Asset Pricing – Empirical Project

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Asset Pricing – Empirical Project

Follow the instructions below and work on the empirical project presented, applying the Fama and MacBeth (1973) approach. The data for the two projects are provided in a file. Use R to do the stock pricing project. Submit your results in a written document that includes a discussion of the econometric approach, the model, the estimation results, their economic interpretation and R-code the not later than May 29th, 2015. 1 Fama and MacBeth (1973) Project The file DataGermanStocks.xlsx provides you with monthly historical prices for 20 German stocks and the DAX as a market index. Apply a Fama and MacBeth (1973) analysis to this data. Use prices to derive log returns. Use the ln-returns for your analysis. a) Step 1: Step 1: Estimate the time series regression rit = αi + βirM t + εit for i = 1, . . . , N = 20. b) Step 2: Use the estimates βˆ i now written as βˆ it to run the following cross sectional regression for each period t in the intervals [1995-2000] and [2005-2012]: rit = γtβˆ it + ait The estimates ˆγt are the realized risk premia at a given date t and ˆait are the pricing errors. c) Step 3: Derive the expected risk premia ˆγ and pricing errors ˆai as well as their varinaces. d) Step 4: Follow the three steps and derive risk premia, pricing errors and their variances for the two sub-periods stated above. Comment on statistical and economic characteristics of the empirical results. 1 Further readings Fama and French (1988), Petersen (2009), Cochrane (2005), Campbell et al. (1997), etc. References Campbell, J. Y., Lo, A. W., and MacKinlay, A. C. (1997). The Econometrics of Financial Markets. Princeton University Press, Princeton. Cochrane, J. (2005). Asset Pricing. Princeton University Press, revised edition. Fama, E. F. and French, K. R. (1988). Permanent and temporary components of stock prices. Journal of Political Economy, 96(2):246–273. Fama, E. F. and MacBeth, J. D. (1973). Risk, return, and equilibrium: Empirical tests. Journal of Political Economy, 81(3):607–636. Petersen, M. A. (2009). Estimating standard errors in finance panel data sets: Comparing approaches. Review of Financial Studies, 22(1):435–480. 2

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