Correlated squared returns
作者机构：Robert H.Smith School of BusinessUniversity of MarylandCollege ParkMD 20742USA Derivative Product StratsMorgan StanleyNew YorkNY 10036USA
出 版 物：《Probability, Uncertainty and Quantitative Risk》 (概率、不确定性与定量风险（英文）)
年 卷 期：2021年第6卷第2期
页 面：139-158页
学科分类：07[理学] 0701[理学-数学] 070101[理学-基础数学]
主 题：Correlated gamma processes Joint characteristic functions Digital moment estimation Path simulation
摘 要：Joint densities for a sequential pair of returns with weak autocorrelation and strong correlation in squared returns are *** marginal return densities are either variance gamma or bilateral ***-dimensional matching of empirical characteristic functions to its theoretical counterpart is employed for dependency parameter *** are reported for 3920 daily return sequences of one thousand *** simulation is done using conditional distribution *** paths display levels of squared return correlation and decay rates for the squared return autocorrelation function that are comparable to these magnitudes in daily return *** of log characteristic functions at different time points are used to estimate time scaling *** of these time scaling coefficients on squared return correlations support the view that autocorrelation in squared returns slows the rate of passage of economic *** analysis of financial markets for 2020 in comparison with 2019 displays a post-COVID slowdown in financial markets.
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