We numerically solve systems of Black–Scholes formulas for implied volatility and implied risk-free rate of return. After using a seemingly unrelated regressions (SUR) model to obtain point estimates for implied volatility and implied risk-free rate, the options are re-priced using these...

We derive an estimator for Black-Scholes-Merton implied volatility that, when compared to the familiar Corrado & Miller [JBaF, 1996] estimator, has substantially higher approximation accuracy and extends over a wider region of moneyness.

We propose a new semi-parametric model for the implied volatility surface, which incorporates machine learning algorithms. Given a starting model, a tree-boosting algorithm sequentially minimizes the residuals of observed and estimated implied volatility. To overcome the poor predicting power of...

We model the dynamics of asset prices and associated derivatives by consideration of the dynamics of the conditional probability density process for the value of an asset at some specified time in the future. In the case where the asset is driven by Brownian motion, an associated "master...

A model-free methodology is used for the first time to estimate a daily volatility index (VIBEX-NEW) for the Spanish financial market.We use a public data set of daily option prices to compute this index and showthat daily changes in VIBEXNEW display a negative, tight contemporaneous...

A model-free methodology is used for the first time to estimate a daily volatility index (VIBEX-NEW) for the Spanish financial market.We use a public data set of daily option prices to compute this index and showthat daily changes in VIBEXNEW display a negative, tight contemporaneous...

This paper specifies and estimates an option price model using non-linear, Seemingly Unrelated Regression (SUR) technique that allows for the incorporation of cross equation correlations and other generalisations. Our results do suggest that this generalisation improves the efficiency of the...

This paper applies to the static hedge of barrier options a technique, mean-square hedging, designed to minimize the size of the hedging error when perfect replication is not possible. It introduces an extension of this technique which preserves the computational efficiency of mean-square...