Download or read book Apply the Least Squares Monte Carlo Approach to Extremely Complex Options A Building Block Methodology written by and published by . This book was released on 2006 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Approving Least Squares Monte Carlo Approach for Valuing American Options written by Lei Zhang and published by . This book was released on 2004 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Numerical study to least squares monte carlo method for pricing american options written by 黃惠君 and published by . This book was released on 2003 with total page 102 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Real Options Valuation written by Andrea Gamba and published by . This book was released on 2019 with total page 71 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper provides a numerical approach based on a Monte Carlo simulation for valuing dynamic capital budgeting problems with many embedded real options dependent on numerous state variables. We propose a way of decomposing a complex capital budgeting problem with many options into a set of simple options, suitably accounting for interaction and interdependence among them. The decomposition approach is numerically implemented using an extension of the Least Squares Monte Carlo algorithm, presented by Longstaff and Schwartz (2001) applied to our multi-option setting. We also provide a number of applications of our approach to well-known real options models and real life capital budgeting problems. Moreover, we present a set of numerical experiments to provide evidence for the accuracy of the proposed methodology.
Download or read book Least Squares Monte Carlo and Quasi Monte Carlo Method in Pricing American Put Options Using Matlab written by Phuc Phan and published by . This book was released on 2016 with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this report, we evaluate the use of the Least Squares Monte Carlo (LSM) method, which was proposed by Longstaff and Schwartz in 2001. The holder of an American option has the right to exercise the option anytime, which makes the option much more difficult to price compared to a European style option. LSM is a simple and powerful method to price American style options and utilizes the use of least squares to estimate the conditional expected payoff to the option holder from continuation value. I provide a simple version of the LSM algorithm using second degree polynomials as basis functions with working code in Matlab to price American put option. I illustrate how the model is affected when input parameter such as risk free interest rate, volatility, underlying stock price, time to maturity are perturbed. After that, I construct the quasi Monte Carlo version of the Least Square algorithm by using Halton sequence and compare the performance of both quasi Monte Carlo and Monte Carlo algorithm.
Download or read book The Cost of Accuracy in the Least Squares Monte Carlo Approach written by Gilles B. Desvilles and published by . This book was released on 2011 with total page 14 pages. Available in PDF, EPUB and Kindle. Book excerpt: This article follows in the footsteps of Longstaff and Schwartz' seminal article about the use of regressions to model expectations in the valuation of American options with Monte Carlo simulation. The article repeats the original American put pricing in order to check for estimation accuracy and computation speed.In addition the article investigates the use of the control variate technique in order to accelerate the Least Squares Monte Carlo simulation, and implements a way to get the delta sensitivity without much raising the response time. However the results underline what is believed to be the main impediment of the approach: the cost of accuracy. Performed in dimension one on a standard computer the simulations lead to conclude that pricing an option agrave; la Longstaff Schwartz is not advised when the option is simple enough to be valued with a recombining binomial tree. Indeed the response times of the binomial pricing are incomparably shorter. Moreover the standard error proposed by the method under study is not reliable both in theory and in practice. There remains a mere conjecture according to which when increasing significantly the number of trajectories then convergence to the true price is reached and the estimated standard error is negligible. But, due to the involved pathwise regressions, such an increase would lengthen considerably the response time.Finally hope comes from computer improvements, especially in the memory field. In the least resource-consuming cases running the simulation with much more trajectories on a recent computer ends up yielding the true prices with no surrounding uncertainty and in a reasonable time. Hence, for similar pricings, one can expect to rely on the estimated standard error to tell when the simulation has converged.
Download or read book Comparison of Least Squares Monte Carlo Methods with Applications to Energy Real Options written by Selvaprabu Nadarajah and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Least squares Monte Carlo (LSM) is a state-of-the-art approximate dynamic programming approach used in financial engineering and real options to value and manage options with early or multiple exercise opportunities. It is also applicable to capacity investment and inventory/production management problems with demand/supply forecast updates arising in operations and hydropower-reservoir management. LSM has two variants, referred to as regress-now/later (LSMN/L), which compute continuation/value function approximations (C/VFAs). We provide novel numerical evidence for the relative performance of these methods applied to energy swing and storage options, two typical real options, using a common price evolution model. LSMN/L estimate C/VFAs that yield equally accurate (near optimal) and precise lower and dual (upper) bounds on the value of these real options. Estimating the LSMN/L C/VFAs and their associated lower bounds takes similar computational effort. In contrast, the estimation of a dual bound using the LSML VFA instead of the LSMN CFA takes seconds rather than minutes or hours. This finding suggests the use of LSML in lieu of LSMN when estimating dual bounds on the value of early or multiple exercise options, as well as of related capacity investment and inventory/production policies.
Download or read book Least Squares Monte Carlo GARCH Methods for American Options written by Lars Stentoft and published by . This book was released on 2004 with total page 169 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Least Squares Monte Carlo and Approximate Linear Programming written by Selvaprabu Nadarajah and published by . This book was released on 2018 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt: Least squares Monte Carlo (LSM) is an approximate dynamic programming (ADP) technique commonly used for the valuation of high dimensional financial and real options, but has broader applicability. It is known that the regress-later version of this method is an approximate linear programming (ALP) relaxation that implicitly provides a potential solution to a familiar ALP deficiency. Focusing on a generic finite horizon Markov decision process, we provide both theoretical and numerical backing for the usefulness of this solution, respectively using a worst-case error bound analysis and a numerical study dealing with merchant ethanol production, an energy real option application, based on an ALP heuristic that we propose. When both methodologies are applicable, our research supports the use of regress-later LSM rather than this ALP technique to approximately solve intractable Markov decision processes. Our numerical findings motivate additional research to obtain even better methods than the regress-later version of LSM.
Download or read book On Improving the Least Squares Monte Carlo Option Valuation Method written by Nelson Areal and published by . This book was released on 2018 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper studies various possible approaches to improving the least squares Monte Carlo option valuation method. We test different regression algorithms and suggest a variation to estimating the option continuation value, which can reduce the execution time of the algorithm by one third. We test the choice of varying polynomial families with different number of basis functions. We compare several variance reduction techniques, and find that using low discrepancy sequences can improve the accuracy up to four times. We also extend our analysis to compound and mutually exclusive options. For the latter, we propose an improved algorithm which is faster and more accurate.
Download or read book Application of the Least Squares Monte Carlo Technique to the Valuation of Gas Storage Assets and Swing Options written by Jim Redington and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Monte Carlo Least Squares Applied to Swing Options written by Michael Fischbach and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Operating a Swing Option on Today s Gas Markets written by Marc Hanfeld and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We investigate, if it pays off for a company to invest into complex swing option algorithms. We first introduce least squares Monte Carlo as a complex valuation algorithm and explain in detail how it works. Using a simulation study and two backtest scenarios we compare the output of this method with a simple myopic approach, and evaluate the results also from a business point of view. We find that myopic operation performs fairly well, but given a certain contract size and a certain contract flexibility, LSMC clearly prevails.
Download or read book Valuation of real options through the least square monte carlo approach written by and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: O presente trabalho tem como objetivo testar empiricamente a eficiência e a aplicabilidade do método dos mínimos quadrados de Monte Carlo (LSM) na avaliação de projetos envolvendo opções reais. Inicialmente, o método passoupor uma série de testes de sensibilidade para validação do mesmo. Em seguida, alguns exemplos de projetos de exploração e produção (E & P) de petróleo com opções reais foram elaborados, e seus valores determinados através do LSM. Estes resultados foram comparados aos resultados obtidos com o modelo binomial que, devido a sua simplicidade e ampla utilização, foi escolhido comobenchmark para analisar a eficiência do método LSM. Devido às semelhanças entre oportunidades de investimento em ativos financeiros e reais, muitos estudos são realizados no sentido de adaptar instrumentos financeiros para a avaliação econômica de projetos. Muitas pesquisas sobre opções reais foram desenvolvidas em exploração de recursosnaturais, em especial de E & P de petróleo. Isso ocorre devido ao porte dos investimentos que são realizados neste setor e as suas características peculiares: o mercado de petróleo é bem desenvolvido (presença de mercado futuro, instrumentos de proteção financeira, derivativos etc); os investimentos ocorrem num ambiente de incertezas econômicas e / ou técnicas; os projetos demandam uma série de flexibilidades gerenciais (prazos alternativos paraexecução dos investimentos, possibilidade de mudanças na escala do projeto, entre outras). Tais características fazem com que seja necessária uma avaliação mais cautelosa e criteriosa destes ativos reais. Uma nova ferramentadesenvolvida neste sentido é o método LSM, que consiste na avaliação de opções americanas através de simulações e de regressões simples.
Download or read book Robust Monte Carlo Methods for Light Transport Simulation written by Eric Veach and published by . This book was released on 1998 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Stanford Bulletin written by and published by . This book was released on 2002 with total page 716 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Energy Research Abstracts written by and published by . This book was released on 1990 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt:
