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Oct 20

Fast and Accurate Long Stepping Simulation of the Heston Stochastic Volatility Model

Posted by abiao at 12:57 | Code » C++ | Comments(1) | Reads(8902)
Heston stochastic volatility model is widely used in both industry and academia, due to the correlation between stock process and volatility process, plus a non-negative square root volatility, simulation of Heston volatility doesn't sound easy & stable. Professor Mark Joshi has a recent working paper Fast and Accurate Long Stepping Simulation of the Heston Stochastic Volatility Model, as its title suggests: this paper aims to provide a better simulation scheme.

In this paper, we present three new discretization schemes for the Heston stochastic volatility model - two schemes for simulating the variance process and one scheme for simulating the integrated variance process conditional on the initial and the end-point of the variance process. Instead of using a short time-stepping approach to simulate the variance process and its integral, these new schemes evolve the Heston process accurately over long steps without the need to sample the intervening values. Hence, prices of financial derivatives can be evaluated rapidly using our new approaches.

heston stochastic volatility monte carlo simulation
looks brilliant indeed, interested readers shall download the C++ code and paper directly at http://www.markjoshi.com/downloads/index.htm

Heston is not stable.....I have been already sick of it!
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