Intraday Market

Intraday market research focuses on understanding and predicting the rapid price fluctuations within a single trading day across various asset classes, primarily aiming to improve forecasting accuracy and optimize trading strategies. Current research employs diverse machine learning models, including LSTM networks, convolutional neural networks (CNNs), and reinforcement learning (RL) algorithms like DDPG and PPO, often incorporating high-frequency data and alternative data sources like search engine query volumes. These advancements offer potential for improved risk management, enhanced portfolio optimization, and more efficient resource allocation in energy markets, but challenges remain in handling high-dimensionality, model robustness, and accurately capturing complex dependencies within the data.