Analysis of Asymmetric GARCH Volatility Models with Applications to Margin Measurement

55 Pages Posted: 15 Jul 2018

See all articles by Elena Goldman

Elena Goldman

Lubin School of Business, Pace University

Xiangjin Shen

Government of Canada - Bank of Canada

Date Written: May 10, 2017

Abstract

We explore properties of asymmetric generalized autoregressive conditional heteroscedasticity (GARCH) models in the threshold GARCH family and propose a more general Spline-GTARCH model, which captures high-frequency return volatility, low-frequency macroeconomic volatility as well as an asymmetric response to past negative news in both autoregressive conditional heteroscedasticity (ARCH) and GARCH terms. Based on maximum likelihood estimation of S\&P 500 returns, S\&P/TSX returns and Monte Carlo numerical example, we find that the proposed more general asymmetric volatility model has better fit, higher persistence of negative news, higher degree of risk aversion and significant effects of macroeconomic variables on the low frequency volatility component. We then apply a variety of volatility models including asymmetric GARCH, GARCH and EWMA in setting initial margin requirements for central clearing counterparties (CCPs).

Keywords: CCP Initial Margins, Tail Risk, Risk Aversion, Procyclicality, Threshold GARCH, Spline, Threshold Autoregressive Model, Realized Variance

JEL Classification: C51, C52, C53, G10, G17

Suggested Citation

Goldman, Elena and Shen, Xiangjin, Analysis of Asymmetric GARCH Volatility Models with Applications to Margin Measurement (May 10, 2017). Pace University Finance Research Paper No. 2018/03, Available at SSRN: https://ssrn.com/abstract=2966352 or http://dx.doi.org/10.2139/ssrn.2966352

Elena Goldman

Lubin School of Business, Pace University ( email )

1 Pace Plaza
New York, NY 10038-1502
United States

HOME PAGE: http://webpage.pace.edu/egoldman/

Xiangjin Shen (Contact Author)

Government of Canada - Bank of Canada ( email )

234 Wellington Street
Ontario, Ottawa K1A 0G9
Canada

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