Stochastic differential equations and comparison of financial models with levy process using Markov chain Monte Carlo (MCMC) simulation

  • Abstract
  • Keywords
  • References
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  • Abstract

    An available method of modeling and predicting the economic time series is the use of stochastic differential equations, which are often determined as jump-diffusion stochastic differential equations in financial markets and underlier economic dynamics. Besides the diffusion term that is a geometric Brownian model with Wiener random process, these equations contain a jump term that follows Poisson process and depends on the type of market. This study presented two different models based on a certain class of jump-diffusion stochastic differential equations with random fluctuations: Black- Scholes model and Merton model (1976), including jump-diffusion (JD) model, which were compared, and their parameters and hidden variables were evaluated using Markov chain Monte Carlo (MCMC) method.

  • Keywords

    Levy Process; Markov Chain Monte Carlo; Black- Scholes Model; Merton Model; Stochastic Differential Equations.

  • References

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Article ID: 4066
DOI: 10.14419/ijasp.v3i1.4066

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