Build rule-based ETF systems with backtests, alerts and automated execution. Run momentum, rebalancing and risk controls via Alpaca, WeBull and TradeStation.
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Instead of guessing entries, Quant ETF strategies on Coinrule let you define clear signals, sizing and exits in a visual builder. Automate orders through Alpaca, Charles Schwab, Robinhood or Tradier from one dashboard with logs, alerts and risk limits.
Traders often prototype in spreadsheets, then struggle to execute consistently. Coinrule turns indicator and price conditions into live rules, like buying when a 50-day MA crosses above the 200-day MA. You can schedule checks daily, weekly or at month-end to match how ETFs are typically managed.
For ETF automation, guardrails matter as much as entries. Set max position size, portfolio-level stops and cooldown timers to avoid overtrading. Add alerts for volatility spikes, gap risk at the open and broker-side order rejections so you can intervene quickly.
Portfolio-first automation
Users set target weights and let the engine calculate trades on a schedule. Example: rebalance to 60-40 monthly, but skip if SPY is below its 200-day MA. Another rule caps any single ETF at 25% and trades only when drift exceeds 3%.
Broker-connected execution
Connect to Trading212, Public, Tastytrade or E*TRADE and run the same logic across accounts. Coinrule focuses on rule-based execution and monitoring, while your assets stay with your broker.
Portfolio Rebalance
Rebalances a basket on a weekly or monthly schedule. Buys underweight ETFs and trims overweight positions. Adds a 2% tolerance band to reduce churn.
Sector Momentum Switcher
Rotates into the top performing sector ETFs over a lookback window. Exits when relative strength drops below a threshold. Runs on daily checks to reduce noise.
Minimum Variance Rebalance
Shifts weights toward lower variance ETFs to smooth portfolio swings. Rebalances monthly with a max turnover limit. Adds a drawdown stop to cut risk during stress.
Risk Parity Allocator
Sets weights by inverse volatility so each ETF contributes similar risk. Updates volatility estimates weekly. Uses a cash buffer when volatility spikes above a set level.
Volatility Regime Switcher
Switches between risk-on and defensive ETFs using a volatility trigger. Moves to bonds when a VIX proxy rises above a threshold. Returns to equities when conditions normalize.
Portfolio Rebalance
Rebalances a basket on a weekly or monthly schedule. Buys underweight ETFs and trims overweight positions. Adds a 2% tolerance band to reduce churn.
Sector Momentum Switcher
Rotates into the top performing sector ETFs over a lookback window. Exits when relative strength drops below a threshold. Runs on daily checks to reduce noise.
Minimum Variance Rebalance
Shifts weights toward lower variance ETFs to smooth portfolio swings. Rebalances monthly with a max turnover limit. Adds a drawdown stop to cut risk during stress.
Risk Parity Allocator
Sets weights by inverse volatility so each ETF contributes similar risk. Updates volatility estimates weekly. Uses a cash buffer when volatility spikes above a set level.
Volatility Regime Switcher
Switches between risk-on and defensive ETFs using a volatility trigger. Moves to bonds when a VIX proxy rises above a threshold. Returns to equities when conditions normalize.
MA Crossover with Volume Filter
Enters when a fast MA crosses above a slow MA and volume confirms. Exits on the opposite cross or a trailing stop. Useful for trend-following ETF exposure.
ADX Trend Strength Filter
Trades only when ADX signals a strong trend. Avoids choppy periods by requiring ADX above a set value. Pairs with a moving average trigger for cleaner entries.
Mean Reversion with Z-Score
Buys when price deviates below its mean by a Z-score threshold. Sells when it reverts toward the mean. Adds a time stop if reversion takes too long.
Volatility Targeted Trend
Targets steadier risk by scaling position size to a volatility target. Follows a trend signal such as MA alignment. Cuts exposure automatically when volatility rises.
Market-Neutral Factor Hedge
Pairs a long factor ETF with a hedge to reduce market beta. Rebalances the hedge ratio on a schedule. Uses limits to keep net exposure near zero.
Unlike one-off trades, a systematic workflow needs iteration. Start with a simple rule, paper trade it, then tighten constraints like slippage buffers and max orders per day. Coinrule logs every decision so you can compare versions and keep what improves stability, not just returns.
Traders running Quant ETF strategies often start with simple comparisons. If 12-month momentum of SPY beats IEF, buy SPY and set a 7% trailing stop. If SPY closes below its 200-day MA, shift 50% into a bond ETF and pause new buys for 5 trading days.
ETFs can gap at the open and trade with wider spreads in the first minutes. Use time filters like placing orders after 10:00 ET, or split orders with a TWAP-style schedule. Add limit orders with a small buffer and cancel if not filled within 15 minutes.
Once a first bot is stable, expand to baskets and constraints. Combine equity, bond and commodity ETFs, then enforce portfolio rules like max correlation exposure or a minimum cash allocation. This keeps the system aligned with your risk plan as markets rotate.
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Risk limits are part of the strategy, not an afterthought. Define max exposure per ETF, max total equity allocation and a hard stop that moves to cash if drawdown hits your level. Constraints keep a model tradable in real conditions.
Templates are starting points, not black boxes. Clone one, change the timeframe and add a second confirmation like volume or ADX. Save versions so you can compare behavior side by side.
Set real-time alerts for fills, partial fills and rule triggers. Review a timeline of decisions to confirm the engine acted as expected. If markets change, pause a rule set and resume when conditions normalize.
Start in simulation to validate order types, schedules and edge cases like holidays. Then go live with small size and a strict max daily order count. Scale only after you trust the process.
A good system is boring in the best way. Once you have a stable core, add overlays like volatility targeting or defensive rotation. Keep changes incremental so you can attribute improvements to specific edits.
Connect your broker, pick a template and adjust the rules to match your risk budget. Coinrule helps you turn repeatable logic into consistent execution, with monitoring and controls built in.
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