Handbook of Research Methods and Applications in Empirical Finance
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Handbook of Research Methods and Applications in Empirical Finance

Edited by Adrian R. Bell, Chris Brooks and Marcel Prokopczuk

This impressive Handbook presents the quantitative techniques that are commonly employed in empirical finance research together with real-world, state-of-the-art research examples.
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Chapter 18: Quantifying time variation and asymmetry in measures of covariance risk: a simulation approach

Ólan T. Henry, Nilss Olekalns and Kalvinder K. Shields


It is well known that equity returns display volatility clustering (Mandelbrot, 1962). This implies that in periods of relatively high risk, the rational risk-averse investor will demand a relatively high expected return and be willing to pay more to hedge exposure to volatility. Similarly, there is evidence that equity volatility responds asymetrically to news; for example, Engle and Ng (1993) argue that bear markets are more volatile than bull markets, all else being equal. If this is the case, then the price of risk should display asymmetry. Braun et al. (1995), Engle and Cho (1999) and Brooks and Henry (2000) detect evidence of such asymmetric responses in various equity markets. In this chapter we present new methods based upon the variance impulse response function methodology of Shields et al. (2005) to detect and quantify the dynamic response to news of measures of undiversifiable risk and benefits to diversification. We demonstrate how these dynamic responses can be used to construct time profiles measuring the effects of news on the future behaviour of unobserved variables such as rates of expected return, conditional correlations, and measures of systematic risk and benefits to diversification. We develop metrics based upon these time profiles to investigate whether these unobserved variables respond asymmetrically in a statistically significant and economically important fashion to news.

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