Summary

Time series momentum (TSMOM) is an investment strategy that involves buying assets whose prices are trending upward and shorting assets that have a downward trend. In 2012, Moskowitz, Ooi & Pedersen published Time Series Momentum¹. They analyzed a simple version of the strategy that buys assets with positive 12-month returns and shorts assets with negative 12-month returns. They found that the strategy had statistically significant outperformance in equity indexes, currencies, commodities, and bond futures from 1985 to 2009.

However, others have raised doubts. Huang, Li, Wang & Zhou (henceforth HLWZ) criticized the strategy in Time Series Momentum: Is It There? (2020)², concluding that the evidence for TSMOM is not statistically reliable.

Some of their criticisms have merit, but TSMOM remains an appealing strategy.

The abstract of Time Series Momentum: Is It There? reads:

Time series momentum (TSMOM³) refers to the predictability of the past 12-month return on the next one-month return and is the focus of several recent influential studies. This paper shows that asset-by-asset time series regressions reveal little evidence of TSMOM, both in- and out-of-sample. While the t-statistic in a pooled regression appears large, it is not statistically reliable as it is less than the critical values of parametric and nonparametric bootstraps. From an investment perspective, the TSMOM strategy is profitable, but its performance is virtually the same as that of a similar strategy that is based on historical sample mean and does not require predictability. Overall, the evidence on TSMOM is weak, particularly for the large cross section of assets.

To rephrase, HLWZ make two central arguments:

1. Moskowitz, Ooi & Pedersen (2012)¹ did a pooled regression and found a statistically significant correlation, but this methodology is flawed: it finds a strong correlation even when time series momentum cannot predict future prices.
2. TSMOM performed similarly to a strategy that simply buys assets with positive long-run historical returns and shorts assets with negative historical returns. The authors call this strategy Time Series History or TSH.

My responses to the two arguments:

1. I agree that a pooled regression is flawed. But a statistically significant correlation on a pooled regression is not what convinced me that TSMOM works. [More]
2. TSMOM and TSH indeed have similar(ish) historical returns. However:
   1. TSMOM’s positive performance cannot be explained by TSH alone. [More]
   2. TSMOM provided better diversification to an equity portfolio. [More]
   3. TSMOM has large unexplained returns when regressed onto a Fama-French factor model. [More]
   4. TSMOM still performed well on a much larger sample going back a century. [More]

TSMOM looks strong in the historical data. TSMOM probably survives fees and trading costs, but the evidence for that is less clear. [More]

Continue reading

You may have seen this graph from Chris Olah illustrating a range of views on the difficulty of aligning superintelligent AI:

Evan Hubinger, an alignment team lead at Anthropic, says:

If the only thing that we have to do to solve alignment is train away easily detectable behavioral issues…then we are very much in the trivial/steam engine world. We could still fail, even in that world—and it’d be particularly embarrassing to fail that way; we should definitely make sure we don’t—but I think we’re very much up to that challenge and I don’t expect us to fail there.

I disagree; if governments and AI developers don’t start taking extinction risk more seriously, then we are not up to the challenge.

Continue reading

Many people in AI safety, especially AI policy, want to increase government expertise. For example, they want to place people with AI research experience in relevant positions within government. That may not be a good idea.

People who better understand AI can write more useful regulations. However, people with relevant expertise (such as ML researchers) tend to be less in favor of strong regulations and more in favor of accelerating AI development.¹ We need regulations to prevent misaligned AI from killing everyone, and to prevent other kinds of catastrophes. If government expertise goes up, all else equal we will get fewer such regulations, not more.

Continue reading

As of a few days ago, my website supported comments via Commento. If you click on that link, you will find that the page doesn’t load. Unfortunately, that website was also hosting my website’s comments, so all the comments are gone now, and I have no way to recover them.¹ Some of y’all left some good comments, but future readers will never know what they were.²

(I knew Commento was no longer actively supported, but in my foolishness, I thought to myself, well, the comments still work, so I’ll keep using it. Too bad I didn’t back up the comments while I had the chance.)

Commento was my third comment system. Originally I used Disqus, but I didn’t like how it impacted page load times, and I didn’t like how it disrespected my readers’ privacy. So I switched to a janky basic HTML commenting system that required me to manually copy/paste people’s comments into a text file so my website could serve them statically. That system was annoying³, so I switched to Commento, which was lightweight, privacy-respecting, and didn’t require manual effort on my part.

Commento is dead. My website now uses Comentario, which is basically the same as Commento except that (1) it still exists and (2) it’s self-hosted, which means even if Comentario stops existing and the website disappears, the comments on my website will still work.

(Commento had an option for self-hosting, but it looked like a lot of work so I didn’t do it.)

(Setting up Comentario self-hosting was a lot of work, confirming my suspicions. It took me about 10 hours, although to be fair, 8 of those 10 hours were spent trying to upgrade my server’s operating system because it was too old to be compatible to Comentario, and also it reached end-of-life in 2021 and probably had a lot of security vulnerabilities, oops. Anyway I hope y’all appreciate all the work I’m doing to prevent Disqus from spying on you.)

Posted on Dec 12, 2025

Notes

I can’t figure out any good way to put a smiley emoticon inside parentheses. There are five choices, all of which are bad:

• Do the straightforward thing of just writing it (which puts two parentheses next to each other in a row, and makes it unclear where the smiley face ends and the parenthesis proper begins :)).¹
• Do that, but put the period inside the parentheses. (Which requires restructuring your sentences, and ends up looking ugly anyway, like some deformed double-mouth emoticon :).)
• Put a space between the emoticon and the close parenthesis (which does look more visually distinct, but there’s no other situation where you put a space before the close parenthesis :) ).
• Only put a single close parenthesis (possibly the worst option because you can’t tell if the parenthesis is part of the punctuation or part of the emoticon :).
• Add some text after the smiley so it’s not at the end of the parenthetical (but maybe you have nothing left to say so the text is superfluous :) haha wouldn’t it be crazy if I wrote some extra stuff here?).

There’s a secret sixth option of “don’t use emoticons inside parentheses” but, like, what if I really want to? (emoticons are important sometimes :) )

Posted on Dec 11, 2025

Notes

I published a post every day of November as part of the Inkhaven program, in which we are required to publish a post every day of November. Some of my readers knew that; others were confused about why I suddenly started posting so much.

If you’re an email subscriber, you didn’t see every post because I only sent out the good ones—I didn’t want to bombard you with emails if you were accustomed to my typical once-per-week-or-three-months posting schedule. If you want to see the bad posts, they’re all on https://mdickens.me/.

Inkhaven had 40 other residents; you can see their posts on the website, and daily highlights at the Inkhaven Spotlight.

Continue reading

I’ve been interested in lucid dreaming since high school, with just enough success to say that my efforts haven’t been a complete waste of time. I have a lucid dream once every few months, which isn’t great. But I still do reality checks multiple times per day.

The simplest way to lucid dream is to follow two steps:

1. Get into the habit of writing down your dreams as soon as you wake up, so you get better at remembering them.
2. Start doing regular reality checks.

(But this is also the least reliable method, hence why I haven’t had much success.)

A reality check is when you examine some aspect of the world to see if it looks unusual. An example of a reality check is to read some text, and then read it again. Many people find that in dreams, they have difficulty reading; or the words shift around and appear to say something different the second time.

Continue reading

A silly argument:

The goal of this activity/institution is to achieve X. It doesn’t really achieve X, but it does achieve Y, which is even better!

If achieving Y is more important, why on earth would you go about that by trying and failing to achieve X? You should directly focus on Y instead.

Continue reading

Not that I’m remotely as funny as George Carlin, or that this list is funny at all. But he had many complaints and grievances, and today I would also like to complain about some stuff.

This post contains spoilers for a lot of things. I won’t hide spoilers, but I will say the name of the thing before giving the spoiler.

Continue reading

This meme got me thinking:

That feeling when you’re smart enough to know how awkward you are, but not smart enough to know how not to be awkward

The reason it works that way is because not being awkward is NP-hard, and I can prove it.

Continue reading