On the Effectiveness of Stop-Loss Rules: An Analytical Framework Based on Modeling Overnight Gaps and the Stationary Bootstrap

24 Pages Posted: 16 Dec 2017

See all articles by Argimiro Arratia

Argimiro Arratia

Polytechnic University of Catalonia (UPC)

Albert Dorador

European Central Bank (ECB)

Date Written: November 29, 2017

Abstract

A stop-loss rule is a risk management tool whereby the investor predefines some condition that, upon being triggered by market dynamics, imply the liquidation of her outstanding position. Such a tool is widely used by practitioners in financial markets with the hope of improving their investment performance by cutting losses and consolidating gains. But, do stop-loss rules really add value to an investment strategy?

In this work we give an answer to this question for four popular implementations of stop-loss rules using two different statistical methods, which complement each other and lead to a more robust answer. On the one hand, we use a model-based approach in which we present two different models for the price of a New York Stock Exchange equity, which consider the phenomenon of overnight gaps; on the other hand, we complement the previous approach with a data-based framework by using the stationary bootstrap to obtain different replicas of the financial time series corresponding to the historical price of several NYSE stocks.

As a general conclusion we find that, in rising markets, stop-loss rules improve the expected risk-adjusted return according to most metrics, while improving absolute expected return in falling markets. Furthermore, we find that in general the fixed percentage stop-loss rule may be the most powerful among the popular rules that we consider in this work, followed by the RSI-based stop-loss rule.

Keywords: Stop-loss, Risk Management, Financial Modeling, Overnight Gap, Bootstrap

JEL Classification: C52, C32, D81

Suggested Citation

Arratia, Argimiro and Dorador, Albert, On the Effectiveness of Stop-Loss Rules: An Analytical Framework Based on Modeling Overnight Gaps and the Stationary Bootstrap (November 29, 2017). Available at SSRN: https://ssrn.com/abstract=3087196 or http://dx.doi.org/10.2139/ssrn.3087196

Argimiro Arratia (Contact Author)

Polytechnic University of Catalonia (UPC) ( email )

C. Jordi Girona, 31
Barcelona, 08034
Spain

Albert Dorador

European Central Bank (ECB) ( email )

Sonnemannstrasse 22
Frankfurt am Main, 60314
Germany

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