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Comment by hogFeast | Hacker News Reader

A tiny firm managing under $100m uses Kelly...and...

The post you replied to is right. The fundamental principle of Kelly is that you know your edge, in the markets that is mostly untrue. Funds will volatility-weight their portfolio but this isn't the same as Kelly in practice. Most fund managers will also weight their portfolio towards their "best" position but that is not necessarily based on return. Indeed, picking high return assets is only half the battle.

I also bet a lot, so I am familiar with Kelly. It is totally unusable in finance, no-one uses it in finance, and retail investors have an obsession with it.

In particular, if you Kelly-weight a value portfolio (which the firm linked to in your post is) then you are setting cash on fire. And if you Kelly-weight a long/short portfolio (again, the firm linked to appears to be doing this) then you are setting cash on fire. It is important to understand how a tool works at a practical level.

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“ The fundamental principle of Kelly is that you know your edge, in the markets that is mostly untrue.” Most every professional investor I’ve met attempts to quantify the risk-reward of each trade and size accordingly. I agree that naieve investors engage in false precision eg assuming backtest sharpe for position sizing, or ignoring correlated risks. That makes them size too aggressively. But that doesn’t mean pros don’t try their best to estimate risk reward and size accordingly. Indeed many of the best traders ever (Buffett, Soros) put on massive bets when the risk reward were highly in their favor.

Correct. That is the gap in understanding here.

When I place a bet, I can estimate my edge because the outcome is binary. When the outcome is continuous, it is far more tricky. It is like saying a kid who learns to ride his trike is ready for MotoGP...they are just totally different.

And yes Soros put on big bets, but what you are missing with Soros is the fact that his hit rate was still 30%. Most of the stuff he did didn't work out, macro is largely bets on skewness not returns. Buffett had a higher hit rate but trying to suggest someone optimise a strategy based on what literally the best investor of all time did is...not smart. Even if you were better than Buffett, you might not be lucky.

The reason why Kelly doesn't work with value investing in particular is because your returns are largely random, you know that your portfolio has an edge but you don't usually know which position is going to revalue.

The reason why Kelly doesn't work with long-short in particular is because you aren't only betting on return but correlation. Anyone who runs Kelly will eventually get a correlation spike and blow up (this is also roughly true of macro, again why Soros isn't a good example, he largely bet on skewness).

I was a "pro" so I am also aware of what most pros do. Again, investors don't only look at return, they have to look at correlation, volatility (note that if you are betting on sports, you don't have to worry about things like correlation).

It sounds like we might mostly agree in substance and a debate over semantics isn’t productive.

I agree that “the inputs to the Kelly formula are imprecise and therefore we should not mindlessly implement its recommendations.”

I agree that retail investors should not model their 401k allocations like Soros and Buffett.

Having run a factor neutral long short book I’m extremely familiar with the role of correlation and volatility in portfolio management and position sizing. As others have noted, there are extensions of Kelly (and related portfolio construction formulas) that account for correlations.

I disagree that risk-reward (broadly defined) shouldn’t be the primary bet sizing metric. I think many investors ignore risk reward calculations in their sizing and they would be better off if they paid attention to it. Many of the smartest investors I know have their entire sizing strategy based on risk reward.

To suggest that active investors should ignore risk reward / odds / whatever you want to call it, is wrong, in my opinion.

> It is important to understand how a tool works at a practical level.

There needs to be a term for "This page you're reading is bogus horseshit theory, do not try to apply it practically".

“Academic”

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