Evolutionary Computation in Option Pricing: Determining Implied Volatilities Based on American Put Options

Keber, Christian

doi:10.1007/978-3-7908-1784-3_21

Cited by 8 publications

(4 citation statements)

References 25 publications

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“…The MLP is also much closer to Black-Scholes than previously on the three remaining performance measures. and have also found that 1 Genetic programming imitates the evolutionary process to generate new pricing formulas which perform better than the initial model, and a few studies have used genetic programming, rather than ANNs, Chen & Lee (1997a, Chen, Lee & Yeh (1998, Chidambaran, Lee, & Trigueros (1998a, 1998b, Keber ( , 2000Keber ( , 2002 and Trigueros (1997).…”

Section: Resultsmentioning

confidence: 99%

Black–Scholes versus artificial neural networks in pricing FTSE 100 options

Bennell

Sutcliffe

2004

Intelligent Systems in Accounting, Finance and Management

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This paper compares the performance of Black–Scholes with an artificial neural network (ANN) in pricing European‐style call options on the FTSE 100 index. It is the first extensive study of the performance of ANNs in pricing UK options, and the first to allow for dividends in the closed‐form model. For out‐of‐the‐money options, the ANN is clearly superior to Black–Scholes. For in‐the‐money options, if the sample space is restricted by excluding deep in‐the‐money and long maturity options (3.4% of total volume), then the performance of the ANN is comparable to that of Black–Scholes. The superiority of the ANN is a surprising result, given that European‐style equity options are the home ground of Black–Scholes, and suggests that ANNs may have an important role to play in pricing other options for which there is either no closed‐form model, or the closed‐form model is less successful than is Black–Scholes for equity options. Copyright © 2005 John Wiley & Sons, Ltd.

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Section: Resultsmentioning

confidence: 99%

Black–Scholes versus artificial neural networks in pricing FTSE 100 options

Bennell

Sutcliffe

2004

Intelligent Systems in Accounting, Finance and Management

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“…Since Economy (and particularly the stock market) is a really dynamic environment, GAs are absolutely suitable to solve problems in this domain. Thus, EC has been largely used to simulate artificial market agents (Arifovic 2001;Fogel et al 2002) as well as to solve theoretical matters of the Financial Engineering, such as Econometry (Koza 1992), Commercial Strategies (Pereira 2002) or the volatility of price selection (Keber 2002) or stock selection in extreme environments (Yan and Clark 2007). The results have been so satisfactory that EC has been applied even for the forecasting of financial systems (Li 2006).…”

Section: Indirect Achievements: Applicationsmentioning

confidence: 98%

On the origin of the evolutionary computation species influences of Darwin’s theories on computer science

Serrano

Castillo

2011

Artif Intell Rev

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This paper presents a small sample of evidences of the direct and clear influence of the Darwin's Theory of Evolution on the Computer Science field, putting the core seed of the well-known Evolutionary Computation and making Computer Science overcome some previous algorithmic limitations. The paper also shows how the more faithful to the Evolution Theory the algorithms, the better their performance and robustness, thus uncovering the crucial importance of the ideas collected in "On the Origin of Species" for the development of Computation and, indirectly through this, for the development of a great diversity of knowledge areas.

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“…However in practice the Black-Scholes implied volatilities are varying over strike price and maturity. Keber [59] has used GP to generate formulae for determining the implied volatility based on American put options.…”

Section: Derivatives Modellingmentioning

confidence: 99%