manhapf

The Do-It-Yourself Market-Neutral Portfolio

Hello Geoff,

Thanks for your software and articles; they've been insightful and helpful. I've been interested in portfolio asset allocation for many years and am a user of some complex software tools; love QPP's format, nicely done! I've been trial using your software and have some questions/observations...

Rebalancing/Optimizati... of Allocations:
One of the implementation details in using QPP is when to future adjust and at what frequency the 'final' asset/security allocations? At present, you either define an allocation weighting of equal or some proportion that 'suits' the investor's preferences for risk/return ideally based on empirical knowledge; eg, 70% equities/30% bonds.

I'm not a fan of software optimization in general as applied to portfolio allocations, I'm quite familiar with the pitfalls and the bad results that typically are produced from even excellent out-of-sample and supposedly robust models. However, since with QPP we're using monte carlo simulations of forward looking return possibilities and 'experimenting' with various assets/security combinations/allocatio... weightings anyways, there is a temptation to use Excel's built-in Solver tool to optimizatize. For example, we can maximize the forward returns by modifying the asset/security allocation weights constrained by the forward looking standard deviation for example.

Ideally, the optimized forward returns/SD yield the best weights and are robust in the sense that they deliver similar optimized/simulated results compared to the historical results over 1, 3 & 5 year time horizons; would you consider longer time horizons? I've attached a before/after example using your market-neutral article to demonstrate the effect of optimizing the allocation weights which appears quite compelling since it also improves on the portfolio beta and diversification values.

So, what frequency of re-running the simulations to adjust the allocation weightings do you normally recommend once they're established to ensure the expected return/SD results are still meaningful; annually? What's your opinion of optimizing the weightings in this manner?

Disclaimers:
1) To what index is Beta used to capture correlation; am assuming S&P500, but should be stated.
3) Based on research I've done, asset/security returns are not normally distributed. I realize that this makes the programming/math easier, but this is an area that could be improved and make QPP a more valuable tool and one that I'd be willing to pay more for!
6) Based on your articles, I assume that this refers to the 1:1 relationship normally displayed between returns and standard deviation; is this correct?

Thanks much for your time and consideration of my questions/observations...