Mebane Faber puts an ancient asset allocation strategy to the test. Interesting results, and I agree that individual investors can and should take advantage of these sorts of strategies themselves, and not just leave them up to the professionals.
Mebane Faber has done us the favor of distilling and summarizing a lot of research around asset allocation strategies into a simple post. He lists the types and compositions of the most popular asset allocation strategies, such as 60/40, David Swensen’s Portfolio (made famous by its use at Yale University), the Permanent Portfolio, the Ivy Portfolio, etc. He also kindly provides a performance table with the key statistics. As expected, the Permanent Portfolio and the Risk Parity Portfolio do best at minimizing drawdown, but the CAGR across the strategies is surprisingly close. As always, read the whole thing.
Neural networks and genetic algorithms are among the most important topics in algorithmic trading and drive much of the research and allocation of computing resources of hedge funds today. Equametrics recently posted two great articles to explain neural networks and genetic algorithms, and their application to trading. Why are they important for the rest of us to know about?