なぜロバストなアルファ（ベータ）推定値が必要なのか-プレミアム VS アノマリーを統計的手法で超えられる?-
2016 年 2016 巻 FIN-016 号 p. 57-
詳細
2016 年 2016 巻 FIN-016 号 p. 57-
OLS (Ordinary Least Square) estimation of sample means and betas can lead to biased estimates of alpha in the presence of certain patterns of heteroscedasticity. There has been discussing on something t o do with background of modern portfolio theory for forecasting risk premium and dealing with anomaly. We demonstrate that those patterns occur in practice, and that a robust estimation process eliminates the bias with some algorithms.
