MarketWeatherForecast
ANALYSIS • NEUTRAL • 2026-03-05

Top 5 Trading Strategies (with Simple Backtests)

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This article explores five practical trading strategies for major ETFs (SPY, QQQ, IWM, TLT, GLD), providing clear rules, risks, and backtest methodologies. It is designed for retail traders and investors seeking to understand systematic approaches, with a focus on transparency and educational value.
SPY
1D: -0.56%
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Top 5 Trading Strategies (with Simple Backtests)

Retail traders and investors often seek systematic approaches to improve their trading outcomes. This article presents five widely-discussed trading strategies, each explained with practical rules, risks, and a summary of how a simple backtest could be conducted. The focus is on major ETFs: SPY (S&P 500), QQQ (Nasdaq 100), IWM (Russell 2000), TLT (20+ Year Treasuries), and GLD (Gold).

Note: This article is educational. It is not investment advice. All strategies are hypothetical and for illustrative purposes only.

1. 50/200-Day Moving Average Crossover

Intuition

This trend-following strategy aims to capture large market moves by buying when the short-term trend (50-day moving average) crosses above the long-term trend (200-day moving average), and selling (or staying out) when the opposite occurs.

Exact Rules

  • Buy Signal: When the 50-day simple moving average (SMA) closes above the 200-day SMA.
  • Sell Signal: When the 50-day SMA closes below the 200-day SMA.
  • Asset: SPY.
  • Position: 100% long or 100% cash.
  • Rebalance: Daily at close.

Risks / Failure Modes

  • Whipsaws in sideways markets can cause frequent losses.
  • Lags behind sudden reversals.
  • Misses gains during rapid rebounds.

Simple Backtest Summary

  • CAGR: TBD (Method: Use daily adjusted close prices for SPY from AlphaVantage. Calculate returns when in position. No leverage. No shorting.)
  • Max Drawdown: TBD
  • Win-rate: TBD
  • Caveats: Results sensitive to start/end dates, data quality, and do not include trading fees or slippage.

2. Relative Strength Rotation

Intuition

This momentum-based strategy allocates capital to the ETF with the strongest recent performance, under the assumption that strength persists in the short term.

Exact Rules

  • Universe: SPY, QQQ, IWM, TLT, GLD.
  • Lookback: 3-month total return.
  • Buy Signal: At each month-end, buy the ETF with the highest trailing 3-month return.
  • Position: 100% long the selected ETF, hold for one month.
  • Rebalance: Monthly.

Risks / Failure Modes

  • Chasing recent winners can lead to reversals (mean reversion).
  • High turnover increases transaction costs.
  • May underperform in volatile or range-bound markets.

Simple Backtest Summary

  • CAGR: TBD (Method: For each month, calculate 3-month returns for all ETFs, select the top performer, and allocate 100% capital for the next month. Repeat.)
  • Max Drawdown: TBD
  • Win-rate: TBD
  • Caveats: Assumes perfect execution at close prices. No slippage or fees included.

3. Mean Reversion with RSI

Intuition

This strategy bets that extreme moves tend to revert. The Relative Strength Index (RSI) identifies overbought or oversold conditions.

Exact Rules

  • Asset: QQQ.
  • Buy Signal: RSI(14) drops below 30 (oversold).
  • Sell Signal: RSI(14) rises above 50.
  • Position: 100% long or 100% cash.
  • Rebalance: Daily at close.

Risks / Failure Modes

  • In strong trends, oversold conditions can persist or worsen.
  • False signals in choppy markets.
  • Market regime shifts can reduce effectiveness.

Simple Backtest Summary

  • CAGR: TBD (Method: Calculate daily RSI(14) on QQQ. Enter position when RSI < 30, exit when RSI > 50.)
  • Max Drawdown: TBD
  • Win-rate: TBD
  • Caveats: No transaction costs or slippage. Performance may vary by parameter choice.
Infographic

4. Volatility Breakout (ATR Channel)

Intuition

This strategy seeks to capture large price moves by buying when price breaks above a volatility-adjusted band, using the Average True Range (ATR).

Exact Rules

  • Asset: IWM.
  • Buy Signal: Close > 20-day high + 1x ATR(20).
  • Sell Signal: Close < 20-day low - 1x ATR(20).
  • Position: 100% long or 100% cash.
  • Rebalance: Daily at close.

Risks / Failure Modes

  • False breakouts in range-bound markets.
  • Large drawdowns if volatility spikes.
  • May miss sustained trends if bands are too wide.

Simple Backtest Summary

  • CAGR: TBD (Method: Calculate 20-day high/low and ATR(20) on IWM. Enter long on breakout, exit on breakdown.)
  • Max Drawdown: TBD
  • Win-rate: TBD
  • Caveats: No trading costs. Results sensitive to parameter choices and volatility regime.

5. Dual Momentum (Absolute + Relative)

Intuition

Combines absolute momentum (trend) and relative momentum (strength vs. peers) to select assets only when both are positive.

Exact Rules

  • Universe: SPY, TLT, GLD.
  • Lookback: 12-month total return.
  • Step 1: At each month-end, calculate 12-month return for each ETF.
  • Step 2: Select the ETF with the highest 12-month return, but only if its return is positive.
  • Step 3: If no ETF has a positive return, stay in cash.
  • Position: 100% long the selected ETF, or cash.
  • Rebalance: Monthly.

Risks / Failure Modes

  • May lag in trend reversals.
  • Periods of all-negative returns lead to cash drag.
  • Results sensitive to lookback window.

Simple Backtest Summary

  • CAGR: TBD (Method: At each month-end, select the ETF with the highest positive 12-month return. Hold for one month. Repeat.)
  • Max Drawdown: TBD
  • Win-rate: TBD
  • Caveats: No trading costs or slippage. Survivorship bias possible.

Data & Methodology

All strategies are designed for educational purposes and use daily adjusted close data from AlphaVantage. Backtests would assume:

  • Dividends: Reinvested (if included in adjusted close).
  • Survivorship bias: Universe is fixed (current ETFs), so historical results may differ from real-world experience.
  • Slippage & Fees: Not included. Actual results would be lower after costs.
  • Execution: Signals are assumed executed at daily close prices.

For each strategy, a simple backtest would involve iterating through historical data, applying entry/exit rules, and tracking performance metrics such as CAGR (Compound Annual Growth Rate), maximum drawdown, and win-rate. However, actual numbers are marked as TBD due to data and execution complexities.

Key Takeaways

  • Systematic trading strategies can help remove emotion and provide structure.
  • Each approach has unique risks and may perform differently across market regimes.
  • Backtest results are highly sensitive to assumptions, data quality, and costs.
  • No strategy guarantees success; diversification and risk management remain essential.

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Sources

Backtests
Buy & Hold
CAGR: +9.02%
Total: +872.45%
Vol: +13.29%
Sharpe: 0.72
Max DD: -38.59%
Buy & Hold equity curve
Buy & Hold drawdown
Trend (Price > SMA200)
CAGR: +6.06%
Total: +371.15%
Vol: +7.80%
Sharpe: 0.79
Max DD: -15.48%
Trend (Price > SMA200) equity curve
Trend (Price > SMA200) drawdown
Golden Cross (SMA50 > SMA200)
CAGR: +6.46%
Total: +420.68%
Vol: +8.75%
Sharpe: 0.76
Max DD: -21.07%
Golden Cross (SMA50 > SMA200) equity curve
Golden Cross (SMA50 > SMA200) drawdown
RSI Mean Reversion (RSI<30 / >50)
CAGR: +2.65%
Total: +99.30%
Vol: +8.13%
Sharpe: 0.36
Max DD: -22.97%
RSI Mean Reversion (RSI<30 / >50) equity curve
RSI Mean Reversion (RSI<30 / >50) drawdown
Momentum (12-1M)
CAGR: +6.93%
Total: +484.63%
Vol: +9.18%
Sharpe: 0.78
Max DD: -21.07%
Momentum (12-1M) equity curve
Momentum (12-1M) drawdown
Sources
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