A RISK-SENSITIVE MOMENTUM APPROACH TO STOCK SELECTION

Abstract

One of the main implica-tions of Lo’s Adaptive Markets Hypoth-esis (2004, 2012, 2017) is that returns of virtually all assets can change over time. We present a local linear trend smoothing method by which this phenomenon can be captured empirically. Moreover, we in-troduce two localised, amended goodness-of-fit indicators capable of capturing both the direction and the continuity of recently observed price trends. Our related empiri-cal investigation is based on a sample of 30 German blue-chip stock price series ob-served over a period of more than 16 years. Its results indicate that the use of these in-dicators as a stock-screening device can be a more useful means of identifying stocks with a superior risk/return profile than ap-plying a conventional momentum strategy. The validity of this finding is underscored by statistical significance tests based on a Moving Blocks Bootstrap procedure.