The Correlation Empirical Research Of FF Model Pricing Factors And Macroeconomic Factors

The stock market has shown many new problems. The traditional CAPM hasbeen tested by the reality because of scale effects and the book-to market effects etc.However those new-founded effects provide a new way to develop CAPM. Under theguide of rational pricing, Fama-French3-factor model (FF model) is an importantsupplement of CAPM. FF model attributed the systematic risk to market factors: thescale factor and the book-to-market factor. The macro-economy fluctuation is themain course of systemic risk in stock market. The main focus of this paper is to findthe relationship between macro-economy indicators and three public factors of FFmodel. The goal of this paper is to give some advise to design portfolio strategy. Italso helps us develop insights of FF model.The statistics of this paper cover from the1stquarter of2004to the3rdquarter of2013, as well as the251stocks and the index of Shenzhen A main board stork market.After screening the macro-indictors and adding “Li keqiang index”,we finally choosethe following indictors:Generating Capacity, Railway Freight Volume, M2, CPI,Unemployment Rate and SHIBOR Rate. And then discover the relationship betweenthese indicators and the three factors. This paper firstly discuss the theory of FFmodel. Secondly, qualitative analyze the relationship between the indicators and thefactors. Thirdly, draw a “roadmap” of the empirical analysis and establish model.Finally, according to the results, explain the weird phenomena shown from theprocess of empirical, then guide the investors.The first step of empirical analysis is the ADF test. If the series is smooth, wecan establish the VAR model and use the pulse response analysis to discover thedynamic relationship between each indicator and each factor. And then we can usethis to conclude the time sensitiveness and the directions of the effect ofmacroeconomic indicators. If the series is not smooth, we use the difference of theseries. After the series becoming fractional integration, we use the cointegrationmodel to analyze the relationship between each indicator and each factor. After testing the indicators and the factors, we decided to use cointegration test to analyze therelationship between the indicators and market factor, while use VAR model and thepulse response analysis to discover the relationship between the indicators and scalefactor or book-to-market factor.After analysis, we conclude the following results.Generating capacity has anegative correlation with market factor,so does M2. Railway freight volume, CPI,unemployment rate and SHIBOR rate show positive correlation with market factor.The changes of generating capacity, unemployment rate and SHIBOR rate havepositive impact on scale factor. The changes of railway freight volume and M2havenegative impact on scale factor. CPI has no effect on scale factor. The changes ofgenerating capacity, railway freight volume, CPI, unemployment rate and SHIBORrate have negative impact on book-to-market factor. The changes of M2has positiveimpact on book-to-market factor. Finally, analyze the reason of the conflictscomparing the theories with the fact.