Bayesian Arbitrage Threshold Analysis

Catherine Scipione Forbes · Guyonne R. J. Kalb · Paul Kofman

39 citations0/0 files storedJournal of Business and Economic Statistics

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Financial Markets and Investment Strategies Monetary Policy and Economic Impact Financial Risk and Volatility Modeling

Abstract

A Bayesian estimation procedure is developed for estimating multiple regime (multiple threshold) vector autoregressive models appropriate for deviations from financial arbitrage relationships. This approach has clear advantages over classical stepwise threshold autoregressive analysis. Whereas classical procedures first have to identify thresholds and then perform piecewise autoregressions, we simultaneously estimate threshold and autoregression parameters. To illustrate the Bayesian procedure, we estimate a no-arbitrage band within which index futures arbitrage is not profitable despite (persistent) deviations from parity.

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References

1993Introduction to Multiple Time Series Analysis 1997Threshold Cointegration 1995A nonlinear approach to US GNP 1991To criticize the critics: An objective bayesian analysis of stochastic trends 1995Arbitrage, Cointegration, and Testing the Unbiasedness Hypothesis in Financial Markets 1998A threshold error-correction model for intraday futures and index returns 1994THRESHOLD AUTOREGRESSIVE MODELING IN FINANCE: THE PRICE DIFFERENCES OF EQUIVALENT ASSETS1 1996Parameter uncertainty and impulse response analysis

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