Deep trading bots are designed to trade using a technique called deep reinforcement learning. Deep reinforcement learning is a subfield of machine learning and artificial intelligence. It combines reinforcement learning and deep learning.
Reinforcement learning is concerned with how an algorithm should take action in a dynamic environment to maximize cumulative reward. The algorithm is required to learn an optimal or nearly optimal policy that maximizes reward. A similar process occurs in animal psychology. Animal brains are hardwired to interpret signals such as pain and hunger as negative reinforcements. They are consequently also hardwired to interpret pleasure and food intake as positive reinforcement. Animals learn to engage in behaviors that optimize these rewards. This means animal brains including human are all capable of reinforcement learning. Reinforcement learning is studied in many fields such as game theory, control theory, operations research, information theory, swarm intelligence, statistics, automated stocks trading, forex trading and cryptocurrency trading.
Deep learning is concerned with artificial neural networks with feature learning. Feature learning allows systems to automatically discover representations needed for classification of raw data. The word "deep" refers to the use of multiple layers in a network. Early forms of deep learning were inspired by the human brain's information processing methods. Nowadays, deep learning models have been able to surpass human expert performance. Deep learning is applied in fields such as speech recognition, computer vision, climate science, board games, language processing, machine translation, stocks trading, forex trading, and cryptocurrency trading.
Using the methods above, deep trading bots can process large amounts of data way faster and with less human input. They can find patterns in the market and trade for you very accurately. This removes the need to spend large amounts of time studying charts. Even in volatile markets they make more accurate trading decisions because of their ability to stay up to date with the latest market movements.