
Behind the Market Swoon: The Herdlike Behavior of Computerized Trading - ryansmccoy
https://www.wsj.com/articles/behind-the-market-swoon-the-herdlike-behavior-of-computerized-trading-11545785641
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lordnacho
Former fund manager here.

Yes, there is herdlike behaviour. But why?

Here's a little story about my investment career.

I once hired a guy for a fund I was partner in. He was a proper old school
equity investor. He'd fly around the world to different countries and visit
businesses. He'd think about each country's prospects, each industry, and each
company. He'd meet withe the CEOs and look them in the eye, and ask them
whether his company was gonna make money. I shit you not. He's come back to
the office and share his thoughts on why one country was good, why this
industry, why this business. It was a different story each time.

Another guy I worked more closely with on a fixed income desk. We'd think
about different countries, their bonds, their IR rates, swaptions, etc.
There's be some global stories inevitably, but a lot of local ones too and
we'd chat about what to do in our trading book.

Then there was quantitative FX trading, another one of my projects. We'd look
at things that affect currencies, patterns in the prices, anything you might
imagine arrives as a live feed. And we built the infrastructure to trade the
regularities that we found. Quite a lot of research and execution
infrastructure. But at the end of the day, the computers are doing what?
Looking at a variety of information and judging what will happen. Just like my
two colleagues.

Fast forward to the last few years. Pretty much every conversation I have with
anyone in the investment business talks about one thing: QE and zero rates.
There's only one thing that matters for everything now. When interest rates
are really low, what happens? Everything is worth buying. Buy houses, buy
stocks. Buy them in the developed countries, buy them in EM. Sell options.

What used to be a conversation containing rates as an ingredient has become a
conversation only containing rates.

People, and computers which learn what worked for people in the recent past,
have gone from a rich market conversation about many things to one about just
QE.

It will be interesting to see what happens in the near future. I can't think
of a lot of bubbles that were deflated in a controlled manner. And I also
expect more differentiation in equity debates. Company does this, industry
does that.

~~~
rayvy
> Yes, there is herdlike behaviour. But why?

> People, and computers which learn what worked for people in the recent past,
> have gone from a rich market conversation about many things to one about
> just QE.

So are you saying that in the past _N_ years since QE and 0 rates, the
parameters that define which assets/resources to buy/trade have gone from
wide-ranging (e.g., "We'd think about different countries, their bonds, their
IR rates, swaptions, etc"), to singular (e.g., "...has become a conversation
only containing rates.") ?

How does this tie back into the "herd-like behavior" comment? Are you saying
that every algo trader is only focusing on rates because that (more so than
anything else), is determining where to allocate capital?

~~~
lordnacho
I doubt that all algos are looking at the stream of interest rates. It's hard
to know since these things are mostly private.

But they can herd into factors specific to their markets that are nonetheless
still the same thing, due to rates causing behaviour everywhere.

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cs702
As the article points out, passive funds, which have become a dominant force
in the stock market, own the same stocks as everyone else in the same
proportion.

When passive funds _as a group_ have net outflows, all their holdings must be
reduced in roughly the same proportion. But passive funds _as a group_ cannot
reduce their holdings by selling stocks to each other! It's impossible to take
water out of a boat by scooping water from one spot and pouring it back into
the same boat in some other spot!

Therefore, to reduce holdings, passive funds (or their broker-dealers)
necessarily must find _other_ \-- i.e., _non-passive_ \-- buyers willing to
take those stocks at some market-clearing price. Alas, everyone else, in the
aggregate, also owns the same stocks in the same proportion.

Potentially, this can produce temporary imbalances between _passive_ net
sellers and _non-passive_ net buyers that get corrected via declines in price.
Passive net sellers, being price agnostic, do not care; they're on automatic.

~~~
nostrademons
A lot of the attention on the stock market is focused on the short term (i.e.
panic sells or a flight to safety in reaction to quick emotional events), but
I wonder what happens when this dynamic plays out in the long term.

Right now, the pool of people putting money into the market has been steadily
increasing as Millenials enter the workforce. Boomers are retiring, but not
really in large numbers yet, so the overall number of folks saving for
retirement has been continually increasing since Boomers started entering
their prime earning years in the early 1980s.

However, the peak of the Boomer years will soon start entering retirement soon
(~2020) while the early Boomers are starting to die off. And the generation
after Millenials - who will start comprising the workforce in 2020 - is much
smaller than the Millenial generation. There are fundamental issues with
demographics that can't be papered over by financial engineering: a smaller
working-age population supporting a larger dependent population (absent
massive technological advancement in care) = lower standard of living for
everyone.

Demographically, this would play out as a generation-long bear market, but
markets tend to correct as soon as everyone adjusts their expectations for the
future. That implies a sudden and massive crisis at some point with stock
market levels correcting to the yields and prices of the 1970s, adjusted for
inflation. That would imply an S&P 500 of about 370 (down ~95%) and interest
rates in the 10% range.

~~~
gnopgnip
There is an underlying presumption here that US stock market and investors
live in the US, or are otherwise correlated with US demographics. Historically
this is not true. International investors make up a sizeable part of the
investors, and within the US investors the very wealthy are a disproportionate
part of the market.

~~~
nostrademons
The same phenomena is playing out throughout the developed world and even in
much of the developing world, though. Europe has even lower birthrates than
the U.S, China had a huge baby boom in the 50s and 60s followed by a huge baby
bust in the 80s under the One Child Only policy, and Japan has been in this
situation since the 90s.

What _would_ reverse this, internationally, is if the high-youth countries of
Latin America, the Middle East, sub-Saharan Africa, and rural India could be
rapidly integrated into the global economy. There are large political,
cultural, and educational barriers to this, though.

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m0j0e
Clifford Asness sums up my feelings about this article pretty well:
[https://twitter.com/cliffordasness/status/107775763347229900...](https://twitter.com/cliffordasness/status/1077757633472299008?s=21)

~~~
Agathos
I also appreciated one of the first replies: "Didn't hear many complaints
about robots on way up"

~~~
eej71
Nor does the "blame the robots" thesis explain 2017.

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hendzen
Many (if not most) quantitative hedge funds are dollar neutral, which means
they have one dollar short for every dollar long. There are typically
additional constraints about having equal long/short exposure on each industry
and investing style (momentum, value, etc).

So contrary to the article, most of these funds don’t take broad bets for or
against the market. What they are really doing is correcting the relative
valuations of each individual company by shifting bits of capital away from
overpriced companies and towards underpriced ones. That doesn’t have the
effect of raising or lowering broad market indices.

Now there are of course other investors who take broad directional bets on the
market but those are probably more likely to be discretionary bets rather than
systematic.

~~~
kingkawn
How does that not result in a net neutral investment return? Forgive my
ignorance if this answer is obvious

~~~
vasco
To expand on pmalynin's excellent answer with an example:

Imagine you think Apple is better than any other technology company and you
want to bet it will outperform other technology companies. If you simply buy
Apple stock, you might lose money even if it outperforms all other tech
companies, in the case that the whole market is going down. Because of the
above, you need to devise a strategy that will earn you money on the
difference between Apple stock and the overall tech sector stocks. Those
strategies usually involve combinations of stock and derivatives and you can
optimize your returns vs exposure with simple models.

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AlphaWeaver
Non paywalled, and cleaner version:
[https://outline.com/9s3xTZ](https://outline.com/9s3xTZ)

------
cultus
It's no surpise that it should be herdlike, since the algorithms are operating
with much of the same information.

~~~
vasilipupkin
Actually, it works in the opposite direction. Here is why: if betting against
the herd was the right thing to do, algos would learn this behavior and all
algos would start betting against a big price down move. This is why algos
actually reduce volatility, not increase it. And volatility is exacerbated by
humans: trade wars, attacks on the fed and general erratic behavior of our
president

~~~
xapata
No, betting with the herd is the correct bet, except that one needs to place
the bet before everyone else does.

Algorithmic, low latency trading reduces bid-ask spread under normal
circumstances, but increases the risk of extreme events.

~~~
vasilipupkin
We had plenty of algorithmic trading and years of very low volatility at the
same time. If algorithmic trading increased risk of extreme events, it would
have shown up during let’s say 2012-2017 years of low volatility. No,
algorithmic trading actually reduces risk of extreme events such as fat
fingers or extreme bets by humans. What drives volatility is macroeconomic
environment.

~~~
xapata
You don't remember any of the "flash" crashes? Turbulence has increased,
regardless of the general trend.

~~~
vasilipupkin
Flash crash of 2010 was extensively investigated and no evidence that
algorithmic trading was at fault was found. After that, we had some of the
lowest turubulence years on record, while algorithmic trading was going on, so
your theory is not supported by evidence.

~~~
xapata
There have been others. Plus there's some enjoyable literature if you're
curious. Mark Buchanan has a nice blog and some links. The gist of it is that
in the low latency space the ratio of players to possible strategies is too
high.

~~~
vasilipupkin
if yoi try to tie low latency or algorithmic strategies to volatility, you
need to be able to explain multiple years of really low volatility despite all
those strategies going on.

~~~
xapata
Low volatility according to what measure? I don't keep up with the literature
anymore, since around 2010/2011, but it'd surprise me if we entered some new
regime. Googling for "flash crash" turns up many more examples than just the
one you mentioned from 2010.

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WalterBright
Humans exhibit herdlike behavior when investing, too. It's why the term
"contrarian" exists (a person who bets against the herd).

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rdlecler1
Markets are moving much faster but we’re still using the same scale on the x
axis (time). We’ve seen a 4,000 point drop so far but if that occurred over a
one year period we would have called it a recession. However if the market
recovers in the next few months we’ll interpret this as the continuation if a
10-year bull market.

~~~
danmaz74
Recessions are base called based on economic output (GDP), not markets.

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based2
fatfinger vs fht

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Banksy_is_Qanon
Is computerized trading more or less herdlike than human trading, or exactly
the same?

Popular Delusions And the Madness of Algos !

~~~
satya71
I suspect it's the same, but operates thousands of times faster.

~~~
ajross
This bear market took a week to develop. The crashes of 1929 and 1987 happened
in a day. I don't think that point holds.

~~~
bboreham
Which particular day in 1929 are you thinking of?

October 24 - 11% drop, followed by some recovery. October 28 - 13% drop
October 29 - 12% drop

The lowest point in 1929 was reached on November 13. The bottom of the crash
was on July 8, 1932.

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User23
It’s those evil computers! Pay no attention to the central bank behind the
curtain.

