Crypto Trading Research & Backtesting Prototype

About the project

Building Better Crypto Strategies with Research and Backtesting

Crypto Trading Research & Backtesting Prototype is currently in the research and prototyping stage, where the overall structure and final scope are still being refined.

At this stage, the system is designed to collect historical cryptocurrency market data, generate technical indicators, and train a machine learning model to analyze trading patterns. It also performs vectorized backtesting to simulate trading strategies and evaluate their performance using risk and stability metrics.

This prototype helps the team test trading ideas, validate strategies through data, and identify improvements that will guide the development of a more advanced trading analysis system.

Artificial Intelligence

Financial Technology

Research & Development

Insights and Problems

Incomplete Pipeline Setup

There was a need to establish a fully functional end-to-end pipeline that could process market data and generate structured back test outputs. This ensured that raw inputs, strategy execution, and result reporting were connected in a reliable and repeatable workflow.

Overfitting & Simulation Bias

Trading strategies risked being overfitted to historical data, ignoring trading costs, or favoring one market direction, which could produce misleading results. The testing process needed controls that reflected more realistic market behavior and execution conditions.

Misleading Performance Metrics

Evaluating strategies solely based on profit without considering risk and stability could result in strategies that look strong in tests but fail in real market conditions. A broader evaluation framework was necessary to measure consistency, drawdowns, and long-term robustness.