Monte Carlo Tree Search (MCTS) has had very exciting results in the field of two-player games. In this paper, we analyze the behavior of these algorithms in the financial field, in trading where, to the best of our knowledge, it has never been applied before and in option hedging. In particular, using MCTS algorithms capable of handling stochastic states and continuous actions, we setup a practical framework testing it on real data both in the trading and hedging case.

Monte carlo tree search for trading and hedging

Vittori E.;Likmeta A.;Restelli M.
2021-01-01

Abstract

Monte Carlo Tree Search (MCTS) has had very exciting results in the field of two-player games. In this paper, we analyze the behavior of these algorithms in the financial field, in trading where, to the best of our knowledge, it has never been applied before and in option hedging. In particular, using MCTS algorithms capable of handling stochastic states and continuous actions, we setup a practical framework testing it on real data both in the trading and hedging case.
2021
ICAIF 2021 - 2nd ACM International Conference on AI in Finance
9781450391481
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1231798
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 4
  • ???jsp.display-item.citation.isi??? 1
social impact