TradingAgents：当 AI 开始炒股——多 Agent 量化交易的风险与机遇

class StrategyParser:
    """解析自然语言策略"""
    
    async def parse(self, natural_language: str) -> Strategy:
        """
        将自然语言转换为结构化策略
        
        示例输入：
        "当 BTC 突破 50日均线且 RSI > 70 时买入"
        
        示例输出：
        {
            'asset': 'BTC',
            'condition': {
                'indicator': 'MA50',
                'comparison': 'cross_above',
                'secondary': {'RSI': {'>': 70}}
            },
            'action': 'BUY',
            'risk_params': {
                'stop_loss': '5%',
                'take_profit': '15%'
            }
        }
        """
        # 使用 LLM 解析意图
        parsed = await self.llm.parse(natural_language)
        
        # 验证策略有效性
        validated = self.validate_strategy(parsed)
        
        return Strategy(validated)

class DataFetcher:
    """获取多源市场数据"""
    
    async def fetch(self, strategy: Strategy) -> MarketData:
        # 并行获取多个数据源
        tasks = [
            self.get_price_data(strategy.asset),
            self.get_news_sentiment(strategy.asset),
            self.get_social_media_trends(strategy.asset),
            self.get_onchain_data(strategy.asset)  # 如果是加密资产
        ]
        
        results = await asyncio.gather(*tasks)
        
        return MarketData(
            price=results[0],
            sentiment=results[1],
            social=results[2],
            onchain=results[3]
        )

class TradeExecutor:
    """生成并执行交易指令"""
    
    async def execute(
        self,
        strategy: Strategy,
        data: MarketData
    ) -> TradeDecision:
        # 评估策略条件
        if self.check_conditions(strategy, data):
            # 计算仓位大小
            position_size = self.calculate_position(
                strategy, 
                self.portfolio
            )
            
            # 生成交易指令
            return TradeDecision(
                action=strategy.action,
                asset=strategy.asset,
                size=position_size,
                order_type='LIMIT',
                risk_params=strategy.risk_params
            )

class RiskManager:
    """评估和控制交易风险"""
    
    async def assess(self, decision: TradeDecision) -> RiskAssessment:
        risks = {
            'market_risk': self.calculate_var(decision),
            'liquidity_risk': self.check_liquidity(decision),
            'concentration_risk': self.check_concentration(decision),
            'correlation_risk': self.check_correlation(decision)
        }
        
        total_risk = sum(risks.values())
        
        if total_risk > self.risk_threshold:
            return RiskAssessment(
                approved=False,
                reasons=['风险超出阈值'],
                suggested_adjustments=self.suggest_adjustments(decision)
            )
        
        return RiskAssessment(approved=True)

class VIXHedgeStrategy:
    def __init__(self):
        self.max_position = 0.10  # 10% 资金上限
        self.trigger_threshold = -0.02  # -2% 触发
        
    async def on_market_data(self, data):
        sp500_change = data['SP500']['daily_change']
        
        if sp500_change < self.trigger_threshold:
            position_size = self.calculate_position_size(
                portfolio_value=data['portfolio']['total_value'],
                max_percentage=self.max_position
            )
            
            return Order(
                symbol='VIX',
                side='BUY',
                quantity=position_size,
                order_type='MARKET',
                time_in_force='IOC'
            )