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Optimum Weighting For The Least Squares Monte Carlo Approach To American Options Under The Cev Model
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Book Synopsis Optimum Weighting for the Least Squares Monte Carlo Approach to American Options Under the CEV Model by : Jason Barden
Download or read book Optimum Weighting for the Least Squares Monte Carlo Approach to American Options Under the CEV Model written by Jason Barden and published by . This book was released on 2015 with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper we propose the optimum weighting scheme for pricing American options under a local volatility model. American options are priced under the constant elasticity of variance volatility model using Monte Carlo simulation. The residuals obtained from regression were heteroscedastic. For spot prices deep out-of-the-money, alternate weighting methods were found to provide improved accuracy over ordinary least squares. For spot prices deep in-the-money, the residuals were also heteroscedastic, however, the number of residuals present in the regression dominated and ordinary least squares provided improved accuracy. Generalised least squares was found to proved the most accurate overall weighting method.
Book Synopsis Approximating the Optimal Exercise Boundary for American Options via Least-Squares Monte Carlo by : Qiang Liu
Download or read book Approximating the Optimal Exercise Boundary for American Options via Least-Squares Monte Carlo written by Qiang Liu and published by . This book was released on 2015 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt: The least-squares Monte Carlo method of Longstaff-Schwartz is utilized to construct the optimal exercise boundary (OXB) of an American put option when the underlying follows a geometric Brownian motion (GBM). The optimal exercise price at each time step is obtained by solving numerically the equation of the exercising boundary condition. The set of such exercise prices, along with their ldquo;standard deviations,rdquo; is then fitted to a smooth, monotonic model of a sum of three exponential functions to approximate the OXB, which turns out to be very close to the exact solution of the boundary. The approach can be efficiently implemented and readily computed in practice, and should be applicable to cases when the underlying price process is not GBM.
Book Synopsis Approving Least Squares Monte Carlo Approach for Valuing American Options by : Lei Zhang
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:
Book Synopsis Monte Carlo Methods for American Option Pricing by : Alberto Barola
Download or read book Monte Carlo Methods for American Option Pricing written by Alberto Barola and published by LAP Lambert Academic Publishing. This book was released on 2014-05-21 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Monte Carlo approach has proved to be a valuable and flexible computational tool in modern finance. A number of Monte Carlo simulation-based methods have been developed within the past years to address the American option pricing problem. The aim of this book is to present and analyze three famous simulation algorithms for pricing American style derivatives: the stochastic tree; the stochastic mesh and the least squares method (LSM). The author first presents the mathematical descriptions underlying these numerical methods. Then the selected algorithms are tested on a common set of problems in order to assess the strengths and weaknesses of each approach as a function of the problem characteristics. The results are compared and discussed on the basis of estimates precision and computation time. Overall the simulation framework seems to work considerably well in valuing American style derivative securities. When multi-dimensional problems are considered, simulation based methods seem to be the best solution to estimate prices since the general numerical procedures of finite difference and binomial trees become impractical in these specific situations.
Book Synopsis Valuing American Options by Simulation by : Laura Hass Thomsen
Download or read book Valuing American Options by Simulation written by Laura Hass Thomsen and published by . This book was released on 2015 with total page 97 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Numerical study to least-squares monte carlo method for pricing american options by : 黃惠君
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:
Book Synopsis Assessing the Least Squares Monte-Carlo Approach to American Option Valuation by :
Download or read book Assessing the Least Squares Monte-Carlo Approach to American Option Valuation written by and published by . This book was released on 2001 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Valuing American Asian Options with Least Squares Monte Carlo and Low Discrepancy Sequences by : Andries Jacobus Van Niekerk
Download or read book Valuing American Asian Options with Least Squares Monte Carlo and Low Discrepancy Sequences written by Andries Jacobus Van Niekerk and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: There exists no closed form approximation for arithmetically calculated Asian options, but research has shown that closed form approximations are possible for Geometrically calculated Asian options. The aim of this dissertation is to effectively price American Asian options with the least squares Monte Carlo approach (Longstaff & Schwartz, 2001), applying Low discrepancy sequences and variance reduction techniques. We evaluate how these techniques affect the pricing of American options and American Asian options in terms of accuracy, computational efficiency, and computational time used to implement these techniques. We consider the effect of, Laguerre-, weighted Laguerre-, Hermite-, and Monomial-basis functions on the Longstaff and Schwartz (2001) model. We briefly investigate GPU optimization of the Longstaff and Schwartz algorithm within Matlab. We also graph the associated implied and Local volatility surfaces of the American Asian options to assist in the practical applicability of these options.
Book Synopsis Sequential Monte Carlo Pricing of American-Style Options Under Stochastic Volatility Models by : Bhojnarine Rambharat
Download or read book Sequential Monte Carlo Pricing of American-Style Options Under Stochastic Volatility Models written by Bhojnarine Rambharat and published by . This book was released on 2013 with total page 43 pages. Available in PDF, EPUB and Kindle. Book excerpt: We introduce a new method to price American-style options on underlying investments governed by stochastic volatility (SV) models. The method does not require the volatility process to be observed. Instead, it exploits the fact that the optimal decision functions in the corresponding dynamic programming problem can be expressed as functions of conditional distributions of volatility, given observed data. By constructing statistics summarizing information about these conditional distributions, one can obtain high quality approximate solutions. Although the required conditional distributions are in general intractable, they can be arbitrarily precisely approximated using sequential Monte Carlo schemes. The drawback, as with many Monte Carlo schemes, is potentially heavy computational demand. We present two variants of the algorithm, one closely related to the well-known least-squares Monte Carlo algorithm of Longstaff and Schwartz (2001), and the other solving the same problem using a “brute force” gridding approach. We estimate an illustrative SV model using Markov chain Monte Carlo (MCMC) methods for three equities. We also demonstrate the use of our algorithm by estimating posterior distributions of the market price of volatility risk for each of the three equities.
Book Synopsis Convergence of the Least Squares Monte-Carlo Approach to American Option Valuation by :
Download or read book Convergence of the Least Squares Monte-Carlo Approach to American Option Valuation written by and published by . This book was released on 2002 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis American Option Pricing Under Stochastic Volatility by : Suchandan Guha
Download or read book American Option Pricing Under Stochastic Volatility written by Suchandan Guha and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: ABSTRACT: We developed two new numerical techniques to price American options when the underlying follows a bivariate process. The first technique exploits the semi-martingale representation of an American option price together with a coarse approximation of its early exercise surface that is based on an efficient implementation of the least-squares Monte Carlo method. The second technique exploits recent results in the efficient pricing of American options under constant volatility. Extensive numerical evaluations show these methods yield very accurate prices in a computationally efficient manner with the latter significantly faster than the former. However, the flexibility of the first method allows for its extension to a much larger class of optimal stopping problems than addressed in this paper.
Book Synopsis Least-Squares Monte Carlo and Quasi Monte Carlo Method in Pricing American Put Options Using Matlab by : Phuc Phan
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.
Book Synopsis The Optimal Exercising Problem from American Options by :
Download or read book The Optimal Exercising Problem from American Options written by and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The fast advancement in computer technologies in the recent years has made the use of simulation to estimate stock/equity performances and pricing possible; however, determining the optimal exercise time and prices of American options using Monte-Carlo simulation is still a computationally challenging task due to the involved computer memory and computational complexity requirements. At each time step, the investor must decide whether to exercise the option to get the immediate payoff, or hold on to the option until a later time. Traditionally, the stock options are simulated using Monte-Carlo methods and all stock prices along the path are stored, and then the optimal exercise time is determined starting at the final time period and continuing backward in time. Also, as the number of paths simulated increases, the number of simultaneous equations that need to be solved at each time step grow proportionally. Currently, two theoretical methods have emerged in determining the optimal exercise problem. The first method uses the concept of least-squares approach in linear regression to estimate the value of continuing to hold on to the option via a set of randomly generated future stock prices. Then, the value of continuing can be compared to the payoff at current time from exercising the option and a decision can be reached, which gives the investor a higher value. The second method uses the finite difference approach to establish an exercise boundary for the American option via an artificially generated mesh on both possible stock prices and decision times. Then, the stock price is simulated and the method checks to see if it is inside the exercise boundary. In this research, these two solution approaches are evaluated and compared using discrete event simulation. This allows complex methods to be simulated with minimal coding efforts. Finally, the results from each method are compared. Although a more conservative method cannot be determined, the least-squares method is faster, more concise, easier to implement, and requires less memory than the mesh method. The motivation for this research stems from interest in simulating and evaluating complicated solution methods to the optimal exercise problem, yet requiring little programming effort to produce accurate and efficient estimation results.
Book Synopsis The Cost of Accuracy in the Least Squares Monte Carlo Approach by : Gilles B. Desvilles
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.
Book Synopsis Valuing Bermuda-Asian Options by Least Squares Monte Carlo Simulation by :
Download or read book Valuing Bermuda-Asian Options by Least Squares Monte Carlo Simulation written by and published by . This book was released on 2007 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Pricing American Options by Canonical Least-Squares Monte Carlo by : Qiang Liu
Download or read book Pricing American Options by Canonical Least-Squares Monte Carlo written by Qiang Liu and published by . This book was released on 2008 with total page 9 pages. Available in PDF, EPUB and Kindle. Book excerpt: Options pricing and hedging under canonical valuation have recently been demonstrated to be quite effective, but unfortunately are only applicable to European options. In this paper, a variation of canonical valuation called canonical least-squares Monte Carlo is proposed to price American options, which proceeds in three stages. First, given a set of historical gross returns (or price ratios) of the underlying for a chosen time interval, a discrete risk-neutral distribution is obtained via the canonical approach. Second, from this canonical distribution independent random samples of gross returns are taken to simulate future price paths for the underlying. Third, to those paths the least-squares Monte Carlo method is then applied to compute a price for an American option. Numerical results obtained from using simulated gross returns under geometric Brownian motion (GBM) show that this new approach yields reasonably accurate prices for American put options and can be utilized as an alternative to pricing American options, whether the underlying follows GBM or not.
Book Synopsis Pricing American Options - Aspects of Computation by :
Download or read book Pricing American Options - Aspects of Computation written by and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
