My understanding is (and I can say that my experience with back-testing such algorithms confirms it) that risk-weighting (e.g., inverse volatility weighting) is really crucial with futures, but less so with stocks, perhaps because they all have volatilities of the same order of magnitude. Clenow is of course right in stating that risk-weighting is the only approach that really makes sense in theory, but in practice there is not much difference whether you weight your portfolio equally or with inverse volatility when dealing with stocks, provided that the portfolio is large enough.

Could you perhaps describe Gray and Vogel's algorithm? I have been trying in vain to build a profitable (fully hedged) momentum-based algorithm for a couple of years now, so I would gladly try to implement theirs if you can tell us how it is supposed to work. Thanks!

Hey Tim, thanks so much for your considered response. What you are saying re: stocks being highly correlated makes sense, and, indeed, Clenow talks about this at length in Stocks on the Move.

I will try to summarize Quantitative Momentum when I have some time later tonight. In the meanwhile, you can find most of the thread if you start here: http://blog.alphaarchitect.com/2016/03/22/why-investors-should-combine-value-and-momentum/

Its a very simple algorithm (if you don't try to blend with value), I might try it tonight and see what I come up with. Basically, you just look at 12-month return, rank, and pick a concentrated portfolio.

Thanks for the link to the summary, Chris, I find the idea that value and momentum are complementary and can be used as such attractive, especially since it fits into a general framework of diversifying one's trading strategies, in addition to the portfolio itself.

Did anyone implement this?