Abstract

The thesis addresses the question of how option pricing can be improved using machine learning techniques. The focus is on the modelling of volatility, the central determinant of an option price, using artificial neural networks. This is done explicitly as a volatility forecast and its accuracy evaluated. In addition, its use in option pricing is tested and compared with a direction option pricing approach.

Year Manuscript Completed

2013

Additional Categories

Mathematics (0405)

Computer Science (0984)

Keywords

Options (Finance) Prices Mathematical models; Futures Mathematical models; Neural networks (Computer science).

Primary Language of Manuscript

EN

01Front.pdf (116 kB)

Share

COinS