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A Risk-Sensitive Momentum Approach To Stock Selection

Author

Listed:
  • Tina Kalayil
  • Somya Tyagi
  • Mahfuza Khatun
  • Sikandar Siddiqui

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.

Suggested Citation

  • Tina Kalayil & Somya Tyagi & Mahfuza Khatun & Sikandar Siddiqui, 2019. "A Risk-Sensitive Momentum Approach To Stock Selection," Economic Annals, Faculty of Economics and Business, University of Belgrade, vol. 64(220), pages 61-84, January –.
    • Handle: RePEc:beo:journl:v:64:y:2019:i:220:p:61-83
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    References listed on IDEAS

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    More about this item

    Keywords

    Adaptive Markets; Local Least Squares smoothing; Moving Blocks Bootstrap;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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