辅导案例-MFIN7034

  • June 6, 2020

Pset1, MFIN7034 Dr. Ye Luo May 29, 2019 Excercise in high-dimensional methods. You should hand in a copy of code and the results. You should hand in a hard copy even if you send an e-copy before the deadline for grading purpose. 1. Merge all the factor data from Fame-French, PS and HXZ.Construct lagged factors with 1,2,3,4,5,6 months of lag of the original factors. 2. Perform a LASSO on the Fama-French regressions for each asset that have data from 19810131-20121231. You should drop the first a few observations to ensure that all your factors exist. You may choose rule of thumb (2σ √ 2 log(pn)/n) for some pre- liminary estimation of σ, e.g., pooled regression, or use cross-validation). Use Training sample period from the beginning to 20080131, and use testing sample from 20080201 to 20121231. 3. Collect in sample and out of sample prediction errors, averaged by all stock ids. Report them and briefly discuss. 4. Collect factors selection frequency, i.e., the percentage of a factor being selected by LASSO over all stocks. For example, if you have 1000 stocks, and 500 of them select the market factor, then the percentage of selection of the market factor is 50%. Report the frequencies in a chart. 1

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