Leverage Effect and Volatility Asymmetry

2018 ◽  
pp. 131-150
Author(s):  
Parthajit Kayal ◽  
S. Maheswaran
Keyword(s):  
Leverage Effect ◽  
Volatility Asymmetry

scholarly journals Think again: volatility asymmetry and volatility persistence

2018 ◽  
Vol 23 (1) ◽  
Author(s):  
Dirk G. Baur ◽  
Thomas Dimpfl
Keyword(s):  
Quantile Regression ◽  
Realized Volatility ◽  
Leverage Effect ◽  
Variance Estimator ◽  
Volatility Persistence ◽  
Volatility Models ◽  
Volatility Asymmetry ◽  
High Volatility ◽  
Volatility Regimes ◽  
Volatility Feedback

Abstract We use a leveraged quantile heterogeneous autoregressive model of realized volatility to illustrate that volatility persistence and the asymmetric “leverage” effect are high volatility phenomena. More specifically, we find that (i) low volatility is not persistent, but high volatility all the more, even featuring properties of explosive processes; and (ii) asymmetry of volatility is only a high volatility phenomenon and there is no asymmetry in low volatility regimes. Our results turn out to be robust to the choice of the realized variance estimator, in particular with respect to jumps. The analysis illustrates that quantile regression can provide information that is hidden in commonly used GARCH or realized volatility models. The quantile regression results can also be linked to the weak empirical evidence of the leverage effect and the volatility feedback effect.

scholarly journals Approximate pricing formula to capture leverage effect and stochastic volatility of a financial asset

2021 ◽  
pp. 102072
Author(s):  
Youssef El-Khatib ◽  
Stephane Goutte ◽  
Zororo S. Makumbe ◽  
Josep Vives
Keyword(s):  
Stochastic Volatility ◽  
Leverage Effect ◽  
Financial Asset ◽  
Pricing Formula

FII, Stock Exchange Return, and the Leverage Effect: Evidence from India

2016 ◽  
Vol 19 (1) ◽  
pp. 103-119 ◽  
Author(s):  
Monica Singhania ◽  
Neha Saini
Keyword(s):  
Stock Exchange ◽  
Leverage Effect

scholarly journals Tail Behavior and Dependence Structure in the APARCH Model

2016 ◽  
Vol 9 (2) ◽  
Author(s):  
Farrukh Javed ◽  
Krzysztof Podgórski
Keyword(s):  
Statistical Inference ◽  
Dependence Structure ◽  
Leverage Effect ◽  
Tail Behavior ◽  
News Shocks ◽  
Negative News ◽  
Asymmetric Responses ◽  
Heavy Tailed ◽  
European Economies ◽  
Theoretical Results

AbstractThe APARCH model attempts to capture asymmetric responses of volatility to positive and negative ‘news shocks’ – the phenomenon known as the leverage effect. Despite its potential, the model’s properties have not yet been fully investigated. While the capacity to account for the leverage is clear from the defining structure, little is known how the effect is quantified in terms of the model’s parameters. The same applies to the quantification of heavy-tailedness and dependence. To fill this void, we study the model in further detail. We study conditions of its existence in different metrics and obtain explicit characteristics: skewness, kurtosis, correlations and leverage. Utilizing these results, we analyze the roles of the parameters and discuss statistical inference. We also propose an extension of the model. Through theoretical results we demonstrate that the model can produce heavy-tailed data. We illustrate these properties using S&P500 data and country indices for dominant European economies.

Estimating and Forecasting Volatility Using Leverage Effect

2017 ◽  
Author(s):  
Christina Dan Wang ◽  
Per A. Mykland ◽  
Lan Zhang
Keyword(s):  
Leverage Effect ◽  
Forecasting Volatility
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