This isn’t related to automated trading systems, but as it overlaps with algorithmic trading, I thought I would mention that Troy Shu has released a beta web app called adaptivwealth [sic] to help retail investors with their asset allocation decisions. Asset allocation is essentially how you divide your investments between different asset classes, such as stocks, bonds, and alternatives (commodities, forex, precious metals, etc.). As Mr. Shu points out, several financial services startups are attempting to address the question of optimal asset allocation (see The Algorithmic Trading and Autotrading Universe under the Model Selection section for a list), but they each suffer from various weaknesses, so he’s attempting to address the problem with his own solution: the adaptive asset allocation tool, which essentially adapts its asset allocation decisions to various market conditions, whereas the other services in this industry tend to pick a fixed portfolio and stick with it, bull or bear market.
Be sure to read his introductory post to get a better sense of what he’s trying to accomplish and how his web app can help. This kind of rules-based investing forms the basis of algorithmic trading, and thus is a helpful framework for thinking about how to generate better risk-adjusted returns than the market index.