Machine learning over the free-parameters of the Black-Scholes equation: Stock market and Option market

Jorge Mario Arraut, Ivan Arraut, Ka I Lei

Keywords: Stock Market - Option Market - Black-Scholes equation - Volatility - Machine learning

Abstract:

The Black-Scholes equation is famous for predicting
values for the prices of Options inside the
stock market scenario. However, it has the limitation
of depending on the estimated value for
the volatility. On the other hand, several Machine
learning techniques have been employed for predicting
the values of the same quantity. In this
paper we analyze some fundamental properties of
the Black-Scholes equation and we then propose
a way to train its free-parameters, the volatility
in particular. This with the purpose of using this
parameter as the fundamental one to be learned
by a Machine Learning system and then improve
the predictions in the stock market.

Submission Type: Archival (to be published in the Journal of LatinX in AI (LXAI) Research)

Submission Number: 24