Hi everyone. I’ve been reading Less Wrong and related material off and on for a few years, and I finally made an account and this is my first comment.
5: There was a huge EMH failure w/r/t C19, and it hasn’t been explained away AFAIK.
I also wondered why it took so long for the market to react in February to the likelihood of a pandemic, especially after cases were increasing in Italy and Iran suggesting it could easily spread worldwide. I’m not a big trader, basically just buying and holding index funds for the long term, and the only thing I did differently was to hold off buying more at the peak—instead waiting for what seemed like an inevitable fall before buying (although I didn’t wait long enough). After reading Wei Dai’s posts about his strategy during this time, it seemed clear that the EMH hadn’t performed well here and I wished I had been more confident in my own analysis beforehand.
Later, it occurred to me that there are relatively few individuals who trade at high enough volumes to actually influence market prices, most of whom work for financial institutions. I’ve never worked in that industry, but I imagine employees are subject to the same social pressures as any company, including a reluctance to act differently than what is culturally acceptable within the organization (especially to take a culturally unacceptable risk which may look foolish initially). Since financial firms generally believe in the EMH, it would be very difficult for an individual employee to act otherwise. A low or mid-level trader is probably authorized to make trades based on any financial news, but they probably can’t just go their manager and say “I think I know better than the entire world that this pandemic will be worse than expected and lower stock prices, and the EMH hasn’t priced it in yet.” Even if a few investors do trade on that assumption, they will initially be overwhelmed by algorithmic trading which would tend to revert prices back to the previous EMH-based equilibrium. The markets wouldn’t actually move until either 1. effects from the pandemic start to change actual financial data, and the trading algorithms begin to account for that, or 2. most of the top leaders of financial institutions become convinced prices should go down, and make it socially acceptable for their employees to sell large volumes of stock or change their trading algorithms accordingly.
Until then, there could be a temporary inadequate equilibrium where nobody who has the power to move market prices has a socially acceptable reason to do so. In this situation, rational individual investors who don’t face these organizational social constraints may be able to outperform the EMH.
Maybe a version of the EMH that takes this into account would be “stock prices accurately reflect all public information that is socially acceptable for high-volume traders to base trades on” or something similar.
Others have written here about similar thoughts on the EMH failure, including Matthew Barnett and Alex Shleizer, but I haven’t seen it proposed explicitly as a result of social pressures or incentives within organizations before, so I thought this could add to the discussion. As I mentioned, I don’t work in the financial industry, so I welcome the comments of those who have more relevant experience in the field.
Since financial firms generally believe in the EMH,
Hm. This seems worth poking at: if a financial firm believes in the EMH, why would they be making trades at all?
My understanding of the EMH is that an oversimplified version is “you can’t beat the market, any public information is already priced in”. If you believe this version, you should just buy into low-fee index trackers.
A more sophisticated version is: “the market has lots of clever people trying to beat it. If you can beat those players, you can beat the market”. Under that version, it makes sense for a large financial firm to make trades despite believing in the EMH, because a large financial firm is exactly the kind of organization to have the resources to beat those people.
But under that version, it seems like the firm needs to have some way for people to signal “I think I know better than the entire world...” and make trades on that, because that’s the only way trades ever get made.
And my intuition-that-I-can’t-justify is that: if people couldn’t make trades in this specific case due to social reality within the firms being out of sync with actual observable reality, then that’s probably not confined to this one particular case; and we’d see individuals beating the market a lot more often than we do.
(This is very much a case of “I don’t actually know what I’m talking about.”)
Totally agree with your analysis, especially that large firms and individuals within them are quite clever and operating as described in your sophisticated version. They are the very people who put the “efficient” in the efficient market hypothesis! And I agree that every trade is essentially a statement that “I know better than the entire world...”, with real money on the line. Yet the combined actions of these clever people, who have huge incentives to beat the market and are used to trading with confidence that they know better than the entire world, seemingly did not move the market quickly enough, and at least some individuals were able to take advantage of this.
And my intuition-that-I-can’t-justify is that: if people couldn’t make trades in this specific case due to social reality within the firms being out of sync with actual observable reality, then that’s probably not confined to this one particular case; and we’d see individuals beating the market a lot more often than we do.
This gets to the crux of the argument—under what circumstances would this disconnect occur, and can others outside the industry recognize when it may be happening? It must be quite rare, otherwise as you mention we would see more evidence of individuals regularly beating the market. It might require several factors to come together at the same time, without which the usual efficiency will be maintained. Some thoughts along these lines, expanding on my earlier comment:
1. Traders might only be willing to bet confidently against the entire world in their field of expertise (analyzing financial data), but not based on data from other fields (pandemic predictions). They may think: there are likely others who know more about this topic than me, and the market hasn’t moved yet (or, the knowledge is priced in already), so how can I justify betting big on my hunch? Especially when I would have to explain it to my manager (or the board of directors) if I was wrong?
2. Related to the last point—loss aversion bias regarding one’s social status with the organization. If someone bets big based on pandemic data, and is right, they will gain some social status and probably a financial reward. But if they’re wrong, they will lose social status and might be at higher risk of being fired. If the potential loss outweighs the potential gain, the safe option would be to not bet on pandemic data, and only trade based on financial data (as would be socially expected within the organization) and face little or no social status penalty.
3. Algorithmic trading was probably based initially only on financial information, which had not turned for the worse yet, so any pandemic prediction-based trades would be overwhelmed by algorithmic trades as far as moving stock prices. This would last until algorithms started taking into account pandemic data and/or the actual financial data got worse due to pandemic effects.
I’m sure others could identify additional relevant factors at play here.
One thing I don’t have any calibration on is how big a trade would have to be to overcome this neutralizing effect of algorithmic trading on overall stock prices. For example, say there is an employee of a large firm who has the authority to risk 1% of the firm’s overall portfolio. If they switched that 1% from a fully long position to fully short, would the market stay lower, or would algorithmic trading revert it to the previous equilibrium? What if the CEO of the firm switched their entire portfolio from long to short? What if the CEO did that, and also announced publicly they had done so and their reasons why? At what point would we expect markets to actually change course?
This quote from Moral Mazes seems relevant to this earlier discussion, and may provide further understanding for why markets were slow to respond to the pandemic (emphasis mine):
115. This explains why the chemical company managers kept putting off a decision about major reinvestment. After the battery collapsed in 1979, however, the decision facing them was simple and posed little risk. The corporation had to meet its legal obligations; also, it had either to repair the battery the way the EPA demanded or shut down the plant and lose several hundred million dollars. Since there were no real choices, everyone could agree on a course of action because everyone could appeal to inevitability. This is the nub of managerial decision making. As one manager says: Decisions are made only when they are inevitable. To make a decision ahead of the time it has to be made risks political catastrophe. People can always interpret the decision as an unwise one even if it seems to be correct on other grounds. (Location 1886)
In Feb/March, if the relevant financial institutions were going through such a behind-the-scenes process of “establishing the inevitability” of the pandemic before large market-moving decisions could be made, this could explain the apparent delay (and corresponding opportunity for the rational individual investor). One can imagine individuals within these firms feeling each other out—“This pandemic might turn into a big deal, huh?” “Yeah, but the boss hasn’t seemed too concerned yet, let’s give it another few days before we bring it up again”—before the consensus grew large enough where the decision became inevitable.
If this model is accurate, when would we expect to see these kinds of delays (and opportunities) in other situations? Here are some factors that may have contributed:
The early pandemic required integrating a lot of information outside the core areas of expertise of firms and their traders, leading to more uncertainty and a longer delay to reach consensus.
People are bad at extrapolating exponential growth (citation needed), and while some individuals within firms may have realized the implications right away, others may have thought their concerns were way overblown, again prolonging the time to reach consensus.
This was a rare event that had not occurred within anyone’s living memory, so there was no good frame of reference to fall back on, also increasing uncertainty.
I feel like there’s something here worth investigating more closely, although I’m still having trouble understanding it as well as I would like to. For now I’ll note that these three factors also seem very applicable to the current state of AGI development, and so may tie in with previous discussions such as this one.
Hi everyone. I’ve been reading Less Wrong and related material off and on for a few years, and I finally made an account and this is my first comment.
I also wondered why it took so long for the market to react in February to the likelihood of a pandemic, especially after cases were increasing in Italy and Iran suggesting it could easily spread worldwide. I’m not a big trader, basically just buying and holding index funds for the long term, and the only thing I did differently was to hold off buying more at the peak—instead waiting for what seemed like an inevitable fall before buying (although I didn’t wait long enough). After reading Wei Dai’s posts about his strategy during this time, it seemed clear that the EMH hadn’t performed well here and I wished I had been more confident in my own analysis beforehand.
Later, it occurred to me that there are relatively few individuals who trade at high enough volumes to actually influence market prices, most of whom work for financial institutions. I’ve never worked in that industry, but I imagine employees are subject to the same social pressures as any company, including a reluctance to act differently than what is culturally acceptable within the organization (especially to take a culturally unacceptable risk which may look foolish initially). Since financial firms generally believe in the EMH, it would be very difficult for an individual employee to act otherwise. A low or mid-level trader is probably authorized to make trades based on any financial news, but they probably can’t just go their manager and say “I think I know better than the entire world that this pandemic will be worse than expected and lower stock prices, and the EMH hasn’t priced it in yet.” Even if a few investors do trade on that assumption, they will initially be overwhelmed by algorithmic trading which would tend to revert prices back to the previous EMH-based equilibrium. The markets wouldn’t actually move until either 1. effects from the pandemic start to change actual financial data, and the trading algorithms begin to account for that, or 2. most of the top leaders of financial institutions become convinced prices should go down, and make it socially acceptable for their employees to sell large volumes of stock or change their trading algorithms accordingly.
Until then, there could be a temporary inadequate equilibrium where nobody who has the power to move market prices has a socially acceptable reason to do so. In this situation, rational individual investors who don’t face these organizational social constraints may be able to outperform the EMH.
Maybe a version of the EMH that takes this into account would be “stock prices accurately reflect all public information that is socially acceptable for high-volume traders to base trades on” or something similar.
Others have written here about similar thoughts on the EMH failure, including Matthew Barnett and Alex Shleizer, but I haven’t seen it proposed explicitly as a result of social pressures or incentives within organizations before, so I thought this could add to the discussion. As I mentioned, I don’t work in the financial industry, so I welcome the comments of those who have more relevant experience in the field.
Hm. This seems worth poking at: if a financial firm believes in the EMH, why would they be making trades at all?
My understanding of the EMH is that an oversimplified version is “you can’t beat the market, any public information is already priced in”. If you believe this version, you should just buy into low-fee index trackers.
A more sophisticated version is: “the market has lots of clever people trying to beat it. If you can beat those players, you can beat the market”. Under that version, it makes sense for a large financial firm to make trades despite believing in the EMH, because a large financial firm is exactly the kind of organization to have the resources to beat those people.
But under that version, it seems like the firm needs to have some way for people to signal “I think I know better than the entire world...” and make trades on that, because that’s the only way trades ever get made.
And my intuition-that-I-can’t-justify is that: if people couldn’t make trades in this specific case due to social reality within the firms being out of sync with actual observable reality, then that’s probably not confined to this one particular case; and we’d see individuals beating the market a lot more often than we do.
(This is very much a case of “I don’t actually know what I’m talking about.”)
Totally agree with your analysis, especially that large firms and individuals within them are quite clever and operating as described in your sophisticated version. They are the very people who put the “efficient” in the efficient market hypothesis! And I agree that every trade is essentially a statement that “I know better than the entire world...”, with real money on the line. Yet the combined actions of these clever people, who have huge incentives to beat the market and are used to trading with confidence that they know better than the entire world, seemingly did not move the market quickly enough, and at least some individuals were able to take advantage of this.
This gets to the crux of the argument—under what circumstances would this disconnect occur, and can others outside the industry recognize when it may be happening? It must be quite rare, otherwise as you mention we would see more evidence of individuals regularly beating the market. It might require several factors to come together at the same time, without which the usual efficiency will be maintained. Some thoughts along these lines, expanding on my earlier comment:
1. Traders might only be willing to bet confidently against the entire world in their field of expertise (analyzing financial data), but not based on data from other fields (pandemic predictions). They may think: there are likely others who know more about this topic than me, and the market hasn’t moved yet (or, the knowledge is priced in already), so how can I justify betting big on my hunch? Especially when I would have to explain it to my manager (or the board of directors) if I was wrong?
2. Related to the last point—loss aversion bias regarding one’s social status with the organization. If someone bets big based on pandemic data, and is right, they will gain some social status and probably a financial reward. But if they’re wrong, they will lose social status and might be at higher risk of being fired. If the potential loss outweighs the potential gain, the safe option would be to not bet on pandemic data, and only trade based on financial data (as would be socially expected within the organization) and face little or no social status penalty.
3. Algorithmic trading was probably based initially only on financial information, which had not turned for the worse yet, so any pandemic prediction-based trades would be overwhelmed by algorithmic trades as far as moving stock prices. This would last until algorithms started taking into account pandemic data and/or the actual financial data got worse due to pandemic effects.
I’m sure others could identify additional relevant factors at play here.
One thing I don’t have any calibration on is how big a trade would have to be to overcome this neutralizing effect of algorithmic trading on overall stock prices. For example, say there is an employee of a large firm who has the authority to risk 1% of the firm’s overall portfolio. If they switched that 1% from a fully long position to fully short, would the market stay lower, or would algorithmic trading revert it to the previous equilibrium? What if the CEO of the firm switched their entire portfolio from long to short? What if the CEO did that, and also announced publicly they had done so and their reasons why? At what point would we expect markets to actually change course?
This quote from Moral Mazes seems relevant to this earlier discussion, and may provide further understanding for why markets were slow to respond to the pandemic (emphasis mine):
In Feb/March, if the relevant financial institutions were going through such a behind-the-scenes process of “establishing the inevitability” of the pandemic before large market-moving decisions could be made, this could explain the apparent delay (and corresponding opportunity for the rational individual investor). One can imagine individuals within these firms feeling each other out—“This pandemic might turn into a big deal, huh?” “Yeah, but the boss hasn’t seemed too concerned yet, let’s give it another few days before we bring it up again”—before the consensus grew large enough where the decision became inevitable.
If this model is accurate, when would we expect to see these kinds of delays (and opportunities) in other situations? Here are some factors that may have contributed:
The early pandemic required integrating a lot of information outside the core areas of expertise of firms and their traders, leading to more uncertainty and a longer delay to reach consensus.
People are bad at extrapolating exponential growth (citation needed), and while some individuals within firms may have realized the implications right away, others may have thought their concerns were way overblown, again prolonging the time to reach consensus.
This was a rare event that had not occurred within anyone’s living memory, so there was no good frame of reference to fall back on, also increasing uncertainty.
I feel like there’s something here worth investigating more closely, although I’m still having trouble understanding it as well as I would like to. For now I’ll note that these three factors also seem very applicable to the current state of AGI development, and so may tie in with previous discussions such as this one.