Name
Abstract | ||
|---|---|---|
Option price data is often used to infer risk-neutral densities for future prices of an underlying asset. Given the prices
of a set of options on the same underlying asset with different strikes and maturities, we propose a nonparametric approach
for estimating risk-neutral densities associated with several maturities. Our method uses bicubic splines in order to achieve
the desired smoothness for the estimation and an optimization model to choose the spline functions that best fit the price
data. Semidefinite programming is employed to guarantee the nonnegativity of the densities. We illustrate the process using
synthetic option price data generated using log-normal and absolute diffusion processes as well as actual price data for options
on the S&P 500 index. We also used the risk-neutral densities that we computed to price exotic options and observed that this
approach generates prices that closely approximate the market prices of these options. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/s10287-010-0126-3 | Computational Management Science |
Keywords | DocType | Volume |
Quadratic Programming,Option Price,Implied Volatility,Average Relative Error,Strike Price | Journal | 8 |
Issue | ISSN | Citations |
4 | 1619-697X | 0 |
PageRank | References | Authors |
0.34 | 5 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| A. M. Monteiro | 1 | 0 | 0.34 |
| R. H. Tütüncü | 2 | 0 | 0.34 |
| luis n vicente | 3 | 176 | 11.24 |