fractionalhare

Someone doing that will normally do it within the confines of an LLC by convention (because it almost always implies a business). But you could do it with investing, too. In either case you need not be a megacorp.

There are also income tax offsets for education, provided your tax bracket isn't too high.

They're making a practical distinction that you generally don't have access to the actual thing in an empirical format for which compression will achieve true learning. Instead you have access to training data which represents, let's say, a projection of the actual thing in a smaller space with fewer dimensions.

Like trying to learn from images instead of the 3d world. Humans learn to distinguish between objects in a 3-dimensional space using sight and interaction. This learning generalizably transfers to recognition in 2 dimensions. We don't generally equip models with robotic interfaces to train in 3d before benchmarking them on ImageNet.

> To be honest, this "ergotic theory" shows signs of snake oil.

lol. Alright, I’m checking out of the discussion when a major subfield of mathematics is described as snake oil.

It seems like you think the problem here is too unsophisticated for ergodic theory or something. Which, fine sure. But this isn't an article intended to teach you about betting. It's an article intended to teach you about ergodicity, using betting as a toy example. The author isn't trying to introduce the best way to analyze betting strategies, they're trying to show what non-ergodicity is. And I think they basically succeed.

Just meet the article where it is, for its intended usage.

I think it's uncharitable to say the article would be easier to understand if it didn't use the language of ergodicity. Its explicit goal is to show how non-ergodicity leads to an example like yours.

So of course your comment seems easier to understand. But that's because you're just saying different distributions can be parameterized by the same mean. Ergodicity is about a lot more than that, and the language of ergodicity was the entire exercise here.

    import random

    l = 0.33
    w = 0.5
    c = 100
    m = 1000
    p = {k: c for k in range(m)}
    n = 1000

    for k in range(n):
        for j in range(m):
     if random.choice([0,1]):
         p[j] += (w * p[j])
     else:
         p[j] -= (l * p[j])

    print(sum([p[k] for k in p]) / len(p))

    print(sum(1 for k in p if p[k] > c) / len(p))

NB: This assumes you bet your entire capital each round instead of a constant bet size. In the presence of non-ergodicity you wouldn't want to do this, but that just means it's an even stronger result that most people come out ahead.

In fact 33% happens to be the maximum loss percentage this system (win rate, win percentage, bet = total capital) can tolerate while still exhibiting higher wealth for most players over time :)

This does not mean that you shouldn't play a game with positive expected value. Expected value is still the salient framework with which you should judge risk. It just means that the size of your bet needs to be considered in conjunction with your total capital, not just whether any individual bet is more likely to win than lose.

The author states this seems to not be well known in finance, but in point of fact this is very well known in both literature and practice. A trading strategy with positive expected value has additional considerations before you execute on it, including your total capital and liquidity.

In my view, a lot of things that are noninteractively inferred are compositions of more fundamental things that required empirical experience. When you've had the causality of gravity thoroughly beaten into you at a young age, a lot of other things seem intuitive that would otherwise completely fall outside a framework for being unempirically learned.

Do you have a specific counterexample of causality you can infer without interaction or empirical experience of something related?

Caveats: I'm not a neurologist or psychologist, so this is mostly philosophical speculation on my part.

Have you ever priced a derivative? What about the estimation of future/realized risk using implied volatility doesn't seem "rooted in statistical analysis" to you?

If you tell people your uncle goes to Vegas every weekend to gamble, they will have a markedly different reaction than if you tell them he goes and counts cards every weekend.

When you to sell the underlying to cover. It's right there in the name. Of course you lose money, it's just that your downside risk is capped.

> Us plebs aren't allowed to write naked options, that privilege only belongs to institutional actors.

Yeah because you'll probably lose all your money. Would you rather be allowed to do something incredibly dangerous and then get met with a dispassionate, "Well, almost everyone fails at this but you tried anyway, should have known better! Thanks for playing."?

Writing any amount of uncovered calls where the present stock price is at least higher than the teens generally exposes you to more risk than the average American can absorb with their entire net worth.

That being said, if you really want to, there are places that will let you do it using margin if you guarantee you know what you're doing. Bad idea though.

Would hate to have been selling put options on VIAC when Archegos shit the bed on $20B with >4x leverage. Good luck foreseeing that.

Reading HN, you'd think every quant trading firm had the exact same culture and hiring practices as RenTech.

As I said elsewhere, calling everything gambling just because it isn't literally guaranteed is reductive and unproductive.

I guess you also believe the entire insurance industry is gambling too. Out of curiosity, what parts of finance do you think aren't gambling?

If you categorize all speculative activity under uncertainty using the same word, that word ceases to be useful.

People tend to vastly overestimate the economic impact of an exploited security vulnerability. A vulnerability which can be patched in a centralized manner has a low value half-life: it rapidly decreases in value over time. I would guess over 90% of active daily users of macOS already have the patch for this bug due to automatic updates. New buyers are essentially guaranteed not to have the vulnerability at all. The vulnerability would have to be absolutely catastrophic to be worth something, and in that case it would probably be used for targeted exploitation and burned after a short period of time.

Contrast with something like heartbleed, which is still around. That is a vulnerability with serious half-life and significant economic impact. The pool of available victims who can be exploited by heartbleed is nontrivial and persistent years later. Criminals will actually pay for something like that.

The better comparison is active users, weighted according to how many apply automatic updates. The vulnerability half-life probably isn't as devastating as you might think it is since Apple has centralized control to push out updates, limited only by users deliberately not installing them.

I would consider a vulnerability in OpenSSH to be far more economically devastating, and there isn't even a company with a market cap behind that software.