Bayesian Arbitrage Threshold Analysis
开发了一种贝叶斯估计方法，用于分析金融套利关系偏离中的多区制误差修正模型，通过设定信息先验来估计无套利区间，对研究套利成本和市场效率的学者有参考价值。
A Bayesian estimation procedure is developed for estimating multiple-regime (multiple-threshold) error-correction models appropriate for deviations from financial arbitrage relationships. This approach has clear advantages over classical stepwise threshold autoregressive analysis. Unlike many other applications of threshold models, the knowledge of some costs involved in setting up arbitrage positions allows us to specify an informative prior. To illustrate the Bayesian procedure, we estimate a no-arbitrage band within which index futures arbitrage is not profitable despite (persistent) deviations from parity.