具有阈值和时间相关的随机波动模型的不对称性

IF 0.7 4区 经济学 Q3 ECONOMICS Studies in Nonlinear Dynamics and Econometrics Pub Date : 2022-04-13 DOI:10.1515/snde-2021-0020
Torben Schäfers, Long Teng
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引用次数: 0

摘要

摘要本文通过在随机波动率(SV)模型中引入阈值、常数和时间相关来研究股票收益与波动率之间的不对称关系。我们开发了仅包括时间相关创新和阈值和时间相关的SV模型。文献表明,只有恒定相关性的SV模型比阈值随机波动(TSV)模型更好地捕捉不对称性。结果表明,具有时间相关的SV模型在捕获不对称性方面优于具有恒定相关的SV模型,同时具有阈值和时间相关的综合模型优于单纯具有阈值、恒定和时间相关以及阈值和恒定相关的SV模型。在我们的综合模型中,波动性和收益是时间相关的,其中时变相关性为负,并且波动性更持久,波动性更小,并且随着预期的负收益而更高。通过实证研究来说明我们的发现。
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Asymmetry in stochastic volatility models with threshold and time-dependent correlation
Abstract In this work we study the effects by including threshold, constant and time-dependent correlation in stochastic volatility (SV) models to capture the asymmetry relationship between stock returns and volatility. We develop SV models which include only time-dependent correlated innovations and both threshold and time-dependent correlation, respectively. It has been shown in literature that the SV model with only constant correlation does a better job of capturing asymmetry than threshold stochastic volatility (TSV) model. We show here that the SV model with time-dependent correlation performs better than the model with constant correlation on capturing asymmetry, and the comprehensive model with both threshold and time-dependently correlated innovations dominates models with pure threshold, constant and time-dependent correlation, and both threshold and constant correlation as well. In our comprehensive model, volatility and returns are time-dependently correlated, where the time-varying correlation is negative, and the volatility is more persistent, less volatile and higher following negative returns as expected. An empirical study is provided to illustrate our findings.
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来源期刊
CiteScore
1.40
自引率
12.50%
发文量
34
期刊介绍: Studies in Nonlinear Dynamics & Econometrics (SNDE) recognizes that advances in statistics and dynamical systems theory may increase our understanding of economic and financial markets. The journal seeks both theoretical and applied papers that characterize and motivate nonlinear phenomena. Researchers are required to assist replication of empirical results by providing copies of data and programs online. Algorithms and rapid communications are also published.
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