Investing - Theory, News & General • The Day The Factors Died

While shorting gets you a higher rebate during periods of higher interest rates, I don't use shorting to get a factor premium because the borrowing cost (for borrowing shares) of shorting is too high and shorting is also too risky to manage (if you're not just doing it to avoid taxes).

Yes that's my point. You mentioned that investors using long-only funds might have trouble. I assumed that meant you short sell. Apparently not. You have to borrow to short sell. You have to pay interest to borrow. It costs money. It costs more money when rates are high.

Momentum has been doing well in Europe and India, but not in the U.S., while East Asia is known for reversals. I'm not quite sure what you mean by momentum being difficult to capture though.

These two sentences are internally inconsistent. Momentum has been doing well in one place and time, but not another. So how do I capture a premium from it if I can't determine where and when it works? That's exactly what I mean be it being difficult to capture.

Regarding Chen's works, many of his papers point out that factors are unlikely to be the product of data mining alone as you said (I also doubted factors as a Bogleheads before I read enough papers):

The Limits of P-Hacking: A Thought Experiment

https://papers.ssrn.com/sol3/papers.cfm ... id=3358905

Most claimed statistical findings in cross-sectional return predictability are likely true

https://arxiv.org/pdf/2206.15365

And the paper I mentioned before:

High-Throughput Asset Pricing

https://arxiv.org/pdf/2311.10685

Yes, Chen's work and many others have shown that the distribution of past returns has shown factor premia. And many of those factors or "anomalies" persist out of sample. I do not doubt that. Few who are academically inclined would. But that's not his or my point. His point is that the premia has decayed. My point is that even if the premia is there, the average retail investor is unlikely to persistently capture it.

His points about data-mining are interesting. The practice is not favored among academics in my field (not economics) because it lacks explanatory power. I know all about "p-hacking". I'm pretty good at it when I want to be. Chen's arguments about it being more useful than previously acknowledged are interesting. But there is some survivor bias there. By that i mean that you can "data mine" a predictive model and have it work really well. Then you can look back, pat yourself on the back and claim victory. But you can also do it and have it fail. The world only remembers the or remarks on the models that in retrospect are successful.

And hat's all fine, but it wasn't the point you made about Chen. You said that his work did not take into account the bull market in factors since 2021. His paper and on that subject predate that bull market. The 2024 paper you cite does not address that topic. If you think he should update his studies, send him an email and see if he responds.

There's another problem with that Chen article, he uses returns instead of alpha. Since most of the factors are negatively exposed to market factors, this causes them to underestimate the alpha that can be gained.

No. "factors" are an academic construct. The single factor long-short portfolios that FF generated, for instance, were explicitly designed to isolate the effects of market on factor estimates. They also explictly exclude trading costs and interest rates. The whole point of the studies was to isolate factor effects from other effects. That's one of the reasons these studies were designed the way they were, as opposed to portfolios that real investors could actually hold.

Return is another story. In the real world investors are subject to market risk, interest rate effects, etc. I think that was Chen's point. Once you introduce those elements, premia decay. You can argue with his methodology. But that's the point he is making.

At last, an individual investor will actually have lower transaction costs because you are trading less. The reason institutional investors need all sorts of weapons to lower transaction costs is because they are whales.

Edit: Supplement the reply

I don't know. I have to trust you on that. My impression is that regular joe with a fidelity account probably isn't winning the bid ask spread by writing market orders when competing with large investors and high frequency computer algorithms, but maybe you're right.

Short sellers actually gain interest, not the other way around. The main problem is that attractive short selling opportunities have higher stock borrowing costs and short squeeze risks. I just wouldn't try it. Maybe you should know the difference between stock borrowing costs and rebates. The latter increases when the interest rate increases.

East Asia's momentum factor underperforms mainly because their value factor is always too strong and they are negatively correlated. When you strip the value factor from price data, the remaining returns will have momentum. Of course, it's true that you can't be sure that a certain type of factor in a place will perform well over time, which is why it's necessary to diversify and stay the course as you do for market factor.

You're just repeating your argument that you don't think data mining can be useful, but hopefully you'll read the paper before responding to what he mentions. In fact, Chen finds that factors with more and "better" explanations perform worse out-of-sample. The machine learning community has also found that the pursuit of explanatory power impairs out-of-sample predictive power. Perhaps what we need is to embrace the intelligence of machines rather than hoping we can explain their results. Bad explanations would hurt your performance. They are even worse than nothing.

As for your later statement that the factors are constructed, you don't seem to understand what I'm talking about, because I didn't say that the factors aren't constructed. The point here is that longs on factors tend to have lower beta and shorts on factors tend to have higher beta, so it is unfair to calculate the role of factors solely in terms of the difference between long and short returns because the consideration of market premium considerations would actually increase excess returns. In addition, the interest rate story actually favors factor investors, which allows them to explain 2009-2020, but I think the story lacks foundation.

In fact, the premium "decayed" less than I thought it would, a difference that was not at all unexpected considering that 2005-2020 included two major factor bear markets, while 1984-2000 was with a period of particularly good factor performance because many retail investors come in and gamble their money.

Also, in order to get good trade execution, you should not (only) use market orders. However, the fact is that if you use robinhood, maybe the market maker will think you are a WSB YOLO APE and give you good execution. I never tried it. After all, you don't actually have to win over high frequency market makers, you can't. You just need to get less bad trading costs.

Edit: Maybe you should know HFT companies and hedge funds are different. Just search VIRT. It is a public-listed HFT company. You can't beat HFT, but you can beat hedge funds in the aspect of trading costs

Edit2: Of course, I understand perfectly well that A.Y. Chen knows about the factor bull market after 2021, which is well known in the industry, just like the momentum crash of '09 and the value super-bear market of '18-20, so I don't see the need to email him. It's just a basic fact, and as you say, maybe he didn't have time to take that into account when he was writing that paper.

However, in any case, it's clear that you don't have any valid counterarguments to my original argument in this regard. Obviously, even if the paper was written at an earlier time and therefore may have limitations, that doesn't mean we can't talk about it with the addition of later circumstances to point out its limitations.

Listen. Truth is in three or four posts you’ve contradicted yourself a few times and so, you’re right, I don’t understand what you are trying to say. This last one was mostly just a word salad.

So why don’t you just show us your strategy, what exactly are you buying and selling? When are you buying and selling it? Are you long? Are you short? Are you borrowing? Are you lending? Are you in a hedge fund? Are you doing this in Robinhood? You got a model? Show me numbers. Pretty please. I promise you, I can handle the truth.

Otherwise, you just sound like the guy in high school who talks about his girlfriend who lives the next town over but who no one has ever seen.

Just because you can't understand because of a lack of cognition doesn't mean there is a self-contradiction. For example, you can't understand why there are reversal-dominated markets where momentum factors are still viable. This is because you don't know what residual momentum means.

Many of the questions you ask I have answered before, maybe you need to read what I said.

Statistics: Posted by folkher0 — Sat Aug 10, 2024 4:00 pm — Replies 211 — Views 16574