something. 

525
00:28:30,600 --> 00:28:33,700
You said you can do something 
about risk and when you Talking 

526
00:28:33,700 --> 00:28:34,900
about doing something about 
risk. 

527
00:28:34,900 --> 00:28:37,900
I think we'll, we can now talk 
about this concept that we know 

528
00:28:37,900 --> 00:28:42,000
as hedging, which is sort of, 
like, sort of, I don't know if 

529
00:28:42,000 --> 00:28:43,500
you were to call it as 
eliminating risk. 

530
00:28:43,500 --> 00:28:47,100
I don't know if you were to call
it as sort of reducing risk or 

531
00:28:47,200 --> 00:28:49,500
doing something to take care of 
your disgusting. 

532
00:28:49,500 --> 00:28:52,300
Broadly, we can, we can Define 
it as so. 

533
00:28:52,300 --> 00:28:56,700
Can you talk about hedging and 
like, the again, both have been 

534
00:28:56,700 --> 00:28:58,600
pretty much this standard for 
every question. 

535
00:28:58,600 --> 00:29:00,800
I'm going to ask you today. 
I need you to answer both from a

536
00:29:01,500 --> 00:29:03,300
life perspective and a finance 
perspective. 

537
00:29:03,900 --> 00:29:05,800
I mean, that is a very good 
concept, right? 

538
00:29:05,800 --> 00:29:08,700
I mean, inherently hedging is 
part of our life, whether we 

539
00:29:08,700 --> 00:29:11,700
knowingly or unknowingly, we do 
it it. 

540
00:29:11,700 --> 00:29:14,800
But when you hedge before 
hedging, is the other aspect, 

541
00:29:14,800 --> 00:29:16,900
right? 
You have this concept, which is 

542
00:29:16,900 --> 00:29:21,200
expected value, right? 
Because hedging is an outcome, 

543
00:29:21,200 --> 00:29:25,100
which is changing the expected. 
So, in a very, crude way, 

544
00:29:25,100 --> 00:29:29,000
expected value is like, the, 
like outcome that you are hoping

545
00:29:29,400 --> 00:29:33,600
the outcome and then you have a 
range or a distribution of it. 

546
00:29:33,700 --> 00:29:36,400
Based on which you are making a 
decision and hedging is a 

547
00:29:36,400 --> 00:29:40,900
process which is essentially 
narrowing those outcomes, right?

548
00:29:40,900 --> 00:29:43,500
I mean expected value, I mean 
and to do that you need to First

549
00:29:43,500 --> 00:29:47,000
understand the principle of 
expected value first, right? 

550
00:29:47,000 --> 00:29:51,400
And the understand the concept 
that expected value the the same

551
00:29:51,400 --> 00:29:55,200
event has a different expected 
value to you to somebody else or

552
00:29:55,200 --> 00:29:57,100
even to you at two different 
points in time. 

553
00:29:57,200 --> 00:30:02,000
I mean t taking an example, you 
know, where you it's a Saturday 

554
00:30:02,000 --> 00:30:04,000
evening and you want to go to 
your Ends. 

555
00:30:04,500 --> 00:30:07,700
You, you know, you could go and 
watch a movie with your friends 

556
00:30:08,100 --> 00:30:12,100
or you could stay back and watch
a movie on Netflix. 

557
00:30:12,300 --> 00:30:14,900
Right? 
And the expected value of these 

558
00:30:14,900 --> 00:30:18,200
two is probably if you're an 
introvert, you might prefer the 

559
00:30:18,200 --> 00:30:19,800
latter. 
If you're an extrovert. 

560
00:30:19,800 --> 00:30:21,400
You may prefer the former, 
right? 

561
00:30:21,500 --> 00:30:24,400
So that's where the same even 
has two different things. 

562
00:30:24,700 --> 00:30:28,300
But independently the, for the 
same person whom I let s take an

563
00:30:28,300 --> 00:30:29,700
example of an extroverted 
person. 

564
00:30:29,900 --> 00:30:33,200
If imagine that the second event
had it with his or her romantic 

565
00:30:33,200 --> 00:30:34,400
interest. 
Right? 

566
00:30:34,500 --> 00:30:37,100
And the second one has more 
value, right? 

567
00:30:37,200 --> 00:30:40,600
So your expected value, 
inherently starts taking into 

568
00:30:40,600 --> 00:30:42,700
account, your utility functions,
your. 

569
00:30:43,200 --> 00:30:47,700
You know, if we didn't have this
dispersion in expected values, 

570
00:30:47,800 --> 00:30:49,800
you would not even have a 
functioning market, and then you

571
00:30:49,800 --> 00:30:53,000
are, you have wrote between the 
buyers and sellers book, right? 

572
00:30:53,000 --> 00:30:56,600
I mean, the buyer and the 
seller, have different value for

573
00:30:56,600 --> 00:30:59,000
the same asset. 
Otherwise, there is no trade, 

574
00:30:59,200 --> 00:31:00,400
right? 
Of course, you I'm buying a 

575
00:31:00,400 --> 00:31:03,500
Samsung phone because Samsung 
values my cash. 

576
00:31:03,600 --> 00:31:06,600
More and I value the for more 
exactly. 

577
00:31:06,700 --> 00:31:11,800
Right, right. 
So now and economics, when they 

578
00:31:11,800 --> 00:31:16,300
go into this and they say that 
this all agents are rational or 

579
00:31:16,400 --> 00:31:20,800
these things, it is true to some
extent, right? 

580
00:31:20,800 --> 00:31:23,900
But where they do a mistake is 
they kind of say that, you know,

581
00:31:23,900 --> 00:31:27,100
every average person and they 
take an average person and then,

582
00:31:27,400 --> 00:31:31,000
you know, remember that in our 
Junior days we used to get this,

583
00:31:31,200 --> 00:31:35,800
you know, what is f of X and 
expectation of f of x. 

584
00:31:35,800 --> 00:31:38,100
And F of expected X. 
Yes, right. 

585
00:31:38,200 --> 00:31:41,400
And these two would be functions
which are not for some of them, 

586
00:31:41,400 --> 00:31:43,700
they would end up being true. 
And some of them they are not 

587
00:31:43,700 --> 00:31:44,700
true. 
Right? 

588
00:31:44,800 --> 00:31:48,500
And that is, and that and we 
make a simplification that it is

589
00:31:48,500 --> 00:31:50,400
actually true. 
And that is where most of the 

590
00:31:50,400 --> 00:31:52,600
problem is, comes in. 
Right? 

591
00:31:52,600 --> 00:31:55,500
We have these laws and, you 
know, taking the adverse 

592
00:31:55,600 --> 00:31:59,200
situation, write my law, my 
utility function from 

593
00:31:59,200 --> 00:32:02,800
committing, a crime is different
from a Psychopaths, utility 

594
00:32:02,800 --> 00:32:05,400
function from committing. 
Being a crime, I'm more scared 

595
00:32:05,400 --> 00:32:08,600
about, you know, being 
imprisoned in suffering, the 

596
00:32:08,600 --> 00:32:12,900
adverse consequences than let's 
say a person who takes Pride out

597
00:32:12,900 --> 00:32:16,100
of it. 
And therefore the deterrent for 

598
00:32:16,200 --> 00:32:19,300
that person is very 
substantially different. 

599
00:32:19,400 --> 00:32:21,400
Right? 
And this kind of we can talk 

600
00:32:21,400 --> 00:32:23,100
about it later. 
But this kind of goes into the 

601
00:32:23,108 --> 00:32:27,600
fact that why a uniform policy 
that you have will not be good 

602
00:32:27,600 --> 00:32:30,400
enough to the say, apply as a 
deterrent for everyone, right? 

603
00:32:31,300 --> 00:32:36,300
So now, for me, my actions is, 
I'm now going to narrow these 

604
00:32:36,300 --> 00:32:39,500
outcomes, right? 
I want to reduce the like if I 

605
00:32:39,500 --> 00:32:42,700
want to go to a movie. 
I want to go to a movie, which I

606
00:32:42,700 --> 00:32:47,000
think I will enjoy, right? 
I will unlikely to take a, you 

607
00:32:47,000 --> 00:32:51,500
know, being let's say not a are 
three kind of a person. 

608
00:32:51,600 --> 00:32:54,300
I am probably going to go to a 
generic movie, which is likely 

609
00:32:54,300 --> 00:32:57,000
to have a moderate range. 
Right? 

610
00:32:57,000 --> 00:32:59,600
Whereas let's say that the art 
movies tend to have a wider 

611
00:32:59,600 --> 00:33:02,200
range of outcomes. 
We're one of them to be either 

612
00:33:02,200 --> 00:33:05,500
extremely good or it can 
completely go over my head and I

613
00:33:05,508 --> 00:33:08,800
won't even understand. 
So that naturally means that I 

614
00:33:08,800 --> 00:33:13,300
will go and up going to a artsy 
movie, not a Nazi movie, but a 

615
00:33:13,300 --> 00:33:17,100
normal movie, right? 
So hedging is nothing but you 

616
00:33:17,100 --> 00:33:21,600
are trying to die, reduce the 
range of outcomes, so that you 

617
00:33:21,600 --> 00:33:24,100
have greater assurance that you 
will not. 

618
00:33:24,100 --> 00:33:27,400
And it feeds into the point that
our utility functions are 

619
00:33:27,400 --> 00:33:32,400
unfortunately not linear, right?
A negative reaction. 

620
00:33:32,400 --> 00:33:35,800
The pain hurts us more than the 
joy. 

621
00:33:36,600 --> 00:33:39,300
Actually, this utility function 
reminds me of, like, I think 

622
00:33:39,300 --> 00:33:44,100
cubs, we have also in some of my
past lives, have done some work 

623
00:33:44,100 --> 00:33:47,300
on utility functions and using 
that to construct portfolios and

624
00:33:47,300 --> 00:33:51,600
things like that, but it reminds
me of Behavioral economists who 

625
00:33:51,800 --> 00:33:55,800
kind of like once I had drawn a 
utility function. 

626
00:33:55,900 --> 00:33:58,600
It is very hard for me to sort 
of think about it. 

627
00:33:58,900 --> 00:34:00,700
What is what is behavioral 
economics? 

628
00:34:00,800 --> 00:34:05,000
Because C4 fundamentally utility
function is like, x axis is how 

629
00:34:05,000 --> 00:34:08,100
much you have lecture income, or
wealth or returns or whatever 

630
00:34:08,400 --> 00:34:11,500
y-axis is the utility. 
And we know that it's a sort of 

631
00:34:11,500 --> 00:34:16,199
a, the, it's an increasing 
function but increases with the 

632
00:34:16,800 --> 00:34:20,699
- diminishing slope, right? 
So I don't have to try to mix or

633
00:34:20,699 --> 00:34:23,400
concave. 
I think it's like a, that's 

634
00:34:23,400 --> 00:34:26,300
something I never understood. 
So based on this, which means 

635
00:34:26,300 --> 00:34:30,000
that if I have 100 rupees, if I 
lose ten bucks, then I'm going 

636
00:34:30,000 --> 00:34:35,699
to The feel a lot more pain than
I would if I were to gain 10 

637
00:34:35,699 --> 00:34:39,800
bucks study from hunting, right?
That's a, it's a sort of 

638
00:34:39,800 --> 00:34:43,500
fundamental, sort of sort of 
everybody had. 

639
00:34:43,600 --> 00:34:46,800
I mean, I may not have liked the
exact shape of the utility first

640
00:34:47,000 --> 00:34:50,600
curve for me, might be different
from it is for you, but but the 

641
00:34:50,600 --> 00:34:53,800
fundamental the nature of the 
curve that it's an increasing 

642
00:34:53,800 --> 00:34:58,500
function, that it's non 
decreasing and that the slope is

643
00:34:59,600 --> 00:35:01,300
decreasing. 
I think that's two. 22 out of 

644
00:35:01,300 --> 00:35:03,400
everyone, right? 
That is true for everyone. 

645
00:35:03,400 --> 00:35:05,100
Absolutely. 
I think I mean there are very 

646
00:35:05,100 --> 00:35:08,000
few instances where this would 
not be like, I mean other than 

647
00:35:08,000 --> 00:35:11,200
compulsive gamblers and few 
other areas, I think in general 

648
00:35:11,200 --> 00:35:15,100
it is true. 
But again, this is where, you 

649
00:35:15,100 --> 00:35:17,900
know, this is made actually the 
good aspect of risk management 

650
00:35:17,900 --> 00:35:20,300
that you mentioned whether in 
real life or whether in 

651
00:35:20,300 --> 00:35:24,300
financial Market comes in 
because net net Equity function.

652
00:35:24,300 --> 00:35:27,300
The way we learn in economics is
like a simple single dimensional

653
00:35:27,400 --> 00:35:32,600
axis, but risk overall is like a
Three dimensional things in many

654
00:35:32,600 --> 00:35:36,300
ways, right? 
For example, if I were to be 

655
00:35:36,300 --> 00:35:39,400
sick and I needed money money 
right now. 

656
00:35:39,400 --> 00:35:42,800
The sickness is defining, and 
the utility for money is far 

657
00:35:42,800 --> 00:35:47,100
greater because it has a 
long-term impact on my survival,

658
00:35:47,900 --> 00:35:50,000
right? 
Whereas, if you are a guy who is

659
00:35:50,000 --> 00:35:52,900
like happily sitting on, let's 
say some Surplus cash flow, 

660
00:35:53,200 --> 00:35:56,500
right? 
That 50,000 Rupees that, let's 

661
00:35:56,500 --> 00:36:00,600
say your your driver, who is 
sick and was you and whereas for

662
00:36:00,600 --> 00:36:02,400
you. 
You who is like, does is 

663
00:36:02,400 --> 00:36:05,200
marginal, you know, it is 
probably going to be in your 

664
00:36:05,200 --> 00:36:08,000
bank and owning a 4% on FD, 
right? 

665
00:36:08,500 --> 00:36:12,400
That is the value that it has so
substantial, you know, the same 

666
00:36:12,400 --> 00:36:15,600
thing can have substantial. 
Don't both of you have a similar

667
00:36:15,600 --> 00:36:18,500
utility function, but because 
you are in a different on 

668
00:36:18,500 --> 00:36:21,800
different dimensions, whether it
is in time or objectives, or 

669
00:36:21,800 --> 00:36:23,900
Etc. 
The same object gives you 

670
00:36:23,900 --> 00:36:26,400
different utilities and this is 
where risk management happens, 

671
00:36:26,800 --> 00:36:29,400
right? 
So, we all have left tales in 

672
00:36:29,400 --> 00:36:32,900
real life, right? 
All scared, We Buy Houses, we 

673
00:36:32,900 --> 00:36:35,600
buy, we have jobs. 
They're worried about our 

674
00:36:35,607 --> 00:36:40,000
families, not all of us. 
Always have dual employment, or 

675
00:36:40,000 --> 00:36:43,000
not offers even jobs, which give
you a guaranteed secure 

676
00:36:43,000 --> 00:36:45,000
employment. 
Like there is a reason why 

677
00:36:45,200 --> 00:36:48,100
government jobs get, you know, 
even for a government job of a 

678
00:36:48,100 --> 00:36:51,900
sweeper, you'd find one is 2000.
Kind of applicants or one is to 

679
00:36:51,900 --> 00:36:54,500
10,000 applicants, right? 
Because there is certain 

680
00:36:54,600 --> 00:36:57,700
security that comes with a 
government job with a pension, 

681
00:36:57,700 --> 00:36:59,400
and all those things right? 
In some sense. 

682
00:36:59,400 --> 00:37:02,700
That is like, the risk free. 
Rate, it's like a risk-free job,

683
00:37:03,000 --> 00:37:06,700
right? 
And yeah, so coming back you do 

684
00:37:06,700 --> 00:37:10,700
so that this multiple times, you
know, rigidity that helps you in

685
00:37:10,700 --> 00:37:13,000
diversify. 
You can actually transfer risk 

686
00:37:13,000 --> 00:37:17,300
from one person to the other 
person and you people have in 

687
00:37:17,300 --> 00:37:20,300
finances. 
Let's say that I am a guy who 

688
00:37:20,300 --> 00:37:24,900
has as a Trader when I used to 
trade options and derivatives in

689
00:37:24,900 --> 00:37:26,900
general. 
I don't manage Delta risk. 

690
00:37:27,000 --> 00:37:28,700
I am always Delta hitched, 
right? 

691
00:37:28,700 --> 00:37:32,100
Which means that I do not. 
Are about the direction of the 

692
00:37:32,100 --> 00:37:34,800
underlying asset. 
Most of the risk, which I would 

693
00:37:34,800 --> 00:37:38,600
manage was either volatility 
risk and correlations risk. 

694
00:37:38,600 --> 00:37:40,800
That is the risk that I was 
comfortable with and I would 

695
00:37:40,800 --> 00:37:44,000
manage that right. 
But I was transferring the Delta

696
00:37:44,000 --> 00:37:47,800
risk to my spot desk, who is 
comfortable managing it, right? 

697
00:37:47,900 --> 00:37:50,600
So in some sense our utility 
functions are different and we 

698
00:37:50,600 --> 00:37:52,800
are able to transfer in real 
life. 

699
00:37:53,000 --> 00:37:55,900
Insurance is like that. 
All of us have loans, all of us 

700
00:37:55,900 --> 00:38:00,100
have made Health in issues and 
liabilities, which we have, we 

701
00:38:00,100 --> 00:38:02,400
take long. 
Term liabilities, you know, in 

702
00:38:02,400 --> 00:38:06,200
hope that you're all live long, 
and you will all prosper and 

703
00:38:06,300 --> 00:38:09,100
Etc. 
But as you said, right, we only 

704
00:38:09,100 --> 00:38:13,400
have one life and in fact, it's 
a very different problem. 

705
00:38:13,400 --> 00:38:15,900
I'm whether if this, right, I 
mean, you are not is ergodicity,

706
00:38:16,100 --> 00:38:19,800
but we all have one life and we 
are very scared about it. 

707
00:38:20,000 --> 00:38:23,800
So you kind of need to hedge 
that aspect of it, right? 

708
00:38:23,800 --> 00:38:27,400
So if you take a housing loan of
about a crow and your income is 

709
00:38:27,400 --> 00:38:31,300
about 15 lakhs per annum you 
want to make Sure that if 

710
00:38:31,300 --> 00:38:34,700
something to untoward happen to 
you tomorrow, that loan burden 

711
00:38:34,700 --> 00:38:38,300
doesn't come back and bite your 
family, take an insurance. 

712
00:38:38,700 --> 00:38:40,800
Right? 
And why is it? 

713
00:38:40,800 --> 00:38:42,800
Because the insurance person, 
you know, for him? 

714
00:38:42,800 --> 00:38:44,200
It's a different risk 
altogether. 

715
00:38:44,400 --> 00:38:46,100
He's taking your risk and 
converting. 

716
00:38:46,100 --> 00:38:48,300
So this is where your original 
problem, right? 

717
00:38:48,500 --> 00:38:52,000
People are able to convert risk 
from one, type to the other 

718
00:38:52,000 --> 00:38:57,100
type, right and bpay because 
it's a left tail risk. 

719
00:38:57,200 --> 00:39:00,600
Despite its expected value. 
Let's say is low. 

720
00:39:00,700 --> 00:39:04,600
Tea and is only about thousand 
or ten thousand, right? 

721
00:39:04,900 --> 00:39:09,200
We end up paying twenty thousand
because we are so risk, averse 

722
00:39:09,200 --> 00:39:12,500
and we, it's the adverse event 
will hurt us so much more, 

723
00:39:12,900 --> 00:39:15,400
right? 
All of us have spent all our 

724
00:39:15,400 --> 00:39:16,900
money. 
I mean, we can give the best 

725
00:39:16,900 --> 00:39:19,300
event on risk is happening right
now, is covid, right? 

726
00:39:19,500 --> 00:39:23,600
I mean, we don't trade on 
probabilities, vitro, we trade 

727
00:39:23,600 --> 00:39:25,100
on our fear of the 
probabilities. 

728
00:39:26,100 --> 00:39:27,400
Yes, yes. 
Yes. 

729
00:39:28,000 --> 00:39:30,400
Yes. 
So, yeah, so that's, that's, 

730
00:39:30,400 --> 00:39:33,200
that's essentially how risk 
management works and hedging 

731
00:39:33,200 --> 00:39:36,200
Works, which is you want to keep
those things that you are 

732
00:39:36,200 --> 00:39:39,500
comfortable managing and you do 
not want those things which are 

733
00:39:39,500 --> 00:39:43,400
in finance obviously because you
measure it even in finance, 

734
00:39:43,400 --> 00:39:46,800
their lots of unmeasurable stuff
and you will see very frequently

735
00:39:46,800 --> 00:39:49,000
that despite the claims of 
Finance industry. 

736
00:39:49,000 --> 00:39:53,400
They always surprised right and 
reason being that none of this 

737
00:39:53,800 --> 00:39:57,100
them are good enough to First, 
and the second third, fourth 

738
00:39:57,100 --> 00:39:59,900
order effects, and these 
systems, like, I mentioned 

739
00:39:59,900 --> 00:40:02,700
earlier, right, the tailed 
systems are those where the 

740
00:40:02,700 --> 00:40:06,000
second and third order effects 
are again, talking about utility

741
00:40:06,000 --> 00:40:08,300
functions and because they sort 
of flattened out, I think 

742
00:40:08,400 --> 00:40:11,600
insurance is, of course, one of 
the one of the made that the 

743
00:40:11,700 --> 00:40:14,200
rate of Returns on insurance is 
low, is one of the things, one 

744
00:40:14,200 --> 00:40:17,700
of the outcomes of the galatea 
are flattening utility 

745
00:40:18,000 --> 00:40:20,000
functions. 
One of the other things is that,

746
00:40:20,000 --> 00:40:24,100
like, if you have a certain 
event and an uncertain, if you 

747
00:40:24,107 --> 00:40:27,900
have a certain pay off, And an 
uncertain payoff and the to have

748
00:40:27,900 --> 00:40:31,400
the same expected value. 
You would be willing to pay more

749
00:40:31,400 --> 00:40:34,900
for the certain payoff, or for 
the more certain payoff than for

750
00:40:34,900 --> 00:40:36,800
the uncertainty of. 
So in some sense. 

751
00:40:36,800 --> 00:40:40,000
I guess, one thing that we have,
sort of, all of us have 

752
00:40:40,000 --> 00:40:44,000
internalised is that when there 
is risk, you need to just be 

753
00:40:44,000 --> 00:40:47,300
compensated for the existed to 
take on the risk. 

754
00:40:47,300 --> 00:40:50,100
You need to be compensated just 
for the existence of the risk. 

755
00:40:51,700 --> 00:40:55,100
Absolutely know that that that 
that is absolutely true. 

756
00:40:55,100 --> 00:40:56,100
Right? 
Imagine. 

757
00:40:56,100 --> 00:41:00,400
You had a job offer, right? 
From a multinational company, 

758
00:41:00,700 --> 00:41:06,500
which probably is paying you X 
and second one is your have a 

759
00:41:06,500 --> 00:41:10,600
job offer from a start-up which 
probably is paying you less than

760
00:41:10,600 --> 00:41:11,500
x. 
And in the multinational 

761
00:41:11,500 --> 00:41:14,400
companies, you have your 
standard utilities and you know,

762
00:41:14,400 --> 00:41:16,000
fringe benefits, corporate 
benefits. 

763
00:41:16,000 --> 00:41:20,400
Good lifestyle, Etc. 
You did the whole ESOP structure

764
00:41:20,400 --> 00:41:25,300
is created to make that happen 
so that the, in reality, the 

765
00:41:25,300 --> 00:41:31,900
expected value of salary from 
overall, or at least, perceived 

766
00:41:31,900 --> 00:41:33,700
expected value. 
Because we never know what is 

767
00:41:33,700 --> 00:41:34,700
true. 
Expected value. 

768
00:41:34,700 --> 00:41:37,500
Anyway, right? 
The perceived expected value 

769
00:41:37,500 --> 00:41:42,200
from your standard company is X.
And the Y that you get from your

770
00:41:42,200 --> 00:41:44,900
startup. 
Y has to be greater than x. 

771
00:41:44,900 --> 00:41:46,600
Otherwise, you won't even 
consider it. 

772
00:41:47,200 --> 00:41:49,100
Right. 
It is a different thing that a 

773
00:41:49,100 --> 00:41:54,300
more risk-averse person will 
need far much higher y than 

774
00:41:54,300 --> 00:41:57,200
let's say you who might be less 
risk-averse. 

775
00:41:58,200 --> 00:42:01,500
Eight, which is why you would 
see all people, in startups, end

776
00:42:01,500 --> 00:42:03,000
up being those risk-taking 
people. 

777
00:42:03,000 --> 00:42:05,900
It's a natural outcome. 
And which is why organizations, 

778
00:42:05,900 --> 00:42:08,200
which are slow moving and 
sturdy. 

779
00:42:08,200 --> 00:42:09,900
There isn't that? 
It's like birds of a feather 

780
00:42:09,900 --> 00:42:13,300
flock together, right? 
So, there is a natural outcome 

781
00:42:13,300 --> 00:42:15,500
of each person's utility 
functions. 

782
00:42:15,500 --> 00:42:18,400
Whether we realize it or not, it
inherently is what happens. 

783
00:42:18,700 --> 00:42:20,200
Yeah. 
So I guess it's like not only 

784
00:42:20,200 --> 00:42:23,100
does risk have a price, but the 
price of risk is different for 

785
00:42:23,100 --> 00:42:26,800
different people. 
And I varies from risk to this, 

786
00:42:26,800 --> 00:42:30,900
coming risk of income has one 
price for somebody risk of 

787
00:42:30,900 --> 00:42:33,300
something else. 
Like, I don't know, like stock 

788
00:42:33,300 --> 00:42:36,800
market is return on investments 
will have different prices for 

789
00:42:36,800 --> 00:42:39,900
different people and and so on, 
I guess so. 

790
00:42:39,900 --> 00:42:42,100
I know that you are a gamer. 
You are a massive gamer. 

791
00:42:42,100 --> 00:42:45,300
I know you pretty much spent 
most of your college Life gaming

792
00:42:45,300 --> 00:42:47,300
and so on. 
And I think there are some games

793
00:42:47,300 --> 00:42:49,800
which are like coming, we had 
another episode of couple of 

794
00:42:50,500 --> 00:42:54,500
months back where we had this 
guy. 

795
00:42:54,900 --> 00:42:57,600
Rahul dravid, who runs a 
Montessori School, who spoke 

796
00:42:57,600 --> 00:43:01,000
about how one of the ways in 
which you can introduce 

797
00:43:01,900 --> 00:43:05,000
analytics to young kids is, by 
introducing them to games. 

798
00:43:05,100 --> 00:43:06,600
He was like one of the 
statement. 

799
00:43:06,600 --> 00:43:08,800
She said in the podcast, is at 
Blackjack is absolutely 

800
00:43:08,800 --> 00:43:13,600
compulsory for 60. 
Let's I agree to that. 

801
00:43:14,100 --> 00:43:15,500
Let's talk to. 
I know that clicker. 

802
00:43:15,500 --> 00:43:18,700
We'd like you also like sort of,
I do you play a bridge. 

803
00:43:18,700 --> 00:43:21,200
I don't know if you play poker 
and so on. 

804
00:43:21,200 --> 00:43:24,000
But let's talk about games and 
the risk in them. 

805
00:43:24,000 --> 00:43:26,100
What we can learn about risk, 
some games. 

806
00:43:26,300 --> 00:43:29,400
And what is the limits of what 
we can learn from? 

807
00:43:29,500 --> 00:43:34,900
Like a situation such as games. 
You know, I mean the point that 

808
00:43:34,900 --> 00:43:38,500
you're, you know, the previous 
podcaster has just mentioned in 

809
00:43:38,500 --> 00:43:42,100
terms of risk and understanding 
games. 

810
00:43:42,200 --> 00:43:44,700
It's actually bang on and it is 
see. 

811
00:43:44,900 --> 00:43:47,000
I mean, it's not just I mean, 
I'm going to take a little 

812
00:43:47,000 --> 00:43:52,500
detour, you know, that all our 
body has chemicals, right? 

813
00:43:52,800 --> 00:43:54,700
And we have been we have 
different chemicals for 

814
00:43:54,700 --> 00:43:57,000
different things, your 
serotonin, oxytocin. 

815
00:43:57,400 --> 00:44:00,200
And during stress. 
I forget the name of the stress 

816
00:44:00,200 --> 00:44:04,100
hormone right now, but It starts
with dopamine serotonin, 

817
00:44:04,100 --> 00:44:07,700
oxytocin the end. 
The bad one is the bad. 

818
00:44:07,700 --> 00:44:12,300
One is something. 
It's not idling, but it comes 

819
00:44:12,300 --> 00:44:15,500
from the same region and it's it
is thing. 

820
00:44:15,500 --> 00:44:16,700
Yeah, so there is a stress 
hormone. 

821
00:44:16,700 --> 00:44:18,200
I think it starts with k. 
I just can't. 

822
00:44:18,200 --> 00:44:20,200
It's at the tip of the tongue 
and I can't remember, right? 

823
00:44:20,400 --> 00:44:25,300
So what typically happens is 
your flight or fight instincts, 

824
00:44:26,500 --> 00:44:29,000
are generate these stress 
hormones? 

825
00:44:29,500 --> 00:44:35,300
And the point is It in mother's 
womb. 

826
00:44:35,700 --> 00:44:39,600
There is a reason why they say 
that mother has to be taken care

827
00:44:39,600 --> 00:44:40,900
of. 
Well, they should not get 

828
00:44:40,900 --> 00:44:43,800
stressed and so on, because what
typically happens is when the 

829
00:44:43,800 --> 00:44:46,700
stress hormone, when it gets 
produced the baby's, it adapts 

830
00:44:46,700 --> 00:44:50,000
to certain level as a base and 
that starts hurting future. 

831
00:44:50,200 --> 00:44:55,000
So inherently all of us, we 
don't like uncertainty when 

832
00:44:55,000 --> 00:44:57,900
there is uncertainty, when there
is lot of water, you know, 

833
00:44:57,900 --> 00:44:59,700
things there is chaos. 
I mean, which is why. 

834
00:44:59,700 --> 00:45:02,700
When I mean, there is this word 
we get Just right. 

835
00:45:03,000 --> 00:45:06,900
Stress is triggered by anxiety, 
uncertainty, and all these 

836
00:45:06,900 --> 00:45:09,300
things. 
And the ability to handle stress

837
00:45:09,600 --> 00:45:12,200
is not uniform, amongst all 
individuals. 

838
00:45:12,500 --> 00:45:15,200
It is a very wide Divergent 
things, right? 

839
00:45:15,300 --> 00:45:18,700
Which is also leads to the 
things why some of us, you know,

840
00:45:19,000 --> 00:45:22,900
Depression hit someone the same 
event, make somebody depressed. 

841
00:45:22,900 --> 00:45:25,700
Whereas somebody not and there's
also a lack of understanding all

842
00:45:25,700 --> 00:45:29,500
these things fit together and in
some sense, introducing your 

843
00:45:29,500 --> 00:45:33,600
kids to uncertainty at a The 
rage is like a vaccination, 

844
00:45:33,700 --> 00:45:35,200
right? 
You should think of it in that 

845
00:45:35,200 --> 00:45:35,900
fashion. 
Right? 

846
00:45:35,900 --> 00:45:38,500
Imagine. 
If your child grew up in a Suraj

847
00:45:38,500 --> 00:45:42,000
barjatya style household, where 
everything was sing song and 

848
00:45:42,000 --> 00:45:47,500
dance, and party, the chances 
that an adverse outcome can 

849
00:45:47,500 --> 00:45:51,100
completely topple the child, the
chances increase. 

850
00:45:52,500 --> 00:45:55,100
Right? 
And you and I, we had friends 

851
00:45:55,100 --> 00:45:57,800
whom we lost because of such 
outcomes, right? 

852
00:45:57,800 --> 00:46:01,100
I mean, I mean, that is one 
where we know that is a specific

853
00:46:01,100 --> 00:46:04,000
group of people. 
And we have spoken, you know, 

854
00:46:04,000 --> 00:46:06,600
many times outside, you know, 
about this event. 

855
00:46:06,600 --> 00:46:11,700
So so so mi, do you uncertainty 
introducing games, which have 

856
00:46:11,700 --> 00:46:16,100
uncertainty, I feel, is a way of
vaccination games by themselves,

857
00:46:16,100 --> 00:46:19,700
are could write, unless again, 
is what I call a complete 

858
00:46:19,700 --> 00:46:22,100
information game, right? 
Which is things. 

859
00:46:22,300 --> 00:46:25,200
Chess where you can actually 
compute boo, but even chess does

860
00:46:25,200 --> 00:46:28,100
not become complete information 
for a child because he's not a 

861
00:46:28,107 --> 00:46:30,100
computer. 
He's not a computer, right? 

862
00:46:30,100 --> 00:46:32,500
So she would have information is
very large. 

863
00:46:32,600 --> 00:46:35,600
So he's very large for them. 
So it for all practical 

864
00:46:35,600 --> 00:46:38,400
purposes. 
It can be considered incomplete 

865
00:46:38,400 --> 00:46:41,700
information, right? 
Because you can't guess and so 

866
00:46:41,700 --> 00:46:45,900
on and so forth, but the point 
is all these games help you to 

867
00:46:45,900 --> 00:46:50,100
handle uncertainty because you 
we are all taught especially in 

868
00:46:50,100 --> 00:46:52,100
your moral science and other 
things. 

869
00:46:52,200 --> 00:46:54,900
Things do good. 
Good will come back to you and 

870
00:46:54,900 --> 00:46:57,600
everything is almost like a 
definitive statement. 

871
00:46:58,000 --> 00:47:00,300
We are not handled 
probabilities. 

872
00:47:00,500 --> 00:47:03,800
The fact that if I say that 
tomorrow in an election, some 

873
00:47:03,800 --> 00:47:07,100
party is going to win, 300 
seats, you know, if it is 

874
00:47:07,100 --> 00:47:10,200
greater than 300, you are proven
wrong, if it is less than 300, 

875
00:47:10,200 --> 00:47:11,700
you're proven wrong. 
I mean, you are an election 

876
00:47:11,700 --> 00:47:13,600
forecaster. 
So I'm sure you got these 

877
00:47:13,600 --> 00:47:17,400
feedbacks, right? 
And what people don't understand

878
00:47:17,400 --> 00:47:20,500
is, there's a difference between
talking about the mean and 

879
00:47:20,500 --> 00:47:24,300
talking about the outcomes. 
Expecting that doing the same 

880
00:47:24,300 --> 00:47:27,800
thing will lead to result to the
same actions. 

881
00:47:27,800 --> 00:47:33,000
Again is something that you 
would want your child to not. 

882
00:47:34,000 --> 00:47:37,600
You know, it's actually risk 
management for a longer life to 

883
00:47:37,600 --> 00:47:40,000
introduce them to that concept, 
right? 

884
00:47:40,000 --> 00:47:43,200
Because natural world, is you 
cycle fast. 

885
00:47:43,200 --> 00:47:45,100
The cycle goes, faster, you 
break it. 

886
00:47:45,100 --> 00:47:47,000
It's consistent. 
Most of the world. 

887
00:47:47,000 --> 00:47:50,800
We mechanical world that we live
in and interact with on a 

888
00:47:50,808 --> 00:47:55,100
day-to-day basis. 
As Unser remove like imagine 

889
00:47:55,800 --> 00:47:58,200
financial markets, right? 
We consider somebody who is 

890
00:47:58,200 --> 00:48:01,300
Right 60% of the time to be, you
know, generating, awesome 

891
00:48:01,300 --> 00:48:03,500
results. 
Now, imagine if your car starts 

892
00:48:03,500 --> 00:48:05,600
60% of the time, would you even 
own that car? 

893
00:48:06,200 --> 00:48:08,700
Right? 
So there is a huge expectation 

894
00:48:08,700 --> 00:48:11,000
difference on what we think on a
day-to-day basis. 

895
00:48:11,000 --> 00:48:15,600
What we think was is this thing 
and that because we are so used 

896
00:48:15,600 --> 00:48:18,000
to certainty. 
We kind of think that the same 

897
00:48:18,000 --> 00:48:20,600
actions should repeat and 
especially this happens with 

898
00:48:20,600 --> 00:48:24,000
human interactions and humans. 
Seeing an overall in events 

899
00:48:24,000 --> 00:48:26,100
that, you know, the things like 
your Butterfly Effects and all 

900
00:48:26,200 --> 00:48:30,100
sorts of things, which bring 
back the uncertainty. 

901
00:48:30,100 --> 00:48:35,400
So games, I think, which have 
uncertainty are absolute even 

902
00:48:35,400 --> 00:48:37,900
starting from your Snakes and 
Ladders, right? 

903
00:48:37,900 --> 00:48:40,700
They are good because there is 
no like not. 

904
00:48:40,800 --> 00:48:43,400
It's not like it is luck and 
you're not most people currently

905
00:48:43,400 --> 00:48:46,300
focus on chess and other things 
which have skilled, but actually

906
00:48:46,300 --> 00:48:48,700
it is not skill. 
I think that is more important. 

907
00:48:48,700 --> 00:48:51,400
You want to go for. 
It's not efficiency that you 

908
00:48:51,408 --> 00:48:53,400
should aim for. 
Her in childhood, especially 

909
00:48:53,500 --> 00:48:56,200
Ukraine for robustness. 
And that is risk management. 

910
00:48:56,200 --> 00:48:57,500
Right? 
Robustness is nothing but your 

911
00:48:57,500 --> 00:49:01,400
ability to handle risk. 
Well, thank you currently are 

912
00:49:01,400 --> 00:49:04,000
suffering from covid because 
we've been trying to be too 

913
00:49:04,000 --> 00:49:06,100
efficient. 
Yes, it is. 

914
00:49:06,200 --> 00:49:09,400
I'd risk management. 
Yeah, they got a video every 

915
00:49:09,400 --> 00:49:10,600
day. 
You see the paper that some 

916
00:49:10,600 --> 00:49:14,100
Automotive manufacturers is 
slowing down because like of the

917
00:49:14,100 --> 00:49:16,300
chip shortage. 
And that's because of, of the 

918
00:49:16,300 --> 00:49:18,300
just in time, over the last 
hundred years, right? 

919
00:49:18,600 --> 00:49:23,100
Like if we had more stocks, if 
we were more Fact, in some 

920
00:49:23,100 --> 00:49:25,900
sense. 
You'd have a lot to receive less

921
00:49:25,900 --> 00:49:29,500
risk and be a lot more robust. 
So what are the things you told 

922
00:49:29,500 --> 00:49:32,400
about how? 
Like, by introducing some risk 

923
00:49:32,400 --> 00:49:35,000
to kids early, you sort of, 
inoculate them against this 

924
00:49:35,000 --> 00:49:36,600
great. 
So, I'm reminded of this line 

925
00:49:36,600 --> 00:49:39,300
from someone of scallops books. 
I don't know which one it is a, 

926
00:49:39,300 --> 00:49:42,400
it's called possibly Black Swan 
where he says, the countries 

927
00:49:42,400 --> 00:49:46,200
where I would least expect a 
political crisis, or a coup or 

928
00:49:46,200 --> 00:49:49,500
something her countries, like 
India and Italy. 

929
00:49:49,500 --> 00:49:51,900
And some other places. 
He might ease because these are 

930
00:49:51,900 --> 00:49:55,800
countries which have like you 
have Alexis you have high 

931
00:49:55,800 --> 00:49:57,400
political instability all the 
time. 

932
00:49:58,200 --> 00:50:00,100
Because you have high political 
instability. 

933
00:50:00,300 --> 00:50:01,800
It means that you are like sort 
of. 

934
00:50:01,900 --> 00:50:05,300
You have a lot of short-term 
volatility, which means that you

935
00:50:05,300 --> 00:50:08,900
are sort of hedged against, 
like, big changes. 

936
00:50:09,600 --> 00:50:12,800
Another example of this is I 
used to ride a motorcycle. 

937
00:50:12,800 --> 00:50:15,500
I used to have a Royal Enfield 
and I had gone on a tour to 

938
00:50:15,500 --> 00:50:19,500
Rajasthan in 2012 and their 
people taught how to motorcycle 

939
00:50:19,500 --> 00:50:23,900
on Sand. 
And what infield guys told us is

940
00:50:23,900 --> 00:50:27,300
that you should always hold a 
bike loosely. 

941
00:50:28,100 --> 00:50:30,900
You should never grip it too 
tightly and let it wobble a bit.

942
00:50:30,900 --> 00:50:33,600
Then if it wobbles a bit, you 
know how much it can wobble in 

943
00:50:33,600 --> 00:50:35,300
it. 
It won't wobble enough for you 

944
00:50:35,300 --> 00:50:39,600
to fall here it. 
Absolutely right. 

945
00:50:39,600 --> 00:50:42,700
What you are doing. 
Is it you're converting things 

946
00:50:42,800 --> 00:50:46,700
moving things from unknown 
unknowns to known unknowns, 

947
00:50:46,800 --> 00:50:49,400
right? 
And if you have known unknowns, 

948
00:50:49,400 --> 00:50:52,000
hopefully your robustness in 
handling, these things matter 

949
00:50:52,300 --> 00:50:56,400
like that is why I like it and 
games like games like on an 

950
00:50:56,400 --> 00:50:58,000
investment side. 
So that is on real life. 

951
00:50:58,300 --> 00:51:02,600
In real life, I think people 
should introduce Blackjack is a 

952
00:51:02,600 --> 00:51:04,900
perfect example. 
I think that is simplest and 

953
00:51:04,900 --> 00:51:06,700
most elegant game that you would
do. 

954
00:51:06,800 --> 00:51:09,700
I like slightly complex games. 
And, you know, for example, 

955
00:51:09,700 --> 00:51:12,500
Seven Wonders is a good game 
where there is certain amount of

956
00:51:12,500 --> 00:51:16,000
Randomness and, you know, I 
played with my kid and it's 

957
00:51:16,000 --> 00:51:19,100
beautiful and they get excited 
and and and so on, but I think 

958
00:51:19,100 --> 00:51:23,000
Blackjack, I mean that's a 
beautiful example, right? 

959
00:51:23,000 --> 00:51:25,500
And the emphasis on things like 
chess. 

960
00:51:25,900 --> 00:51:28,000
I would, if anything I would 
argue should be lesser. 

961
00:51:28,100 --> 00:51:30,900
ER, than compared to these 
blackjacks. 

962
00:51:30,900 --> 00:51:32,900
I mean, you should play chess. 
That's a skill game. 

963
00:51:33,100 --> 00:51:37,500
But overall you want more and 
more of these things. 

964
00:51:37,800 --> 00:51:40,000
And there's also a certain 
difference right now, coming 

965
00:51:40,000 --> 00:51:42,600
back to the other hat that you 
asked me to join, which is on a 

966
00:51:42,607 --> 00:51:45,200
financial hat, right? 
So, there are two kinds of 

967
00:51:45,200 --> 00:51:47,800
games, right? 
One is what I would call Al 

968
00:51:47,800 --> 00:51:50,300
classify as poker. 
And the other one is, I would 

969
00:51:50,300 --> 00:51:55,700
call as Bridge, right? 
In a poker. 

970
00:51:56,600 --> 00:51:58,200
Yeah, sure. 
You have an edge. 

971
00:51:58,200 --> 00:52:00,800
If you know, certain things you 
can keep your accounts and so 

972
00:52:00,800 --> 00:52:04,300
on. 
But a lot of edge comes from 

973
00:52:04,300 --> 00:52:07,300
behavioral patterns, right? 
Your ability. 

974
00:52:07,300 --> 00:52:11,300
So there is a significant role 
of individual and individuals 

975
00:52:11,300 --> 00:52:17,100
personality which comes into 
play in in that game Bridge. 

976
00:52:17,200 --> 00:52:20,100
On the other hand, especially 
your duplicate bridge that you 

977
00:52:20,100 --> 00:52:24,100
know, we all used to play, you 
know, it's a different there. 

978
00:52:24,300 --> 00:52:26,700
There are opposite. 
So you have more meth So there 

979
00:52:26,700 --> 00:52:29,300
is a method to the madness, 
right? 

980
00:52:29,400 --> 00:52:32,700
You're trying to be consistent. 
You're trying to replicate, you 

981
00:52:32,700 --> 00:52:36,000
know, uncertainty, but you are 
trying to replicate a certain 

982
00:52:36,000 --> 00:52:38,100
process over a longer period of 
time. 

983
00:52:38,300 --> 00:52:42,000
And you think that overall that 
narrows the outcomes, right? 

984
00:52:42,100 --> 00:52:45,600
So again, they will meet, there 
is a Midway, its Spectrum. 

985
00:52:45,600 --> 00:52:49,200
It is not uniform, but on the 
right hand side in Bridge is 

986
00:52:49,200 --> 00:52:52,300
what I would call more and 
investing style and left hand 

987
00:52:52,300 --> 00:52:55,600
side is what I would call more 
trading Style. 

988
00:52:56,100 --> 00:52:57,900
And you know, it actually feeds 
into that. 

989
00:52:57,900 --> 00:53:01,700
I have seen historically in in 
my experience like most of the 

990
00:53:01,700 --> 00:53:05,500
Traders whom I would not you 
know, who know the things. 

991
00:53:05,500 --> 00:53:08,100
Well, the Traders are. 
Those people who actually know 

992
00:53:08,100 --> 00:53:11,400
their behavioral and behavior of
the other people around them. 

993
00:53:11,400 --> 00:53:14,500
They know the behavior of the 
market like they trade by gut 

994
00:53:15,100 --> 00:53:17,300
right and on the right hand 
side. 

995
00:53:17,300 --> 00:53:20,700
You have Kwan's who sure there 
is obviously a basis in 

996
00:53:20,700 --> 00:53:24,200
everything but they're you know,
the Renaissance and all those 

997
00:53:24,200 --> 00:53:25,900
things ranging from quants all 
the way. 

998
00:53:26,200 --> 00:53:28,800
What you're doing is you I like 
my as a Quant. 

999
00:53:28,800 --> 00:53:30,900
I like more trades. 
In fact, I like short term 

1000
00:53:30,900 --> 00:53:34,600
trades more trade because then 
I'm moving back my distribution 

1001
00:53:34,600 --> 00:53:36,800
and narrowing the outcomes, 
right? 

1002
00:53:36,800 --> 00:53:40,800
So that's the investment hat on 
the games and but playing 

1003
00:53:40,900 --> 00:53:44,700
uncertain incomplete information
games where the same sequence of

1004
00:53:44,700 --> 00:53:47,000
events. 
Don't lead to same outcome. 

1005
00:53:47,200 --> 00:53:51,700
I think for the kids. 
It's it must So actually I have 

1006
00:53:52,100 --> 00:53:53,600
this Parks, multiple thoughts 
for me. 

1007
00:53:53,600 --> 00:53:56,400
Actually one thing where when 
you spoke about Raiders and 

1008
00:53:56,400 --> 00:54:00,200
quants being partial to Bridget 
poker am reminded of this story,

1009
00:54:00,200 --> 00:54:04,800
again going back to the weekend 
of 13, 14 September 2008, where 

1010
00:54:04,800 --> 00:54:07,600
apparently they were trying to 
contact Bob Diamond. 

1011
00:54:07,600 --> 00:54:10,800
I think who was the CEO of 
Buckley's and he couldn't take 

1012
00:54:10,800 --> 00:54:13,700
the call of the other Bankers 
because he was busy playing 

1013
00:54:13,700 --> 00:54:15,500
Rich. 
That's the story in too big to 

1014
00:54:15,500 --> 00:54:19,100
fail. 
And yeah, I'd also like in some 

1015
00:54:19,100 --> 00:54:22,700
way like in Bridge The 
uncertainty that you deal with 

1016
00:54:22,700 --> 00:54:26,500
is the uncertainty with the of 
the lay of the cards, once the 

1017
00:54:26,500 --> 00:54:28,700
cards have been laid 
irrespective of who, your 

1018
00:54:28,700 --> 00:54:30,700
opponent is. 
I mean, some might like to 

1019
00:54:30,700 --> 00:54:33,300
finish more than the others. 
Some might like to play for 

1020
00:54:33,300 --> 00:54:36,500
something else, but more or less
you're playing the board rather 

1021
00:54:36,500 --> 00:54:38,900
than playing your opponent's. 
While in poker. 

1022
00:54:38,900 --> 00:54:42,300
I guess you're playing your 
opponent's far more than you're 

1023
00:54:42,300 --> 00:54:45,900
playing the lay of the kites. 
Absolutely that. 

1024
00:54:45,900 --> 00:54:46,800
That is true. 
Right. 

1025
00:54:46,800 --> 00:54:50,000
I mean also the number of cards 
like in a bridge, all 52 cards 

1026
00:54:50,000 --> 00:54:52,100
are on the deck right around the
table. 

1027
00:54:52,100 --> 00:54:55,400
You have it and you pay or on 
the air or on the table, right? 

1028
00:54:55,500 --> 00:54:58,800
And also, I mean, you know, that
the bridge Rue timing, right? 

1029
00:54:58,900 --> 00:55:01,600
A typical Bridge games takes 
about 7 minutes and they say 

1030
00:55:01,600 --> 00:55:04,600
that the first three minutes, 
we'll probably spent in bidding.

1031
00:55:04,800 --> 00:55:08,400
And then they say that, you 
know, once the lead happens on 

1032
00:55:08,400 --> 00:55:11,700
the dummy comes down, that is 
when the declarer need supposed 

1033
00:55:11,700 --> 00:55:15,000
to think, then that is when a 
maximum amount of Means a lot 

1034
00:55:15,000 --> 00:55:17,800
for everybody because everybody 
is thinking but afterwards in a 

1035
00:55:17,800 --> 00:55:20,400
professional, you know, the 
cards the next Forty thirteen 

1036
00:55:20,400 --> 00:55:23,000
cards, which go happen in a 
jiffy, right? 

1037
00:55:23,200 --> 00:55:26,800
And you also decide it's not 
like in Bridge, you always pay 

1038
00:55:26,800 --> 00:55:29,000
the probability. 
In fact, we are taught that in 

1039
00:55:29,000 --> 00:55:32,600
Bridge, you play to win, right? 
Even if it is a low probability.

1040
00:55:32,700 --> 00:55:35,400
There is a one way to play. 
You just play that because 

1041
00:55:35,400 --> 00:55:38,100
you're playing to win but that 
is subject to actually stop you 

1042
00:55:38,107 --> 00:55:41,100
here because you need me to this
other concept which is of what I

1043
00:55:41,100 --> 00:55:42,800
call is finite and infinite 
games. 

1044
00:55:43,200 --> 00:55:46,200
It's a beautiful book by the 
Written by a guy named James 

1045
00:55:46,200 --> 00:55:48,500
casts. 
He was a hero energy and I think

1046
00:55:48,500 --> 00:55:53,100
at Harvard, and it's a short 
book, but a beautiful book. 

1047
00:55:53,100 --> 00:55:56,600
So basically the concept is what
the title suggests is. 

1048
00:55:56,600 --> 00:55:59,000
The finite game. 
There's an infinite game in a 

1049
00:55:59,000 --> 00:56:03,800
finite game your you only 
capture you're playing games one

1050
00:56:03,800 --> 00:56:05,800
at a time. 
All that matters is for you to 

1051
00:56:05,800 --> 00:56:09,200
win the game. 
In an infinite, gave the 

1052
00:56:09,400 --> 00:56:11,900
objective of the game is to just
continue to play. 

1053
00:56:12,400 --> 00:56:17,200
So it's some things in Bridge, 
for example, even if I don't 

1054
00:56:17,200 --> 00:56:21,000
know, like, even if I let us 
say, we are playing a sort of a 

1055
00:56:21,000 --> 00:56:23,400
event or something, even if I go
seven down or whatever. 

1056
00:56:23,500 --> 00:56:26,400
It doesn't matter. 
I start the next hand at zero 

1057
00:56:27,400 --> 00:56:30,900
while in poker, if I lose all my
money, now, I can't play the 

1058
00:56:30,900 --> 00:56:33,900
next time, so it's a sort of a 
infinite game in that sense, 

1059
00:56:33,900 --> 00:56:36,400
right? 
It is in fact, that's why you 

1060
00:56:36,400 --> 00:56:39,200
change the way you play Bridges.
The, you know, there's Swiss 

1061
00:56:39,200 --> 00:56:42,800
pairs versus duplicate. 
You play slightly differently, 

1062
00:56:43,000 --> 00:56:45,800
right? 
The risk of going fi down is 

1063
00:56:45,800 --> 00:56:50,000
much bigger in imps in, you 
know, in duplicate bridge and it

1064
00:56:50,000 --> 00:56:52,600
will hurt you. 
Whereas, you know, my 14th 

1065
00:56:52,600 --> 00:56:55,200
ranked, if I'm let's say it, 14 
pairs, the 14th ranked will be 

1066
00:56:55,200 --> 00:56:57,400
14th, ranked and, you know, 
there's a difference in pairs 

1067
00:56:57,400 --> 00:56:59,800
and there's also, you know, 
where there's a Common Board 

1068
00:56:59,900 --> 00:57:02,400
against which you are compared. 
So that influences, right? 

1069
00:57:02,400 --> 00:57:06,100
That you're playing strategy 
changes based on the game. 

1070
00:57:06,100 --> 00:57:10,100
And the finite and infinite 
actually works very well and it 

1071
00:57:10,100 --> 00:57:15,300
is Aspect in fund management 
where if you don't know matter, 

1072
00:57:15,400 --> 00:57:20,800
I mean imagine that I have two 
returns 1 is minus 100 percent 

1073
00:57:20,800 --> 00:57:22,900
under in second is a plus 100 
percent. 

1074
00:57:22,900 --> 00:57:27,200
And in contrast, let's say I 
have a plus 10% under - 10 % are

1075
00:57:27,200 --> 00:57:29,300
thematically, both of them 
healed the same. 

1076
00:57:29,700 --> 00:57:33,300
But geometrically it is 0 
because it doesn't really 

1077
00:57:33,300 --> 00:57:35,500
matter. 
You you're dead in one case. 

1078
00:57:35,700 --> 00:57:38,900
So a lot of fund management goes
into the first Android hedge 

1079
00:57:38,900 --> 00:57:42,700
funds in some sense originally 
were Like you got to have that 

1080
00:57:42,700 --> 00:57:47,900
survival thing first before, you
know, if you are alive you can 

1081
00:57:47,900 --> 00:57:51,300
eat another day, right? 
You don't need a feast every 

1082
00:57:51,300 --> 00:57:53,600
day. 
First thing rule of any game is 

1083
00:57:53,600 --> 00:57:57,400
to survive. 
Now you have finite games and 

1084
00:57:57,400 --> 00:58:00,900
you have infinite games and 
Let's ignore agency conflict and

1085
00:58:00,900 --> 00:58:03,600
all those things. 
And suddenly you will find that 

1086
00:58:03,600 --> 00:58:07,500
fund management and all those 
things which are multiplicative 

1087
00:58:07,500 --> 00:58:09,800
in nature. 
You would find that these are 

1088
00:58:10,300 --> 00:58:13,500
you know, where you Defensive 
because you want to survive and 

1089
00:58:13,500 --> 00:58:17,600
you don't just play to win. 
But now contrast that with a 

1090
00:58:17,700 --> 00:58:21,500
agency conflict comes in where 
in a hedge fund or in any Bank, 

1091
00:58:21,600 --> 00:58:25,200
where the guy is downside, is 
limited to the salary that he 

1092
00:58:25,200 --> 00:58:28,900
has been paid, right earlier. 
And even that was not the case, 

1093
00:58:29,100 --> 00:58:31,300
they would not, they would know 
clawbacks, but currently there 

1094
00:58:31,300 --> 00:58:33,200
are clawbacks, right? 
So you the same. 

1095
00:58:33,300 --> 00:58:36,300
So what they would do is they 
would take an enormous amount of

1096
00:58:36,300 --> 00:58:39,700
risk because inherently what 
they would convert is, they 

1097
00:58:39,700 --> 00:58:44,000
would convert this into An 
infinite set of finite games 

1098
00:58:44,300 --> 00:58:47,700
because you have a job. 
You would go, you would play you

1099
00:58:47,700 --> 00:58:50,400
play to win. 
If it doesn't, you get fired. 

1100
00:58:50,400 --> 00:58:53,100
You go find another job. 
So you are just sequentially, 

1101
00:58:53,100 --> 00:58:55,000
buying options, which is good 
for you. 

1102
00:58:55,100 --> 00:58:56,500
Right? 
And that's how you make money. 

1103
00:58:57,000 --> 00:59:00,100
You are effectively gaming, the 
system by converting what 

1104
00:59:00,100 --> 00:59:03,300
appears to be. 
If, you know, the finite not 

1105
00:59:03,300 --> 00:59:06,100
necessarily an infinite game, 
you're converting it into a 

1106
00:59:06,107 --> 00:59:09,700
bunch of finite infinite game or
rather in finite, finite games. 

1107
00:59:09,900 --> 00:59:12,800
And you know, Grabbing value, 
that is how most of the money 

1108
00:59:12,800 --> 00:59:16,100
was made in finance from. 
Let's say it 1990s all the way 

1109
00:59:16,100 --> 00:59:19,600
till 2010 Stephen probably, now 
little even 2020s. 

1110
00:59:20,600 --> 00:59:22,900
So, one of the other things I 
was thinking about, I keep 

1111
00:59:22,900 --> 00:59:25,000
thinking about risk and logical 
fallacies, right? 

1112
00:59:25,000 --> 00:59:27,800
Sometimes I think, I think one 
of the things that we, as humans

1113
00:59:28,100 --> 00:59:31,700
sort of don't do very well, is 
to, in, a lot of cases is to 

1114
00:59:31,700 --> 00:59:34,700
assess the risk. 
Some of the times we sort of, 

1115
00:59:34,700 --> 00:59:36,400
sort of, like, we use small 
samples. 

1116
00:59:36,400 --> 00:59:41,000
They will, once I went once I 
invested in the stock market, 

1117
00:59:41,100 --> 00:59:42,800
And I lost ten percent of my 
money. 

1118
00:59:42,800 --> 00:59:44,300
So I'm never investing in the 
stock market. 

1119
00:59:44,300 --> 00:59:45,800
Again, you look at small 
samples. 

1120
00:59:46,200 --> 00:59:48,400
You look at selection bias, you 
look at all these logical 

1121
00:59:48,400 --> 00:59:50,400
fallacy. 
So I will singing it will call 

1122
00:59:50,400 --> 00:59:53,600
context of our recent discussion
on finite and infinite Games 

1123
00:59:54,400 --> 00:59:57,900
movies to a pretty bad job of 
teaching us risk because most 

1124
00:59:57,900 --> 01:00:01,100
movies by definition are finite 
gains the whatever. 

1125
01:00:01,100 --> 01:00:04,200
The plot of the movie is it it's
like maybe the hero is in 

1126
01:00:04,200 --> 01:00:06,900
trouble, the plot of the movie 
is for him to get out of 

1127
01:00:06,900 --> 01:00:08,000
trouble, by the end of the 
movie. 

1128
01:00:08,000 --> 01:00:10,600
There's a finite game for this 
it finish. 

1129
01:00:10,700 --> 01:00:13,600
Which You to get out of which 
means that you take all sorts of

1130
01:00:13,600 --> 01:00:15,500
bliss. 
Can you do all sorts of sort of 

1131
01:00:15,500 --> 01:00:17,800
heroic things and stuff and you 
get out? 

1132
01:00:17,900 --> 01:00:20,800
But what they don't tell you is 
the, what happens next II mean, 

1133
01:00:20,800 --> 01:00:22,400
unless there's a sequel of 
course by itself. 

1134
01:00:22,800 --> 01:00:25,500
In that sense. 
We don't do a good job, CT. 

1135
01:00:25,500 --> 01:00:27,500
Uracil it movies. 
Absolutely not. 

1136
01:00:27,500 --> 01:00:30,700
I mean movies will teach you 
that romance is probably one of 

1137
01:00:30,700 --> 01:00:33,000
the most beautiful things in the
world, but what they don't tell 

1138
01:00:33,000 --> 01:00:35,700
you is, I mean other than a few 
where there is a certain amount 

1139
01:00:35,700 --> 01:00:38,900
of friction, which always 
exists, you know, no matter what

1140
01:00:38,900 --> 01:00:41,300
between any two, people friction
have incomes but in Because you 

1141
01:00:41,300 --> 01:00:43,600
won't even leave that, that 
happens, right? 

1142
01:00:43,600 --> 01:00:46,300
Or they would make you believe 
that is one hero who will come. 

1143
01:00:46,300 --> 01:00:48,000
And, you know, we like to 
imagine, see there are 

1144
01:00:48,600 --> 01:00:52,000
originally or anywhere stories 
movies. 

1145
01:00:52,000 --> 01:00:54,300
They're all meant to be 
exaggerations. 

1146
01:00:55,600 --> 01:01:00,800
I hate, but what we mistake is 
often exaggerations create a 

1147
01:01:00,800 --> 01:01:03,700
certain amount frequency of that
makes it kind of normalize this 

1148
01:01:03,700 --> 01:01:06,200
things, right? 
It is your most common thing 

1149
01:01:06,200 --> 01:01:08,100
other waiting is right. 
Imagine. 

1150
01:01:08,600 --> 01:01:11,700
The very widely used code man. 
Bites dog. 

1151
01:01:11,700 --> 01:01:17,300
Was his dog bites man. 
Right now, if imagine if I 

1152
01:01:17,300 --> 01:01:21,300
sample, if somebody is samples 
all the newspapers historically,

1153
01:01:21,700 --> 01:01:24,900
they would find that most of the
news. 

1154
01:01:25,200 --> 01:01:28,400
Would always be there will be 
bad news, right? 

1155
01:01:28,500 --> 01:01:33,800
Or will be man biting dog and 
somebody will not get a real 

1156
01:01:33,800 --> 01:01:35,900
distribution of how often dogs 
bite, man. 

1157
01:01:36,300 --> 01:01:40,600
And the simple reason is that 
they are not meant to give you 

1158
01:01:40,600 --> 01:01:43,700
information. 
They are meant to trigger some 

1159
01:01:43,700 --> 01:01:46,700
reactions in you. 
Right here meant to trigger your

1160
01:01:46,700 --> 01:01:49,300
interest. 
We confuse them for being 

1161
01:01:49,300 --> 01:01:52,800
providing information and being 
representative of a real world, 

1162
01:01:52,800 --> 01:01:55,200
which they are not. 
Yeah, I'd actually this get Is 

1163
01:01:55,200 --> 01:01:58,200
it social media? 
Because at least the newspaper, 

1164
01:01:58,200 --> 01:02:02,000
which is why I sort of off late 
rely on broadsheet newspapers to

1165
01:02:02,000 --> 01:02:05,100
get menus rather than social 
media because they at least they

1166
01:02:05,100 --> 01:02:07,600
give you a distribution. 
They talk about everything 

1167
01:02:07,600 --> 01:02:11,300
that's happening in the world. 
They might be on average - but 

1168
01:02:11,400 --> 01:02:13,400
overall, it's hedged. 
But if you go to social media, 

1169
01:02:13,400 --> 01:02:16,100
they'll be one topic of the day.
And like you think that's the 

1170
01:02:16,100 --> 01:02:18,100
most important thing in the 
world today and tomorrow will be

1171
01:02:18,100 --> 01:02:20,000
something else. 
Exactly? 

1172
01:02:20,000 --> 01:02:23,300
Right, so that it completely 
distorts your perception, right?

1173
01:02:23,400 --> 01:02:26,200
Which is all the more important 
that Not get. 

1174
01:02:26,900 --> 01:02:29,000
It is very important. 
And, you know, the biggest 

1175
01:02:29,000 --> 01:02:33,300
challenge in risk management is 
actually not managing risk. 

1176
01:02:33,400 --> 01:02:35,500
It is in knowing that you have 
risk. 

1177
01:02:35,800 --> 01:02:40,000
That is the fundamental and most
basic thing, which most people. 

1178
01:02:40,300 --> 01:02:42,500
I mean, even in people who are 
supposedly, professional Risk 

1179
01:02:42,500 --> 01:02:46,000
Managers, they would always tend
to get short sided be can, you 

1180
01:02:46,000 --> 01:02:49,600
know? 
Because he thinks like it is the

1181
01:02:49,600 --> 01:02:52,300
second third multi order 
effects, which come back like 

1182
01:02:52,300 --> 01:02:54,700
the Algos when social media was 
invented. 

1183
01:02:54,700 --> 01:02:57,100
It was Invented for something. 
Then it became something. 

1184
01:02:57,200 --> 01:03:00,800
It is aimed to gather clicks. 
It is aim to gather certain and 

1185
01:03:00,800 --> 01:03:04,200
we will see the impact of on the
kids generation and all that the

1186
01:03:04,200 --> 01:03:07,400
attention span DK, which you 
will find, right? 

1187
01:03:07,500 --> 01:03:11,600
It's all will come to us in some
years, down the line. 

1188
01:03:11,700 --> 01:03:13,000
Now, there are some good things 
about it. 

1189
01:03:13,000 --> 01:03:15,400
Obviously without that, they 
will not be, but they're all 

1190
01:03:15,700 --> 01:03:17,300
again. 
When we speak of risk in real 

1191
01:03:17,300 --> 01:03:18,300
world. 
We normally talk about the 

1192
01:03:18,300 --> 01:03:20,000
downsides, not about the 
upsides, right? 

1193
01:03:21,000 --> 01:03:25,000
So that is definitely right. 
So these are all factors. 

1194
01:03:25,100 --> 01:03:28,200
This is the fallacy of you 
observing and thinking that you 

1195
01:03:28,200 --> 01:03:30,000
are a representative. 
Right? 

1196
01:03:30,000 --> 01:03:32,300
I mean I once tweeted about this
angle, right? 

1197
01:03:32,300 --> 01:03:36,600
I would be a bad Equity analyst 
because I am in one of the 

1198
01:03:36,600 --> 01:03:39,600
standard ways is, you know, you 
want to find what people will 

1199
01:03:39,600 --> 01:03:42,400
consume, what people will this 
thing etcetera. 

1200
01:03:42,500 --> 01:03:47,600
And I mean, you know me and you 
know, you be so you know that as

1201
01:03:47,600 --> 01:03:50,800
a people we generally don't like
there is very little that you 

1202
01:03:50,800 --> 01:03:54,200
would want and you would fallacy
is that you think most of the 

1203
01:03:54,200 --> 01:03:55,600
people in the world are Like 
you. 

1204
01:03:55,700 --> 01:03:59,000
And I imagine animated when I 
started, Facebook was listed and

1205
01:03:59,000 --> 01:04:01,800
I saw it fall, I said it is true
because I would never spend my 

1206
01:04:01,800 --> 01:04:04,100
time on Facebook. 
I still don't spend my time on 

1207
01:04:04,100 --> 01:04:07,800
Facebook, but that's a good 
stock to buy because a lot of 

1208
01:04:07,800 --> 01:04:11,000
people who do that. 
So using yourself as a 

1209
01:04:11,000 --> 01:04:14,300
representative sample of the 
world, using your, you know, 

1210
01:04:14,400 --> 01:04:18,900
that your experience is somehow.
He's The Ensemble experience and

1211
01:04:18,900 --> 01:04:21,500
I think we should really talk 
about ergodicity after when we 

1212
01:04:21,500 --> 01:04:24,800
use the word Ensemble, is these 
are all the standard things that

1213
01:04:24,800 --> 01:04:27,900
we In risks and these are the 
things we do mistakes and then 

1214
01:04:27,900 --> 01:04:32,100
therefore the ability to manage 
risk completely, you know, goes 

1215
01:04:32,100 --> 01:04:34,800
Haywire. 
Right. 

1216
01:04:35,000 --> 01:04:37,900
Now our God is it e is actually 
a principle. 

1217
01:04:37,900 --> 01:04:40,700
Which is it's a it's a complex 
thing, right? 

1218
01:04:40,700 --> 01:04:44,200
It is again, it is you're 
talking amount about F of 

1219
01:04:44,300 --> 01:04:47,000
expectation of X versus 
expectation of f of x. 

1220
01:04:47,000 --> 01:04:51,100
Now, just add one more element 
called, time into it, it and 

1221
01:04:51,100 --> 01:04:53,300
understanding ergodicity, 
really? 

1222
01:04:53,300 --> 01:04:54,900
If you wince, you understand, 
it. 

1223
01:04:54,900 --> 01:05:00,400
It is a brilliant concept. 
And tells you how, why, and how 

1224
01:05:00,400 --> 01:05:03,200
can risk be managed and risk? 
Be transformed and so on. 

1225
01:05:03,400 --> 01:05:06,800
I mean the most obvious example 
I will take is as follows. 

1226
01:05:07,100 --> 01:05:12,200
Imagine that there is a sum game
happening in a carnival where 

1227
01:05:12,200 --> 01:05:16,500
they are playing Russian 
roulette' and you know, they're 

1228
01:05:16,500 --> 01:05:19,300
giving to do, they'll take one 
dollars for a bit and two 

1229
01:05:19,300 --> 01:05:21,700
dollars. 
If you come back alive, right? 

1230
01:05:22,100 --> 01:05:23,900
Then you get two dollars if you 
come back alive. 

1231
01:05:24,300 --> 01:05:30,100
Now if I had a clone army, like 
I'm the Star Wars guy and I had 

1232
01:05:30,100 --> 01:05:33,300
a clone me. 
All I would do is I would keep 

1233
01:05:33,400 --> 01:05:35,900
keep like every instance round. 
Let's call it. 

1234
01:05:35,900 --> 01:05:38,900
Six is equal to one round and 
every instance. 

1235
01:05:38,900 --> 01:05:41,400
I would send, six people go each
of them. 

1236
01:05:41,400 --> 01:05:44,100
I'll give one dollar. 
Five of them will come back and 

1237
01:05:44,100 --> 01:05:46,400
I will get $10. 
So I'm making a four dollar 

1238
01:05:46,400 --> 01:05:50,200
profit and I would repeat this 
ad infinitum, right? 

1239
01:05:50,300 --> 01:05:53,800
So if you ask me, what is my 
expected profit in one round, it

1240
01:05:53,800 --> 01:05:57,300
is four dollars, right? 
My long-term expected value is 

1241
01:05:57,300 --> 01:06:00,700
infinity because I have a clone 
army and I can keep doing this 

1242
01:06:00,700 --> 01:06:04,300
forever right now. 
Is the equation? 

1243
01:06:04,300 --> 01:06:06,500
I'm not in Star Wars world and 
it's just me. 

1244
01:06:07,000 --> 01:06:08,800
Now. 
You ask me if I will go and do 

1245
01:06:08,800 --> 01:06:12,000
it. 
The answer is no by your 

1246
01:06:12,000 --> 01:06:15,000
long-term expected value is 0 
after six shots. 

1247
01:06:15,000 --> 01:06:17,900
You were even if your luck 
favours and but 60 short, you go

1248
01:06:17,900 --> 01:06:19,500
to die. 
I hate. 

1249
01:06:19,800 --> 01:06:22,900
So once you die, it doesn't 
matter what your money is, your 

1250
01:06:22,900 --> 01:06:26,900
it's zero. 
So the point is the time average

1251
01:06:27,500 --> 01:06:31,300
for a single person is different
from The Ensemble average, 

1252
01:06:31,600 --> 01:06:33,300
right, which is a cross 
sectional average. 

1253
01:06:33,400 --> 01:06:37,000
Courage and it is this 
difference, which is what you 

1254
01:06:37,000 --> 01:06:37,600
would call. 
Like. 

1255
01:06:37,600 --> 01:06:41,300
My experience on time is very 
different from a cross-sections 

1256
01:06:41,300 --> 01:06:43,800
experience and the utility 
functions on all these things, 

1257
01:06:43,800 --> 01:06:46,400
right? 
And coming back to the original 

1258
01:06:46,400 --> 01:06:49,900
point. 
We have only one life if we have

1259
01:06:49,900 --> 01:06:52,100
one life. 
The value of that life is 

1260
01:06:52,200 --> 01:06:55,500
immense for us for the insurance
company. 

1261
01:06:55,700 --> 01:06:59,400
You and I are same as any Tom 
Dick and Harry in any part of 

1262
01:06:59,400 --> 01:07:01,600
the world. 
So they have some correlations 

1263
01:07:01,600 --> 01:07:05,100
between based on some geography.
Is and Healthy Lifestyles and so

1264
01:07:05,100 --> 01:07:07,400
on. 
But otherwise what you are doing

1265
01:07:07,400 --> 01:07:11,000
by buying insurance is you are 
converting your time average 

1266
01:07:11,000 --> 01:07:14,300
risk and translating it into an 
ensemble average risk for 

1267
01:07:14,300 --> 01:07:17,000
somebody else. 
Well, it's over. 

1268
01:07:17,100 --> 01:07:19,700
Now. 
I think one of the ways in which

1269
01:07:19,700 --> 01:07:22,500
I think, people try to manage 
this cutting, right is to kind 

1270
01:07:22,500 --> 01:07:24,900
of start having. 
I mean, typically when you want 

1271
01:07:24,900 --> 01:07:27,300
to manage something, they say 
that you cannot manage something

1272
01:07:27,300 --> 01:07:30,600
that you cannot measure it. 
So you start measuring it and 

1273
01:07:30,600 --> 01:07:33,200
then you come up with certain 
Matrix, so too. 

1274
01:07:33,400 --> 01:07:36,800
For the lack of a better term. 
And with all puns intended. 

1275
01:07:36,800 --> 01:07:41,100
Let's call it risk Matrix. 
Okay, which is I think I think 

1276
01:07:41,100 --> 01:07:43,700
it was initially started at JP 
Morgan in the mid-90s and then 

1277
01:07:43,700 --> 01:07:46,600
it was spun off as a separate 
company, which introduced this 

1278
01:07:46,600 --> 01:07:50,300
call concept of VAR. 
There is value at risk, which is

1279
01:07:50,300 --> 01:07:56,300
that Why, what is the maximum 
amount of money that I can lose 

1280
01:07:57,000 --> 01:08:01,200
in the left five percent of the 
time or something? 

1281
01:08:01,200 --> 01:08:02,100
It is something like that, 
right? 

1282
01:08:02,100 --> 01:08:05,800
So can you talk about risk 
Matrix in a generic term and the

1283
01:08:06,100 --> 01:08:10,800
concept of VAR and what happens 
when you have a matrix like this

1284
01:08:10,800 --> 01:08:14,700
to measure risk? 
Now, this is actually one of my 

1285
01:08:14,700 --> 01:08:18,300
favorite topics in the sense 
that when people and risk and 

1286
01:08:18,300 --> 01:08:21,000
they start talking about it. 
And, you know, in the fund, we 

1287
01:08:21,000 --> 01:08:24,899
get these, we need to present to
our investors and clients. 

1288
01:08:24,899 --> 01:08:28,000
And, you know, I take pains to 
say that these metrics while 

1289
01:08:28,000 --> 01:08:30,300
they are visible is actually not
our key things. 

1290
01:08:30,300 --> 01:08:33,399
The key metrics in our fund is 
various other things. 

1291
01:08:33,399 --> 01:08:34,899
Like, you know, we have to 
manage liquidity. 

1292
01:08:34,899 --> 01:08:39,399
We have to manage regulatory, 
which not necessarily do not 

1293
01:08:39,399 --> 01:08:43,600
have a quantifiable things, but 
there is a great Fascination 

1294
01:08:43,700 --> 01:08:47,300
about measuring things, which is
good when there is a logic Merit

1295
01:08:47,300 --> 01:08:52,000
behind it, but what typically 
happens is, once you measure 

1296
01:08:52,000 --> 01:08:55,300
something, you also get comfort 
with something and once you get 

1297
01:08:55,300 --> 01:08:58,899
comfort you then think that the 
measure is be all and end all 

1298
01:08:59,200 --> 01:09:01,000
you know, it's one of my 
favorite laws, which is that 

1299
01:09:01,000 --> 01:09:04,200
good Hearts law, right, which is
once use what gets measured 

1300
01:09:04,200 --> 01:09:07,399
starts getting managed and it 
also starts influencing your 

1301
01:09:07,399 --> 01:09:10,300
behavior value at risk. 
The way it is, measured is very 

1302
01:09:10,300 --> 01:09:13,000
simple. 
It is like you take your Leo 

1303
01:09:13,000 --> 01:09:16,000
either you run Monte Carlo, 
simulations, or you run 

1304
01:09:16,600 --> 01:09:19,600
historical simulations or you 
use implied volatility, is 

1305
01:09:19,608 --> 01:09:21,500
there. 
Many ways to slice the cat 

1306
01:09:21,899 --> 01:09:26,100
bread, right? 
So but what they do is they say 

1307
01:09:26,100 --> 01:09:30,700
that okay, 95% of our what is 
the downside risk that happens 

1308
01:09:30,800 --> 01:09:33,700
once in 20 days? 
And you want to have that as a 

1309
01:09:33,700 --> 01:09:37,500
measure because that in some 
sense gives you okay. 

1310
01:09:37,500 --> 01:09:40,700
If that measure is increasing it
means you are taking greater 

1311
01:09:40,700 --> 01:09:45,300
risk and that is correct. 
And it's a good metric in that 

1312
01:09:45,300 --> 01:09:48,100
fashion. 
Now what typically happens is 

1313
01:09:48,700 --> 01:09:51,899
you think that 95 measure then 
you think that that is 

1314
01:09:51,899 --> 01:09:55,200
somewhere, it gets normalized, 
then people. 

1315
01:09:55,400 --> 01:09:58,700
You don't realize that actually 
that means that it is probably 

1316
01:09:58,700 --> 01:10:02,300
the Minima in some sense, right?
It also assumes that there is a 

1317
01:10:02,300 --> 01:10:05,400
normal distribution, right? 
So sometimes what would happen 

1318
01:10:05,400 --> 01:10:10,500
is your 95% of our gets hit in 
three consecutive days, and then

1319
01:10:10,500 --> 01:10:12,500
your people is like it is 
supposed to happen one. 

1320
01:10:12,600 --> 01:10:15,600
In 20 days, I mean, why exactly 
once a month, you know, why are 

1321
01:10:15,600 --> 01:10:19,200
we having three kinds of things?
But that's not the the so that 

1322
01:10:19,200 --> 01:10:22,600
is where from you're having a 
metric, not understanding the 

1323
01:10:22,600 --> 01:10:24,800
metric, and the limitations of 
it comes into place. 

1324
01:10:25,100 --> 01:10:29,000
Right? 
And so, that is a single biggest

1325
01:10:29,000 --> 01:10:30,400
challenge. 
I mean, whether it falls in the 

1326
01:10:30,400 --> 01:10:34,100
fallacy of under, you know, or 
whether it is in understanding, 

1327
01:10:34,100 --> 01:10:36,000
lack of understanding, whichever
way it is. 

1328
01:10:36,200 --> 01:10:40,200
So you have these metrics and 
you don't and then you realize a

1329
01:10:40,200 --> 01:10:42,500
post an event that this war by 
itself. 

1330
01:10:42,700 --> 01:10:46,700
Ridiculous or not useful, right?
And it's actually not, the 

1331
01:10:46,700 --> 01:10:50,800
problem of VAR bar is doing what
it is supposed to it. 

1332
01:10:50,800 --> 01:10:53,700
Is you who didn't understand? 
What were its limitations, 

1333
01:10:53,700 --> 01:10:55,600
Right? 
Is coming back to the quants. 

1334
01:10:55,700 --> 01:10:58,300
You need to know as a model, 
when a model. 

1335
01:10:58,300 --> 01:11:01,300
So what's been somebody use me. 
I mean, we do have internal 

1336
01:11:02,000 --> 01:11:04,800
points and we do model building.
And one of the first questions I

1337
01:11:04,800 --> 01:11:07,900
ask is not what are the returns 
and what are these things I 

1338
01:11:07,907 --> 01:11:11,200
asked when will you fail? 
Right. 

1339
01:11:11,300 --> 01:11:17,200
So remember our favorite XKCD 
comic, right, which is you stir 

1340
01:11:17,200 --> 01:11:19,900
and of data and then you get the
results that you want. 

1341
01:11:20,000 --> 01:11:22,000
So there are two kinds of 
modeling, right? 

1342
01:11:22,000 --> 01:11:25,900
One is you stir the data and 
then you get a result second is 

1343
01:11:25,900 --> 01:11:28,500
you have an hypothesis and then 
you build a model and you get a 

1344
01:11:28,500 --> 01:11:29,600
result. 
Right? 

1345
01:11:30,100 --> 01:11:34,500
The first one is a random via 
things but Algos use that so 

1346
01:11:34,500 --> 01:11:39,000
typically you want to have risk 
Matrix which compensate for it, 

1347
01:11:39,000 --> 01:11:41,800
which is those Horse, which are 
data-driven. 

1348
01:11:42,000 --> 01:11:45,000
You want them to be high sharp, 
right? 

1349
01:11:45,000 --> 01:11:47,000
So high frequency quantile goes 
will have. 

1350
01:11:47,000 --> 01:11:50,100
Hi Char because High sharp is 
essentially saying that I have 

1351
01:11:50,100 --> 01:11:52,200
low volatility and higher 
returns. 

1352
01:11:52,400 --> 01:11:55,000
So I'm getting better risk, 
adjusted return, but it is not 

1353
01:11:55,000 --> 01:11:57,300
really better risk. 
Adjusted return it is like 

1354
01:11:57,600 --> 01:12:01,300
because the way risk is measured
is volatility and volatility is 

1355
01:12:01,300 --> 01:12:04,900
measured in short term duration,
which by itself will not capture

1356
01:12:04,900 --> 01:12:06,700
tails. 
You know, that standard 

1357
01:12:06,700 --> 01:12:09,800
deviation is good only for a 
normal distribution, right? 

1358
01:12:09,900 --> 01:12:12,000
I mean, you have Distribution, 
which don't even have standard 

1359
01:12:12,000 --> 01:12:16,300
deviation exactly, right? 
So, to compensate for that, in 

1360
01:12:16,300 --> 01:12:18,300
some sense. 
It has become like a proxy 

1361
01:12:18,300 --> 01:12:21,100
black-scholes where it becomes a
language, you sharp becomes a 

1362
01:12:21,400 --> 01:12:23,600
language rather than a metric by
itself. 

1363
01:12:23,700 --> 01:12:27,700
So if there is a high frequency 
Quant, where I don't know when 

1364
01:12:27,700 --> 01:12:29,800
it doesn't work on, it is being 
driven by data. 

1365
01:12:30,000 --> 01:12:32,900
I want a high shop. 
I want to maybe three or a six. 

1366
01:12:33,000 --> 01:12:36,500
Depends on different methods and
logic but you want that? 

1367
01:12:36,900 --> 01:12:39,800
And the reason is effectively, 
you know, that there is a hidden

1368
01:12:39,800 --> 01:12:42,100
risk that you are. 
Measuring and it will break 

1369
01:12:42,100 --> 01:12:43,700
down. 
It will cost you money. 

1370
01:12:43,900 --> 01:12:46,700
And you want a compensation for 
that in contrast. 

1371
01:12:46,700 --> 01:12:49,100
Let's imagine that there is a 
model driven, like a bridge 

1372
01:12:49,100 --> 01:12:53,500
water or, you know, you know 
other people who build it. 

1373
01:12:53,800 --> 01:12:56,200
There. 
There is a certain element of 

1374
01:12:56,200 --> 01:13:00,100
robustness, which comes in two 
models will feign inherently, 

1375
01:13:00,300 --> 01:13:02,300
you know, that these are the 
things which don't work. 

1376
01:13:02,300 --> 01:13:05,200
It already has high wall in some
sense. 

1377
01:13:05,300 --> 01:13:09,200
High wall is a measure of 
robustness if you see the 

1378
01:13:09,200 --> 01:13:14,100
difference over there. 
Right, so it's ironical, but in 

1379
01:13:14,100 --> 01:13:15,800
some sense, it is a measure of 
robustness. 

1380
01:13:16,000 --> 01:13:17,700
You would think that because it 
is high wall. 

1381
01:13:17,700 --> 01:13:21,100
You would have seen all possible
scenarios and because it is 

1382
01:13:21,100 --> 01:13:24,100
model driven or whatever it is. 
And therefore, you will have a 

1383
01:13:24,100 --> 01:13:27,100
lower sharp threshold for those 
things, right? 

1384
01:13:27,200 --> 01:13:30,400
We all invest in equities, and 
equities have a sharp ranging 

1385
01:13:30,400 --> 01:13:35,100
from point 5 2 .8, right. 
Whereas, if I were to invest in 

1386
01:13:35,100 --> 01:13:38,300
a hedge fund, I probably would 
demand a much higher Sharpe 

1387
01:13:38,300 --> 01:13:40,500
because there is an unknown risk
element over there. 

1388
01:13:40,900 --> 01:13:43,200
Right inequities. 
It's visible. 

1389
01:13:43,400 --> 01:13:48,000
It's this thing and so on you're
talking about unknown risks. 

1390
01:13:48,000 --> 01:13:49,500
Now. 
We started talking about the 

1391
01:13:49,500 --> 01:13:53,900
2008 financial crisis because 
you were sort of involved in it,

1392
01:13:53,900 --> 01:13:57,400
in some sense like you're on the
floor there, but it's putting 

1393
01:13:57,400 --> 01:13:59,300
those two together soon after 
the crisis. 

1394
01:13:59,300 --> 01:14:01,500
I remember one, one of the 
popular magazines either, 

1395
01:14:01,500 --> 01:14:03,500
Vanity. 
Fair or wired or someone, they 

1396
01:14:03,500 --> 01:14:07,500
published an article called the 
formula that brought down Wall 

1397
01:14:07,500 --> 01:14:10,900
Street, and this was something 
called the gaussian copula or I 

1398
01:14:10,907 --> 01:14:14,600
think this was, I this brings me
to this concept of correlation, 

1399
01:14:14,600 --> 01:14:16,900
which I think we have not spoken
about. 

1400
01:14:17,400 --> 01:14:19,900
So, because I think what 
happened then was that, like I 

1401
01:14:19,900 --> 01:14:24,700
think the gaussian copula had 
been used to sort of, like, in 

1402
01:14:24,700 --> 01:14:29,000
some way, quantify correlations 
between different assets and 

1403
01:14:29,000 --> 01:14:31,600
then the regime change the 
correlations change like that, 

1404
01:14:31,600 --> 01:14:34,600
led to the failure of a lot of 
models and things like that. 

1405
01:14:34,600 --> 01:14:38,200
So can we talk a little bit 
about correlation? 

1406
01:14:38,400 --> 01:14:43,300
I mean, This is a tricky topic. 
I mean it is also not 

1407
01:14:43,300 --> 01:14:46,000
necessarily so I don't know how 
deep in depth. 

1408
01:14:46,000 --> 01:14:51,400
We want to go here, but see 
effectively everything is about 

1409
01:14:51,400 --> 01:14:53,100
modeling. 
In fact, especially in financial

1410
01:14:53,100 --> 01:14:54,900
things. 
There is a behavior that is a 

1411
01:14:54,900 --> 01:14:57,900
pattern that you want to model 
in subprime crisis. 

1412
01:14:57,900 --> 01:15:01,100
You had your packaging 
Securities together, you're 

1413
01:15:01,100 --> 01:15:04,600
saying that the Securities 
Behavior will behave in certain 

1414
01:15:04,600 --> 01:15:06,800
fashion. 
So already there is a this thing

1415
01:15:07,000 --> 01:15:09,000
collateralization and giving 
cash flows. 

1416
01:15:09,300 --> 01:15:12,100
And then you knew have another 
package where you were putting 

1417
01:15:12,100 --> 01:15:14,300
on top of it. 
So what you are doing is copulas

1418
01:15:14,300 --> 01:15:17,900
as you know, I mean again for 
this thing is our functions in a

1419
01:15:17,907 --> 01:15:20,400
correlation functions between 
two variables, right? 

1420
01:15:20,700 --> 01:15:23,300
But now they are in some sense 
normalized. 

1421
01:15:23,300 --> 01:15:25,400
Gaussian copula has our simple 
functions. 

1422
01:15:26,200 --> 01:15:29,000
What they don't have is they 
don't take into account. 

1423
01:15:29,000 --> 01:15:31,800
They are in some sense. 
There's a randomized correlation

1424
01:15:31,800 --> 01:15:33,700
function, right? 
With the normal distribution and

1425
01:15:33,700 --> 01:15:36,700
blah, blah, blah, but what 
typically happens is again. 

1426
01:15:36,800 --> 01:15:40,600
This is where understanding the 
Right, when initially, when you 

1427
01:15:40,600 --> 01:15:44,300
spoke about how do I understand?
Tailed distributions tailed 

1428
01:15:44,300 --> 01:15:46,100
distributions. 
Are best understood in 

1429
01:15:46,100 --> 01:15:48,800
understanding from figuring out 
our, their Auto correlative 

1430
01:15:48,800 --> 01:15:50,900
effects, are their Network 
defects, right? 

1431
01:15:50,900 --> 01:15:53,700
Whether it is from the VC world 
or an fa, you know, my hair 

1432
01:15:53,800 --> 01:15:56,800
Financial world or whatever. 
It is, need to understand that 

1433
01:15:57,100 --> 01:16:01,300
correlation has ask you, like, 
how volatility has asked you or 

1434
01:16:01,300 --> 01:16:04,100
volatility is, you know, 
considered heteroscedastic. 

1435
01:16:04,100 --> 01:16:06,900
And you know, it is auto 
correlative nature, low wall 

1436
01:16:06,900 --> 01:16:09,200
brings low wall and high, 
volatility brings highwomen. 

1437
01:16:09,300 --> 01:16:12,200
Volatility right? 
There is a correlation effect in

1438
01:16:12,600 --> 01:16:15,600
similarly correlation or the 
correlation. 

1439
01:16:15,600 --> 01:16:19,700
Also has asked you when 
so-called risk assets. 

1440
01:16:20,100 --> 01:16:22,200
They all tend to go down 
together. 

1441
01:16:22,700 --> 01:16:25,600
Is it logical? 
Probably not, but does it 

1442
01:16:25,600 --> 01:16:27,900
happen? 
The answer is yes, right. 

1443
01:16:28,100 --> 01:16:32,300
So imagine to give you an idea. 
I mean, we priced options. 

1444
01:16:32,300 --> 01:16:35,700
We I and Lehman and Barclays. 
I used to trade this multi 

1445
01:16:35,700 --> 01:16:39,200
currency options, right? 
If a multi currency option. 

1446
01:16:39,400 --> 01:16:42,300
Hide strikes, which are what are
called at the money, which is 

1447
01:16:42,300 --> 01:16:45,200
current spot level. 
The correlations are different, 

1448
01:16:45,200 --> 01:16:47,500
right? 
They are X like dollar. 

1449
01:16:47,500 --> 01:16:51,400
If imagine that I'm doing dollar
dollar against rupee dollar 

1450
01:16:51,400 --> 01:16:54,000
against China as an simpler 
example. 

1451
01:16:54,300 --> 01:16:58,400
Right now in current benign 
environment world, you would 

1452
01:16:58,400 --> 01:17:00,400
think that China and India 
slightly. 

1453
01:17:00,500 --> 01:17:03,000
Yes, they are Emerging Markets. 
Therefore they are correlated, 

1454
01:17:03,000 --> 01:17:06,900
but they are not so correlated. 
That is it slightly, you know, 

1455
01:17:06,900 --> 01:17:11,900
it's like a dog and Drunkard 
with a positive 20 percent 

1456
01:17:11,900 --> 01:17:15,400
correlation write that kind of a
behavior is what you would 

1457
01:17:15,400 --> 01:17:19,800
expect and you would price. 
But if somebody says that, I 

1458
01:17:19,800 --> 01:17:23,500
want to price an option between 
dollar China at 7 and dollar 

1459
01:17:23,500 --> 01:17:28,300
rupee at 80 together, right? 
If I use today is correlation. 

1460
01:17:28,600 --> 01:17:32,600
I am massively underpricing it 
because if China goes to seven 

1461
01:17:32,600 --> 01:17:36,400
dollar China goes to 7, it is 
very likely that dollar rupee 

1462
01:17:36,400 --> 01:17:38,600
will be at 80 so conditionality,
right? 

1463
01:17:38,600 --> 01:17:40,800
I mean we never spoke. 
About this Bayesian thing. 

1464
01:17:41,000 --> 01:17:43,200
So in all these things are, 
there is a conditional, 

1465
01:17:43,200 --> 01:17:45,100
probabilities conditional, 
correlations. 

1466
01:17:45,100 --> 01:17:49,000
All these things, come into 
place and we all model Things 

1467
01:17:49,000 --> 01:17:51,600
based on it. 
It's like, you know, I have a 

1468
01:17:51,608 --> 01:17:52,900
hammer. 
I need to find a tool. 

1469
01:17:53,700 --> 01:17:56,300
Or I have only this skill set 
and therefore, reduce me. 

1470
01:17:56,300 --> 01:17:57,700
I need to find a nail, right? 
Sorry. 

1471
01:17:58,500 --> 01:18:00,200
I need to have a hammer and a, 
to find a nail. 

1472
01:18:00,300 --> 01:18:04,600
So that is your challenge and 
you don't price that correlation

1473
01:18:04,600 --> 01:18:08,000
skew because you didn't have 
tools about it or you don't even

1474
01:18:08,000 --> 01:18:10,400
think about it. 
Right? 

1475
01:18:10,500 --> 01:18:13,500
And it is that what causes 
models to collapse? 

1476
01:18:13,800 --> 01:18:15,700
It? 
Is that which causes a risk you,

1477
01:18:15,700 --> 01:18:18,800
which is what even in real life.
It happens, right? 

1478
01:18:18,800 --> 01:18:21,500
And they say it in Hindi, right,
who privilege of data has 

1479
01:18:21,500 --> 01:18:24,100
suffered Market data, which is 
essentially when it rains, it 

1480
01:18:24,100 --> 01:18:27,900
pours, you know, in the other 
direction, when you are in 

1481
01:18:27,900 --> 01:18:31,300
crisis, you would find that con 
you always get more and more 

1482
01:18:31,300 --> 01:18:34,400
things which acts 2008 crisis, 
right? 

1483
01:18:34,800 --> 01:18:37,500
It happens. 
It happens not because the do 

1484
01:18:37,500 --> 01:18:39,100
didn't know of the distribution 
or anything. 

1485
01:18:39,400 --> 01:18:43,400
It happens because the pain the 
aspect all those things are all 

1486
01:18:43,400 --> 01:18:47,600
linked together, right? 
It is a natural phenomenon and 

1487
01:18:47,600 --> 01:18:51,200
it is this which causes always 
the pain to Wall Street and you 

1488
01:18:51,200 --> 01:18:54,800
know, even in real life even for
us, it causes entities. 

1489
01:18:54,800 --> 01:18:58,400
This avoidance of this worst 
case where you know, which 

1490
01:18:58,400 --> 01:19:00,900
causes a makes us all to be 
defensive which is what in some 

1491
01:19:00,900 --> 01:19:03,800
sense. 
We are all the market Falls 20%.

1492
01:19:03,800 --> 01:19:07,400
We see a 40%, it actually might 
make sense to invest a 20 

1493
01:19:07,400 --> 01:19:10,000
percent correction, but we are 
always I worried about forty 

1494
01:19:10,000 --> 01:19:12,800
percent, right? 
So our Primal brain, you know, 

1495
01:19:12,800 --> 01:19:16,300
the fight-or-flight reactions 
they all trigger, which is why 

1496
01:19:16,300 --> 01:19:18,600
you would want your money to be 
managed. 

1497
01:19:18,600 --> 01:19:21,400
Ideally. 
I mean, by in a systematic or 

1498
01:19:21,400 --> 01:19:24,300
methodical fashion where there 
are behavioral anomalies that 

1499
01:19:24,300 --> 01:19:28,600
you can overcome right and mean 
you know as well maybe spoke 

1500
01:19:28,600 --> 01:19:33,100
about it many times, but that's 
the, I mean, that's the broader 

1501
01:19:33,100 --> 01:19:38,000
principle about not being able 
to see how correlation itself 

1502
01:19:38,000 --> 01:19:41,500
has a smile. 
This problems and brings things,

1503
01:19:41,500 --> 01:19:45,600
may brings down things and I 
think as you rightly mentioned, 

1504
01:19:45,600 --> 01:19:47,500
it has a we forget financial 
markets. 

1505
01:19:47,500 --> 01:19:50,900
I think even in real life a lot 
of things are like lot of our 

1506
01:19:51,000 --> 01:19:53,200
risks have to do with 
correlations and with 

1507
01:19:53,200 --> 01:19:57,400
correlations with change and you
kind of like the and when they 

1508
01:19:57,400 --> 01:19:59,800
change you don't know how to 
handle it and then you sort of 

1509
01:20:00,100 --> 01:20:04,500
get exactly and so on. 
And we use current expectations 

1510
01:20:04,500 --> 01:20:06,100
to risk the correlations. 
Right? 

1511
01:20:06,400 --> 01:20:08,200
Dre. 
You're having good times today. 

1512
01:20:08,200 --> 01:20:12,400
You're having your job is not 
related to your stock market. 

1513
01:20:13,300 --> 01:20:14,700
Eight. 
You think both of them are 

1514
01:20:14,700 --> 01:20:17,600
independent, but what we do not 
know inherently is the 

1515
01:20:17,600 --> 01:20:20,000
probability of you getting fired
increases as your stock market, 

1516
01:20:20,000 --> 01:20:22,000
portfolio goes down. 
So there is a positive 

1517
01:20:22,000 --> 01:20:24,200
correlation or negative 
correlation which way you want 

1518
01:20:24,200 --> 01:20:26,800
to think is there and you kind 
of have to manage it which is 

1519
01:20:26,800 --> 01:20:30,500
why when if you had a good 
financial advisor, in fact, you 

1520
01:20:30,500 --> 01:20:32,700
know, one of the things is if 
you have a financial advisor, 

1521
01:20:32,900 --> 01:20:36,200
ideally you should hate him or 
her right? 

1522
01:20:36,400 --> 01:20:39,000
Because it's like a his that 
person is supposed to be like a 

1523
01:20:39,000 --> 01:20:42,000
doctor making you to go on a 
diet making you to do things 

1524
01:20:42,000 --> 01:20:45,200
which you don't. 
Like like put force you to take 

1525
01:20:45,200 --> 01:20:47,200
insurance, which will never see 
any value. 

1526
01:20:47,400 --> 01:20:49,700
It said money down the drain 
force, you to take medical 

1527
01:20:49,700 --> 01:20:53,000
insurance or force you to keep 
like one or, you know, two years

1528
01:20:53,000 --> 01:20:56,700
of capital just so that you 
survived right now, you will see

1529
01:20:56,700 --> 01:20:58,400
that capital. 
And you would think that, oh, if

1530
01:20:58,400 --> 01:21:00,300
I put that money last year in 
stock market, this year, it 

1531
01:21:00,308 --> 01:21:03,100
would have doubled, right? 
So you should hate that 

1532
01:21:03,100 --> 01:21:05,200
financial advisor. 
But ideally, your financial 

1533
01:21:05,200 --> 01:21:08,100
advisor is supposed to be 
protecting you from these 

1534
01:21:08,100 --> 01:21:09,700
correlation Tales of 
correlation. 

1535
01:21:09,700 --> 01:21:12,500
Skew, if you really have a good 
one obviously agency. 

1536
01:21:12,700 --> 01:21:14,600
Conflicts come into picture. 
That's a different thing. 

1537
01:21:14,600 --> 01:21:17,200
But you have a truly good one. 
That's what that person is 

1538
01:21:17,200 --> 01:21:18,400
supposed to do. 
Possibly. 

1539
01:21:18,400 --> 01:21:19,700
This has been a fascinating 
conversation. 

1540
01:21:19,700 --> 01:21:22,900
I think we've been talking for a
long time now, and now, as a 

1541
01:21:22,900 --> 01:21:25,300
closing question are like, I 
mean like let's say you're a 

1542
01:21:25,400 --> 01:21:28,300
young person who is for whatever
reason interested in the risk. 

1543
01:21:28,400 --> 01:21:30,500
Later. 
Your you've mastered black 

1544
01:21:30,500 --> 01:21:34,700
jacket 6 poker at 9, GJ 12 and 
so on liquor and you think 

1545
01:21:34,700 --> 01:21:37,500
you're a, you're very good at 
risk understanding risk, its 

1546
01:21:37,500 --> 01:21:41,300
own, like now after the global 
financial crisis, I guess the 

1547
01:21:41,500 --> 01:21:45,400
overall Financial Tree, which is
what - mostly hosted this 

1548
01:21:45,400 --> 01:21:48,300
coefficient. 
Is that sort of like diminishing

1549
01:21:48,300 --> 01:21:51,100
now, so if you are, if you want 
to make a career in Risk, what 

1550
01:21:51,100 --> 01:21:55,700
you do, so the broadly two ways 
in looking at risk one, is you 

1551
01:21:55,700 --> 01:21:57,900
can be a risk, professional 
yourself, right? 

1552
01:21:57,900 --> 01:22:00,800
We're all organizations. 
Legally compliant spies 

1553
01:22:00,800 --> 01:22:02,300
everywhere. 
There are mandated. 

1554
01:22:02,400 --> 01:22:05,800
They risk teams need to be 
independent, and there is a 

1555
01:22:05,900 --> 01:22:09,600
tremendous value in having a 
good risk person in any 

1556
01:22:09,600 --> 01:22:13,200
organization, right? 
And, and I am not Just about 

1557
01:22:13,200 --> 01:22:18,100
finance that is now, we mean, if
you hear any of these podcasts 

1558
01:22:18,100 --> 01:22:21,300
about Supply chains recently, 
you would find that somebody the

1559
01:22:21,300 --> 01:22:25,400
job of risk is like to get gpus 
to operate your sass farm, 

1560
01:22:25,600 --> 01:22:27,900
right? 
That itself is a risk and you 

1561
01:22:27,900 --> 01:22:30,000
could not procure, because there
was no supply chain. 

1562
01:22:30,000 --> 01:22:31,700
There was in availability in the
markets. 

1563
01:22:31,900 --> 01:22:35,200
So, risk management is manifold 
Right. 

1564
01:22:35,200 --> 01:22:37,400
Medical insurance, medical area.
Is another thing. 

1565
01:22:37,500 --> 01:22:41,000
So there are lots of areas. 
We speak about Enterprise risk, 

1566
01:22:41,000 --> 01:22:44,500
Financial Risk Logistics. 
And so many areas where you can 

1567
01:22:44,500 --> 01:22:46,500
do, right? 
And in Financial Risk, obviously

1568
01:22:46,500 --> 01:22:49,300
specifically, you have 
requirements like frm and, and 

1569
01:22:49,300 --> 01:22:53,700
so on, but in and separately, 
obviously, as a Trader, you 

1570
01:22:53,700 --> 01:22:56,700
know, to fader is, being risk 
manager in and out, right? 

1571
01:22:56,900 --> 01:22:58,600
You don't live by external 
world. 

1572
01:22:58,600 --> 01:23:01,100
You inherently have to be a 
risk, manager yourself. 

1573
01:23:01,100 --> 01:23:05,700
In fact, I mean, it might be not
widely, might want your popular 

1574
01:23:05,700 --> 01:23:07,600
opinion, but actually think very
good. 

1575
01:23:07,600 --> 01:23:10,000
Predators usually, end up being 
very good Risk Managers. 

1576
01:23:10,200 --> 01:23:12,500
And you can see the top hedge 
funds, the risk. 

1577
01:23:12,700 --> 01:23:16,900
They have are usually extruders 
who kind of done quite well, 

1578
01:23:16,900 --> 01:23:19,300
whether it's Millennium or, you 
know, anything etcetera. 

1579
01:23:19,600 --> 01:23:23,900
So career-wise, I think risk is 
one area where there is greater 

1580
01:23:23,900 --> 01:23:27,300
awareness. 
There is in fact, the word risk 

1581
01:23:27,400 --> 01:23:32,200
now has much wider and it so to 
speak and even if you were to be

1582
01:23:32,200 --> 01:23:34,400
a start-up, in fact, what should
happen is? 

1583
01:23:34,500 --> 01:23:38,200
It's like computers right now. 
You no longer mean, computer 

1584
01:23:38,200 --> 01:23:39,800
science. 
Engineering is kind of a 

1585
01:23:40,300 --> 01:23:45,400
programming skills is now, Now 
necessary for any job right. 

1586
01:23:45,800 --> 01:23:49,200
Similarly risk. 
And in fact, I will go one step 

1587
01:23:49,200 --> 01:23:51,800
back in some sense understanding
data. 

1588
01:23:53,200 --> 01:23:57,200
Eight, which is a precursor for 
understanding risks, right? 

1589
01:23:57,500 --> 01:24:00,100
He's a necessity in any job 
anything, right? 

1590
01:24:00,100 --> 01:24:04,400
It's a skill that it is not like
Risk jobs will value more. 

1591
01:24:04,700 --> 01:24:07,900
In fact, if you were CEO of a 
company and you understood your 

1592
01:24:07,900 --> 01:24:11,300
wrist, when you can add far more
value than somebody who doesn't 

1593
01:24:32,000 --> 01:24:34,000
thank you for listening to data 
shatter. 

1594
01:24:34,600 --> 01:24:38,100
If you like this show, please 
leave a comment, share and 

1595
01:24:38,100 --> 01:24:41,400
subscribe to the podcast. 
You can find this podcast on 

1596
01:24:41,400 --> 01:24:45,300
Apple podcasts Spotify or 
wherever else you go to get your

1597
01:24:45,300 --> 01:24:48,300
podcasts. 
Once again, this is Karthik 

1598
01:24:48,300 --> 01:24:49,800
signing off. 
Thank you.