TESTING FOR EMBEDDABILITY BY STATIONARY REVERSIBLE CONTINUOUS-TIME MARKOV PROCESSES
针对离散时间平稳可逆马尔可夫过程观测，提出一种保守检验方法判断其能否被连续时间可逆马尔可夫过程嵌入，并发现汇率数据比股指数据更常被拒绝。
Given an observation of a discrete-time process { Y i , i = 0... n } assumed to be Markov, stationary, and time reversible, we develop a (conservative) test procedure of embeddability by a continuous-time reversible Markov process. The test statistic is derived from a set of moment inequality restrictions implied by the spectral properties of such continuous-time processes. Most interesting is that the embeddability condition of interest is a direct extension of the well-known embeddability problem by a two-state Markov chain. Empirical experiments show that the embeddability hypothesis is rejected more frequently for exchange rate daily data than for stock indices data.