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This paper presents a novel method for estimating parameters of financial models with jump diffusions. It is a Particle Filter based Maximum Likelihood Estimation process, which uses particle streams to enable efficient evaluation of constraints and weights. We also provide a CPU-FPGA collaborative design for parameter estimation of Stochastic Volatility with Correlated and Contemporaneous Jumps model...
This paper uses information on VIX to improve the empirical performance of GARCH models for pricing options on the S&P 500. In pricing multiple cross-sections of options, the models’ performance can clearly be improved by extracting daily spot volatilities from the series of VIX rather than by linking spot volatility with different dates by using the series of the underlying’s returns. Moreover,...
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