To respect customer privacy and business confidentiality, we have used pseudonyms in the following case, and certain content may have been adapted. Nevertheless, this story effectively showcases how X-Ray’s backtesting framework, X-BT, improves trading strategies through historical data calculations. Let’s consider the example of a trader from a trading company.
Li Feng is a seasoned trader at a commodity trading company, where he manages the company’s physical and paper trading alongside his team.
Seizing Market Opportunities, Optimizing Trading Decisions
One day, there was a significant price fluctuation in the market for a commodity used in the automotive industry. To capitalize on this trading opportunity, Li Feng decided to explore X-Ray’s backtesting framework, X-BT, to see if it could assist in enhancing his trading strategy.
X-Ray, as a super-practical tool, automates the processing of business data, generating real-time updated data reports to facilitate data analysis and decision-making. The highlight feature within X-Ray is the backtesting framework, X-BT, which simulates various trading strategies based on historical market data and indicator models, recording and calculating the effects of each decision. This supports Li Feng in comparing and evaluating different trading strategies, providing reliable support for making informed trading decisions.
Flexible Application of X-Ray’s Backtesting Framework, X-BT
While using X-Ray’s backtesting framework, X-BT, Li Feng found it to be user-friendly and highly flexible. He didn’t have to manually update historical data, as X-Ray automatically stored and updated data reports, providing him with the latest data support.
With a sufficient amount of historical data, he discovered that the system had provided generic indicator formulas based on actual situations. He could easily choose suitable formulas, perform multidimensional calculations based on his needs and historical data, and visualize the results using X-Ray’s chart visualization feature. This enhanced the intuitiveness of his analysis and decision-making, facilitating the comparison and analysis of different strategies.
During the backtesting of historical data, Li Feng identified that the existing formulas were insufficient to meet his calculation needs. He needed more custom indicators and formulas, such as market trends, moving averages, and volatility, and required new formulas for expression.
Fortunately, X-Ray also provided a complete IX-BTE development environment, allowing him to operate in a familiar VSCode. This environment enabled him to easily create various custom indicators and formulas, along with appropriate code writing and backtesting operations.
Multiple Backtests, Strategy Optimization, Risk Control
The backtest results showed that Li Feng’s developed trading strategy had performed well over the past few years, yielding substantial profits. However, he also noticed that the strategy might experience significant drawdowns during certain periods. Drawdown refers to the situation where assets or portfolios fall from a peak to a low point over a period, indicating potential significant losses for the trader. To address this challenge, Li Feng once again used the X-BT backtesting framework to conduct a series of backtests. Based on the comparative results of the strategies, he carried out parameter optimization and adjustments. Eventually, he found a set of more robust parameter configurations, successfully reducing historical drawdowns.
In subsequent trades, Li Feng continued to use X-Ray and the X-BT backtesting framework to monitor the market in real-time, comparing the latest market data with backtest results. This enabled him to quickly seize market opportunities, maximizing the chances of successful trades.
Thanks to the X-BT backtesting framework, Li Feng’s trading decisions became more precise and reliable. He deeply analyzed historical data, actively optimized trading strategies to adapt to market changes, and achieved outstanding performance in commodity trading, generating substantial profits for the company.
