کیانوش فتحی واجارگاه

کیانوش فتحی واجارگاه

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۱.

Optimization of estimates and comparison of their efficiency under stochastic methods and its application in financial models(مقاله علمی وزارت علوم)

کلید واژه ها: Stochastic Differential Equation random sequence Quasi-random sequence (Quasi) Monte Carlo simulation

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تعداد بازدید : 262 تعداد دانلود : 912
In this paper, first, the stochastic differential equations are introduced as well as the definition and basic theories about Monte Carlo and quasi-Monte Carlo and Sobel and Halton sequences are expressed. Indeed, we introduce and use simulations under these methods to compare the efficiency of the solutions, which the results show that the approximation of the resulting Sobel sequence is much better than other stochastic methods. The comparison of the efficiency of random and quasi-random methods, the geometric Brownian movement and the price index of Tehran stock (equal weight and weight-value) is studied. The results show that the quasi-Monte Carlo method is better than other methods.
۲.

Oil Price estimating Under Dynamic Economic Models Using Markov Chain Monte Carlo Simulation Approach(مقاله علمی وزارت علوم)

کلید واژه ها: Oil Prices Stochastic volatility Jump-Diffusion Process Markov chain Monte Carlo Simulation

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تعداد بازدید : 531 تعداد دانلود : 597
This study, attempts to estimate and compare four different models of jump-diffusion class combined with stochastic volatility that are based on stochastic differential equations, and their parameters latent variables are estimated by Markov chain Monte Carlo (MCMC) methods. In the Stochastic Volatility with Correlated Jumps (SVCJ) model, volatilities are scholastic, and the term jump is added to both scholastic prices and volatilities. The results of this study showed that this model is more efficient than the others are, as it provides a significantly better fit to the data, and therefore, corrects the shortcomings of the previous models and that it is closer to the actual market prices. Therefore, our estimating model under the Monte Carlo simulation allows an analysis on oil prices during certain times in the periods of tension and shock in the oil market

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