tryactions

• tryactionsFeb 24, 2021, 8:25 PM

  5 points

  in reply to: gilch’s comment on: A No-Non­sense Guide to Early Retirement

  Skimming that link, I think it shows backtesting; have you actually beaten the index yourself with real money? For what time period /​ amount of assets?

  I mostly avoided leverage in this post because I don’t use it and kind of don’t trust it. But if I had to give a better defense of avoiding it, it would be because 1. it’s really easy to lose a bunch of money if you use it wrong and 2. I’m not sure there’s a reliable way to borrow money at low enough rates to get good results. Most of what I’ve read about leverage pretends the interest rate is 0, which it’s not—looks like Robinhood offers 2.5%? What’s the most reliable interest rate people can get, and does this rate kill results?

  Definitely agree not to discount bonds though; without leverage, small amounts give you large risk reductions for small reductions in growth. I personally am 100% stocks because I’m preferring to maximize (unleveraged) growth, and have decided I can tolerate the increase volatility over 10-20 year time spans.

• tryactionsFeb 24, 2021, 8:08 PM

  1 point

  in reply to: DanArmak’s comment on: A No-Non­sense Guide to Early Retirement

  Re: 1., I’m personally unwilling to move outside the U.S. but agree it could make sense if you can make it work for you while maintaining a high salary.

  Re: 2 and 3, I completely agree. I think in particular about longevity medicine as a potential future expense. You can certainly build up support for higher-than-current expense levels to address these risks. You might also retire to less profitable or more risky activities that you find more enjoyable (but that supply >0 income), or simply stay in your current profession—but with the advantage of having higher option value.

A No-Non­sense Guide to Early Retirement

• tryactionsJan 17, 2021, 10:08 PM

  1 point

  in reply to: ike’s comment on: Why do stocks go up?

  I agree the company’s current price should be lower than $10 million. But if it starts at price P and I expect it to go up at the risk free rate r, then at a time T later the company’s price should be $P{r}^T$ in expectation. At some point, that’ll be substantially more than the $10 million I expect it to pay out.

• tryactionsJan 17, 2021, 9:49 PM

  3 points

  in reply to: lsusr’s comment on: Why do stocks go up?

  • I’d be interested for both 100% growth and 100% dividend stocks—I’m not sure why they’d behave differently w.r.t. to this.

  • By underlying value, I’m not sure. Something like the real dollar value of all of its capital—or the real dollar price someone would pay to own it in its entirety?

  • By price, I mean what you can buy the stock for on the market.

  Let me try clarifying: The volatility argument seems formal rather than empirical, so I’m wondering what we formally need to assume to make it go through.

  I’d summarize the argument as “since stock prices are volatile, they’re expected to go up over time (more than the risk-free rate)”. But then why are stock prices volatile? I assumed that they’re volatile due to “underlying value” being volatile/​hard to predict.

  So my hypothetical is a company whose “underlying value” is hard to predict, but where the expectation of its “underlying value” is constant over time. To make it easier, assume the company is a magic vault that currently contains $10 million real dollars, and the money will undergo a stochastic process with the given property, and everyone knows this. Maybe it will disperse it’s full value as a dividend at some random future point.

  It seems obvious to me I shouldn’t expect this company’s price to go up faster than the risk free rate, yet the volatility argument seems to apply to it. So I’m trying to identify what I’m missing.

• tryactionsJan 17, 2021, 8:57 PM

  1 point

  in reply to: lsusr’s comment on: Why do stocks go up?

  Question: say I have a company whose underlying value is volatile, but whose expected underlying value after any time span is the same as today’s value. Both of the above arguments seem to suggest I should expect the company’s price to increase over time, but wouldn’t this unanchor the company’s price from its underlying value?

• tryactionsJan 17, 2021, 8:36 PM

  3 points

  in reply to: Vladimir_Nesov’s comment on: Why do stocks go up?

  This makes sense!

  Do you know anything about the state of evidence re: to what extent this is happening and/​or driving stock returns? I’m not sure how you’d pick this apart from other causes of currency devaluation.

• tryactionsJan 17, 2021, 8:22 PM

  2 points

  in reply to: lsusr’s comment on: Why do stocks go up?

  Rephrase attempt: If you were to buy and hold a company’s stock, and you don’t expect to know better than the market, then your anticipated gains over time are independent of what you think the company’s underlying value will do (since the market has already priced that in). But you should still anticipate gains over time due to volatility’s effect on pricing.

• tryactionsJan 17, 2021, 8:01 PM

  2 points

  in reply to: lsusr’s comment on: Why do stocks go up?

  Fixed.

• tryactionsJan 17, 2021, 7:45 PM

  2 points

  in reply to: lsusr’s comment on: Why do stocks go up?

  Ok, so the argument would go:

  • Stocks’ expected values (in terms of time-discounted dividends or similar) have volatility, from things like business decisions, technology development, and capital re-investment.

  • A stocks expected value serves as an anchor point for its current price (kind of?)

  • A stock’s price will change around that anchor until it has expected returns that justify the volatility risk.

  • Thus a stock price will increase when either its expected value goes up, or its volatility goes down (without changing expected value).

  • In an efficient market, knowledge that changes your expected value of the stock is probably already priced in, but you can still capture the gains due to volatility.

  Does that seem in line with what you’re saying?

• tryactionsJan 17, 2021, 7:18 PM

  6 points

  in reply to: Vladimir_Nesov’s comment on: Why do stocks go up?

  You may have to hold my hand on this one: I can agree the value of the stock (in the time-discounted future dividends sense) will go up after 10 years due to time-discounting—the technology would enable value production that “comes into scope” as it gets closer in time.

  But is there any reason other than time-discounting that the PRICE won’t go up immediately? For instance, if I expect the time-discounted dividend value of the stock is $50 today and will be $5,000 ten years from now, and the rest of the market prices it at $50 today, then I could earn insane expected returns by investing at $50 today. Thus, I don’t think the market would price it at $50 today.

• tryactionsJan 17, 2021, 7:09 PM

  3 points

  in reply to: gareth’s comment on: Why do stocks go up?

  Is this the same as positing “the market is continually surprised by the pace of technology”?

  E.g., say I value company X’s stock at $100. Then I learn a new fact that there’s a 50% independent chance the company will discover a technology that doubles its value by 1 year from today. If I ignore all other factors, my estimate of the company’s value 1 year from today should then be $150. If the company discovers the technology, I’ll value it at $200, and if not, I’ll value it at $100.

  For the market to trend upward as it does, it seems like either:

  • Everyone’s consistently getting those bets wrong, and underestimating how often/​how much technology will pay off, OR

  • There’s something else to the story, like time-discounting or a different way of thinking about risk.

• tryactionsJan 17, 2021, 6:57 PM

  6 points

  in reply to: lsusr’s comment on: Why do stocks go up?

  For growth stocks, why is the expected future growth not already priced in? If I know the company will be re-investing into future growth later, why not invest now?

  There may be uncertainty, but if stocks on average trend upwards, doesn’t it mean that the market continuously underestimates the amount that companies will re-invest?

  Stock prices go up even in the absence of technological advancement because stocks are tied to the bond market via arbitrage.

  If I’m understanding correctly, you’re suggesting they should go up at least at the bond market nominal rate—but they tend to go up much faster than that? I didn’t fully read through the argument, so I might be misunderstanding.

[Question] Why do stocks go up?

• tryactionsDec 15, 2020, 5:00 PM

  9 points

  on: To listen well, get curious

  For anyone like me: it’s easy to read this advice as “if you’re not curious, you’re therefore bad/​doing something bad”, which might suggest attempting to brute force an emotional state of curiosity. I think that’s probably emotionally harmful.

  It can be the case that:

  • Curiosity is very useful for being a good listener

  • You are not curious about (this person) in (this situation)

  From there, you could:

  • Hide your current lack of curiosity and go through the motions as best you can. I think this is the best option quite often!

  • Tell them your honest feelings. Maybe you’re not very interested at the moment but are worried about them feeling not cared about, and you can tell them that. Might be a bad idea if they’re vulnerable or not trustworthy.

  • Investigate why you are not curious (either internally or with the other person), which might spark curiosity or suggest how else you should move the conversation.

  • (any other option)

  I think it’s healthier to grow curiosity as a natural extension of your desires instead of shoving it in as “ah, now I have to take the curiosity action to perform this task”. I don’t think the author was suggesting the latter, I just noticed my inclination to read it that way.

• tryactionsJun 9, 2020, 8:17 PM

  1 point

  in reply to: seed’s comment on: GAN Discrim­i­na­tors Don’t Gen­er­al­ize?

  No worries, was worth clarifying. I edited the post to link this comment thread.

• tryactionsJun 9, 2020, 7:32 PM

  7 points

  in reply to: seed’s comment on: GAN Discrim­i­na­tors Don’t Gen­er­al­ize?

  Yes, I understand this point. I was saying that we’d expect it to get 0% if its algorithm is “guess yes for anything in the training set and no for anything outside of it”.

  It continues to be surprising (to me) even though we expect that it’s trying to follow that algorithm but can’t do so exactly. Presumably the generator is able to emulate the features that it’s using for inexactly matching the training set. In this case, if those features were “looks like something from the training/​test distribution”, we’d expect it to guess closer to 100% on the test set. If those features were highly specific to the training set, we’d expect it to get closer to 0% on the test set (since the model should reject anything without those features). Instead it gets ~50% which means whatever it’s looking for is completely uncorrelated to what the test data looks like and present in half of the examples—that seems surprising to me.

  I’d currently interpret this as “the discriminator network acts nonsensically outside the training set + generator distribution, so it gets close to chance just because that’s what nonsensical networks do.”

• tryactionsJun 9, 2020, 4:20 PM

  1 point

  in reply to: gwern’s comment on: GAN Discrim­i­na­tors Don’t Gen­er­al­ize?

  Thanks for sharing thoughts and links: discriminator ranking, SimCLR, CR, and BCR are all interesting and I hadn’t run into them yet. My naive thought was that you’d have to use differentiable augmenters to fit in generator augmentation.

  You can ask him on Twitter.

  I’m averse to using Twitter, but I will consider being motivated enough to sign-up and ask. Thanks for pointing this out.

  “compression” is not a helpful concept here because every single generative model trained in any way is “compressing”

  I am definitely using this concept too vaguely, although I was gesturing at compression in the discriminator instead of the generator. Thinking of the discriminator as a lossy compressor in this way would be… positing a mapping f: discriminator weights → distributions, which for trained weights does not fully recapture the training distribution? We could see G as attempting to match this imperfect distribution (since it doesn’t directly receive the training examples), and D as modifying weights to simultaneously 1. try to capture the training distribution as f(D), and 2. try to have f(D) avoid the output of G. Hence why I was thinking D might be “obfuscating”—in this picture, I think f(D) is pressured to be a more complicated manifold while sticking close to the training distribution, making it more difficult for G to fit it.

  Is such an f implicit in the discriminator outputs? I think that it is just by normalizing across the whole space, although that’s computationally infeasible. I’d be interested in work that attempts to recover the training distribution from D alone.

  I think it’s decently likely I’m confused here.

GAN Discrim­i­na­tors Don’t Gen­er­al­ize?