Create rule-based equity strategies with systematic stock trading automation. Execute disciplined approaches across brokers like Alpaca, Trading212 and WeBull with consistent risk management.
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Instead of second-guessing entry points, you define conditions like RSI below 30 with volume above average and let systematic stock trading execute automatically. Your strategies run the same way whether markets gap up, crash or trade sideways, removing emotion from equity decisions.
The platform translates your trading logic into automated rules that monitor stocks across Alpaca, Trading212, WeBull and Robinhood simultaneously. You might set a momentum strategy that buys when price breaks above 20-day highs with volume exceeding 150% of average, then exits when RSI crosses back below 70.
Every automated strategy includes position sizing, stop losses and profit targets defined upfront. Rules can limit single positions to 2% of portfolio value while setting trailing stops that tighten from 5% to 2% as gains exceed 15%. The system enforces discipline you might abandon manually.
Templates for systematic approaches
Choose from tested templates covering momentum breakouts, mean reversion and sector rotation strategies. Each template includes entry conditions, exit rules and risk parameters that you can customize for your risk tolerance and time horizon.
Multi-broker execution engine
Connect multiple stock brokers to diversify execution and access different markets. Your systematic rules can route orders to the broker with best pricing or liquidity for each specific trade.
Moving Average Scalper
Enters long when price crosses above 20-period MA with volume confirmation. Exits on opposite cross or 1.5% profit target. Quick systematic entries for trending stocks.
RSI Oversold Rebound
Buys when RSI drops below 25 on daily charts with price above 50-day MA. Sells when RSI exceeds 75. Systematic approach to oversold bounces in uptrends.
Breakout Plus Retest
Enters on breakout above resistance with volume spike, then adds on successful retest. Stops below retest low. Systematic momentum capture strategy.
Volatility Breakout
Triggers when price moves beyond 2x average true range with volume confirmation. Captures systematic breakouts from low volatility periods.
Momentum Pullback
Buys pullbacks to 10-day MA in stocks showing 20-day momentum above 5%. Systematic way to enter trending stocks on temporary weakness.
Moving Average Scalper
Enters long when price crosses above 20-period MA with volume confirmation. Exits on opposite cross or 1.5% profit target. Quick systematic entries for trending stocks.
RSI Oversold Rebound
Buys when RSI drops below 25 on daily charts with price above 50-day MA. Sells when RSI exceeds 75. Systematic approach to oversold bounces in uptrends.
Breakout Plus Retest
Enters on breakout above resistance with volume spike, then adds on successful retest. Stops below retest low. Systematic momentum capture strategy.
Volatility Breakout
Triggers when price moves beyond 2x average true range with volume confirmation. Captures systematic breakouts from low volatility periods.
Momentum Pullback
Buys pullbacks to 10-day MA in stocks showing 20-day momentum above 5%. Systematic way to enter trending stocks on temporary weakness.
Support Resistance Bounce
Enters long at identified support levels with RSI below 40. Exits at resistance or 3% gain. Systematic range trading approach.
Earnings Drift Rider
Enters positions following positive earnings surprises with analyst upgrades. Holds for 5-10 days capturing post-earnings momentum systematically.
Sector Momentum Switcher
Rotates between sector ETFs based on relative strength rankings. Systematic approach to sector rotation using momentum indicators.
High Beta Risk-On Basket
Increases allocation to high-beta stocks when VIX drops below 20. Systematic risk-on positioning during low volatility periods.
Dividend ETF Seasonality
Enters dividend ETFs before ex-dividend dates in tax-advantaged periods. Systematic approach to dividend capture strategies.
Test your rule-based strategies against historical data to validate performance before risking capital. The backtesting engine shows how your approach would have performed across different market cycles, helping refine entry and exit conditions. You can optimize parameters like lookback periods and threshold levels based on historical results.
Beyond individual stock rules, create portfolio-wide controls that manage overall exposure and correlation. Set rules that reduce position sizes when portfolio volatility exceeds targets or rotate between growth and value based on market regime indicators. These overlays help maintain consistent risk profiles.
Your rule-based strategies can operate across multiple timeframes simultaneously. Daily scans identify stocks meeting fundamental criteria while intraday rules time precise entries using technical indicators. This multi-timeframe approach combines stock selection with tactical execution timing.
Monitor how each approach performs with detailed analytics showing win rates, average holding periods and risk-adjusted returns. Compare performance across different market conditions to identify which strategies work best in trending versus ranging markets. Use these insights to allocate capital more effectively.
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Start with simple rules and gradually add complexity as you gain confidence in rule-based execution. Begin with basic momentum or mean reversion strategies, then incorporate additional filters and risk controls.
Continuously refine your rule-based approaches using performance data and changing market conditions. Optimization involves testing parameter variations and identifying which combinations produce the most consistent results. Regular review ensures your automated strategies remain effective.
As your strategies prove successful, scale them across larger position sizes and additional stocks. The rule-based nature makes scaling straightforward since the same logic applies regardless of portfolio size. Approaches that work with small positions often scale effectively.
Combine multiple approaches to reduce dependence on any single strategy. Mix momentum and mean reversion rules, different timeframes and various technical indicators. This diversification helps smooth returns and reduces the impact of any individual strategy's poor performance.
Explore sophisticated approaches like pairs trading, sector rotation and market regime detection. These advanced strategies require more complex rules but can provide exposure to market inefficiencies that simpler approaches might miss.
Your trading will evolve as you gain experience with rule-based execution and market analysis. What starts as basic automated entries can develop into sophisticated strategies that adapt to changing market conditions while maintaining disciplined, emotion-free execution.
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