A RISK-SENSITIVE MOMENTUM APPROACH TO STOCK SELECTION

Tina Kalayil, Somya Tyagi, Mahfuza Khatun and Sikandar Siddiqui

Economic Annals, 2019, vol. 64, issue 220, 61 - 84

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.

Keywords: Adaptive Markets; Local Least Squares smoothing; Moving Blocks Bootstrap (search for similar items in EconPapers)
JEL-codes: C58 G11 (search for similar items in EconPapers)
Date: 2019
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