Multilevel Monte Carlo and its Applications in Financial Engineering

التفاصيل البيبلوغرافية
العنوان: Multilevel Monte Carlo and its Applications in Financial Engineering
المؤلفون: Sinha, Devang, Chakrabarty, Siddhartha P.
سنة النشر: 2022
المجموعة: Quantitative Finance
مصطلحات موضوعية: Quantitative Finance - Computational Finance
الوصف: In this article, we present a review of the recent developments on the topic of Multilevel Monte Carlo (MLMC) algorithm, in the paradigm of applications in financial engineering. We specifically focus on the recent studies conducted in two subareas, namely, option pricing and financial risk management. For the former, the discussion involves incorporation of the importance sampling algorithm, in conjunction with the MLMC estimator, thereby constructing a hybrid algorithm in order to achieve reduction for the overall variance of the estimator. In case of the latter, we discuss the studies carried out in order to construct an efficient algorithm in order to estimate the risk measures of Value-at-Risk (VaR) and Conditional Var (CVaR), in an efficient manner. In this regard, we briefly discuss the motivation and the construction of an adaptive sampling algorithm with an aim to efficiently estimate the nested expectation, which, in general is computationally expensive.
نوع الوثيقة: Working Paper
الوصول الحر: http://arxiv.org/abs/2209.14549Test
رقم الانضمام: edsarx.2209.14549
قاعدة البيانات: arXiv