Take Action

Home | Faculty & Research Overview | Research

Research Details

Parametric Inference and Dynamic State Recovery from Option Panels, Econometrica

Abstract

We develop a new parametric estimation procedure for option panels observed with error which relies on asymptotic approximations assuming an ever increasing set of observed option prices in the moneyness-maturity (cross-sectional) dimension, but with a fixed time span. We develop consistent estimators of the parameter vector and the dynamic realization of the state vector that governs the option price dynamics. The estimators converge stably to a mixed-Gaussian law and we develop feasible estimators for the limiting variance. We provide semi-parametric tests for the option price dynamics based on the distance between the spot volatility extracted from the options and the one obtained non-parametrically from high-frequency data on the underlying asset. We further construct new formal tests of the model fit for specific regions of the volatility surface and for the stability of the risk-neutral dynamics over a given period of time.

Type

Article

Author(s)

Torben Andersen, Nicola Fusari, Viktor Todorov

Date Published

2015

Citations

Andersen, Torben, Nicola Fusari, and Viktor Todorov. 2015. Parametric Inference and Dynamic State Recovery from Option Panels. Econometrica. 83(3): 1081-1145.

KELLOGG INSIGHT

Explore leading research and ideas

Find articles, podcast episodes, and videos that spark ideas in lifelong learners, and inspire those looking to advance in their careers.
learn more

COURSE CATALOG

Review Courses & Schedules

Access information about specific courses and their schedules by viewing the interactive course scheduler tool.
LEARN MORE

DEGREE PROGRAMS

Discover the path to your goals

Whether you choose our Full-Time, Part-Time or Executive MBA program, you’ll enjoy the same unparalleled education, exceptional faculty and distinctive culture.
learn more

Take Action