ETF Central » risk management

Reading List, Week of Jan. 10, 2010

Michael Bommarito — Mon, 10 Jan 2011 19:40:20 +0000

Instead of posting papers separately, I’ve decided to transition to a weekly reading list format. I’ll update this post over the course of the week, but here’s the initial list:

Gelpern, Anna and Gulati, G. Mitu, Sovereign Snake Oil. Law and Contemporary Problems, Forthcoming.
Chan, Kam Fong and Marsden, Alastair D.E., Empirical Tests on the Credit Default Swap and Stock Markets During the Global Credit Crisis.
Friedman, Craig and Zhang, Yangyong, Estimating Flexible, Fat-Tailed Conditional Asset Return Distributions.
Han, Bing and Zhou, Yi, Term Structure of Credit Default Swap Spreads and Cross-Section of Stock Returns.

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Paper freely available from Quantitative Finance for RiskMinds 2010

Michael Bommarito — Thu, 09 Dec 2010 15:05:10 +0000

I received an email from Quantitative Finance informing me that my paper with A. Duran,
A Profitable Trading and Risk Management Strategy Despite Transaction Cost, will be freely available online in a “virtual issue” of the journal on risk. This issue is designed to coincide with the RiskMinds 2010 conference currently taking place. Please access the published version of my paper from InformaWorld here or the entire Risk issue here through the end of the month.

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Paper: L. Kang, S. Babbs. Modelling Overnight and Daytime Returns Using a Multivariate Garch-Copula Model

Michael Bommarito — Mon, 22 Nov 2010 02:42:20 +0000

Abstract: We introduce a multivariate GARCH-Copula model to describe joint dynamics of overnight and daytime returns for multiple assets. The conditional mean and variance of individual overnight and daytime returns depend on their previous realizations through a variant of GARCH specification, and two Student’s t copulas describe joint distributions of both returns respectively. We employ both constant and time-varying correlation matrices for the copulas and with the time-varying case the dependence structure of both returns depends on their previous dependence structures through a DCC specification. We estimate the model by a two-step procedure, where marginal distributions are estimated in the first step and copulas in the second. We apply our model to overnight and daytime returns of SPDR ETFs of nine major sectors and briefly illustrate its use in risk management and asset allocation. Our empirical results show higher mean, lower variance, fatter tails and lower correlations for overnight returns than daytime returns. Daytime returns are significantly negatively correlated with previous overnight returns. Moreover, daytime returns depend on previous overnight returns in both conditional variance and correlation matrix (through a DCC specification). Most of our empirical findings are consistent with the asymmetric information argument in the market microstructure literature. With respect to econometric modelling, our results show a DCC specification for correlation matrices of t copulas significantly improves the fit of data and enables the model to account for time-varying dependence structure.

L. Kang, S. Babbs. Modelling Overnight and Daytime Returns Using a Multivariate Garch-Copula Model. http://ssrn.com/abstract=1710799.

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