Multiple Factor Model Summary
In this post I want to summarize all the material I covered in the Multiple Factor Models series. The Multiple Factor Model can be used to decompose returns and calculate risk. Following are some examples of the Multiple Factor Models:
- The expected returns factor model: Commonality In The Determinants Of Expected Stock Returns by R. Haugen, N. Baker (1996)
- The expected returns factor model: CSFB Quantitative Research, Alpha Factor Framework on page 11, page 49 by P. N. Patel, S. Yao, R. Carlson, A. Banerji, J. Handelman
- The risk factor model: MSCI Barra United States Equity Multi-Factor Model, page 101
The factors in the model are usually created using pricing, fundamental, analyst estimates, and proprietary data. I will only show examples of factors using pricing and fundamental data because these infromation is readily available from Yahoo Fiance and ADVFN.
Following is a summary of all posts that I wrote about Multiple Factor Models:
- Multiple Factor Model – Fundamental Data – in this post I demonstrate how to get company’s Fundamental Data into R, create a simple factor, and run correlation analysis.
- Multiple Factor Model – Building Fundamental Factors – in this post I demonstrate how to build Fundamental factors described in the CSFB Alpha Factor Framework and compute quantiles spreads. For details of the CSFB Alpha Factor Framework please read CSFB Quantitative Research, Alpha Factor Framework on page 11, page 49 by P. N. Patel, S. Yao, R. Carlson, A. Banerji, J. Handelman.
- Multiple Factor Model – Building CSFB Factors – in this post I demonstrate how to build majority of factors described in the CSFB Alpha Factor Framework, run cross sectional regression to estimate factor loading, create and test Alpha model.
- Multiple Factor Model – Building Risk Model – in this post I demonstrate how to build a multiple factor risk model, compute factor covariance using shrinkage estimator, forecast stocks specific variances using GARCH(1,1).
- Portfolio Optimization – Why do we need a Risk Model – in this post I explain why do we need a risk model and demonstrate how it is used during portfolio construction process.
- Multiple Factor Model – Building 130/30 Index – in this post I demonstrate how to build 130/30 Index based on the CSFB Factors and the Risk Model we created previously. The 130/30: The New Long-Only (2008) by A. Lo, P. Patel paper presents a very detailed step by step guide to building 130/30 Index using average CSFB Factors as the alpha model and MSCI Barra Multi-Factor Risk model.
- Multiple Factor Model – Building 130/30 Index (Update) – in this post I demonstrate how to build Market-Neutral and Minimum Variance strategies and compare their performance to the 130/30 Index.
There is an excellent discussion of portfolio construction problems and possible solutions in the The top 7 portfolio optimization problems post by Pat Burns. I want to highlight two problems that are relevant to the Multiple Factor Models.
- Problem 3: The expected returns provided by Alpha model sometimes need to scaled or converted to be used in optimization. The Converting Scores into Alphas – A Barra Aegis Case Study (2010) by I. Gleiser, D McKenna paper provides a step by step guide.
- Problem 7: Factor alignment problem is present when different factors are used in the Alpha model and Risk model. An Empirical Case Study of Factor Alignment Problems using the United States Expected Returns (USER) Model – Axioma Research Paper (2011) by A. Saxena, R. Stubbs paper investigates this problem and proposes an alternative portfolio construction methodology.