Problem

Developing and implementing new trading systems for the financial markets is a time-consuming process that requires extensive backtesting to ensure effectiveness. Our team faced the challenge of streamlining this process while maintaining accuracy and reliability.

We needed a solution that could automate backtesting, generate reliable data, and provide accurate analysis of new trading strategies in a timely manner.

Solution

To address this problem, we designed an automated back-testing system that utilized Monte Carlo simulation and randomized ‘in samples’ data sets. The system performed over 1000 backtests on ‘out of sample’ data sets, generating 1000 reports which were then averaged to obtain the mean analysis of the strategies being created.

This solution allowed us to streamline the development, implementation, and backtesting of new trading systems while ensuring accuracy and reliability. We were able to generate fully automated and properly backtested (over 25 years of data) trading systems for the financial markets with ease.

Impact

Reduced time required for developing and testing new trading systems by X%
Increase in accuracy and reliability of generated data by X%
Improved profitability of trading strategies by X%

Quote of how incredible of an impact this had.

Team

Team Member #1 - Software Engineer
- Oversaw the creation and implementation of the platform
- Built algorithms for Monte Carlo simulation and randomized ‘in samples’ data sets
Team Member #2 - Data Analyst
- Analyzed and interpreted the generated data to obtain mean analysis of the strategies being created
- Developed statistical models for backtesting and analysis of trading systems

Click here for more information on our automated back-testing system.

Automated Backtesting Boosts Trading System Development