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IntradayBill, It;s a "Leverage Factor," not a "fraction." The two are only the same value under certain circumstances (which rarely occur in trading). Using the leverage factor (which is what the answer that satisfies the kelly criterion returns) as a fraction to risk, will have you...

kut2k2, Kelly and Optimal f are different indeed, and Kelly does NOT yield the optimal fraction. If you think .80 as a result of the Kelly Criterion means you you have .80 of your stake at risk, you are completely wrong and don't understand what the formulations are returning to you. To...

goodgoing, Kelly is not a %. Using it as such will REALLY get someone into trouble, It's not the same thing as the Optimal f. Let's suppose I have one market where the Optimal f is .25. Do you think you are at any less risk trading 25 markets at .01 where the correlations between all pairs...

The largest loss is only important so as to bound your answer (for optimal f, a fraction between 0 and 1, unlike the kelly Criterion answer, which is a leverage factor between 0 and infinity). By bounding your answer between 0 and 1, you open up all kinds of very favorable things. However, you...

My apologies.

A superhero? I don't need to be. My apologies if I sound antagonistic. Forgive me.

I'mBatman, My guess is everyone who is giving you advice here still has losing trades. I don't. You can decide for yourself who to listen to in this regard.

I'mbatman, You need to first discern what you are doing any of this for. To arbitrarily pick a percentage is to flounder -- it defaults to meaning you are in this to make as much as you can, within the constraint of not losing more than x% per trade (is THAT what you are really in this for...

dtrader: You wouldnt happen to havea link to the Chapman paper, would you?

Yes, I see. Very interesting. Thanks.

Yes, this is a problem we are all wrestling with. Everyone pretty much agrees that thr ground is really moving under our feet -- things are changing and rapidly, seemingly accelerating. The reasons are many from the geopolitics of the world to the mechanics of the markets with the nascent 24...

It really is not an alternative per se. My point is, you are IN leverage space, somewhere, unavoidably, whether acknowledged by you or not. You are very likely moving around in it as well, further complicating things. The "alternative," (upon acknowledging this unavoidable fact) is to harness...

An interesting wikipedia article -- but it is not what I am doing here. My point is I am using the LSP model in a manner not to maximize profits, but to maximize the probability of being profitable at a given horizon in time. This was an interesting discussion guys. Thanks.

Its simple -- but I won't get too specific as I don't owe anyone any more than that. However, my criteria has been to maximize being profitable, as opposed to maximizing profit itself.

Exactly -- they do NOT know what they want. Not just on the downside (Is it variance? Is it drawwdown? What is it?) but on the upside as well (geometric growth optimality? Inreased average return?) For answers to these very things, I turn to economic theory -- and jsut what makes people tick...

[[What about using the Spearman Rank correlation? - Looks like providing a bit less information, but worth considering...]] Yes, that was my experience too -- but, (and contradictorily, if that is a word) the robustness of the Spearman r seemed to be a nice quality. It seemed to have the...

Indeedy -- the past is never the entire sample space, and I am not claiming that it is. However, my point that the joint probability matrix suffers less information loss than a simple, single parameter isn;t nullified by this. The single parameter does NOT prepare me for that -10,-10 period...

I KNOW that a matrix of probabilties of cross scenarios has less information loss than the simple, single metric of correlation -- particularly in the tails. I have written about this at length, performed ample studies on it, and have experienced the benefits and consequences of both, firsthand...

Correlation is a good metric for measuring, say, how well two data sets track, and their respective lead/lag, or for autocorrelation of an individual data stream. It's a fatal mistake, however -- and I mean FATAL (I say this from firsthand experience on numerous occassions) to use correlation...

As an aside, these very institutions that employed mean variance allocation models, were also, generally, employing VAR as a misk metric. We've seen the effects of that too.