#我的策略演变 The evolution of trading strategies in BTC from novice to expert is reflected in the shift from blindly chasing highs and lows to systematic decision-making. Novices often rely on a single indicator (such as RSI) or are driven by emotions, trading frequently while neglecting risk management, making them prone to losses during volatility. As they progress, they begin to learn technical analysis, combining moving averages, Bollinger Bands, and other indicators, trying trend-following or breakout strategies, but may still be thwarted by misconfigured parameters or false signals. With accumulated experience, traders turn to multidimensional analysis, integrating fundamentals (such as policies, on-chain data) and market sentiment, optimizing position management and setting strict stop-losses. In the intermediate stage, there is a preference for DCA (dollar-cost averaging) or swing trading to reduce emotional interference. Upon becoming experts, strategies become more flexible, incorporating quantitative models, arbitrage, or cross-market operations, while emphasizing long-term trends and macroeconomics, such as Federal Reserve policies or BTC reserve plans. Alternative predictions like astrology are only for reference; the core still relies on data-driven approaches. Experts emphasize discipline, strictly executing plans, controlling leverage, and pursuing stable returns rather than windfall profits. The key to evolution lies in continuous learning, summarizing experiences, and improving the risk management system.