TY - UNPB
T1 - Combining Factors
AU - Reschenhofer, Christoph
PY - 2022/4/20
Y1 - 2022/4/20
N2 - While the academic literature primarily investigates factor exposures based on covariances (i.e. beta exposure), most practitioners apply characteristics-based scorings to obtain factor portfolios. It hereby remains largely unexplored how firm-level characteristics can be combined to obtain optimal factor portfolios. This paper derives multi-factor portfolios that are formed via a combination of stock characteristic scores. Portfolios that are formed on multiple characteristics are less volatile, and exhibit higher after cost returns compared to the market and single factor portfolios. In addition, return, risk and turnover preferences are very sensitive to buy- and sell-thresholds. We further identify optimal weights for individual factor characteristics, but have to recognize the 1/N factor portfolio as a tough benchmark.
AB - While the academic literature primarily investigates factor exposures based on covariances (i.e. beta exposure), most practitioners apply characteristics-based scorings to obtain factor portfolios. It hereby remains largely unexplored how firm-level characteristics can be combined to obtain optimal factor portfolios. This paper derives multi-factor portfolios that are formed via a combination of stock characteristic scores. Portfolios that are formed on multiple characteristics are less volatile, and exhibit higher after cost returns compared to the market and single factor portfolios. In addition, return, risk and turnover preferences are very sensitive to buy- and sell-thresholds. We further identify optimal weights for individual factor characteristics, but have to recognize the 1/N factor portfolio as a tough benchmark.
KW - Portfolio construction
KW - factor investing
KW - transaction costs
KW - investment strategies
U2 - 10.2139/ssrn.4080705
DO - 10.2139/ssrn.4080705
M3 - Working Paper/Preprint
BT - Combining Factors
ER -