Dr. R H Patil Memorial Lecture 2019

Dr. R H Patil Memorial Lecture 2019


may I have your attention ladies and
gentlemen we will commence the program in a very short while from now you are
requested to kindly be seated and please turn your cellphone’s to the silent mode
so as to avoid disturbances during the proceedings if you require any
assistance feel free to contact any of the support staff thank you a very good evening everybody
good evening on behalf of NSC it gives me mana see immense delight in extending
a hearty welcome to all of you especially the honorable guests esteem
dignitaries and all you invitees for this extremely special event the Dr.
RH Patil Memorial Lecture in keeping with the Indian tradition we will
commence by lighting the official ceremonial lamp, i request the Nobel
prize-winning economist professor Robert Engle to kindly do us the honors I also
request MD and CEO of NSE Mr. Vikram Limaye to please join in sir in Sanskrit translates the lamp is
luminous its radiance grants victory it’s light in paths Dharma artha kama
and Moksa that is righteousness prosperity
pleasure and finally emancipation this is the significance of lighting a
lamp and hence a lamp should be lit lamp as we know is also a symbol of knowledge
the lamb being lit we will take a nice picture which will be treasured in
memories thank you gentlemen you may please take your seats ladies and gentlemen this year is very
special for NSE as the National Stock Exchange of India is celebrating its
silver jubilee NSE has an important role to play in fulfilling the aspirations of
India becoming a five trillion US dollar economy we will now play a short film
dedicated to all NSE partners kindly take a look at the screen it has an aura
it radiates energy and it is India’s symbol of prosperity you see it
everywhere in homes in bundles at inaugurations at companies
the Marigold it announces personal unions and corporate partnerships the one flower that says here is someone
celebrating a success but joy a journey
besides lemare cold there’s yet another Indian symbol of prosperity that spread
across India National Stock Exchange of India Limited NSE the marigold and NSE
two icons of India one symbolizes prosperity the other enables it the year 1994 India
was ready the winds of economic liberalisation were flowing across India
it now required an engine of growth taking a landscape changing step the
government using SEBI as a pivot roped in key institutions to set up the
National Stock Exchange barriers had been demolished India had finally
connected to India entrepreneurs could easily raise capital Indians across
India could now invest in stock markets in its domestic role it is India’s
largest stock exchange and amongst the largest exchanges growing for
international markets and investors it is the gateway to India’s growth story
NSE today is a symbol of national pride the nifty 50 the de facto symbol of the
direction of the Indian economy is India’s most well-known global financial
brand NSE AFSC a gift City Gujarat is yet another initiative from the
Government of India and NSE to bring international clothes to India
beyond achievements putting purpose before profit how by making the markets
truly democratic by insuring more people participated in the growth of India but
participation in markets required education so curriculum in schools
investor gaps and international speakers today 25 years later NSC is ready yet
again now to facilitate the transition of India’s 2.5 trillion dollar economy
to a five trillion dollar economy yes connecting India to India and further
integrating India with other world markets because NSC is committed to help
India achieve its calling to be amongst the world’s largest economies or nation
to be admired may india always bloom with respecting so ladies and gentlemen that was NEC is
glorious journey right from its establishment through its achievements
and accomplishments over the last 25 years put in a nutshell for all of you
I will now request the MD and CEO of NSC mr. Vikram LeMay to please step on stage
for the welcome address sir good evening ladies and gentlemen a very
warm welcome to all of you this year as we celebrate NSE silver jubilee
this annual lecture in the memory of our founding managing director dr. RH
party’ll is a truly special one this annual lecture features thought leaders
of the highest caliber and reputation as a fitting tribute to the memory of dr.
Patel who was one of the tallest leaders and institution builders of the Indian
financial services industry it was the passing of the SEBI Act in 1990 to post
the Harshad Mehta scam which paved the way for setting up of a modern exchange
and IDBI was charged with the responsibility of leading a group of
institutions that would eventually set up the National Stock Exchange the then
chairman of IDBI h3 SS not Carney assigned the project to dr. RH party NSE
was incorporated in 1993 and commenced trading in 1994 it was the first deem
utilized exchange that was professionally managed and with an
institutional shareholding base the new exchange managed to achieve the
remarkable feat of overcoming tradition practices and strong loyalties that were
over a century old a lot of skepticism from market participants and resistance
from entrenched businesses dr. podila had the foresight and vision to set up a
technology led nationwide disruptive platform that challenged the status quo
and brought in best-in-class standards and practices NSE revolutionized markets
through a pan-indian network of connectivity and technology that was no
mean achievement during the mid-90s nationwide 24 by 7 connectivity was a
daunting task during those times and it was achieved through a VSAT network NSE
had to in fact become a telecom company as it became an exchange NSE under the
leadership of dr. party led many firsts including a role in setting up the first
depository and The Clearing Corporation these were critical market
infrastructure institutions to guarantee settlement and to provide d-mat
securities to erratic to eradicate problems of bad delivery and fraudulent
and duplicate certificates this established trust in markets which
is absolutely key for the development of Indian capital markets NSE o is a deep
sense of gratitude to the vision and missionary zeal of dr. Patel the
founding team past and present employees Sebby and the government for putting in
place critical market infrastructure institutions that have been responsible
for the tremendous growth of our economy and capital markets over the past
two-plus decades dr. Patil was an institution builder and a wonderful and
humble human being with strong value system and ability to motivate and
nurture talent and as he was indeed fortunate to have dr. Patel as its
founding managing director and was a deep sense of gratitude to his many
contributions NSE over a relatively short period of time has emerged as not
only the largest exchange in India but also amongst the top three exchanges in
the world it is also the largest derivatives exchange in the world in
terms of the number of contracts traded few institutions in India have built a
strong global reputation and I would submit that and I would submit that NSE
is one of them as an institution of national importance and as he plays a
critical role with regulators government and market participants in the
development of markets NSE has always focused on what is in the best interest
of the Indian economy markets and investors and is focused on improving
the financial well-being of people we recognize a responsibility to help in
they achieve its aspirations and take its rightful place amongst the world’s
leading economies in order to achieve sustainable high rates of GDP growth it
is critical that we expedite market development and capital formation while
the equity markets in India are relatively well developed penetration is
still at very low levels relative to the emerging market averages we need to
continue to focus on finding creative ways for investor education and
awareness NSE has a very elaborate investor education and awareness program
that runs across six hundred plus districts in the country and includes
over 4,000 programs conducted through the year and several partnerships to
deliver digital programs in order to achieve scale
beyond the equity markets bond markets currency and commodity markets are at a
nascent stage relative to potential and it is critical that these markets
develop over the next two to three years access to capital for SMEs is another
important aspect to support growth and employment NSE is doing its bit to
provide an ecosystem for equity and debt financing for SMEs through the NSE
emerge platform for SME IPOs and the bill discounting exchange are xil for
providing working capital financing to SMEs through a joint venture with SIDBI
it is important that the trust in markets is enhanced and that we further
integrate the indian economy and markets into the global ecosystem we need to
therefore make sure that markets developed in a disciplined way and NSE
is focused on ensuring the highest standards of governance amongst listed
corporates and the integrity of markets through regulation and surveillance of
market intermediaries and trading activity technology and risk management
in all its dimensions are critical areas of focus and we will continue to invest
in these areas from a policy and regulatory standpoint it is important to
demonstrate stability of policy regulations and taxation in order to
give confidence to investors we also need to focus on making sure that we
continue to streamline compliance requirements to make it easier for
people to invest in Indian markets product innovation and simplicity are
also critical to further penetrate an intermediate intermediate retail savings
into markets and the growth of the ETF market could be an important driver to
improve penetration we have come a long way over the last 25 years in the
evolution of markets and the growth of our economy the aspirations of our
country is a guiding light as India powers itself forward to a five trillion
economy we all need to recommit ourselves to creating the right
environment an institutional architecture that is important to drive
growth and development over the next 25 years NSE is committed to contributing
to the development of the economy markets and the financial well-being of
people as we reflect on the evolution over the last 25 years and the bold
vision of dr. Patil in creating institution
that have stood the test of time and I’ve been critical for our development
we need to reimagine the future and embrace technology and encourage
innovation to drive productivity and growth we were very fortunate and
honored to have with us today professor Robert Engel as a keynote speaker for
the dr. Patel memorial lecture for 2019 professor angle the Michael R Molina
professor of finance at New York University’s Stern School of Business
was awarded the 2003 Nobel Prize in Economics professor angle is an expert in time
series analysis with a long-standing interest in the analysis of financial
markets his arch model and its generalizations have become
indispensable tools not only for researchers but also for analysts of
financial markets who use them an asset pricing and in evaluating portfolio risk
he’s currently the director of the NYU Stern volatility Institute and is the
co-founding president of the Society for financial econometrics a global
not-for-profit organization housed at NYU
before joining NYU Stern in 2000 professor Engel was the chair of the
economics department at the University of California San Diego and an associate
professor of economics at the Massachusetts Institute of Technology
the dr. R each party memorial lecture is an annual event and we are committed to
honoring dr. patel’s legacy by inviting world-renowned thought leaders that is
all put our hands together to welcome professor Engel and for we will gain valuable insights
from Professor angles lecture and thoughts and we would like to thank all
of you for coming thank you very much good evening it’s a great pleasure to be
here and thank you so much to the NSC and I am very honored to be the RH putty
lecturer this year the NSE has done an amazing job as we just heard and I thank
mr. dr. LeMay for the very nice introduction and and discussion uh I’d
like to talk about geopolitical risk tonight and we are in a time when
geopolitical risk is on everybody’s mind and as we study and plan our investment
portfolios and look at our performance it’s very common to say well I would
have done better if it hadn’t been for geopolitical risk so can we talk more
precisely about what we mean by geopolitical risk and this slide kind of
suggests one view of what we mean by geopolitical risk it’s it’s it’s a
picture of a sculpture in a garden in Budapest which is dedicated to Soviet
era art and it really captures that idea and is this really what we mean by
geopolitical risk well let’s take a look I’m going to talk about paper tonight
which is joint with susana martins and discusses a way of measuring
geopolitical risk and then examining how it impacts financial market stability so
what actually do we mean by geopolitical risk is this about politics or is it
about economics is it about terrorism military risks cyber risks or is it
about more conventional changes like elections and congressional actions and
political movements is it about the level of risk or is it about the
surprise and is it best measured in the news or in the financial markets
themselves this leads to a lot of different ways to measure geopolitical
risk as you answer these questions a couple of quotes might lead the way to
what I’m going to do tonight we are drowning in information and starving for
knowledge not too bad and then from the work of the statisticians that have
brought us a lot of the big data and artificial intelligence research comes
the answer the statisticians job is to make sense of it all to extract
important patterns and trends and understand what the data says we call
this learning from the data we are going to try to learn from the data what
geopolitical risk really is we have a website at the volatility and risk
Institute at NYU which produces measures of risk all over the world
every day and when you go to our website the first thing you’ll see is a
volatility map and what this is is a map of the world color-coded for volatility
and this is the what it looked like on I guess Saturday which was the forecast of
what Monday was going to look like and the idea is that in countries where
volatility is low they’re color-coded as green and when volatility is high
they’re color-coded as red and then there’s gradations in between so the
surprising thing you see from looking at this map is of course how much green
there is we often think volatility in this in asset markets is high but in
fact it’s typically these days quite low and it has been low for quite a long
time although there are pockets of time and pockets of places where it’s higher
you see on here notably Chile in Argentina
both have had political difficulties and show heavy red color coding for their
financial markets but not too many other places show that kind of high volatility
but if you look back in time of course after the brexit vote you see that a
great deal of the world turned red in particular something like 20 markets in
in you in Europe are all red in this picture as well as the US Canada
Australia South Africa Japan Thailand that lots of places are red so one of
the things we see when we look at measures of volatility and this is again
from V lab you see that volatility is continually going up and down and what’s
plotted on here is the volatility different asset classes some of these
are stocks some are bonds some are real estate we have commodities and I think
even and the euro is on there and I think even exchange rates are on this
this map so on this chart why do volatilities move like this well
it’s not too surprising really we have an explanation for this which is
generally that factors that we consider to be important in pricing assets and
measuring the risk around the world or the the reason that they all those
factors carry this information and these factors explain why assets are
correlated with each other but it turns out that these factors of asset pricing
do not explain why volatilities are correlated with each other if you take
out the factors so that we see only what’s called the idiosyncrasies that is
the part of returns that are not explained by the factors they also peak
at the same time so it really is not our the factors that we tend to study and we
build our financial morals about that explain why volatilities move together so what is it well I think its
geopolitical risk and that’s where we’re going tonight so here’s some facts about
volatilities that we’ll find useful in understanding this even though asset
returns are nearly impossible to predict volatilities are not too hard to predict
we can build statistical models to predict volatility that’s what I got my
Nobel Prize for and it’s what I showed on that
last last slide so called arch and GARCH models are early candidates and there
are much more recent candidates for this now but if you can predict something
then you can talk about the surprises in this prediction if you predict something
and what happens is different then that’s a surprise we call it an
innovation and what we are going to show is that the volatile stew volatility are
really where geopolitical risk lies these shocks to the volatility of one
asset class and the shocks to volatility of another asset class of a one country
and another country are all correlated with each other so the fact that these
volatility shocks are correlated means that that this is a pervasive factor
that we have not previously identified and it’s a volatility factor which we’re
going to examine so I’m going to call this factor G of all so that we give it
a name and it stands for it geopolitical volatility but it stands for it in a
very particular fashion when G of all has a high value it means that all asset
returns are more volatile they aren’t necessarily going down they might be
going up but their volatile and so G of all is going to be high when there is
news which affects all asset classes and all countries around the world that’s
the idea sometimes G of all will reflect
political or military or terrorist activities sometimes it’s very impactful
economic news but altogether we’re going to think of it as geopolitical
volatility so how do we measure the shocks to volatility well if you have a
way of predicting volatility which the arts and GARCH models are a way of doing
this then we can talk about how good your predictions are and so if we look
at the return on stock – what it was predicted to be using past information
and these factors of production that’s the error in predicting what the stock
market was going to do and the volatility is the square of that we’re
going to divide it by the predicted level of volatility to make it a
percentage error in volatility and that is the raw material that we’re going to
talk about tonight the difference between what the stock return is and
what is predicted to be is a forecast error and it’s square is a volatility
shock so we construct our factors of production so that there’s no more
correlation across assets but this does not imply that the squares of this asset
are not correlated and this is the factor which we’re going to use to
define GOL we can look at the correlation across assets in this square
of this volatility shock and see whether in fact there is something something
that we hadn’t previously observed which we are going to call the G of all so I said I wasn’t going to have any
equations tonight I I promised that I wouldn’t have any equations I know
you’re heartbroken about this but well here’s one I think it’s the only one
which says let’s write down an equation which tells you how this G of all shock
affects a particular asset so this is an asset that you’re holding in your
portfolio and we want to know what its variance is when we do risk management
we’re always interested in variances and so this is a question what is the
variance of of the asset that you’ve got and it’s if X is the G of all we think
that this asset might have a coefficient which is this impact so this is a factor
well in the language of factors this is a factor loading but in language of just
common sense it’s the fraction of G of all that you’re going to get so if your
if your asset is not very exposed your little s is going to be a small number
if your asset is highly exposed to geopolitical risk then your little s is
going to be a big number and since we know that the variance of e is supposed
to be 1 since we this is a normalization that we’ve already done then we have to
add 1 minus s to this and this is our little simple equation for how a
political volatility affects the assets that we own it affects all of them but
it affects some more than others ok ok so our interpretation is that X is
like a variance and when the factor loading is high it means that
the stocks which have this high factor loading will have a bigger standard
deviation than stock when this X is small and when the s is small it isn’t a
big difference but when s is big there’s a big difference between times of
geopolitical volatility and times without it so this looks like another
equation but it’s really the same equation and for people who know how
I’ve written volatility models in the past we can think about the shot to our
asset return as being written as volatility their standard deviation
times a purely random shock and this is the equation which we use for arch
models we use for GARCH models and but this is a different version of it which
is specifically designed for this GEVO factor okay how does this work let’s
take a look at a data set and this is a country data set with one ETF which are
traded in the US and the picture in blue is for the returns of the first asset
and the data set which happens to be Austria so you can see from this that
sometimes what returns are more volatile than others and if you’re interested in
what we mean by volatility it means that the amplitude is high and you can see
the financial crisis it is a time of very high amplitude or high volatility
for this asset if you build a GARCH model on this asset and you plot two
standard deviations of it you get the red curve on the top and you can see
that’s a way of measuring the volatility at every
point in time and when I showed you the volatility of map of the world it would
be the last point on this picture if this was the end of our data set would
be telling you what the volatility is predicted to be tomorrow so you can see
it goes up when volatility is high and goes back down otherwise and so it’s
it’s a clever little statistical model which does that the bottom curve is our
shocks to returns divided by the predicted standard deviation and when we
think we have a good model for volatility what it means is there is no
more change in amplitude that’s predictable there’s no more what we call
volatility clustering in the green curve and looking at that picture you say this
was successful and I tell my students look at this when there’s no more
volatility clustering it means that you’ve done a good job estimating this
model and people all over the world stopped modeling at that point but
tonight we’re going to carry it a step further because you can see that there
are some days in which the volatility is bigger than usual and some days when
it’s smaller than usual and what we’re going to recognize is that the days when
it’s bigger than usual for Austria it’s likely to be bigger than usual for all
the other countries and that’s the new piece of information that we’re going to
use to define geopolitical volatility okay so this is what the data looks like you
know these are the stock returns in all these different countries when you’ve
estimated the the models for each of the country you get this is the green
picture for each of these countries they don’t look exactly the same but what we
want to know is whether they’re big at the same time in different countries so
a way of doing that is to square them so that positives and negatives tree are
treated the same and then look at the correlation structure and if you look at
them we have something like 45 countries so this correlation matrix has a whole
lot of entries in it and this is just a little part of it and this is the
correlation between the first 16 of these and the first six over here you
see the numbers aren’t very big but there is something very special about
these numbers they’re all positive and if these were random there half of them
would be negative but they’re all positive and if you look at this 45 by
45 matrix you still you will see that I think all of them are positive still so
this is very significant evidence that there is a geopolitical volatility
factor which is driving all these countries at the same time so I have a
nice little econometrics way of estimating this it involves estimating
time series models to get the to get the factor loadings and cross section models
to get the estimate of G of all and then doing it over and over again until it
converges probably you don’t want me to do that right okay let me just show you
the results this is in the middle here there we go in the middle here is the
data on the G of all and it’s sorted so that the largest day is first and then
there are something like 5,000 days in the data set so the smallest one is way
under the platform here so let’s just look at the at the top of this list the
date of the largest G of all event is 2001 September 17th so what is that date
well that date is one week after the 9/11 terrorist crashing the airplanes
into the World Trade Towers in New York and the markets were closed for a week
and so this is the day they reopened and this is the the biggest geo volatility
shock in our data set by this measure the second one is 2016 June 24th that’s
brexit this is the day after the brexit election vote the third one is 2007
February 27th so this is the first early warning of the financial crisis and it’s
also a day when the Chinese stock market had a big big drop Chinese stock market
had a big drop and UBS had some hedge funds that were invested in mortgage
securities which got into trouble so this actually was a harbinger for the
financial crisis and move markets dramatically I don’t think we have a good
identification of April 21st but in 1997 October 27th there was a stock market
crash which caused the exchange in New York to be closed early then we see we
have down here the the Trump election in 2016 11:09 that’s November 9th going
down a little further we get commodity collapse and Chinese stock they call it
Black Monday this is when the the bubble and the Chinese stock market actually
collapsed and 2008 September 29th is the day on which the house rejected the tarp
bill and down here 2008 October 13th is the day they passed the tarp bill in any
case you can go down this list and may you may be able to identify some events
that I haven’t done yet but it’s a pretty reasonable list of things that
have happened over the last two decades two to two and a half decades really and
which ones really moved all the markets of the world that means that they are
geopolitical events on the far right hand side is what the average of all
these markets did on that day and so you see many of those are negative so that
when when there’s the geopolitical event typically the returns or negative
however for some of these events the returns are positive they move the
markets a lot but it could be up or it could be down now corresponding to these events our
factor loadings so these are what tell you which asks which countries are most
impacted by these geopolitical events so you multiply the geopolitical factor by
s for each country tells you how much of it you’re you’re getting and the highest
ones are France Netherlands Germany Spain Belgium so those are all European
countries and they were impacted together but then you also see Thailand
Malaysia Korea United States is down a little a little bit further and you go
down this list China is in the the second top of the second column and as
you keep going down and you find you come to the ones at the bottom which are
less impacted by geopolitical risk and there’s Pakistan New Zealand and the
third went up is India so it’s the countries that are in the bottom of this
list may have a lot of volatility but it’s not so coordinated with the rest of
the world so they’re less sensitive to geopolitical risk and I think a lot of
that makes sense and so the
I think it’s interesting to see what these are this is really our first
estimate of these factors but it may be that this is leading us to a way of
taking our portfolios and tilting them a little bit toward assets which are less
correlated with the geopolitical events of our times so what are what are the Kippur some other
approaches to measuring geopolitical risk and do they give the same answer as
this well first of all let’s take a look at these numbers and look at these as a one a monthly average and what you see
are some of these events here you see the 911 as is the biggest on the screen
but also laymen’s collapses hi Chinese bubble Dow Jones the debt crisis
brexit Trump but interestingly when you get all the way to the present it
doesn’t look that high we tend to think that we are in an age when geopolitical
risk is really elevated but the markets don’t seem to know about that the
markets think this is not a time that’s especially dangerous and that’s the
green that we showed on the volatility plot map it’s the markets are not so
worried about these geopolitical events as we tend to be here are two more
measures of geopolitical risk one of which is the geopolitical estimate of
political uncertainty and that’s in blue this is by three professors Baker bloom
and Davis and what you see is it was somewhat elevated during 2001 when the
World Trade Towers were hit it was somewhat elevated during the financial
crisis but it’s actually higher since 2016 and maybe the highest
on the entire graph is in 2000 2019 that’s this year so this is a measure
which is based on newspapers reading the newspapers and seeing how much political
uncertainty is there when you read the newspaper and there’s a lot of political
uncertainty when you when when writers write about the geopolitical risk
they’re very concerned about the events of our times and it shows in the
newspapers and it’s on the screen a second one is by two researchers at the
New York at the the Federal Reserve Bank in Washington and that’s a little bit
more focused on stress between countries but particularly military and terrorist
stress and you see it has an enormous spike around 9/11 and also subsequently
the Iraq war that relatively disastrously we did so it shows a little
bit of a rise at the end but it’s certainly not the highest it ever was
and but it is elevated here’s a third one and this is comes from Blackrock
which has a careful analysis of geopolitical risk based on experts they
asked expert opinion what are the 10 things that you’re most worried about
and let’s figure out how they are going to impact financial markets and how
likely they are to happen and how big is the effect going to be and so as they do
that they come up with this picture of rising and following geopolitical risk
and this also thinks that today is particularly high in geopolitical risk I
must say if if your broker tells you to worry
about this then you might buy some stock or sell some and I think if this chart
didn’t show anything Blackrock wouldn’t be doing it so I
think that the I think that there is a real reason to be interested in the most
recent part because that’s where the clients are are trading so I think again
there is evidence that black rocks experts think that geopolitical risk is
high but all together these four measures
don’t tell the same story they’re not the same measures they’re measuring
different things but if you’re interested in how vulnerable the markets
are it is not a time when when the geopolitical risk seems to be high so
what are the implications of this for financial stability do we have a heavy
weight over over us supposed to be funny yeah it’s okay so this is a nice
sculpture park outside of New York City and it seems like a reasonable thing to
look at when we’re asking whether there is an implication for financial
stability of this geopolitical risk so I’m going to show you some data on this
risk which is what we call systemic risk and what it is is a way of measuring
whether the financial sector is under stress whether the financial sector is
under capitalized we calculate this measure
once a week for more than a thousand financial firms around the world we can
do it with publicly available information it uses some of the
statistical methods from the Nobel Prize to talk about time varying volatilities
and correlations but basically it’s a pretty simple measure what’s it supposed
to measure it’s supposed to measure the number of dollars a financial firm would
need in order to continue to function normally if there is a global stock
market decline of 40 percent over the next six months okay so there’s the
stock market goes down financial firms stock goes down with it does it go down
so far that they need to raise capital in order to continue to do their
business that’s the question and if they have to raise capital how much they have
to raise how does it work it looks at the ratio of the market cap
to the accounting liabilities it looks not just in what that ratio looks like
today it looks like what that ratio would look like if the global stock
market fell by 40 percent okay and then it says okay how much capital would you
need to bring it back up to a normal level which we interpret is 8 percent
for many financial institutions that’s more or less where they operate so s
risk as a consequence is high when the market value of assets is low that is
when they’re the loans that they’ve written or are low in value or the
companies that they own go down in value and it’s especially high when the firm
is highly levered and big so why is this important well in Western economies when
the firm has highest risk it means that it’s vulnerable if there’s going to be a
financial crisis it’s at risk you know no one wants to raise capital in the
middle of downturn so the risk manager and the
regulator are going to come to these companies and say you shouldn’t have so
much leverage you should reduce your s risk you should reduce your leverage
reduce improve strengthen your balance sheet commonly this is done by selling
assets and using the proceeds to retire debt so if one firm does this it’s
likely to be pretty successful in its strength in its balance sheet but if
it’s one of many firms in a country that are trying to strengthen their balance
sheet at the same time then there are no buyers for these assets and that’s
exactly when the price is going to fall a lot unless international buyers will
buy these these assets these loans these bonds but if the rest of the world is
also undercapitalized at this point and they’re not going to buy them either so
they’re going to fall dramatically in value as they fall in value the stock
prices will fall even further for these financial firms they will there s risk
will get even higher and we have what we call a fire sale spiral where the values
spiral down because everyone’s trying to sell these assets you could think about
the the mortgage-backed securities that that banks tried to sell during the
financial crisis the values fell so far that they decided they often that they
wouldn’t sell them but they couldn’t really restructure their balance sheets
it shows how hard it is to do this when you try to do it all at the same time so
the risk of one country depends on its financial institutions and how high
their SRS is but it also depends on the rest of the world
and this is one of the reasons why cooperation in coordination of monetary
and and and financial policy across central bank’s is tremendously important
I should say that this is described in more detail in a paper in the
Proceedings of the National Academy of Science that I wrote with my co-author
Tian Yu Rouen who is a professor at National University of Singapore why is
this important in China or why is it important in India well in economies
such as China and India where many of the financial institutions are
state-owned the pressure for an undercapitalized institution to deliver
is reduced because there is since their state-owned there is no possibility that
a Chinese bank is going to fail and I don’t know but I don’t think there’s a
strong possibility that an Indian public li owned government owned bank is likely
to fail there will be capital forthcoming – to bail them out they
won’t have to rely on the private sector to try to do this nevertheless if such a
bank is undercapitalized they are not going to want to make new loans if they
make new loans and then it turns out that they are they need to go and beg
for money to the government they are going to feel like they’re going to be
criticized as bad managers who don’t know what they’re doing and perhaps lose
their job so they’re on top of this state-owned banks often have legacy
loans that are underperforming they may be non performing or just
underperforming and there will be pressure on them to extend re-extend
loans to to these companies and that puts further pressure on the
balance sheet of the banks so as a consequence if the state-owned or or
private borrowers weaken the banks tend to weaken even in state-owned systems
and so the same kind of dynamic maybe not true there what to do well rather
than extending new loans to legacy borrowers we state-owned banks can
contemplate letting the loans default in letting the loans default has not been
very common in China China tends to think that that’s leads to social unrest
and so they have stopped doing they stopped a lot of defaults from happening
in India there is a new bankruptcy law which will some of you know a lot about
so in any case if we think that bankruptcy laws are like a hospital for
distressed companies then really it might make sense to fail to roll over
existing loans and make new loans to more profitable companies and let the
old loans default there is some collateral that you can recover and it
may be actually that has more value as a strategy than rolling over the old loans
so from a social point of view of course this also makes sense because you’d like
to reduce your exposure to industries which are growing slowly or declining
and increase your exposure to the growth industries you don’t want to you don’t
want to maintain zombie banks something sorry zombie firms as your creditors if
you’re a bank so let’s take a look at the data data
comes in all different shapes and colors and let’s see what we see
so here is the picture that worries me this is the sum of all the s risk of all
the countries in the world so this is what we calculate every week and if you
add up all the dollars it looks like in the financial crisis it would have taken
a little bit less than four trillion dollars to recapitalize all the banks in
the world in this European sovereign-debt crisis it would have
taken just a little bit more a hair more maybe maybe four trillion to
recapitalize them all the third peak doesn’t have a name but I think it’s got
something to do with China but the last one is the one we want to talk about
where it’s actually inched above the same level of everything we’ve seen
since 2000 so today we have the sum of s risk that’s higher than it’s ever been
by our measurement so we have to understand a little better where it is
what the causes are is it likely to lead us to a financial crisis here is a
picture of what you see when you look at the Americas this is North and South
America and at least by this low point which is January of 2018 it’s clear that
the level of s risk has come down and at the if we stopped time at exactly the
right moment we’d say in fact we’ve gotten back to pre-crisis levels but
it’s now rising at the end and I think that could be interpreted as a
consequence of this trade war if we look at Europe you see something
similar although it has not declined as much but it’s also not rising as fast if
you look at China I mean at Asia you see a very different story we see debt
rising the under capitalization of the financial sector is increasing in a
pretty inexorable way over this whole sample period particularly since the
financial crisis if you look at China by itself you see it’s even steeper so this
is obviously where some of this high s risk is coming from if you look at Hong
Kong you see the very sharp rise just at the end but I mean that’s probably due
to the protests in Hong Kong which have I think decimated the financial markets
to some extent and you want to see the next one or not what is the next one
going to be it’s India you’re right so what do you see when you look at
India well it doesn’t have this rise at the end it’s been sort of the same level
for maybe eight or nine years and it’s jiggling around but it’s not really
getting worse and it’s not getting better it’s just sort of level so the
question that you’re asking yourselves is is this is this a problem so we want
to get to that so if we summarize all these pictures that I just showed you
here’s China the highest second highest Japan I didn’t show you that
then we have the United States UK France Canada Korea and so forth and then
here’s India well right in the middle you can see it there and so it’s by no
means the biggest of all at all it’s really sort of in the middle and there
are of course many countries down below this that are have no asterisk at all
this is just these are these are the the largest if you think that this fire sale
is the concern then you should use the same scaling some of these countries are
bigger than others and that makes a difference to how much s risk you would
expect and how much s risk you can tolerate a good way of scaling is the
total assets in the financial sector and that’s the way Tian Yu and I scaled them
in the National Academy paper and this is now the same picture but scaled by
total assets and now you see first of all China is no longer on top it’s moved
down a few spaces India is still sort of in the middle but Japan is on top and
then we have Korea and actually Jersey and Denmark a sort of smaller countries
there they probably don’t have have the impact but they might have the risk and
if you look more closely at India I’m sorry if if I offend anybody here anyway
the bulk of the s risk for India is the State Bank of India how many of you bank
there okay so do you have risk well probably not because it’s it’s a
state-owned enterprise we don’t think it actually has risk but it may be
contributing to the risk of India and ultimately to the financial system
as a whole well bankruptcy reform is kind of what
we think might be the solution for this it’s in in in China there is a new push
to have lots of new bankruptcy courts that are using a more US style
bankruptcy program and that is probably a good thing there are there are NASA
and bankruptcies in China there are mostly there in the private sector but
there have been some defaults in the public sector in the state-owned
enterprises and my feeling is that by providing a much more extensive set of
court systems and a more liberal bankruptcy law it’s going to be possible
for China to reduce the debt load on its banks India is doing the same thing so
in a sense there is a lot of similarity between these two countries even though
there of course many differences the bankruptcy reforms were passed in 2016
which actually forced lenders to send borrowers to bankruptcy for any missed
payment so the idea that there could be long term non-performing loans on your
balance sheet is isn’t challenged by this law it doesn’t mean that you can’t
extend new credit to someone so that they can actually pay back the old one
so that still is an option that banks must decide whether they’re going to do
or not however this has fins a blowers was struck to
this by the courts who blocked restructuring and sr steel and putting
this whole program in limbo but I gather in just about a week ago the Supreme
Court rejected the lower court ruling and has now allowing the new bankruptcy
procedures to continue in a timely fashion so I think that that the
prospects for bankruptcy reform and removing the non-performing loans from
the Indian banks or actually look pretty promising as well excessive red tape and
interminable judicial schedules make it difficult for everyone to plan what to
do about non-performing loans it makes it difficult for the banks to decide
whether to extend new credits it makes it difficult for firms to decide how
much risk to take it makes it difficult for the banks to decide whether to send
extend the first loans to a risky company so transparency in this judicial
system will be extremely valuable incompetence is going to be extremely
important so much remains to be done to reduce the backlog but I think the
direction is quite promising you can see here the increase in ongoing bankruptcy
cases in India and the also the increase in closed and you know resolved
bankruptcy filings in India so this doesn’t go up to the present but I think
it probably my guess is it continues to look like this so in closing the
question is are we prepared and I leave you with that question so thank you anyone has any questions please use this
opportunity I think you’ll probably get a lot more through Q&A as well so we’ll
just have to get mics around professor my question please do the markets over a
period of time trying to they become used to certain level of geopolitical
risk and therefore the next peaking is much higher or much lower because they
have absorbed into their working the markets have absorbed into their work
working certain levels of geopolitical risk it is like a child when the child
grows the ability is better so it’s somewhat similar so so you’re asking
whether people learn whether or whether bankers learn I guess I should hope so
you know after after a big downturn such as the financial crisis or the Asian
currency crisis which had a lot of a lot of people that I think banks became more
conservative but not everywhere some of the you know that I wouldn’t say there’s
evidence of that in in China those well of course maybe they didn’t feel the
really the the brunt of the financial crisis so maybe that would explain why
that they didn’t seem to learn but it’s also that you know you get the next
generation of managers they weren’t there we have seen in the u.s. that ten
years after the financial crisis Congress and the Trump administration
have pretty much agreed that the regulations are now too strong we should
really deregulate the financial sector and
you know that could be there could be some truth to that
but it also sounds like they’re forgetting what happened so anyway I
like to think that we learned something from this yes I agree I see one back
there okay hello hello professor you talk about as risk and how you calculate
it when the stock market Falls by 40% but there could be different kinds of
decline in the stock market for example when there was a tech burst the stock
market did fail but the banking sector was not that much stressed compared to
the 2008 crisis so I was wondering how do you take into account the two
different kinds of stock market crashes and another question was that there can
be different kinds of geopolitical risk which will affect different kind of
assets differently for example a gas power would affect India very
differently and SJ could be very high for a gulf war compared to say a brexit
which would affect India much lesser so you have kept the weight on the asset
constant but it could be different for different kinds of geopolitical risk so
do you have any comment on that well on your first question see what Oh different kinds of crises so
in in the measure of s risk of course we don’t know whether there’s a financial
crisis happened but when we built this little statistical model that would I
didn’t really show you but I talked about our dependent variable in that was
a measure of whether this country has a financial crisis at this moment and how
severe it is and so the tech bubble doesn’t appear in in this kind of
dependent variable so I’m only looking at whether s risk helps predict a
financial crisis not just a downturn okay so that’s the first part of the
question the second question right okay so the model that we’ve that
I’ve estimated and I showed you tonight treats them the same you know whatever
volatility shock is is large we call it a G of all shock and we have one factor
loading for this G of all shock is it too simple a model maybe and I think
there’s a scope to have two gu Vols jus vol 1 and G of all – and then you’d have
separate factor loadings but I think you know we want to start with something
small but we can probably ask questions like are these things all the same and
it wouldn’t be it wouldn’t be hard to do a test for that but I think what you two
have a hard time doing is deciding which of these five thousand days you’re going
to think of as G of all one and which of the five thousand days you’re going to
think of as G of all – you know we can maybe do it with a top ten but after
that it’s going to be hard to figure out how to go professor
yes it would be good for people to also identify themselves until tanker I’m
from the National Stock Exchange professor what’s the intuition behind
relatively low levels of gia wall and lifetime high risk high levels of s risk
at the moment how do we see them these two these two things together I mean why
am I putting them in the same talk yes yes so if so the question is how much of
the increase in s risk is due to geopolitical news I think that’s really
the question that’s what I’m I am concerned about and if you think it’s
the trade war then we’re talking about geopolitical news which Blackrock
observes and my measure doesn’t observe and that would be the explanation from
what’s going on if we think that the reason Chinese s risk is so high is
because of the dynamics of the Chinese economy where they’re trying to hit
growth targets where they’re trying to transform their economy from a export
oriented investment economy to more of a consumption economy then it’s a
different it’s not G of all it all that it’s causing this so I think I think I
don’t exactly have an answer I think what I’ve done is tried to raise the
question of do we think it’s really Jiabao geopolitical news that’s causing
the financial sector to be as undercapitalized as it is but it doesn’t
really feel like the financial sector is sufficiently undercapitalized that we’re
going to have a financial crisis in in the immediate future but the trend
doesn’t look very good so I have a very similar is sanguine from our bein coal
we have a very simple question we are thinking of acquiring a company in UK
the problem is that there are lot of inefficient staff working there and if
we are to remove them we are given the legal advice that it will be big
compensation to be paid due to local Social Security No
in UK this is a geopolitical risk can you call it as a geopolitical risk so you’re you’re asking okay whether
there are issues going on in the UK there are geopolitical risk do you think
they’re moving markets all over the world they’re just moving they’re moving
your business maybe but I don’t think that they’re going to be shocking
increasing volatility in in the US and then in Latin America and so forth so I
don’t think that would end up showing up one of my GU ball out out put if I
understand correctly thank you Thank You professor my name is a pho
confirmation Center for corporate governance and sustainability for me
personally it was a great tutorial for geopolitical analyst though it was a bit
of a mind gem for me but I want to step back and talk about wherever you go
internationally today you think you listen of another risk which is climate
climate risk and I would like to know from a Nobel laureate like you for
example companies like ExxonMobil are being already questioned by a security
Exchange Commission that billions of dollars which are logged into fossil
fuel all kind of a thing while the whole business model and world is moving
towards renewable energy the climate risk how will is going to impact the
capital markets so is climate risk a geopolitical risk is that is that a
short version of your question no oh is of course I’ve been been United States
pulls out of the right you know 2010 records it’s one but overall I wanted to
know whether climate risk per se I mean one of the things about climate changes
it’s pretty gradual and it’s got a long horizon but I I do believe that when
there’s news about the climate that does move markets I think that if you’re
holding a portfolio that includes a lot of fossil fuels companies and there is
news that the climate is worse than people thought and it might be news that
shows up as weather or wildfires or something else but it’s it’s an event
then your portfolio of fossil fuel companies may be impacted and you might
expect and yeah you know we think I what I
think is that there’s a factor which is a climate factor that we don’t identify
and it would be fossil fuel companies that would be in it and it would be
probably you know alternative energy companies that you’d short in this
portfolio and that portfolio is going to go up and down as there’s news about the
climate change so the question of whether this is the geopolitical risks
or not there’s a question of how many people hold this portfolio I think and
whether it moves it very much hi this is Badou shaker from CFA Institute you use
the same measure s risk systemic risk for us as well as China you know all
countries and these are very different markets the response to a shock would be
very different in a state control financial system like China versus you
know what we can expect from the US so is how useful is s risk as a measure
when applied to very different contexts and how does it connect to contagion so
for instance China may have very high s risk measure but we need not worry too
much about it because they may manage it in a way that is very different from how
the UK will manage it well I think I agree that China is very different from
many other countries but so was India and so is the United States and and
there’s a lot of differences so I think that that we are trying all the time to
figure out whether this model applies to China and I think actually that’s what I
discussed tonight is whether the the model of how a financial crisis
would occur is the same in China and India as it is in say Western Europe or
the United States and you know we my view is that they are they do look
different and we need to take that difference into account which is
actually what I described now there are other things that are different which
are interesting as well and for example there’s a big shadow banking sector in
China that is not in our data set well if what were really in there s risk
would be higher there is also because of the government guarantees of these banks
you could imagine that the stock market valuation is actually higher than it
would be if there was really a possibility that they would default
that’s also would lead to a higher risk than what we have it seems to me most of
the corrections to my measure of s risk would make it higher in China than what
we’re observing I mean maybe that’s what your point was but so I think we are
trying to be conscious of the biases that might be in here but still be
comprehensive we want to have a measure that we can use in 70 different
countries which have all sorts of different standards and accounting
systems and stock markets and you know no one else can do that
so we had to we did it in a way that’s kind of as well as we possibly can
preserves the features of each country and yet is
sensitive to the data and so forth that’s available this is all V Neela Canton from
Catherine so my question was about your G oval measure and I noticed that it was
the highest measures were for the US and then to a lesser extent China so I’m
wondering to what extent G of all is a proxy for the size of the economy and
its integration with the rest of the world or whether it’s capturing
something more than that well we tried to capture that with the factor loadings
by saying that you know different countries would have different exposures
to it but I think it’s also not so surprising to find that events that
happen in the US are more likely to impact the whole world than events that
happen in Ireland and so I don’t think I don’t think that all countries have an
equal impact on on global markets so it might be if we had a different different
dataset or or use currencies that we didn’t have in here it would be somewhat
different I think the basic features would be the same but it would be some
differences since we love to take another two to three questions with
respect to what you said about can you identify yourself as such in from
Business Standard this is with respect to what you said about financial
institutions in India in particular what advice would you give to the
meant with regard to the undercapitalization that you currently
see and how urgent would a recapitalisation be or would you suggest
other measures such as a privatization well I think I think that if if the
banking sector and in India worked to follow the new bankruptcy guidelines it
would actually reduce there s risk it would improve the profitability and it
would improve the growth rate of the Indian economy so that is actually going
to have the same effect of recapitalizing the banks because they
will be more profitable more profitable and a higher higher stock market
valuations so I kind of think that that that is a good strategy for dealing with
this rather but it could be that that the that the natural thing to do would
be for the banks to actually sell some of these loans but I don’t know what the
market looks like for them I don’t know how they’re structured I don’t know how
easy it would be to sell the the kinds of loans that are non performing but
there are actually lots of distressed debt funds and so forth that take
non-performing loans and go try to collect them and you know there that’s
another strategy for trying to improve the strength of your balance sheet and
it might be more profitable to do it that way then through default I don’t
know it depends on how the institutions are working the last two questions and
then we’ll take one here go ahead please yes good evening sir
de su chuan J Basu from national institute of bank management Pune I had
two questions first shouldn’t there be an end or charity between s risk and
geopolitical risk higher geopolitical risk believe it is risk but sure it s
risk also versus geopolitical risk that’s what we saw during the eurozone
crisis that was a major factor that’s questionable one questionable to
archon GARCH models they do capture volatility clustering during periods of
high and low volatility but my question was can they capture capture or predict
a spike in volatility or correlation breakdown when markets are come to
signal the onset of a crisis thank you sir yes I think there is every reason to
think that G of all and s risk would be endogenous but I don’t think that
changes what we would do it might change the policy implications of it but really
there aren’t a lot of policy implications of gol because it’s not
even predictable so you know I think I think it is that’s why I put them
together on the slide actually so the second question oh yeah predictable hello
during a benign or calm market period can your arch and arch models predict a
sharp spike in future volatility and correlation breakdown to signal the
onset of a crisis well I mean arts and GARCH models never are anticipated to
predict things that that are that are surprised if you talk about the onset of
a financial crisis and you know it’s not predictable the arts and arts models
aren’t going to predict it either and so what happens is that they predict that
volatility will be what whatever they predicted as of the day before and then
when it turns out that this is the day when a financial crisis starts and there
is a big return shock probably a negative shock then that says ooh that’s
a big volatility shock and the the volatility the next day is going to be
high as a result of it and so what we’re doing in the Geo ball is were extracting
that shock and saying you know that’s what happened on the day the crisis
started what else happened on the day the crisis started did this show up as a
big shock in in Belgium and a big shock in New Zealand then the big shock in in
India or not and so that’s exactly where we get the power to do the G of all the
last question please this is Roberta from NEC
I want you to understand about the geopolitical
Indians that you have created do you think that depends on the frequency or
frequency of data that have used because if you see on 9/11 the Giavanna index
was the you know highest as compared to the other period but if you see new in
the trade war time the Geo mall declines it did not show us much of and you know
pink in the volatility so if the geopolitical risk previous for a longer
period of time then the index value is not showing that much of peak for that
particular time as compared to the 9/11 which which is a single day event right okay thank you so a continuous
event isn’t going to show up particularly strongly in the G of all
measure because there isn’t one day in which this happens but during a
continuous event like the trade war you will see elevated volatilities every day
you’re likely to anyway and so when I took averages of the G of all over a
month things that were small but systematically above-average
volatilities did show up in in the average G of all even though it doesn’t
show up on my top 10 list okay thank you very much everyone and once again thank
you very much professor angle for taking those questions thank you so please stay back for a second
professor request mr. limit to please present a memento to felicitate
professor Robert angle sir please accept this special slab as a token of
gratitude and appreciation thank you we are indeed very very privileged and
fortunate to listen to you gentlemen please take your seats while I call upon
mr. je la vie chandran director NSE to propose the vote of thanks a Silver Jubilee is a big moment but
equally important is the recognition of the architects of the institution the
dr. Raj Patel Memorial Lecture seeks to honor a man who was the founding
managing director of NSE and helped transform the financial markets
he was an institution builder par excellence and a simple humble person
professor Engel thank you very much for agreeing to be the keynote speaker at
this Tata Norwich Patel memorial lecture event we are indeed grateful that
despite a hectic travel schedule and extensive commitments you took time to
stop by and spend so much time with us in recent times geopolitical risks in
recent times geopolitical risks have escalated along with political
uncertainty and Markus have felt the full impact of this your research and
experience from both academia and practice provided us with some excellent
insight about how to understand this and be better prepared to handle that we are
grateful to the government say B or ba and other regulators our trading and
clearing members investors shareholders listed companies technology partners
business partners industry associations members of the media our Board of
Directors and our employees past and present for their roles in building and
strengthening this iconic institution to all of you who are present today thank
you very much for your presence support and encouragement in helping us host the
dr. Patel memorial lecture and making it successful this lecture is an annual
event and we look forward to our continued presence
inspiration and support air after year thank you very much on that note we
conclude today’s event thank you all for being a wonderfully lovely audience
kindly proceed for dinner that has been arranged in the adjoining foyer this is
Marcy taking your leave have a great time ahead thank you you you

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