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http://dx.doi.org/10.5351/KJAS.2022.35.3.347

Multiple-threshold asymmetric volatility models for financial time series  

Lee, Hyo Ryoung (Department of Statistics, Sookmyung Women's University)
Hwang, Sun Young (Department of Statistics, Sookmyung Women's University)
Publication Information
The Korean Journal of Applied Statistics / v.35, no.3, 2022 , pp. 347-356 More about this Journal
Abstract
This article is concerned with asymmetric volatility models for financial time series. A generalization of standard single-threshold volatility model is discussed via multiple-threshold in which we specialize to twothreshold case for ease of presentation. An empirical illustration is made by analyzing S&P500 data from NYSE (New York Stock Exchange). For comparison measures between competing models, parametric bootstrap method is used to generate forecast distributions from which summary statistics of CP (Coverage Probability) and PE (Prediction Error) are obtained. It is demonstrated that our suggestion is useful in the field of asymmetric volatility analysis.
Keywords
asymmetric volatility; multiple-threshold; parametric bootstrap;
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Times Cited By KSCI : 5  (Citation Analysis)
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