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Econometrics 2016, 4(1), 14; doi:10.3390/econometrics4010014

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
3
Institute of Econometrics and Statistics, Faculty of Economics and Sociology, University of Lodz, Lodz, 90-255, Poland
4
Department of Econometrics and Tinbergen Institute, Vrije Universiteit Amsterdam, Amsterdam, 1081 HV, The Netherlands
5
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
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)
View Full-Text   |   Download PDF [299 KB, uploaded 10 March 2016]

Abstract

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
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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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.

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