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Behind the Market Swoon: The Herdlike Behavior of Computerized Trading

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Re: Behind the Market Swoon: The Herdlike Behavior of Computerized Trading

#51

Earlier quoted context omitted.

It's not any different other than the speed it happens at. 20 years ago it would have taken minutes/hours for some of the drops we've seen to materialize. Now you can watch the NQ drop 100 points in less than 5 minutes, 20 years ago that would have taken hours, possibly all day. People had to wait on quote services via satellite, telephone calls to their floor traders, or actually be in the pits during the selloffs.…

> 20 years ago it would have taken minutes/hours for some of the drops we've seen to materialize. Twenty years ago was 1998. Ten years before that , Black Monday was faster and more vicious than anything we've seen since. It remains "the largest one-day percentage decline in the DJIA" [1]. [1] https://en.wikipedia.org/wiki/Black_Monday_(1987)

Black Monday is the edge case

Re: Behind the Market Swoon: The Herdlike Behavior of Computerized Trading

#52

Earlier quoted context omitted.

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 overal…

> the peak of the Boomer years will soon start entering retirement soon (~2020) Boomers were born 1945-1960, meaning in 2020 they'll be 60-75. They started retiring long ago.

Some did. Peak births per year happened in 1957, and during the boom, total births were skewed toward the latter end of the 1947 to 1965 period. In 2017 the median retirement age in the USA seems to have been 62, I can only imagine that number will have increased over 2018 and will continue to increase as the markets stagnated. That would put us just now approaching peak retirement rates. Add to that the fact that investment advisors still seem to want to wait most people toward equities for their first few years of retirement (at 60, your investment horizon is still 20 years out these days...) switching fully to more fixed income and few years in, I think that all is a recipe for the rotation just beginning.

Re: Behind the Market Swoon: The Herdlike Behavior of Computerized Trading

#53

Earlier quoted context omitted.

>> 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. THIS. This is how it works. They also have similar basis prices for their positions, and similar pain thresholds. It's not a big surprise that when Institution XYZ reaches its' pain threshold and stop loss orders are used, a few more dozen Institution ABC, D…

> They also have...similar pain thresholds Passive funds have no pain thresholds which force them to sell. Investors in them may. But that’s a difference in how individual investors’ risk tolerances are abstracted to broad market pricing, not a change in those risk expressions themselves.

I disagree, I'd argue that exactly 4 times a year, passive funds must sell, and must buy again. Contract expiration dates cause huge volumes of activity from so-called "passive" funds. The seconds, minutes, hours, and (occasionally) days that elapse between rolling out from current month to forward month contracts are all about the fund managers pain threshold. The exception to this rule is if your fund has governance specifying that rollovers have to happen ASAP(as in, as each contracts are sold from the current month, forward month contracts must be bought before repeating the process), which is not common.

edit: Sometimes I'm blinded by the part of "market" I operate within, which is the commodity futures market. I could be(and likely am) completely wrong when you apply this to the securities market, which I am less familiar with.

Re: Behind the Market Swoon: The Herdlike Behavior of Computerized Trading

#54

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 the…

Pretty much every conversation I have with anyone in the investment business talks about one thing: QE and zero rates.

Well, the Fed seems to ending that. Certainly it's signaling an end to this. How would this change the conversion?

Re: Behind the Market Swoon: The Herdlike Behavior of Computerized Trading

#55

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.

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

Re: Behind the Market Swoon: The Herdlike Behavior of Computerized Trading

#56

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.

This was a healthy correction. I was expecting a bounce at $251 on $SPY but it went much lower. This is insanely healthy when we recover. Now we can have a 15-20 year bull run.

Re: Behind the Market Swoon: The Herdlike Behavior of Computerized Trading

#57
post #5

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

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

Re: Behind the Market Swoon: The Herdlike Behavior of Computerized Trading

#58
post #5

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

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

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.

Re: Behind the Market Swoon: The Herdlike Behavior of Computerized Trading

#59
post #58

Earlier quoted context omitted.

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

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.

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.

Re: Behind the Market Swoon: The Herdlike Behavior of Computerized Trading

#60
post #58

Earlier quoted context omitted.

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.

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.

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