Can you improve your investment process in such a way that it selects the right stocks for the current environment? That’s the question addressed by a new white paper on Quantitative Stock Selection issued by Saemor Capital.

The growing importance of the macro-economy as a driver for asset returns has resulted in a testing environment for investors. Saemor Capital has navigated this environment well. The company’s Saemor Europe Alpha Fund is currently nominated for a EuroHedge award in the category of equity market neutral & quantitative strategies.

Most quantitative stock selection models are based on ‘alpha drivers’ or ‘factors’ – usually fundamental criteria such as the Price/Earnings and Debt/Assets ratios. These factors are backed by academic and other research, and are applied by both quantitative and fundamental managers alike. But quantitative models are as different from one another as the methods used by fundamental managers.
When it comes to multi-factor models, the devil is in the detail. Saemor research has shown that some factors cannot be taken at face value, while other factors show a better payoff when implemented in a slightly different way. So which factors are the most reliable for generating positive returns?

Saemor Capital is a specialist in quantitative stock selection. The company applies a highly distinct method when selecting alpha drivers, employing a tailored approach for specific stocks and market segments, and changing macro-economic regimes.
These methods have helped these selections withstand the headwinds of this year’s European sovereign debt crisis. All aspects of the quantitative investment process have been included in Saemor Capital’s research, from alpha generation to portfolio construction to risk management.
 Saemor Capital’s latest white paper highlights some of the fund’s most successful techniques with regard to alpha generation, including:

• Using dynamic factor weights – research has shown that models that adapt weights to the macro-economic environment outperform traditional, static models
• Evaluating stocks from different angles – beyond sector classification.
• Asymmetric behaviour in stock selection criteria – improving factor effectiveness.
• The new theory of Gradual Information Diffusion by advisor Ben Jacobsen and co-author Helen Lu – describing how information flows across markets.

Access Saemor Capital’s white paper on Quantitative Stock Selection online here