کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4609214 1338440 2006 24 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A central limit theorem and improved error bounds for a hybrid-Monte Carlo sequence with applications in computational finance
موضوعات مرتبط
مهندسی و علوم پایه ریاضیات آنالیز ریاضی
پیش نمایش صفحه اول مقاله
A central limit theorem and improved error bounds for a hybrid-Monte Carlo sequence with applications in computational finance
چکیده انگلیسی

In problems of moderate dimensions, the quasi-Monte Carlo method usually provides better estimates than the Monte Carlo method. However, as the dimension of the problem increases, the advantages of the quasi-Monte Carlo method diminish quickly. A remedy for this problem is to use hybrid sequences; sequences that combine pseudorandom and low-discrepancy vectors. In this paper we discuss a particular hybrid sequence called the mixed sequence. We will provide improved discrepancy bounds for this sequence and prove a central limit theorem for the corresponding estimator. We will also provide numerical results that compare the mixed sequence with the Monte Carlo and randomized quasi-Monte Carlo methods.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Complexity - Volume 22, Issue 4, August 2006, Pages 435-458