We present a deep reinforcement learning framework for an automatic trading of contracts for difference (CfD) on indices at a high frequency. Our contribution proves that reinforcement learning agents with recurrent long short-term memory (LSTM) networks can learn from recent market history and...

We present a deep reinforcement learning framework for an automatic trading of contracts for difference (CfD) on indices at a high frequency. Our contribution proves that reinforcement learning agents with recurrent long short-term memory (LSTM) networks can learn from recent market history and...

The financial derivatives market in Romania is still at an early stage of development. However, the oldest and, in our opinion, the most important market operator, the Sibiu Stock Exchange (Sibex) always tried to include in its portfolio new types of instruments, providing new opportunities for...