A valid trading system must have five core elements: clear entry/exit rules, risk control modules, multi-timeframe verification logic, capital management strategies, and backtestable and optimizable properties. These elements should be interconnected and operate in a closed loop.

1. Clear Entry/Exit Rules
Rules should be based on quantifiable signals, such as combining multi-timeframe technical indicators (e.g., daily Bollinger middle band + 4-hour MACD golden cross) to trigger entries. Clear conditions for stop-loss (e.g., fixed points stop-loss, trailing stop) and take-profit (e.g., target levels, partial profit-taking) must be defined to eliminate subjective judgment.

2. Strict Risk Control Module
The core is to limit risk exposure per trade, such as restricting loss per position to no more than 1%-2% of total capital. It should also include position limits (e.g., no more than 30% of total funds in a single currency), and rules for extreme market conditions (e.g., forced position reduction during black swan events) to prevent a single trade from severely damaging the account.

3. Multi-Timeframe Verification Logic
Single timeframe signals can produce false breakouts. Verification should involve a "big timeframe trend determination + small timeframe entry points" approach. For example, confirming a bullish trend on the daily chart, then looking for RSI oversold signals on the 2-hour chart to find entry opportunities, thereby improving signal validity.

4. Scientific Capital Management Strategy
Different from risk control, capital management focuses on dynamic position adjustment, such as adding to winning positions (pyramiding) after profits, or strictly reducing positions or halting new entries during losses. The core goal is to "let profits run and cut losses short."

5. Backtestable and Optimizable Properties
The system should be backtested using historical data (e.g., cryptocurrency market data from the past 1-3 years) to verify key parameters like win rate and profit/loss ratio. It should also allow for optimization, adjusting indicator parameters based on market environment changes (e.g., bull-bear transitions) to prevent system failure.