Modelling the implied volatility surface: Does market efficiency matter?

Cassese, Gianluca; Guidolin, Massimo

doi:10.1016/j.irfa.2005.10.003

Cited by 12 publications

(2 citation statements)

References 40 publications

(63 reference statements)

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“…Since the implied volatility provides an unbiased and efficient forecast of future market, capturing the volatility process is a main approach for value-at-risk estimation. Hence, the implied volatility models in Section 2 can be used for computing value-at-risk portfolios, which include assets whose payoffs/returns are functions of the S&P 500 index or Nikkei 225 Index (Cassese & Guidolin, 2003), although it is not www.ccsenet.org/ijsp…”

Section: Further Applicationsmentioning

confidence: 99%

See 1 more Smart Citation

Stochastic Modeling and Estimation of Market Volatilities with Applications in Financial Forecasting

Zheng

Xie

2012

IJSP

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This paper aims to provide a framework for modeling and estimating the implied volatilities of stock prices using stochastic processes. The CIR (Cox-Ingersoll-Ross) model is proposed to capture the mean reversion characteristic as shown in the movement of the daily implied volatilities of the S&P 500 Index and Nikkei 225 Index. The maximum likelihood procedure is applied to estimate the parameters appearing in the model, where both analytical and approximation techniques are sought to handle the difficulties arising from the corresponding optimization problem. The procedure is validated with varying sampling methods by setting different time horizons and observation intervals. Results from numerical experiments show that the stochastic volatility model proposed in this paper functions well in both the US and Japan markets. As one of the applications, our approach is tested to be effective in detecting jumps in likelihood ratios, hence useful for forecasting stock market shocks and crisis.

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Section: Further Applicationsmentioning

confidence: 99%

“…In Cont and Fontseca (2002), a contrast study focusing on out of money options is reported using S&P500 index and FTSE100 index. Cassese and Guidolin (2003) studies whether the implied volatility is a function of time to maturity, moneyness, or the interaction between the two with data of the DOTM options of MIB30 index on Italian market.…”

Section: Introductionmentioning

confidence: 99%

Stochastic Modeling and Estimation of Market Volatilities with Applications in Financial Forecasting

Zheng

Xie

2012

IJSP

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Pricing commodity futures and determining risk premia in a three factor model with stochastic volatility: the case of Brent crude oil

et al. 2021

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In this paper we introduce a three factor model to price commodity futures contracts. This model allows both the spot price volatility and convenience yield to be stochastic, nevertheless futures prices can be obtained conveniently in closed form. Further, we use Brent crude oil futures prices to calibrate the model using the extended Kalman filter. In comparison to the benchmark model for commodity futures pricing, the Schwartz two-factor model, our three factor model shows a superior fit for contracts that have longer maturities. We further assess risk premia in Brent crude oil through the two models and observe that the Schwartz two-factor model over-predicts risk premia in comparison to the new model.

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Semi-parametric forecasts of the implied volatility surface using regression trees

Audrino

Colangelo

2009

Stat Comput

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We present a new semi-parametric model for the prediction of implied volatility surfaces that can be estimated using machine learning algorithms. Given a reasonable starting model, a boosting algorithm based on regression trees sequentially minimizes generalized residuals computed as differences between observed and estimated implied volatilities. To overcome the poor predictive power of existing models, we include a grid in the region of interest, and implement a cross-validation strategy to find an optimal stopping value for the boosting procedure. Back testing the out-of-sample performance on a large data set of implied volatilities from S&P 500 options, we provide empirical evidence of the strong predictive power of our model.

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Modelling the implied volatility surface: Does market efficiency matter?

Cited by 12 publications

References 40 publications

Stochastic Modeling and Estimation of Market Volatilities with Applications in Financial Forecasting

Stochastic Modeling and Estimation of Market Volatilities with Applications in Financial Forecasting

Pricing commodity futures and determining risk premia in a three factor model with stochastic volatility: the case of Brent crude oil

Semi-parametric forecasts of the implied volatility surface using regression trees

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