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Mastering R for Quantitative Finance by Edina Berlinger, Ferenc Illés, Milán Badics, Ádám Banai, Gergely Daróczi, Barbara Dömötör, Gergely Gabler, Dániel Havran, Péter Juhász, István Margitai, Balázs Márkus, Péter Medvegyev, Julia Molnár, Balázs Árpád Szűcs, Ágnes Tuza, Tamás Vadász, Kata Váradi, Ágnes Vidovics-Dancs

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Volatility modeling

It is a well-known and commonly accepted stylized fact in empirical finance that the volatility of financial time series varies over time. However, the non-observable nature of volatility makes the measurement and forecasting a challenging exercise. Usually, varying volatility models are motivated by three empirical observations:

  • Volatility clustering: This refers to the empirical observation that calm periods are usually followed by calm periods while turbulent periods by turbulent periods in the financial markets.
  • Non-normality of asset returns: Empirical analysis has shown that asset returns tend to have fat tails relative to the normal distribution.
  • Leverage effect: This leads to an observation that volatility tends to react ...

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