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

Amini, Shima; Hudson, Robert; Urquhart, Andrew; Wang, Jian


Shima Amini

Andrew Urquhart


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 behaviour 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 behaviour observed. The behaviour also has implications for the appropriate calculation of important risk measures such as value at risk.


Amini, S., Hudson, R., Urquhart, A., & Wang, J. (in press). Nonlinearity everywhere: implications for empirical finance, technical analysis and value at risk. The European journal of finance,

Journal Article Type Article
Acceptance Date Jan 16, 2021
Online Publication Date Mar 19, 2021
Deposit Date Jan 16, 2021
Publicly Available Date Oct 27, 2022
Journal European Journal of Finance
Print ISSN 1351-847X
Electronic ISSN 1466-4364
Publisher Routledge
Peer Reviewed Peer Reviewed
Keywords Technical analysis; Nonlinear; Value-at-risk; Dependence; Predictability
Public URL


Article (716 Kb)

Copyright Statement
©2021 The authors. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright holder

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