2 citations · 3 across the 4 of their papers we have counts for
4 papers
Application of Deep Reinforcement Learning to At-the-Money S&P 500 Options Hedging
Zofia Bracha, Paweł Sakowski, Jakub Michańków
This paper explores the application of deep Q-learning to hedging at-the-money options on the S\&P~500 index. We develop an agent based on the Twin Delayed Deep Deterministic Polic…
Combining Deep Learning and GARCH Models for Financial Volatility and Risk Forecasting
Jakub Michańków, Łukasz Kwiatkowski, Janusz Morajda
In this paper, we develop a hybrid approach to forecasting the volatility and risk of financial instruments by combining common econometric GARCH time series models with deep learn…
Hedging Properties of Algorithmic Investment Strategies using Long Short-Term Memory and Time Series models for Equity Indices
Jakub Michańków, Paweł Sakowski, Robert Ślepaczuk
This paper proposes a novel approach to hedging portfolios of risky assets when financial markets are affected by financial turmoils. We introduce a completely novel approach to di…
Mean Absolute Directional Loss as a New Loss Function for Machine Learning Problems in Algorithmic Investment Strategies
Jakub Michańków, Paweł Sakowski, Robert Ślepaczuk
This paper investigates the issue of an adequate loss function in the optimization of machine learning models used in the forecasting of financial time series for the purpose of al…