# Daily momentum reversal strategy
1. Get adjusted close for last 21 days for all stocks in universe
2. Compute 21-day return = (close_t / close_t-21) - 1
3. Rank stocks by return: highest = worst recent (for reversal)
4. Go long bottom 20% (losers), short top 20% (winners)
5. Scale position size by 1/volatility of each stock
6. Apply 1% transaction cost, 10 bps slippage
7. Rebalance daily
8. Stop if market volatility > 30% annualized (reduce size by 50%)
Build a simulation environment that replicates the microstructure of your target venues. Include realistic slippage, latency, and, crucially, the behavior of other bots. Use reinforcement learning (RL) where the agent (your strategy) interacts with this twin.
Standard risk metrics (VaR, CVaR) look backward. Strategy Quant X uses counterfactual reasoning. For every trade, the system asks: "If I had done the opposite, would I have made money?" This creates a dynamic hedging overlay that reduces tail risk without sacrificing upside. strategy quant x