توجه: محتویات این صفحه به صورت خودکار پردازش شده و مقاله‌های نویسندگانی با تشابه اسمی، همگی در بخش یکسان نمایش داده می‌شوند.
۱Solution of Optimal Control Problems by Modified State Parameterization
اطلاعات انتشار: کنفرانس بین المللی مدل سازی غیر خطی و بهینه سازی، سال
تعداد صفحات: ۷
In this paper a new parameterization is introduced by Boubaker polynomials, which can accurately represent state variable with only a few parameters.In fact, an efficient algorithm forsolving optimal control problems and the controlled linear and Duffing oscillator is presented. This algorithm converts these problems to a non–linear optimization problem. By this method, the control and state variables can be approximated as a function of time. Also, the numerical value of the performance index is obtained readily. Convergence of the algorithms is proved and someillustrative examples are presented to show the efficiency and reliability of the presented method<\div>

۲Solution of Stochastic Optimal Control Problems and it's Financial Applications
نویسنده(ها): ، ،
اطلاعات انتشار: کنفرانس بین المللی مدل سازی غیر خطی و بهینه سازی، سال
تعداد صفحات: ۷
Stochastic optimal control problems frequently occur in Economics and Finance. In stochastic optimal control problems with linear control, optimal strategy switches between two modes, a maximum and a minimum control mode The Hamilton–Jacobi–Bellman equation effectively breaks down into two differential equations. Which are linked at the threshold where it is optimal to switch. In this article we study problems that are linear in the control and illustrate A method to solve such problems Finally, we simulate a financial example.<\div>

۳American Options Pricing by Using Stochastic Optimal Control Problems
نویسنده(ها): ، ،
اطلاعات انتشار: سومین کنفرانس ریاضیات مالی و کاربردها، سال
تعداد صفحات: ۵
Stochastic optimal control problems frequently occur in Economics and Finance. Dynamicprogramming method represents the most known method for solving optimal control prob–lems analytically. As analytical solutions for problems of optimal control are not alwaysavailable, finding an approximate solution is at least the most logical way to solve them.In this paper, we present some of the basic ideas which are in current use for the solutionof the dynamic programming equations. Also, based on the Markov chain approximationtechniques, a numerical procedure is constructed for solution of stochastic optimal controlproblems. We focus on the approximation in value space method. And the Jacobi andGauss–Seidel relaxation (iterative) methods are discussed. These are fundamental iterativemethods which are used in value space approach. Finally, American options pricing arepresented as simplest control problem which is called optimal stopping problem.<\div>

۴A numerical method for portfolio selection based on Markov chain approximation
نویسنده(ها): ، ،
اطلاعات انتشار: سومین کنفرانس ریاضیات مالی و کاربردها، سال
تعداد صفحات: ۵
In this paper, A portfolio selection problem is approximated by a Markov chain which ismodulated by a continuous–time, finite–state, Markov chain. The main ingredient of theMarkov chain approximation is to approximate the wealth process and utility function oforiginal utility optimization problem by a controlled Markov chain. under the convergenceof the approximation scheme, Policy iteration methods as to obtain the optimal controls. Anumerical example is provided to illustrate the reability of the algorithm.<\div>

۵Introduction to Numerical Simulation of Stochastic Differential Equations by Using R Software and its FinantialApplication
نویسنده(ها): ، ،
اطلاعات انتشار: سومین کنفرانس ریاضیات مالی و کاربردها، سال
تعداد صفحات: ۴
Stochastic differential equation (SDE) models play a prominent role in a range of applicationareas, including biology, chemistry, economics, and finance. In this paper, we will introducenumerical methods for stochastic differential equations and simulate them with R saftware.<\div>
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