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Open AccessArticle

Return and Risk of Pairs Trading Using a Simulation-Based Bayesian Procedure for Predicting Stable Ratios of Stock Prices

1
Institute of Financial Analysis, University of Neuchatel, Neuchatel, 2000, Switzerland
2
Department of Finance, Insurance and Real Estate, Laval University, Quebec City, G1V 0A6, Canada
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Institute of Econometrics and Statistics, Faculty of Economics and Sociology, University of Lodz, Lodz, 90-255, Poland
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Department of Econometrics and Tinbergen Institute, Vrije Universiteit Amsterdam, Amsterdam, 1081 HV, The Netherlands
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Econometric Institute, Erasmus University Rotterdam, Rotterdam, 3062 PA, The Netherlands
*
Author to whom correspondence should be addressed.
Academic Editors: Nalan Baştürk, Francesco Ravazzolo and Roberto Casarin
Econometrics 2016, 4(1), 14; https://doi.org/10.3390/econometrics4010014
Received: 3 September 2015 / Revised: 26 January 2016 / Accepted: 28 January 2016 / Published: 10 March 2016
(This article belongs to the Special Issue Computational Complexity in Bayesian Econometric Analysis)
We investigate the direct connection between the uncertainty related to estimated stable ratios of stock prices and risk and return of two pairs trading strategies: a conditional statistical arbitrage method and an implicit arbitrage one. A simulation-based Bayesian procedure is introduced for predicting stable stock price ratios, defined in a cointegration model. Using this class of models and the proposed inferential technique, we are able to connect estimation and model uncertainty with risk and return of stock trading. In terms of methodology, we show the effect that using an encompassing prior, which is shown to be equivalent to a Jeffreys’ prior, has under an orthogonal normalization for the selection of pairs of cointegrated stock prices and further, its effect for the estimation and prediction of the spread between cointegrated stock prices. We distinguish between models with a normal and Student t distribution since the latter typically provides a better description of daily changes of prices on financial markets. As an empirical application, stocks are used that are ingredients of the Dow Jones Composite Average index. The results show that normalization has little effect on the selection of pairs of cointegrated stocks on the basis of Bayes factors. However, the results stress the importance of the orthogonal normalization for the estimation and prediction of the spread—the deviation from the equilibrium relationship—which leads to better results in terms of profit per capital engagement and risk than using a standard linear normalization. View Full-Text
Keywords: Bayesian analysis; cointegration; linear normalization; orthogonal normalization; pairs trading; statistical arbitrage Bayesian analysis; cointegration; linear normalization; orthogonal normalization; pairs trading; statistical arbitrage
MDPI and ACS Style

Ardia, D.; Gatarek, L.T.; Hoogerheide, L.; Van Dijk, H.K. Return and Risk of Pairs Trading Using a Simulation-Based Bayesian Procedure for Predicting Stable Ratios of Stock Prices. Econometrics 2016, 4, 14. https://doi.org/10.3390/econometrics4010014

AMA Style

Ardia D, Gatarek LT, Hoogerheide L, Van Dijk HK. Return and Risk of Pairs Trading Using a Simulation-Based Bayesian Procedure for Predicting Stable Ratios of Stock Prices. Econometrics. 2016; 4(1):14. https://doi.org/10.3390/econometrics4010014

Chicago/Turabian Style

Ardia, David; Gatarek, Lukasz T.; Hoogerheide, Lennart; Van Dijk, Herman K. 2016. "Return and Risk of Pairs Trading Using a Simulation-Based Bayesian Procedure for Predicting Stable Ratios of Stock Prices" Econometrics 4, no. 1: 14. https://doi.org/10.3390/econometrics4010014

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Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

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