Sequential Monte Carlo Methods for Option Pricing
نویسندگان
چکیده
منابع مشابه
Sequential Monte Carlo Methods for Option Pricing
In the following paper, we provide a review and development of sequential Monte Carlo (SMC) methods ([17, 18, 24]) for option pricing. SMC are a class of Monte Carlo-based algorithms, that are designed to approximate expectations w.r.t a sequence of related probability measures. These approaches have been used, successfully, for a wide class of applications in engineering, statistics and physic...
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The pricing of options is a very important problem encountered in nancial markets today. The famous Black-Scholes model provides explicit closed form solutions for the values of certain (European style) call and put options. But for many other options, either there are no closed form solutions, or if such closed form solutions exist, the formulas exhibiting them are complicated and diicult to e...
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The advantage of Monte Carlo simulations is attributed to the flexibility of their implementation. In spite of their prevalence in finance, we address their efficiency and accuracy in option pricing from the perspective of variance reduction and price convergence. We demonstrate that increasing the number of paths in simulations will increase computational efficiency. Moreover, using a t-test, ...
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Pricing financial options is amongst the most important and challenging problems in the modern financial industry. Except in the simplest cases, the prices of options do not have a simple closed form solution and efficient computational methods are needed to determine them. Monte Carlo methods have increasingly become a popular computational tool to price complex financial options, especially w...
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We propose nested sequential Monte Carlo (NSMC), a methodology to sample from sequences of probability distributions, even where the random variables are high-dimensional. NSMC generalises the SMC framework by requiring only approximate, properly weighted, samples from the SMC proposal distribution, while still resulting in a correct SMC algorithm. Furthermore, NSMC can in itself be used to pro...
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ژورنال
عنوان ژورنال: Stochastic Analysis and Applications
سال: 2011
ISSN: 0736-2994,1532-9356
DOI: 10.1080/07362994.2011.548993