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Seminario RoDeO on the Road: Q-Learning and SARSA: Two intelligent approaches for financial trading

Giovedì 17 Marzo 2016, ore 15:00 - Aula 2BC30 - Marco Corazza

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Giovedì 17 Marzo 2016 alle ore 15:00 in Aula 2BC30, Marco Corazza (Università Ca' Foscari) terrà un seminario del ciclo RoDeO on the Road dal titolo "Q-Learning and SARSA: Two intelligent approaches for financial trading".

Abstract
The purpose of this contribution is to design an intelligent stochastic control system for optimizing the performances of a trading system. Two model-free machine learning algorithms based on Reinforcement Learning algorithms are considered: Q-Learning and SARSA. Both these models optimize their behaviors in real time on the basis of the reactions they get from the environment in which operate. The idea to use Reinforcement Learning tools for designing intelligent trading systems is based on a new emerging theory about the financial market efficiency: the Adaptive Market Hypothesis. We develop both the models for trading on single stock price time series. They use simple state variables and operate selecting an action among three possible ones: buy, sell, and stay out from the market. We perform different applications based on different parameter settings
which are checked on an artificial stock prices time series and on different daily real ones from the Italian stock market. Furthermore, performances are both gross and net of transaction costs.
Authors: Marco Corazza and Andrea Sangalli.

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