Bayesian Arbitrage Threshold Analysis
提出一种贝叶斯方法，用于估计金融套利关系偏离中的多阈值向量自回归模型，能同时估计阈值和自回归参数，优于传统逐步方法。
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.