Hi all, Could you please help me understand the relation between risk models and trading strategies? Esp. I don't understand the following sentences: "Alternatively, portfolios can be rebalanced with objectives and constraints simultaneously incorporating different risk models. " Any thoughts? Thanks! --------------------------------------------------------------- For the last five years, Axioma has provided portfolio managers with fundamental and statistical risk models that are fully updated on a daily basis. These models can be used within AxiomaÂ¡Â¯s portfolio construction software platform to manage portfolios using multiple risk perspectives. For example, the predicted risk and tracking error of any given portfolio can be measured with both a fundamental and a statistical risk model to provide a range of risk predictions. Alternatively, portfolios can be rebalanced with objectives and constraints simultaneously incorporating different risk models. Research has shown that using multiple risk models for portfolio construction can significantly improve realized performance. In this talk, we consider the possibility of constructing alpha signals by comparing the differences in risk model predictions across both risk model type (fundamental vs. statistical) and across small differences in time (an up-to-date risk model vs. one that is a few days older). These signals exhibit intra-month variations that are essential for extracting a reliable signal. When these intra-month variations are taken into account, the signals found prove to be high quality and reliable. This signal extraction process produces benchmark-dependent, daily alpha signals that can be easily incorporated into an existing portfolio management process. For example, if an existing process rebalances on the fourth trading day of the month, the alpha signals corresponding to the given asset universe and trading day of the month can be used to augment an existing rebalancing process. The signals provide an easy to use and readily understood tool for leveraging the intra-month alpha signals embedded in daily, fundamental and statistical risk models to improve performance.