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A new method for solving of a backward stochastic differential equations by using a basic functions

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In this paper, we purpose a method for numerical solution of a backward stochastic differential equations driven by standard Brownian motion  as follows: { dX X(T (s) = ) =p. f(X(s))ds + g(X(s))dB(s), s ∈ [0, T), The method is...

A numerical method for portfolio selection based on Markov chain approximation

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In this paper, A portfolio selection problem is approximated by a Markov chain which is modulated by a continuous-time, finite-state, Markov chain. The main ingredient of the Markov chain approximation is to approximate the wealth process and utility function of...

A Survey on exact analytical and numerical solutions of some S.D.E.s based on martingale approach and changing variable method

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In this paper, we decide to represent analytical and numerical solutions for stochastic differential equations, specially reputed and famous  equations in pricing and investment rate odels. By making martingale process from an arbitrary process in L2(R) space, we infer equations...

American Options Pricing by Using Stochastic Optimal Control Problems

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Stochastic optimal control problems frequently occur in Economics and Finance. Dynamic programming method represents the most known method for solving optimal control problems analytically. As analytical solutions for problems of optimal control are not always available, finding an approximate solution...

An approximate method to option pricing in the Heston model

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The Heston model is one of the most popular stochastic volatility models for derivatives pricing, and it is a mathematical model describing the evolution of the volatility of an underlying asset. The model proposed by Heston(1993), takes into account non-lognormal...

An Efficient Numerical Approximation of the American Option Pricing Problem

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This paper deals with developing an efficient numerical approximation of the American option pricing problem as a free boundary problem. The recently introduced artificial boundary conditions of Han and Wu  are also employed. In order to solve the problem, a...

An introduction to descriptive statistics: A review and practical guide

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This paper, the first of two, demonstrates why it is necessary for radiographers to understand basic statistical concepts both to assimilate the work of others and also in their own research work. As the emphasis on  evidence-based practice increases, it...

An introduction to inferential statistics: A review and practical guide

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Building on the first part of this series regarding descriptive statistics, this paper demonstrates why it is advantageous for radiographers to understand the role of inferential statistics in deducing conclusions from a sample and their application to a wider population....

An Introduction to Variable and Feature Selection

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An Introduction to Variable and Feature Selection

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Variable and feature selection have become the focus of much research in areas of application for which datasets with tens or hundreds of thousands of variables are available. These areas include text processing of internet documents, gene expression array analysis,...
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