重尾过程协整检验的Bootstrap逼近

重尾过程的协整检验统计量渐近分布含有不可估计的重尾指数α,针对重尾过程的协整检验运用Bootstrap抽样算法,在不估计重尾指数α的情况下,计算了该检验统计量的临界值,并且证明了该算法在理论上的合理性.Monte Calo模拟说明该方法有效.

Bootstrap approximation for cointegration tests in heavy- tailed observations

It is known that the asymptotic distribution of a cointegration test statistic in heavy- tailed observations has the inestimable index parameter. This research uses the Bootstrap method in the cointegration test in heavy-tailed processes,calculates the critical value of the cointegration test without estimating the index parameter,and proves the theoretical validity of this Bootstrap method. Monte Calo simulations demonstrate the efficiency of the proposed method.