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Nonlinearity everywhere: implications for empirical finance, technical analysis and value at risk

Amini, S., Hudson, R., Urquhart, A. ORCID: https://orcid.org/0000-0001-8834-4243 and Wang, J. (2021) Nonlinearity everywhere: implications for empirical finance, technical analysis and value at risk. European Journal of Finance. ISSN 1466-4364

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To link to this item DOI: 10.1080/1351847X.2021.1900888

Abstract/Summary

We show that expected returns on US stocks and all major global stock market indices have a particular form of non-linear dependence on previous returns. The expected sign of returns tends to reverse after large price movements and trends tend to continue after small movements. The observed market properties are consistent with various models of investor behavior and can be captured by a simple polynomial model. We further discuss a number of important implications of our findings. Incorrectly fitting a simple linear model to the data leads to a substantial bias in coefficient estimates. We show through the polynomial model that well known short term technical trading rules may be substantially driven by the non-linear behavior observed. The behavior also has implications for the appropriate calculation of important risk measures such as value at risk.

Item Type:Article
Refereed:Yes
Divisions:Henley Business School > ICMA Centre
ID Code:95565
Publisher:Taylor and Francis

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