A Brain-Inspired Cerebellar Associative Memory Approach to Option Pricing and Arbitrage Trading

  • S. D. Teddy
  • E. M. -K. Lai
  • C. Quek
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4234)


Option pricing is a process to obtain the theoretical fair value of an option based on the factors affecting its price. Currently, the nonparametric and computational methods of option valuation are able to construct a model of the pricing formula from historical data. However, these models are generally based on a global learning paradigm, which may not be able to efficiently and accurately capture the dynamics and time-varying characteristics of the option data. This paper proposes a novel brain-inspired cerebellar associative memory model for pricing American-style option on currency futures. The proposed model, called PSECMAC, constitute a local learning model that is inspired by the neurophysiological aspects of the human cerebellum. The PSECMAC-based option pricing model is subsequently applied in a mis-priced option arbitrage trading system. Simulation results show a return on investment as high as 23.1% for a relatively risk-free investment.


Option Price Call Option Trading System Strike Price Underlying Asset 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • S. D. Teddy
    • 1
  • E. M. -K. Lai
    • 1
  • C. Quek
    • 1
  1. 1.Centre for Computational Intelligence, School of Computer EngineeringNanyang Technological UniversitySingapore

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