quantitative framework
The firm has built a proprietary alpha generation model, as well as a risk model and optimizer, all based on both academic research and industry experience. The principals of the firm have developed an active quantitative investment process that ranks all equity stocks in the global universe across four alpha categories (value, growth, quality, and sentiment), calculates risk characteristics for each stock in the universe, and ultimately constructs portfolios that maximize the expected alpha subject to a level of benchmark relative volatility and additional diversification and holdings constraints.
Multiple factors are included in each of the aforementioned alpha categories in an effort to ensure that a complete quantitative assessment is done on each stock. Stocks are ranked among their global industry peers for each of the individual alpha factors. Those ranks are then combined by applying predetermined percentage weights for each factor. The weights are based on a combination of testing, experience, and intuition.
Through optimization, buy and sell ideas are produced, all within risk constraints set in advance. Those constraints are based on regional location, economic sector, and risk factor constraints such as beta. Before a new company is added to the portfolio, we examine a variety of research sources for information that may not have been identified by the model. The data is updated daily for the purposes of performing alpha and risk calculations for the entire universe. Daily portfolio optimizations are run to identify buy ideas. Final optimizations are run periodically, up to monthly, with a focus on the buy ideas that were generated throughout the month.
