A generalization of the Barone‐Adesi and Whaley approach for the analytic approximation of American options

Guo, Jia-Hau; Hung, Mao Wei; So, Leh Chyan

doi:10.1002/fut.20361

Cited by 3 publications

(21 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our numerical results provide a comparison of our proposed model, the LSMC method, and the quadratic approximation scheme proposed by Guo et al (2009) for the stochastic volatility models with jumps. The parameters reported in Bakshi and Cao (2003) and Guo et al (2009) are used to compute the numerical results. The least-squares Monte Carlo simulation is based on 1,000,000 (500,000 plus 500,000 antithetic) paths for the stock price, using 24 exercise points per year.…”

Section: Numerical Results and Comparisonsmentioning

confidence: 99%

“…The accelerated recursive integration method, the LSMC method, and the quadratic approximation provided by Guo et al (2009) are represented by Recursive American, LSMC American, and BAW American, respectively. The standard errors of the simulation estimates (s.e.)…”

Section: Numerical Results and Comparisonsmentioning

confidence: 99%

“…The parameters used are adopted from Table II of Guo et al (2009) to compute values of American options. As shown, the values of the American options from our proposed method are close to those obtained from the LSMC method.…”

Section: Numerical Results and Comparisonsmentioning

confidence: 99%

“…One stream of the American option pricing literature 2 is to utilize the quadratic approximation scheme for pricing American option values, see e.g., Barone-Adesi and Whaley (1987), Ju and Zhong (1999), Chang, Kang, Kim, and Kim (2007), and Guo, Hung, and So (2009). One stream of the American option pricing literature 2 is to utilize the quadratic approximation scheme for pricing American option values, see e.g., Barone-Adesi and Whaley (1987), Ju and Zhong (1999), Chang, Kang, Kim, and Kim (2007), and Guo, Hung, and So (2009).…”

Section: Introductionmentioning

confidence: 99%

“…Stochastic volatility models with double jumps proposed by Duffie, Pan, and Singleton (2000) and Guo et al (2009) are used as examples to highlight the generalization of the recursive integration method, followed by a comparison with the least-squares Monte Carlo simulation method proposed by Longstaff and Schwartz (2001) and the quadratic approximation method proposed by Guo et al (2009). Several stochastic volatility models with double jumps have been widely introduced in the literature.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

A Generalization of the Recursive Integration Method for the Analytic Valuation of American Options

Chang

Guo

Hung

2015

Journal of Futures Markets

Self Cite

View full text Add to dashboard Cite

This article provides a general accelerated recursive integration method for pricing American options based on stochastic volatility and double jump processes. Our proposed model is a generalization of the recursive integral representation method. American option prices can be evaluated by the sum of a corresponding European option price and an early exercise premium integral. Numerical results show that our proposed method is efficient and accuracy in pricing American options with stochastic volatility and double jump processes. © 2015 Wiley Periodicals, Inc. Jrl Fut Mark 36:887–901, 2016

show abstract

Section: Numerical Results and Comparisonsmentioning

confidence: 99%

Section: Numerical Results and Comparisonsmentioning

confidence: 99%

Section: Numerical Results and Comparisonsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A Generalization of the Recursive Integration Method for the Analytic Valuation of American Options

Chang

Guo

Hung

2015

Journal of Futures Markets

Self Cite

View full text Add to dashboard Cite

show abstract

A Forward Monte Carlo Method for American Options Pricing

Miao

Lee

2012

Journal of Futures Markets

View full text Add to dashboard Cite

This study proposes a forward Monte Carlo method for the pricing of American options. The main advantage of this method is that it does not use backward induction as required by other methods. Instead, the proposed approach relies on a wise determination about whether a simulated stock price has entered the exercise region. The validity of the proposed method is supported by the mathematical proofs for the vanilla cases. With some adaption, it is shown that this forward method can be extended to price other American style options such as chooser and exchange options. This study demonstrates the effectiveness of the proposed approach using a series of numerical examples, revealing significant improvements in numerical efficiency and accuracy in contrast with the standard regressionbased method of Longstaff and Schwartz (2001). C 2012 Wiley Periodicals, Inc. Jrl Fut MarkWe are grateful for the helpful comments and suggestions from Bob Webb (Editor) and an anonymous referee.Due to the lack of analytic solutions to American options prices, researchers have developed a number of methods for these pricing problems. Broadie and Detemple (2004) provided an excellent review summarizing the existing methods for the pricing of American options. Roughly speaking, these approaches can be separated into two main categories: the analytical approximation and the numerical methods. The former is dated back to Barone-Adesi and Whaley's (1987) quadratic approximation, which is regarded as the most representative work of its kind. Many subsequent studies extended their work to consider more complicated options or models, such as the recent examples of Chang, Kang, Kim, and Kim (2007) and Guo, Hung, and So (2009). On the other hand, Monte Carlo simulation is considered to be the most powerful numerical techniques for the valuation of American options. Unlike other methods (e.g., finite difference), the Monte Carlo method has higher flexibility, wider applicability to various products, and is convergent to the true values. Moreover, it is also less sensitive to the problem dimension and therefore better suited to pricing problems involving multiple assets.Using Monte Carlo methods for option pricing dates back to Boyle (1977) for European options. Earlier applications of the Monte Carlo to American option pricing include Tilley's (1993) bundling algorithm, Barraquant and Martineau's (1995) stratified state aggregation algorithm, Broadie and Glasserman's (1997) stochastic tree based algorithm, Longstaff and Schwartz's (2001) regression-based algorithm. Boyle, Broadie, and Glasserman (1997) and Areal, Rodrigues, and Armada (2008) provide a comprehensive review of these methods. The Longstaff and Schwartz's method (also known as the least squares method [LSM]) is perhaps the most popular and promising one of these methods. Many researchers have adopted, modified, and extended this method over the years, including Liu (2010). The main idea of LSM is to estimate the continuation value through a least square regression on future simulated s...

show abstract

On Extensions of the Barone-Adesi & Whaley Method to Price American-Type Options

Mathys

2019

SSRN Journal

View full text Add to dashboard Cite

A generalization of the Barone‐Adesi and Whaley approach for the analytic approximation of American options

Cited by 3 publications

References 11 publications

A Generalization of the Recursive Integration Method for the Analytic Valuation of American Options

A Generalization of the Recursive Integration Method for the Analytic Valuation of American Options

A Forward Monte Carlo Method for American Options Pricing

On Extensions of the Barone-Adesi & Whaley Method to Price American-Type Options

Contact Info

Product

Resources

About

A generalization of the Barone‐Adesi and Whaley approach for the analytic approximation of American options

Cited by 3 publications

References 11 publications

A Generalization of the Recursive Integration Method for the Analytic Valuation of American Options

A Generalization of the Recursive Integration Method for the Analytic Valuation of American Options

A Forward Monte Carlo Method for American Options Pricing

On Extensions of the Barone-Adesi &amp; Whaley Method to Price American-Type Options

Contact Info

Product

Resources

About

On Extensions of the Barone-Adesi & Whaley Method to Price American-Type Options