• Short prediction horizons

Machine learning models excel in short-term predictions due to their ability to analyze real-time data and quickly adapt to changing market conditions. Short prediction horizons typically range from a few seconds to minutes, allowing these models to capture and react to market dynamics effectively.

• Availability of real-time order book data

Real-time order book data provides valuable information about market liquidity, supply, and demand. Machine learning models can leverage this data to identify patterns and make informed trading decisions within short timeframes.

• Acknowledging the probabilistic nature of trading

Machine learning models in trading recognize the probabilistic nature of predicting asset prices. Even models with modest accuracy, around 55% to 60%, can provide valuable insights and contribute to profitable trading strategies. By understanding the inherent uncertainty in financial markets, machine learning models can generate probabilistic predictions that guide trading decisions.

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