Measurement of the volatility/covariance of financial-asset returns plays a central role in many issues in finance, e.g., risk and investment management, hedging strategies, forecasting. In connection with financial markets the word volatility is usually associated with the concepts of risk and opportunity, thus referring to a measure (as well as a feeling) of the movements and uncertainty in the markets. As a matter of fact, the constant-volatility assumption prescribed by the Black & Scholes model (Black and Scholes (1973)) does not account for some stylized facts such as variance heteroscedasticity, predictability, volatility smile, covariance between asset returns and volatility (the so-called leverage effect).

Fourier-Malliavin volatility estimation Theory and Practice

Mancino Maria Elvira;
2017

Abstract

Measurement of the volatility/covariance of financial-asset returns plays a central role in many issues in finance, e.g., risk and investment management, hedging strategies, forecasting. In connection with financial markets the word volatility is usually associated with the concepts of risk and opportunity, thus referring to a measure (as well as a feeling) of the movements and uncertainty in the markets. As a matter of fact, the constant-volatility assumption prescribed by the Black & Scholes model (Black and Scholes (1973)) does not account for some stylized facts such as variance heteroscedasticity, predictability, volatility smile, covariance between asset returns and volatility (the so-called leverage effect).
2017
Springer
978-3-319-50967-9
Nonparametric estimation Volatility Fourier analysis
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11384/79748
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