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That post made me write this post, but I'm not sure that I'm referring to the same thing. Basically I mean something like "people whose beliefs or actions are so unreasonable, even on things that they should have thought long and hard about, that they seem to belong to a different species from myself." Like Robin Hanson in this tweet or Elizer Yudkowsky when he thought he would singlehandedly solve all the philosophical problems associated with building a Friendly AI (looks like I can't avoid giving examples after all). I'm pretty sure these two belong in the top 0.1 percentile of all humans as far as being reasonable, hence the title.

You could use things like being able to outperform the market, being consistently ahead of the Overton window, finding a reception for your less objectively verifiable ideas among (a small group of) other high-performing individuals. This doesn't guarantee that you're not still a lizardman among the 99.9%+ lizardmen, just in a high-performing contrarian cluster (hence my rule #1), but at least rules out being a crazy person living in a normal world (unless you're just hallucinating all of the evidence, but there's no point worrying about that).

Sorry for being unclear. I meant producers of those commodities, except for uranium for which I also have some exposure to the commodity itself.

If you spend any time following stock touts on twitter / stock picking forums etc you will see these people quickly.

The people I follow generally don't advertise their track record? For the hedge fund manager I mentioned, I had to certify that I'm an accredited investor and sign up for his fund letters to get his past returns. For the ones that do, e.g., paid services on SeekingAlpha that advertise past returns, it has not been my experience that they "then fail to do so out of sample" (at least the ones that passed my filter of being worth subscribing to).

I generally find posts like this are net-negative EV.

Personally, I wish I had seen a post like this 10 years ago. My guess is that there's at least 2 or 3 people on LW who could become good traders if they tried. Even if 10 times that many people try and don't succeed, that seems overall a win from my perspective, as the social/cultural/signaling and monetary gains from the winners more than offset the losses. In part I want LW to become a bigger cultural force, and clear success stories that can't be dismissed as "luck" seem very helpful for that.

Especially if those are after tax returns!


I have never achieved anything close to those levels of returns, but would sorely love to do so.

Maybe try some of my tips, if you haven't already? :)

Without even checking, I can think of a bunch of assets which 7x'ed since Jan 2020. (BTC/general crypto, TSLA, GME/AMC etc).

I figured that's the first thing someone would think of upon hearing "7x" which is why I mentioned "This was done using a variety of strategies across a large number of individual names" in the OP. Just to further clarify, I have some exposure to crypto but I'm not counting it for this post, I bought some TSLA puts (forgot whether I made a profit overall), and didn't touch AMC. I had a 0.1% exposure to some GME calls which went to 1% of my portfolio and that's the only involvement there.

Personally, I have seen enough people claiming to outperform, but then fail to do so out of sample.

Can you please give some examples of such people? I wonder if there are any updates or lessons there for me.

Either way, I think it's very hard to convince me with just ~1.5 years of evidence that you have edge. I think if you showed me ~1k trades with some sensible risk parameters at all times, then I could be convinced.

I don't think I've done that many trades (depending on how you define a trade, e.g., presumably accumulating a position across different days doesn't count as separate trades). Maybe in the low hundreds? But why would you need ~1k trades to verify that I was not doing particularly high variance strategies? I guess this is mostly academic though, as it would take a lot of labor to parse my trade logs and understand the underlying market mechanics to figure out what I was doing and how much risk I was taking (e.g., some pair/arbitrage trades were spread across several brokers depending on where I could find borrow). I don't supposed you'd actually want to do this? (I also have some privacy concerns on my end, but maybe could be persuaded if the "value added" in doing this seems really high.)

Or if in another year and a half you have $300mm because you've managed to 7x your small HF AUM, I will be convinced

I'm definitely not expecting such high returns going forward. ("600% return" was meant to be Bayesian evidence to update on, not used to directly set expectations. I thought that went without saying around here...) Obviously there was a significant amount of luck involved, for example as I mentioned the market was particularly inefficient last year. One of the hedge fund managers I follow had returns similar to mine this year and last year, but not in the years before that. I'd guess 20-50% above market returns is a realistic expectation if market conditions stay similar to today's, and I hope I can still outperform if market conditions go more "out of sample" but I currently have no basis to say by how much.

Also, I'm already starting to feel diminishing returns (is there a more technical term for this in the investing world?) kick in at my AUM level, as I now have to spend multiple days accumulating some positions to the sizes that I want (and they sometimes take off before I finish), or ignore some particularly illiquid instruments that I would have traded in the past.

1 in 5 isn't especially strong evidence.

I agree this isn't a very strong argument. I think theoretically we can probably get a much tighter probability bound than 20% by looking directly at the variance of my strategy, and concluding that given that variance, the probability of getting 600% return by chance (assuming expected return = market return) is <p for some smaller p. But in practice I'm not sure how to compute this variance. Intuitively I can point to the fact that my portfolios did not have very high leverage/beta, nor did I put everything into a single or very few highly volatile stocks or sectors, which are probably the two most common high variance strategies people use. (Part of the reason for me writing this post is that while LW does have a number of people who achieved very high investment returns, they all AFAIK did it by using one of these two methods, which makes it hard to cite them as exemplifying the power of rationality.)

Assuming the above is still not very convincing, I wonder what kind of evidence would be...

I currently have ~100 positions spread across: uranium, copper, lithium, oil, fertilizer, shipping, Nvidia Google Microsoft Baidu (hedge against short AI timeline), a basket of SPAC/deSPAC commons&warrants (which I bought after the SPAC sector became severely depressed), individual "value stocks" and "special situations" in various other sectors. Most of these were entered within the last few months, and my portfolio looked pretty different before that, but I can't really talk about what I was doing before without risking de-anonymizing myself.

The efficient markets model says that any strategy during this period had expected return of 50%.

Wait, I think this is wrong. It actually says that any beta 1 strategy had the same expected return as the market as a whole. If my portfolio had a beta of 2, for example, either by using leverage or by buying only high beta stocks, then my expected return would be double that of the market.

I wish I could say that I kept my portfolio's beta at or below 1 at all times, which would make the reasoning easier, but I did sometimes trade derivatives that arguably had high beta. It would be pretty cumbersome to calculate the exact overall beta, but I'd guess that the average over time probably wasn't more than 1.5, so you could perhaps redo your reasoning using that.

I recommend looking at commentators as a source of data, but doing your best to not believe anything that could reasonably be classified as an opinion rather than a fact. That includes opinions about what topics deserve attention.

This must be the biggest disagreement between us. I think I couldn't possibly have gotten the return that I did if I had followed this advice, especially the latter part about what deserves attention. Can you say more about why you think this?

ETA: Aside from the fact that it seems to have worked in practice, my theory is that it's easier to detect good ideas than to generate them, especially when you read/hear arguments/comments from multiple perspectives, which is often possible (e.g., multiple SeekingAlpha articles plus their comments, and analyst reports about the same stock). (The same core premise makes AI Safety via Debate plausible.)

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