Quantitative strategies combine Big Data analysis, machine learning, and fully automated trading. The core principle involves identifying under-reactions or over-reactions in the market, with the portfolio primarily composed of trend-following models. An ensemble of thousands of weakly correlated algorithms significantly increases the final Sharpe ratio through the diversification effect. The system operates on liquid futures, eliminating human error and aiming for returns independent of market direction. Multi-level risk management includes pre-trade controls, position limits, and 24/7 monitoring. A key feature is dynamic volatility management: algorithms assess real-time market volatility every minute and adjust position sizes relative to the account balance. This ensures the actual leverage never exceeds the predefined risk level, protecting capital from unforeseen fluctuations and ensuring the stability of the strategy.