tag:blogger.com,1999:blog-5465015914589377788.post3485930031766191330..comments2020-05-23T10:03:42.823-04:00Comments on Michael James on Money: Portfolio OptimizationMichael Jameshttp://www.blogger.com/profile/10362529610470788243noreply@blogger.comBlogger4125tag:blogger.com,1999:blog-5465015914589377788.post-36829644965959615392017-11-30T14:49:08.441-05:002017-11-30T14:49:08.441-05:00@Anonymous: My experience was similar. When I as...@Anonymous: My experience was similar. When I assigned ranges to expected returns, variances, and correlations, the range of portfolio percentages was wild. I found no useful way to use MPT.Michael Jameshttps://www.blogger.com/profile/10362529610470788243noreply@blogger.comtag:blogger.com,1999:blog-5465015914589377788.post-43053035421490050982017-11-24T11:40:29.344-05:002017-11-24T11:40:29.344-05:00I experimented with MPT when setting up a strategi...I experimented with MPT when setting up a strategic allocation years ago. Seeing the allocation was extremely sensitive to the correlation coefficients, and realizing those are not well known and actually should be modeled as time varying, I ignored its results.<br /><br />Even within a particular asset class, annual returns are non-stationary process. Also, multi-year returns are not independent (e.g. the business cycle), and MPT does not account for that. From time to time, I use a non-Markov process that builds in mean reversion in an ad hoc way, inserting that into a Monte-Carlo simulation I run. But any particular choice is arbitrary and does not necessarily model market returns well enough to be of value in the Monte Carlo results.<br />Anonymousnoreply@blogger.comtag:blogger.com,1999:blog-5465015914589377788.post-44411501982177251512017-11-20T08:12:42.865-05:002017-11-20T08:12:42.865-05:00@Martin: The fundamental problem is an inability t...@Martin: The fundamental problem is an inability to know the probability distribution of future returns. The fact that returns are not lognormal is usually dealt with by choosing a low target for variance (otherwise the model calls for absurd levels of leverage). Having "solved" that problem, the next is to choose expected return, variance, and correlation parameters for the different asset classes. Unfortunately, as you say, the computed "optimal" allocation is very sensitive to these parameters. The best we can do is to use historical returns from some period to estimate these parameters, but all that matters is the future. In the end, mean-variance portfolio theory makes the whole process look scientific, but it's questionable whether the optimization has much influence over the final allocation chosen. And that's probably a good thing.Michael Jameshttps://www.blogger.com/profile/10362529610470788243noreply@blogger.comtag:blogger.com,1999:blog-5465015914589377788.post-89090361214606463462017-11-20T07:43:51.775-05:002017-11-20T07:43:51.775-05:00Hi MJ. I haven't read the book you refer to, b...Hi MJ. I haven't read the book you refer to, but in my work, I've helped a number of institutional investors make such portfolio choices. The "accepted standard of care" is mean-variance portfolio theory as the optimization approach, with scenario stress-testing to set boundary conditions for extreme conditions (which, as you say, are not adequately covered by MVPT). <br />In my experience, the dirty little secret isn't these days that extremes would be neglected, but that both in the mean-variance calibration as well as in the stress scenarios, there is great sensitivity to the historical timeframes used to choose the assumptions. And so your answer is analytically quite unstable, provoking -- not absurdly -- decisionmakers to deviate from the analytics much more cheerfully.<br />In addition, while most pension funds have admirably long time horizons, driven by their long-term asset-liability matching, their management teams, Boards, and other stakeholders do not. The fund may well have 20+ years to recover from a misstep, or a market downturn may be a genuine buying opportunity, but it's hard to live that with zen-like calm when your mark-to-market valuation is down 25%, journalists are asking whether retirees should be worried -- and when, as usual, if you look hard enough, there is something about your decisions that in retrospect makes you have egg on your face. Martin Perglerhttp://www.balrisk.comnoreply@blogger.com