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Stochastic differential equations and comparison of financial models with levy process using Markov chain Monte Carlo ( MCMC ) simulation
| Content Provider | Semantic Scholar |
|---|---|
| Author | Vajargah, Kianoush Fathi |
| Copyright Year | 2015 |
| 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: BlackScholes 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. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://www.sciencepubco.com/index.php/IJASP/article/download/4066/1588 |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Arabic numeral 0 Black–Scholes model Doctor of Law Hidden variable theory JD - Java Decompiler Leucaena pulverulenta Markov chain Monte Carlo Monte Carlo method Sample Variance Simulation Stochastic process Time series ferrosoferric oxide |
| Content Type | Text |
| Resource Type | Article |
