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An Overview of the Determinants of Financial Volatility: An Explanation of Measuring Techniques

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  • Kevin Daly

Abstract

The majority of asset pricing theories relate expected returns on assets to their conditional variances and covariance’s. Since conditional variances and covariance’s are not observable, researchers have to estimate conditional second moments relying on models. An important concern is the accuracy of these models and how researchers may estimate them more accurately. In this paper, various measures of volatility have been examined ranging from time invariant to time variant measures. In the former case one of the simplest measures examined was the standard deviation. A weakness of this measure is the assumption that volatility is constant, this being due to the standard deviation of returns increasing with the square root of the length of the period. Empirical evidence, however, shows us that the behavior of asset returns in the real world changes randomly over time. This led us to an examination of time variant models for measuring volatility.

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  • Kevin Daly, 2011. "An Overview of the Determinants of Financial Volatility: An Explanation of Measuring Techniques," Modern Applied Science, Canadian Center of Science and Education, vol. 5(5), pages 1-46, October.
    • Handle: RePEc:ibn:masjnl:v:5:y:2011:i:5:p:46
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    References listed on IDEAS

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    Cited by:

    1. Hartwell, Christopher A., 2014. "The impact of institutional volatility on financial volatility in transition economies: a GARCH family approach," BOFIT Discussion Papers 6/2014, Bank of Finland Institute for Emerging Economies (BOFIT).

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    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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