How strong is the arbitrage effect of P123 members?

AI Machine Learning
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All,

TL;DR: I think downloads are key. We can share general methods (to trim or not to trim data on stock returns for example), keep a few secrets if people are concerned. And pursue your own ideas without having to convince everyone else of its worth or how high of a priority it should be (which could actually be a big secret that you do not want to convince everyone else to start doing anyway).

Lets imagine that Yuval, Duckruck, Walter, SteveA, Azouz, pvdb, Jonpaul, Marco, Dan, Judith and others all started emailing each other after Yuval comes up with a unique method that he wants to discuss and perfect. Maybe it is so revolutionary, unique and effective that they even sign an NDA. Working together they automate it. But alas, despite the NDA, it leaks out to the rest of the community.

With the code that is published in the forum, Python and ChatGPT to answer questions for code -illiterates (like me) a large part of the community starts using it.

So, first of all, the idea that even the majority of the community would all agree that a method is great is pretty ridiculous. Even if it is great, I mean. The community is contrarian and egos prevent them from liking an idea that they did not originate. Not that some natural skepticism is necessarily a bad thing.

But in any case, would the method still work or would the benefit be arbitraged away once it became public at P123 and widely used by the members?

Obviously I do not know the answer. It does make me wonder sometimes about how much of my method I should discuss in the forum.

For example, do I want everyone at P123 being aware of the Day-of-the-week-effect and opening ports on Friday? Maybe switching over to TWAP for VWAP? Even if the idea is wrong do I really want everyone else doing it? Convince them to start doing some of the things that seem to be working for me?

And it is not like Whycliffes (originator of that thread on opening vs closing transactions) is ever going to thank me. Marco did thank me for my machine learning ideas in the past and does take some feature ideas from the forum (including some of mine). Thank you @marco for that!!!

BTW, @yuvaltaylor listened to my idea and acknowledged my contribution on opening vs closing prices. In addition, he is not in charge of product development so ultimately we don’t have to reach a consensus–or for each of us to even fully understand an idea—in order to get a feature request considered. Anyway, thank you @yuvaltaylor.

Even without specifics of the method would we want every Kaggle member coming to P123 and using advance Deep Learning methods and automated reinforcement learning online-methods to asses every factor and their interactions on AWS servers almost real-time (which would not be unreasonable at today’ prices and the right investment size)?

My take: The P123 community is not that large compared to say BlackRock who also invests in the small-cap, micro-cap space it seems. I am not really sure what Medallion is doing but they might not want to miss every clearly opportunity in the small-cap space. Others, including, BlackRock, Numrai etc., are probably already using the “super-secret” method. Maybe it won a contest at Quantopian and the person paying for the contest-prize noticed at the time. It might not even be new method.

Maybe anyone who visits Yahoo could figure out that opening prices thing. My only point being much of what we do is duplicated elsewhere, albeit much of it by professional fund (and even some retail investors). Screeners, at least, are not rare (e.g., at Zacks with some cross-over on analysts’ data I would guess).

And actually, there could be a benefit. To some extent what we do works because others think the same way we do (including the P123 members and BlackRock). You may have to get in earlier, but if you do get in early, the buying that comes after you get in could be a good thing.

Thoughts?

Jim

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The arbitrage effect in the P123 community isn’t going to be very large in my opinion, especially not for methodology. Methods of testing don’t get arbitraged; stock-picking strategies might, but to a very limited degree. That’s just my two cents, not gospel.

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This question of arbitrage effect was actually one of the first questions I had when I joined. I also have not reached an answer.

It seems the entire field of factor investing has had a big effect on factor returns as we see many factors loose effectiveness over time. But I assume that is from a much much larger group of investors using them instead of just P123. Or maybe it is from other market conditions…

I think that answering this would be very difficult as you would likely need to see live portfolio performance before and after the “secrets” were shared. I don’t think you can use something like the core combinations as I assume many if not all of those factors are used in academic studies and thus are widely known even outside of P123. Also I don’t think it has live performance before the ranking system was public.

Maybe you can look at alpha decay of popular factors to see how fast they rise and fall as an estimate???

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There’s a very good argument to be made that price-to-book stopped working at around the same time that everyone started using it as a proxy for value. Once dozens of ETFs started to be based precisely on this ratio, how could it possibly work well any more? This is an extreme case, of course, but arbitrage is also the reason that Benjamin Graham’s net-nets strategy also stopped working, and maybe it’s even to blame for the O/S failure of Greenblatt’s “magic formula.” There was no price-to-sales ratio prior to the 1980s (it was invented by Ken Fisher in 1983) and it worked really well for a while. Everyone was using it, and it was greatly popularized by not only Fisher but also Jim O’Shaughnessy. And then it more or less stopped working, except during certain periods. Was it arbitraged away or not? I don’t know.

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TL;DR: Stocks move on new information. That movement has a time-course. What else do you want to know to answer this question? Isn’t that what we mean by arbitrage in this context?

I do think arbitrage has a kind of esoteric meaning and gets in the way of this discussion. We are really trying to answer what new information moves markets and how quickly that information moves the market here in 2023. is alternative data disseminated as quickly? Maybe people buy credit card data because it take a while for retrial investors to get that information.

Some at P123 place important on finding new factors that make sense to them but are not being used by others (the equivalent of Fisher’s price to sales). We can argue it that really worked for Fisher or not (or O’shaughnessey) but some believe in that.

Even, I who likes the method more than the factors understand you have to have good factors. And the stocks need some turnover—in part because the new information eventually gets priced-in.

We have a post showing that for some models some of that movement can occur in the first day of trading on a Monday. "Next open" always the best - #47 by yuvaltaylor

Which just suggests this arbitrage can occur relatively quickly at times.

With reduced movement by Friday for some ports (on the now 5-day old information). I.e., The new information can be priced-in by Friday.

But why do we ever even sell a position? Isn’t it because, at least to some extent, the new information in our ranking system evenytually gets arbitraged way for basically every port ever created at P123?

I am not sure what more you would need to show that there CAN be arbitrage.

There has to be some arbitrage somewhere, at some point for the market to even work, I think.

Jim

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Correct. So it is a matter of not using the same definitions in the discussion, I think.

Unless you think that your discussion of different factors above comes under the umbrella of “arbitrage.” In which case, some people are overthinking this.

New information eventually gets priced-in. Full stop. The only question worth considering is: How fast and which factors work best here in 2023.?

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I’m not interested in a lot academic discussion involving definitions.

Personally, I find it useful to have recent information. The more recent the better. For my present models and for my machine learning models that I rebalance on Fridays, I like to have the data from the overnight update. I find it preferable to the data from the previous weekend.

That has been my major thrust in the forum for a while.

Simple enough for me.

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Duckruck,

Great question!!! My simple answer is not enough to reach a good conclusion that would be helpful to you.

I paper traded a port for a time. Seemed like forever at the time but not very long really. And I think I was not using good factors then either. So an n of one and a pretty lame n at that. But I was unimpressed with the results if that helps at all.

Jim

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I think the only way that I have tested the difference is with the paper-traded port I mentioned above.

So I you have been able to backtest daily rebalance you are using largely technical data that is updated daily for daily rebalance at P123?

Interesting. Than you for sharing.

Jim

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Correct on both counts I think. Fundamentals are updated weekly, I believe.

But you write formulas that update value-based factors daily based on price (or other technical data)?

So just trying to understand. If I use a FCF/Price as a pre-built P123 factor in a ranking system it might be updated weekly in a sim ranking system.

But you thought of putting FCF/close(0) in a by rule?

Not sure, but very smart if that is what you are doing to get around that.

Edit: And one could kind of simulate the ranking system in a buy rule like: 1 * FCF/close + 3 EBITDA/close(0)……Using the normalized weights of value factors that include price in your ranking system? You might even be able to get a factor that is sort of like enterprise value using close(0). I am sure Yuval would know how to do that.

Second edit. You could even add weekday != 2 to your buy or sell rule so that your port uses the ranking system on Monday. You would have to include something so that you did not get wip-sawed selling on a Monday and buying on Tuesday with a Buy rule that was not exactly like the ranking system.

Maybe include a minimum price-change rule to make sure that a price-change is triggering the buy or sell along with a minimum holding period after being bought perhaps.

So like sell rule (close(0) - close(3))/FCF > 0.2; if you are pretty sure that would kick it out of your ranking system that included FCF/P. So it would not be bought again on a Monday unless the price had changed again (or a new FCF with an earnings report).

Jim

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Just my .02 as someone who self admittedly knows nothing…

If you look as to why someone “deserves” alpha, it would be an informational advantage, a systemic advantage or a behavioral advantage. I think it makes sense that net-nets and Price to Book should be arbitraged away. First of all, these are simple single factor or formula arbitrages. To discover a net-net in the days of Ben Graham, it took a tremendous amount of work. You had to spend hours and hours manually piling through 13Fs looking for them. An investor should have been rewarded for that kind of informational advantage. It makes sense that that advantage should disappear when anyone can run a simple screen looking for net-nets and get a list of them in seconds on any number of free screeners provided by any large brokerage Likewise, I think it make sense that Price to Book should largely lose efficacy when anyone can pull up Vanguard and buy an Value ETF of the cheapest price to book with billions and billions in AUM in a matter of seconds. What advantage have they earned to deserve alpha?

I’m personally skeptical that P123 community itself could arbitrage away alpha like that using a multi-factor , even on small and microcaps. There’s just too many frictions involved, even if you were to just blindly follow the P123 Core system. It’s just too hard to implement on an institutional scale, and on the retail scale there’s a pretty sizable learning curve involved just to blindly copy an existing system, much less having the behavioral discipline to stick with it during underperformance. P123 users are still rewarded for informational, systemic and behavior advantages that come with being the type of person who becomes an P123 user. Now, if someone finds a way to create an ETF with a P123 microcap multi-factor system where anyone could emulate with a few clicks on Schwab or Fidelity, that’s another matter. But I personally think that would be difficult to pull off.

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I see 50% drawdowns in P123 models all of the time. I leave it to Yuval to quantify drawdowns for his models. But I did not think he claimed there were no drawdowns (possibly significant but I will let Yuval characterize his drawdowns).

Speaking only for myself, the sim of one of the ports I am funding has a 54% drawdown, I would probably be wrong to call it a port with pure value factors but it does turn out to be pretty correlated with the SP 1500 pure value benchmark……

……Hm that VALUE BENCHMARK had a drawdown of 76%.

I think you are right except the you are the first person in this thread to actually post the claim (attributed to some unknown person who is not you, I get) that value investing is safe, I think.

Just as an aside, did I mention I do choose to diversify with some ETFs using Portfolio Visualizer before?

Jim

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So InmanRoshi did not lump all value stocks together whether it was I or someone else who tried to do that as a debating tactic. My apologies if it was me.

He made a cogent argument that value investing continues to work but certain value factors have lost their effectiveness once they become widely know. I think Yuval made a similar point.

Not proof but some good evidence, I think. To be clear good points ImanRoshi.

But it is also true that timing of events, by itself, does not prove cause and effect, which may be one of your points. I am simply apologizing for any unfair debating tactics in the thread if, in fact, I did that. And recognizing the value of ImanRoshi’s nuanced argument at the same time.

Jim

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Got it. I guess I will have to move to those consistently effective growth factors. :wink:

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I use whatever works including a good number of growth factors. It turns out I do not use a lot of momentum factors (Yuval introduced me to some industry momentum factors I occasionally use) or volatility factors. My choices are objective (e.g., Spearman’s Rank Correlation) so not a ton of bias against any factor, on my part anyway.

But I have to admit I have neglected my backtesting over the 1825 - 1871 period. Although some days I feel old enough that I think I should be able to remember that period :slight_smile:

I am simply pointing out that your graphics about value factors says exactly zero (nada, zilch, goose egg) without a comparison.

Show us growth factors if I am wrong about that.

Jim

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This is a fascinating discussion. Just a few points:

  • There are no daily ranks in backtests. If a price changes over the course of a week, the rank stays exactly the same. Daily rebalancing in simulations means that buy and sell rules and universe rules are evaluated every day rather than only weekly. But ranks are not revisited.

  • There are a number of different meanings of the word arbitrage (of course). Jim says, “There has to be some arbitrage somewhere, at some point for the market to even work” and duckruck replies, “Arbitrage requires that the asset that is long and the asset that is short are close enough together. For example, long APE and then short AMC is arbitrage, but long value stocks and then short glamour stocks is not arbitrage.” The word is being used in two different ways here.

  • The only purely academic book on finance I have read from cover to cover is Charles Lee and Eric So’s Alphanomics, which I wrote about here: Alphanomics: The Study of Security Mispricing - Portfolio123 Blog. I loved it and I think it’s pertinent to this discussion of arbitrage. Lee, for what it’s worth, is an active user of Portfolio123 and uses it to teach his finance classes.

  • I would be interested in hearing from you, duckruck, an elaboration of your theory about the place of “pump-and-dump schemes” in market history and predictability, as well as why you characterize the success of PFIE as an example of one.

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Duckruck,

I did make an error in using the word abritrage. Thank you for pointing it out.

Alpha Architect is constantly beating the drum that there are investable opportunities due to Limits of Arbitrage

I broadened that concept to include the effect retail investors have in reacting to new news and helping to create an efficient market. I misused the word arbitrage when I did that.

My broader point (whether correct or not) is that new information gets priced-in whether it is largely due to arbitrage, or due to retail investors or funds like BlackRock that may or may not be fully hedged (which I mentioned above).

Thank you for the correction.

Jim

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Duckruck,

TL;DR: I am happy for the discussion and certainly will be more precise in the use of the word arbitrage going forward. I am only interested in how new information gets incorporated. Whether P123 members do much of that (moving the market), how fast it occurs and what factors move the markets most.

Please do not misunderstand my point here. I am EXTREMELY happy about your comments. Mainly just for the opportunity do discuss this and learn from the discussion…

Your quote suggests that the EMH might have a broader meaning for arbitrage among the proponents of the efficient market hypothesis. Please understand I am not saying that it is a good theory or complete if it has any merit at all.

And I am certainly happy to be more precise in my wording. I will try to use another word in the future or add a modifier, context or whatever is necessary to be clearer (AND ACCURATE) in the future…

But I was interested in how the EMH uses the term as it would would seem that arbitrage would have to have a broader meaning to create an efficient market as true arbitrage is done by few even if their assets may be large.

Q to Chat GPT: “The efficient market hypothesis often say inefficiencies will be “arbitraged away”. Do they literally mean arbitrage in the sense that a person is buying and selling similar assets or would institutions buying an asset without hedging be included?”

A: "The term “arbitraged away” in the context of the Efficient Market Hypothesis (EMH) can encompass a broad range of trading strategies, not limited to literal arbitrage strategies. Here’s a more detailed explanation:

  1. Literal Arbitrage: This is what is classically thought of as arbitrage, where traders exploit price differences in truly identical or very similar assets across markets or over time. They aim to make risk-free profits. For instance, buying a stock in one market where it’s cheaper and selling it in another market where it’s more expensive.

  2. Statistical Arbitrage: This is a more generalized form of arbitrage where traders use statistical and mathematical models to identify trading opportunities. These aren’t risk-free but are based on perceived statistical mispricings. This can include pairs trading, where traders take long and short positions in two assets that are historically correlated.

  3. Exploiting Inefficiencies without Hedging: Many institutions and traders try to exploit market inefficiencies without necessarily hedging their positions. This could be based on fundamental analysis, technical analysis, or other forms of analysis. These strategies are not arbitrage in the classical sense because they are not risk-free; they involve taking on some form of market risk.

  4. Behavioral Arbitrage: In some cases, traders might try to exploit behavioral biases of other market participants. For instance, if a stock is undervalued because of irrational pessimism, a trader might buy the stock expecting that the market will eventually correct this mispricing. This is also not risk-free arbitrage, as it involves betting on a particular market outcome.

So, when the EMH states that inefficiencies will be “arbitraged away,” it can mean that market participants, using various strategies, will trade in a way that corrects the mispricing, bringing prices more in line with their true underlying values. This includes both classical arbitrage strategies (which are hedged and aim to be risk-free) and other trading strategies that aim to exploit perceived inefficiencies (which involve taking on market risk).

The idea is that the presence of many participants actively trying to exploit these inefficiencies helps to make markets more efficient over time."

Again, thank you for your comments!!! And I don’t exclude the possibility that ChatGPT could be hallucinating, be delusional and in need of lithium and a cocktail of antipsychotics. :dizzy_face: Or even just be wrong.

Jim

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I propose the name “RoseBud” if you prefer going forward (In honor of that classic capitalist movie Citizen Kane). To summarize, the entire movie is a search for the mysterious meaning (and therefore the definition) of the word Rosebud. And of course a Rosebud any other name….

And it probably will not be confused with gold. Very good point. We have to be careful when making definition. My wife would have been very upset if I got a Dogecoin engagement ring (mainly be cause it is only worth $0.063281 USD). You have to understand my wife.

Maybe things have changed but when I took my logic courses in college definitions were just that: definitions. Neither true nor false. With theorems (not definitions) that were either logically correct or not. Kids these days. :slight_smile:

I am not opposed to “Sh$t Fama and French Theory” if that makes you feel better. But given the mysterious nature of our very important inquiry and the fact that Citizen Kane if often called one of the greatest films in the history of cinema (next to Bill & Ted’s Excellent Adventure, of course) I prefer RoseBud. :thinking:

Maybe we can move on at some point with a new definition whatever we may agree upon……

Jim

37

Exactly like those dimensionless points in geometry. Or in physicics, those perfect spheres. Or “absolute zero” that will never be seen in reality. You are beginning to understand science! :wink:

In math, those pretend….uh I mean imaginary numbers (i) which are absolutely necessary to fully explain the reality of quantum physics.

Or even your PCA regression. 6 dimensions you say?

Simplifying assumption are entirely new to you? Seriously?