Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/197874 
Year of Publication: 
2018
Series/Report no.: 
Bank of Canada Staff Working Paper No. 2018-21
Publisher: 
Bank of Canada, Ottawa
Abstract: 
We explore properties of asymmetric generalized autoregressive conditional heteroscedasticity (GARCH) models in the threshold GARCH (GTARCH) 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 lowfrequency volatility component. We then apply a variety of volatility models in setting initial margin requirements for a central clearing counterparty (CCP). Finally, we show how to mitigate procyclicality of initial margins using a three-regime threshold autoregressive model.
Subjects: 
Econometric and statistical models
Payment clearing and settlement systems
JEL: 
C58
G19
G23
G28
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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