Measure distorted arrival rate risks and their rewards

• Main Author: Dilip B. Madan
• Format: Article
• Language: English
• Published: SpringerOpen 2017-06-01
• Series: Probability, Uncertainty and Quantitative Risk
• Subjects: Variance Gamma; Hunt process; Markov chain approximation; Matrix exponentiation; Momentum function; Measure distortion
• Online Access: http://link.springer.com/article/10.1186/s41546-017-0021-8

Abstract Risks embedded in asset price dynamics are taken to be accumulations of surprise jumps. A Markov pure jump model is formulated on making variance gamma parameters deterministic functions of the price level. Estimation is done by matrix exponentiation of the transition rate matrix for a continuous time finite state Markov chain approximation. The motion is decomposed into a space dependent drift and a space dependent martingale component. Though there is some local mean reversion in the drift, space dependence of the martingale component renders the dynamics to be of the momentum type. Local risk is measured using market calibrated measure distortions that introduce risk charges into the lower and upper prices of two price economies. These risks are compensated by the exponential variation of space dependent arrival rates. Estimations are conducted for the S&P 500 index (S P X), the exchange traded fund for the financial sector (X L F), J. P. Morgan stock prices (J P M), the ratio of JPM to XLF, and the ratio of XLF to SPX.