The strategy was built on several fundamental principles that have proven effective through years of research and market trading:

• Identifying Strong Trends – Instead of trying to "guess" bottoms and tops, the strategy identifies strong market trends and moves with them. It's like sailing at sea- instead of fighting the current and waves, we identify the strong current and sail with it, allowing us to reach a much higher speed than we could achieve on our own.
• Aggressive Risk Management – The secret to successful trading over time is not just making money, but also (and perhaps primarily) not losing it. The strategy includes an advanced risk management system that identifies danger signs in the market and exits positions before significant declines. It's like driving with an advanced automatic braking system - it identifies the danger and stops the vehicle before you even notice the problem.
• Objectivity and Discipline – We remove emotion from trading. The algorithm is neither fearful nor greedy - it makes decisions based on objective metrics only, without the influence of human emotions. This ensures absolute discipline and consistent implementation of the strategy in all market conditions.
• Simplicity of Implementation – Despite the technological sophistication, the implementation is extremely simple - 2-3 actions per month, with clear and unambiguous instructions.

Identifying market trends is a critical capability, especially when dealing with leveragedETFs. The algorithm uses a sophisticated combination of methods:

• Structural Analysis of Prices – The algorithm examines the structure of price movements - are higher highs and higher lows forming (uptrend) or lower highs and lower lows (downtrend) Unlike simplistic approaches, our algorithm analyzes the deep structure of price movement.
• Momentum Measurement System – The algorithm measures the strength of price movements, not just their direction. A strong uptrend is characterized not only byrising prices but also by strong positive momentum.
• Multiple Confirmation – The algorithm seeks confirmation from multiple sources before making a decision. This reduces the risk of "false signals" that are so common in trading.

The decision of when to enter a position and when to exit it is critical. The algorithm uses a sophisticated approach:

• Optimal Entry Points – The algorithm looks for specific "windows of opportunity" -situations where the chance for a strong movement in the trend direction is particularly high. This is similar to a chess move - instead of moving in every turn, a good player waits for a situation where his move will be particularly effective.
• Dual Exit Management – The algorithm manages two types of exits - protective exits(to limit losses) and profit exits (to realize profits). Protective exits are predetermined, while profit exits are more dynamic and take into account the momentum of the movement.
• Optimization Based on Historical Performance – The algorithm has been optimized based on the analysis of thousands of historical trades, which allowed us to identify the characteristics of particularly successful entry and exit points.
• Handling Extreme Cases – One of the significant advantages of the algorithm is the ability to identify and handle extreme cases - unusual market conditions that were not often seen in the past.

The field of artificial intelligence has made giant strides in recent years, and the x3strategy incorporates advanced AI techniques:

• Machine Learning for Pattern Recognition – The algorithm uses machine learning techniques to identify complex patterns in market data. Unlike traditional indicators that focus on single parameters, our ML model can weigh hundreds of variables and find non-linear relationships between them.
• Real-time Event Processing – The algorithm analyzes events in real-time and adjusts the strategy accordingly. For example, if significant macro data or central bank announcements are published, the system can adjust the level of exposure.
• Continuous Optimization – While the standard version of the strategy remains stable, we run more advanced models in parallel that examine potential improvements. When a new model proves itself over a sufficient period, we incorporate its improvements into the standard version.

Based on historical data, the strategy has yielded impressive results:

• Average Annual Return: About 65% over the 12-year test period with TQQQ, compared to about 8-10% in the general market
• Maximum Drawdown: Only 25%, compared to drawdowns of 70-85% in TQQQ with Buy & Hold

Interestingly, the strategy achieves a success rate of only 30-38% in trades, but the average profit in successful trades is significantly larger than the average loss in losing trades. This highlights an important principle in trading - you don't have to be right most of the time; you need to be right when it really matters, and know how to minimize losses when you're wrong.