Multi-Stock RSI Strategy

Use your trading platform's screener with criteria: RSI(14) < 30, average daily dollar volume > $20M. Run the scan after market close (4:00 PM ET) for next-day trades. Sort results by RSI from lowest to highest to prioritize the most extreme stocks.

No. RSI < 30 is just the first filter. You should also check: trend (prefer above the 200 DMA), confirmation (wait for RSI to cross above 30), volume (higher on the bounce), and fundamentals. Only trade stocks that pass multiple filters.

Aim for 5-10 stocks for diversification without overcomplication. Start with 3-5 as a beginner. Each stock should be roughly 5-10% of your trading capital. More than 10 becomes difficult to manage and dilutes returns.

Typically 2-10 trading days. Most RSI reversion happens within a week of confirmation. If RSI hasn't improved after 10 days, consider exiting. Some traders use shorter (2-3 day) or longer (15-20 day) periods based on their style.

Two common methods: (1) Below the recent swing low - place the stop below the lowest point of the oversold period. (2) 2x ATR below entry - a volatility-adjusted stop. Either way, ensure the stop represents 2% or less of your total capital.

Compare price lows/highs with RSI lows/highs. Bullish divergence: price makes a lower low, but RSI makes a higher low (momentum improving despite the price decline). This is powerful confirmation of an impending reversal. Many platforms have divergence scanners.

Prioritize uptrend (price above the 200 DMA) for long positions. You're buying a pullback in a rising trend - trend momentum supports recovery. Downtrend oversold is riskier - you're trying to catch a falling knife. Use stricter criteria and smaller size for downtrend entries.

Calculate the average RSI for each sector (e.g., the average RSI of all Financials stocks, or simply track the sector ETF such as XLF). When a sector's average RSI drops below 35, it's a rotation candidate. Buy the 3-4 best stocks from that sector. As the sector recovers, all holdings benefit.

For oversold stocks: long calls (bullish), bull call spreads (defined risk), or sell cash-secured puts (collect premium). For overbought stocks: long puts, bear put spreads. IV is often elevated on oversold stocks, making selling strategies attractive.

When weekly and daily RSI conflict (e.g., weekly overbought, daily oversold), the higher timeframe usually dominates. Daily oversold in a weekly overbought is likely just a bounce - trade with reduced size and quick exits. The best setups have weekly and daily aligned.

Collect historical data for your universe. Optimize RSI parameters (period, thresholds) using walk-forward testing. Add filters (trend, quality) and measure improvement. Use ML to combine RSI with other features for return prediction. Backtest with realistic costs (spread, fees, slippage). Validate out-of-sample before live trading.

Calculate each stock's volatility (20-day std dev). Weight = 1/Volatility, then normalize weights to sum to 100%. Low-vol stocks get more capital, high-vol stocks get less. This equalizes risk contribution. Rebalance weekly when volatilities change.

Bull market: stricter oversold (25), looser overbought (75). Bear market: stricter overbought (65), looser oversold (35). High volatility: trade only extremes (<20, >80) with half position size. Ranging: standard 30/70 works well. Detect regime using the 200 DMA trend and the VIX level.

Typically: RSI level, RSI velocity (rate of change), distance from the 200 DMA, sector RSI, and volume ratio. These capture mean reversion potential and trend context. Feature importance analysis helps identify what matters most for your specific universe.

Calculate portfolio volatility using risk parity weights. Set a target vol (e.g., 15% annual). Scale the entire portfolio: Leverage = Target Vol / Realized Vol. If realized is 12%, scale up by 1.25x. If realized is 20%, scale down by 0.75x. This maintains a consistent risk profile over time.