Sequential Tracking in Pricing Financial Options Using Model Based and Neural Network Approaches
Abstract
This paper shows how the prices of option contracts traded in finan(cid:173) cial markets can be tracked sequentially by means of the Extended Kalman Filter algorithm. I consider call and put option pairs with identical strike price and time of maturity as a two output nonlin(cid:173) ear system. The Black-Scholes approach popular in Finance liter(cid:173) ature and the Radial Basis Functions neural network are used in modelling the nonlinear system generating these observations. I show how both these systems may be identified recursively using the EKF algorithm. I present results of simulations on some FTSE 100 Index options data and discuss the implications of viewing the pricing problem in this sequential manner.
Cite
Text
Niranjan. "Sequential Tracking in Pricing Financial Options Using Model Based and Neural Network Approaches." Neural Information Processing Systems, 1996.Markdown
[Niranjan. "Sequential Tracking in Pricing Financial Options Using Model Based and Neural Network Approaches." Neural Information Processing Systems, 1996.](https://mlanthology.org/neurips/1996/niranjan1996neurips-sequential/)BibTeX
@inproceedings{niranjan1996neurips-sequential,
title = {{Sequential Tracking in Pricing Financial Options Using Model Based and Neural Network Approaches}},
author = {Niranjan, Mahesan},
booktitle = {Neural Information Processing Systems},
year = {1996},
pages = {960-966},
url = {https://mlanthology.org/neurips/1996/niranjan1996neurips-sequential/}
}