Finite Sample Performance in Cointegration Analysis of Nonlinear Time Series with Long Memory
研究了多元金融时间序列的非线性函数可能具有长记忆和分数协整，但现有分析工具基于不合理的假设，通过蒙特卡洛模拟表明渐近理论未必能良好近似有限样本行为。
Nonlinear functions of multivariate financial time series can exhibit long memory and fractional cointegration. However, tools for analysing these phenomena have principally been justified under assumptions that are invalid in this setting. Determination of asymptotic theory under more plausible assumptions can be complicated and lengthy. We discuss these issues and present a Monte Carlo study, showing that asymptotic theory should not necessarily be expected to provide a good approximation to finite-sample behavior.