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Webinar: Ernest Chan on Capital Allocation and Risk Management (Kelly)
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Webinar: Ernest Chan on Capital Allocation and Risk Management (Kelly)

  #21 (permalink)
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cygnetnoir View Post
I get what you are saying, but I still do not see that halving the bet size should be necessary. I missed the first part of Chan's webinar, and so maybe he is using a derivation or variation of Kelly. As I understand Kelly, the formula is asKelly described it: Max Gain = edge/odds, or (P*W-L)/P, where P = expected payoff, W = probability of winning your bet and L = probability of losing your bet. These variables, while certainly subject to a standard deviation that likely does not follow a normal distribution, nonetheless are not (or at least should not) be randomly selected.

Again, my thoughts are predicated upon having a fairly certain and accurately calculated edge, which, by definition, requires an accurately calculated expected payoff. If you have these two numbers, and they are based upon actual trading from the cockpit and not some "pie in the sky" assumptions, then you should not need so large a "margin or error" safety net as a halving of bet size, which will have a much more deleterious efect on growth potential than merely halving it.




Kelly's formula actually describes a method of bankroll management that allows you to maximize capital growth while at the same time minimizing the risk of ruin. Of course, if you start with a small stake, then Kelly may not prevent your capital from experiencing a drawdown sufficient to cause you no longer to meet minimum margin requirements to trade, effectively taking you out of the game, which is, of course, a form of ruin, even if you are not, technically, "broke."

The problem isn't the estimate of the expected payoff, it's the assumption of normalcy. Financial return series tend to have far heavier tails than the normal distribution implies. While "half" isn't a hard and fast rule, you should treat Kelly as a ceiling on your sizing, not the target.

Unless of course you have a good estimate of the shape of the distribution of your strategy, and expect it to not change in the future....

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  #22 (permalink)
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imPairsonator View Post
The problem isn't the estimate of the expected payoff, it's the assumption of normalcy. Financial return series tend to have far heavier tails than the normal distribution implies...

I was making no such assumption:


cygnetnoir View Post
...These variables, while certainly subject to a standard deviation that likely does not follow a normal distribution, nonetheless are not (or at least should not) be randomly selected...


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artemiso View Post
...Your edge can't be calculated, it can only be estimated...

I can only imagine that in that case, what you are speaking of when you say "edge" is not the same thing that I mean when I refer to "edge."

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The recording for the webinar has been posted:

Webinar: Ernest Chan - Capital Allocation and Risk Management




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Big Mike View Post
I want to thank Ernie for a truly fantastic webinar. I hope it was as beneficial to others as it was to me

Congratulations to the five winners of the autographed books:

@Lejcus, @Porsche, @Chancellor, @moses, @artemiso

I will contact you shortly via PM.

I will be posting the recording of the webinar sometime tomorrow.

Mike

The books have been mailed to the winners.

Mike

Due to time constraints, please do not PM me if your question can be resolved or answered on the forum.

Need help?
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  #26 (permalink)
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@Fat Tails,

I am wondering if you watched this webinar and if so, what you thought?

Mike

Due to time constraints, please do not PM me if your question can be resolved or answered on the forum.

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  #27 (permalink)
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imPairsonator View Post
While "half" isn't a hard and fast rule, you should treat Kelly as a ceiling on your sizing, not the target.

This is correct. The common Kelly derivation maximizes log growth but says nothing of the drawdowns that you will experience. And if you in fact do assume the moments are constant in time and satisfy a normal distribution and simulate using Kelly leverage on every trade, the drawdowns will clearly not stand the test of real-life constraints although it keeps to the promise of keeping your ROI above -1. I want to reiterate that most people complain about the normal distribution but this is a minor issue.


Big Mike View Post
The books have been mailed to the winners.

Mike

As promised, I've given away my copy to someone else as I don't think it's in the spirit of this giveaway that I keep the book. I found a college sophomore at one of the Ivies who wants to work at the prop desk of an investment bank, but the odds are stacked against her because she has a speech disability.

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cygnetnoir View Post
Again, my thoughts are predicated upon having a fairly certain and accurately calculated edge, which, by definition, requires an accurately calculated expected payoff. If you have these two numbers, and they are based upon actual trading from the cockpit and not some "pie in the sky" assumptions, then you should not need so large a "margin or error" safety net as a halving of bet size, which will have a much more deleterious efect on growth potential than merely halving it.

I realize that I am answering an old post but I think I'd try to contribute, if not for the OP's benefit, then for the other members reading this "sticky" thread.

First of, for the record, the half-Kelly bet is not equal half the size of the full Kelly bet.

That aside, the main reason to bet half-Kelly is that there is a big difference between underbetting the full Kelly and overbetting it. While EV>0 (expectancy is positive), the former ensures that the Expected Growth (EG) is positive while the latter ensures that the EG is negative! This mathematical fact is counterintuitive for the Kelly novices because the common sense tells us that slightly overbetting full Kelly should be a bit less profitable than betting full Kelly. In fact, it's a money loosing proposition!

So, once you plug in the fact that one can only estimate his trading edge, it is obvious that even for a risk neutral trader it is better to err on a safe side.

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