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Alan L. Lewis

Publications and source records attributed to Alan L. Lewis.

5 recordsLinked to original sources

Proof of non-convergence of the short-maturity expansion for the SABR model

We study the convergence properties of the short maturity expansion of option prices in the uncorrelated log-normal ($β=1$) SABR model. In this model the option time-value can be represented as an integral of the form $V(T) = \int_{0}^\infty e^{-\frac{u^2}{2T}} g(u) du$ with $g(u)$ a "payoff function" which is given by an integral over the McKean kernel $G(s,t)$. We study the analyticity properties of the function $g(u)$ in the complex $u$-plane and show that it is holomorphic in the strip $|\Im(u) |< π$. Using this result we show that the $T$-series expansion of $V(T)$ and implied volatility are asymptotic (non-convergent for any $T>0$). In a certain limit which can be defined either as the large volatility limit $σ_0\to \infty$ at fixed $ω=1$, or the small vol-of-vol limit $ω\to 0$ limit at fixed $ωσ_0$, the short maturity $T$-expansion for the implied volatility has a finite convergence radius $T_c = \frac{1.32}{ωσ_0}$.

q-fin.MF

Option-based Equity Risk Premiums

We construct the term structure of the (forward-looking, US market) equity risk premium from SPX option chains. The method is "model-light". Risk-neutral probability densities are estimated by fitting $N$-component Gaussian mixture models to option quotes, where $N$ is a small integer (here 4 or 5). These densities are transformed to their real-world equivalents by exponential tilting with a single parameter: the Coefficient of Relative Risk Aversion $κ$. From history, I estimate $κ= 3 \pm 0.5$. From the inferred real-world densities, the equity risk premium is readily calculated. Three term structures serve as examples.

q-fin.CP

A First Option Calibration of the GARCH Diffusion Model by a PDE Method

Time-series calibrations often suggest that the GARCH diffusion model could also be a suitable candidate for option (risk-neutral) calibration. But unlike the popular Heston model, it lacks a fast, semi-analytic solution for the pricing of vanilla options, perhaps the main reason why it is not used in this way. In this paper we show how an efficient finite difference-based PDE solver can effectively replace analytical solutions, enabling accurate option calibrations in less than a minute. The proposed pricing engine is shown to be robust under a wide range of model parameters and combines smoothly with black-box optimizers. We use this approach to produce a first PDE calibration of the GARCH diffusion model to SPX options and present some benchmark results for future reference.

q-fin.CP