Let's cut through the comforting narratives and examine a common behavioral pattern with a sharper lens: the stark difference between how anger is managed in professional settings versus domestic ones. Many individuals can navigate challenging workplace interactions with remarkable restraint, only to unleash significant anger or frustration at home shortly...
[Redacted a few paragraphs talking about why it seems like I'm living in a 99.9+% lizardman world. Unlikely to convince anyone who doesn't already think this, and will probably offend a bunch of people, such as the ones I used as examples.] 1. Don't make things worse. If you find...
I started trading equities (and equity derivatives) full time last year, without any prior training or experience, beyond some basic economics and finance courses that I took in college many years ago. I figured things out as I went by making a lot of mistakes, and listening to many podcasts....
Let's cut through the comforting narratives and examine a common behavioral pattern with a sharper lens: the stark difference between how anger is managed in professional settings versus domestic ones. Many individuals can navigate challenging workplace interactions with remarkable restraint, only to unleash significant anger or frustration at home shortly after. Why does this disparity exist?
Common psychological explanations trot out concepts like "stress spillover," "ego depletion," or the home being a "safe space" for authentic emotions. While these factors might play a role, they feel like half-truths—neatly packaged but ultimately failing to explain the targeted nature and intensity of anger displayed at home. This analysis proposes a more unsentimental approach, rooted in... (read 588 more words →)
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).
[Redacted a few paragraphs talking about why it seems like I'm living in a 99.9+% lizardman world. Unlikely to convince anyone who doesn't already think this, and will probably offend a bunch of people, such as the ones I used as examples.]
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... (read more)
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.
... (read 390 more words →)Personally,
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... (read more)
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.)
Seems a good idea. Thanks for the question.
I started trading equities (and equity derivatives) full time last year, without any prior training or experience, beyond some basic economics and finance courses that I took in college many years ago. I figured things out as I went by making a lot of mistakes, and listening to many podcasts.
My portfolio has gone up ~600%, counting from Jan 2020. (The US stock market went up ~50% during this time.) This was done using a variety of strategies across a large number of individual names, so it probably wasn't just the result of luck. My AUM (assets under management) is currently about that of a small hedge fund. (I'd prefer to not talk... (read 871 more words →)