Hello and welcome back to Patrick Boyle on Finance - where we learn all about
quantitative finance. Today we'll be discussing what correlation is and why
it matters to traders and investors. We'll learn why correlation is so high
right now and why investors might care. Keep watching till the end of the video
and I'll explain a trading strategy where traders can profit from rises and
falls in stock market correlation. [Music] ok so here's an interesting statistic for you
right now in June 2020 the S&P 500 index's three-month realized correlation has
settled around the 0.8 level its highest in about eight years
even though other gauges of market stress such as the VIX index has
returned to normal levels. The divergence between these indicators suggests that
investors continue to focus on just one main driver - the global coronavirus
pandemic, making it harder for active fund managers to beat their benchmarks.
Essentially it means that all stocks are rising and falling together and it
doesn't really matter which ones you pick to invest in. Correlation is a
statistical measure that indicates the extent to which two or more variables
fluctuate together. It measures the degree to which two phenomena are
related to one another. A positive correlation indicates the
extent to which variables increase or decrease in parallel. A negative
correlation indicates the extent to which one variable increases as the
other decreases. Uncorrelated variables have a covariance of zero. If two
variables are uncorrelated there's no linear relationship between them.
Correlation is one of the most useful statistics to a trader. This video by the
way is based on my newest book which is called statistics for the trading floor
and it has been released a couple of days ago on Amazon.com. I'll put a link
to it in the description of the video below if you're interested. You can
also check out my other books, one is on derivatives
The other one is on corporate finance.
The S&P 500 index is three-month realized
correlation began the year with a value of around point to the gauge of how
closely the top stocks in the S&P 500 move in relation to one another spiked
to 0.85 in mid-march the peak of the coronavirus sell off before steadying
down at around point 8 a maximum possible correlation of Warren would
signify that all stocks are moving in precise lockstep with each other during
periods of high correlation over the last decade people have blamed the rise
of index funds or quantitative trading algorithms that rely on historical
relationships and end up blindly reinforcing those correlations investors
argued that something was broken in the pricing and capital allocation functions
of the stock market and that all of the different stocks simply rose and fell
together trading like the same stock this time the argument is different
the current explanation for high correlations in the stock market are
that in February there was an economy then in March the economy shut down and
eventually there either will be an economy or there won't if there is an
economy than different companies will have different earnings but if there's
not then no companies will have any earnings obviously every company will be
better off if there is an economy than if there isn't your bet on whether there
will be an economy and when will almost certainly determine whether you think
any particular company's stock is over or under priced particular differences
in the outlook for specific companies have become in this environment
essentially irrelevant this is of course an oversimplification the S&P
correlation is 0.8 not 1.0 and certain companies that are holding up well in
this environment are of course performing better than the most hard-hit
sectors but overall this might be the correct rough model if you're an active
fund manager who spent the last few years argue
that index funds are fine in rising markets with high correlations but in
more complicated times investors will need the human intuition of active fund
management this outcome is far from ideal you were hoping for the market to
go back to normal with some stocks going up and others going down so that you
could pick the ones that go up while index funds were forced to also hold the
ones that go down instead the bull market broke in a way that ended up
increasing correlations in early 2020 all companies were overwhelmed by the
same novel risk they sold off together and then they recovered together based
upon global government interventions one thing that sometimes confuses traders
about correlation is the to us it's can actually be very highly correlated and
stay that way yet one asset might yield a + 50 percent return in a year while
the second asset could yield a minus 50 percent return over the same period the
reason for this confusion is that traders often misunderstand what
correlation means and doesn't mean correlation is best thought of as
representing the general directional relationship between two assets if two
assets start out with a price of will say $20 and every time the first asset
goes up by 1% the second asset goes up by 5% and that ratio of 5 to 1 is
consistent the correlation will be 1 even though the second asset is
producing 5 times the return of the first asset in addition to this there
can be very high correlations between assets where one asset has a decay using
the same example as above let's say that the first asset lost 20 cents of value
every day in addition to its relationship with the second asset there
can still be an extremely high correlation coefficient
despite the first asset falling to zero while the second asset rises in price a
common real-world example of this effect is levered ETFs I made a video about
them blaah weeks ago the double shortly Vord
real estate ETF in 2008 was almost perfectly negatively correlated with the
underlying real estate ETF yet ended up losing almost all of its value if you
had just shorted the real estate ETF rather than buying the double short ETF
you would have actually made money so why does high correlation upset active
managers the idea is that when correlations are high investors should
spend more time worrying about the things that affect all stocks rather
than the things that affect the differences between particular stocks
which is usually what active managers focus on in particular fundamental
managers when correlations are low doing research to find the best stocks will be
more valuable than when they are high we're having an accurate opinion on how
quickly the economy will reopen is significantly more useful so can traders
trade correlation yes they can actually correlation trading is an advanced
trading strategy in which the investor bets on the future realized correlation
amongst the member stocks of a given stock market index the goal in trading
correlation is to predict when future realized correlation amongst the stocks
of a particular index will be greater or less than the implied correlation level
which can be backed out from the pricing of options or other derivatives on the
index and the stocks that make up the index due to the nature of
diversification the volatility of a portfolio of securities is less than or
equal to the average volatility of the individual securities that make up the
portfolio the lower the correlation is between the individual securities the
greater the diversification benefits and the lower the overall portfolio
volatility thus when expected correlation is very low index volatility
will be a lot lower than the volatility of the individual index members and when
expected correlation is very high index volatility will be
to the average volatility of the individual securities that make up the
index to sell correlation a trader can either sell index options while buying a
basket of options on the individual stocks that make up the index or sell a
variance swap on the index and buy variants swaps on the individual
constituents or sell a correlation swap to buy correlation a trader would just
do the opposite of that okay so hit the like and subscribe buttons and if you
found this video useful check out my book on Amazon which is linked to in the
description below bye
you