Replication data for "Shrinking factor dimension: A reduced-rank approach"

This is the replication data for "shrinking factor dimension: A reduced-rank approach", published in Management Science. <br> The "data" folder includes all data files. The "codes" folder includes four folders with coding scripts: "Matlab for Main", "Python for Figures", "R", and "Matlab for LASSO Factors" <br> <br> ***** Data***** Main data files: Portfolio_returns.xlsx: data of riskfree rate, anomalies, FF48 portfolios, 202 characteristic managed portfolios stock_ret.mat: common stock returns stock_ret_nomicro: common stock returns (exclude micro caps) <br> intermediate data files： S2_1.xlsx, S2_3.xlsx, S2_5.xlsx, S2_6.xlsx: new weighting matrix W2, used for generating alternative RRA factors in Table 4. Run "weighting matrix.R" in folder "codes\R" to create. FGX_factors.mat: LASSO selected factors using Feng, Giglio, and Xiu (2020) method. Run "FGK_factors.m" in folder "codes\Matlab for LASSO Factors" to create. SCS_IS.mat: LASSO selected factors using Kozak, Nagel, and Santosh (2020) method. Run "KNS_factors.m" in folder "codes\Matlab for LASSO Factors" to create. figures.xlsx: spreadsheet "factor weights 48": weights of PCA, PLS, and 1 to 5 RRA factors. Run "Fig_factors_weights.m" in folder "codes\Matlab for Main" to create. spreadsheet "alphas 48" : absolute alphas of 48 industry portfolios. Run "Fig_alphas.m" in folder "codes\Matlab for Main" to create. <br> ***** How to Replicate ****** Tables: all main codes are in folder "codes\Matlab for Main" 1. Run "Main_code_for_Table1" to create Table 1 (summary statistics of factor proxies). 2. Run "Main_code_for_Table2_Table3" to create Table 2 (performance of different factor models: in-sample) and Table 3 (PLS and RRA factors using alternative basis assets). Estimated running time:27 mins 3. Run "Main_code_for_Table4" to create Table 4 (an alternative estimation of RRA factors), besides main data files, also needs S2_1.xlsx, S2_3.xlsx, S2_5.xlsx, S2_6.xlsx. Estimated running time:4 mins <br> 4. Run "Main_code_for_Table5" to create Table 5 (performance of different factor models: out-of-sample). Estimated running time:3 mins 29 secs <br> 5. Run "Main_code_for_Table6" to create Table 6 (performance of RRA factors estimated with a pricing error restriction). Estimated running time:17 mins 30 secs <br> 6. Run "Main_code_for_Table7" to create Table 7 (performance of different factor models with pre-specified FF five factors). Estimated running time:13 mins <br> 7. Run "Main_code_for_Table8" to create Table 8 (performance of alternative PCA factors). Estimated running time:13 mins <br> 8. Run "Main_code_for_Table9" to create Table 9 (performance of LASSO selected factors), besides main data files, also needs FGX_factors.mat and SCS_IS.mat. Estimated running time:9 mins <br> <br> <br> Figures: run "Fig1_3.py" in folder "Python for Figures" to create figure 1, 2, and 3. Needs figures.xlsx. Please install openpyxl before running. <br> <br> <br>