Whitepapers

We have written some Whitepapers on Quantitative Stock Selection – covering 4 subjects related to our model. The whitepapers highlight some of the enhancements that we have made to our model, including: Style timing, factor efficacy, asymmetry of alpha and information diffusion. 

Please contact us if you are interested in reading the full pdf articles.

Highlights

Style Timing, or Dynamisation of Multifactor Models: Quant investors are becoming wary of sudden style shifts, severe macro events and shorter macro cycles – and style timing is gaining prominence in the investment process as dynamic factor weighting has come in vogue. Here we focus on ‘style momentum’, i.e. the continuation of style performance from one period to the next and find high levels of persistence in style performance.

Conditional Factor Efficacy: All quant investors aim to select the best set of alpha drivers and a combination several factors lies at the heart of this process. Most quantitative investment processes have different models for each sector, but neglect other important characteristics of stocks. Considering more angles than only sector classification can vastly improve quantitative models for stock selection.

Asymmetry of Alpha: Have you ever wondered why on the one hand, debt-ridden companies underperform healthy ones, while on the other hand, triple AAA companies do not outperform average ones? Welcome to the world of factor asymmetric alpha. In this paper, Rani Piputri explores this subject and shows how to benefit from this phenomenon.

Gradual Information Diffusion, by Professor Ben Jacobson and PhD candidate Helen Lu. Ben is an advisor to Saemor Capital: Is the oil price a leading indicator for stock returns? And if so, how? Do some industries lead the market? And which ones? Questions like these are on many investors’ minds. Gradual information diffusion – a new theory describing how information flows across markets – is providing more of an answer for quant investors. If the supporting empirical evidence uncovered to date is anything to go by, this method is quickly becoming a promising means for predicting market returns.