Automate an AI focused ETF plan with Coinrule using rule-based entries, exits and rebalancing across brokers, with clear risk limits and logs.
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Instead of reacting to headlines, use Coinrule to manage an ai etf plan with clear triggers and guardrails. Set rules like buy 2 percent when price drops 4 percent in 5 days, then take profit at 8 percent. Run the same logic across Alpaca, Charles Schwab, WeBull and Tradier from one dashboard.
Traders often like AI exposure but struggle with timing and position sizing. Coinrule turns your thesis into repeatable automation with allocation caps, cooldown timers and stop rules. You can define a max 25 percent portfolio weight, pause buys after a 3 trade streak, and log every action for review.
When you have a hypothesis, you need a way to validate it without overtrading. Build conditions using moving averages, RSI and time windows, then paper test before going live. For example, enter when MA50 crosses above MA200 on daily candles, and exit if RSI falls below 40 for two sessions. The platform keeps the logic consistent so you can compare results month to month.
ETF Automation Templates
Templates help you launch faster, then customize. Clone a rebalance rule, adjust thresholds, and add a safety stop in minutes. You can schedule weekly checks, set a 1 percent max slippage guard, and require confirmation from two indicators before buying.
Broker Connected Execution
Connect your brokerage account and let the engine place orders when conditions match. You keep control of your account while Coinrule executes your rules and records decisions. Use separate strategies for entries, exits and hedges so changes stay isolated and auditable.
Portfolio Rebalance
Rebalances to target weights weekly. If any holding drifts more than 3 percent, it trims or adds. Adds a max trade size cap to reduce churn.
Minimum Variance Rebalance
Shifts weights toward lower volatility holdings on a monthly schedule. Uses a volatility lookback window and a max allocation limit. Exits if portfolio volatility rises above a set threshold.
Sharpe Targeting Rebalance
Adjusts exposure to aim for a target risk adjusted return. Recomputes on a fixed cadence and applies position caps. Pauses changes during high volatility weeks.
Volatility Regime Switcher
Switches between risk-on and defensive allocations based on volatility. If 20 day volatility exceeds a threshold, it reduces exposure. Restores exposure after a cooldown period.
MA Crossover with Volume Filter
Buys when MA20 crosses above MA50 and volume is above its 10 day average. Sells on the reverse cross or a fixed stop. Designed for trend confirmation.
Portfolio Rebalance
Rebalances to target weights weekly. If any holding drifts more than 3 percent, it trims or adds. Adds a max trade size cap to reduce churn.
Minimum Variance Rebalance
Shifts weights toward lower volatility holdings on a monthly schedule. Uses a volatility lookback window and a max allocation limit. Exits if portfolio volatility rises above a set threshold.
Sharpe Targeting Rebalance
Adjusts exposure to aim for a target risk adjusted return. Recomputes on a fixed cadence and applies position caps. Pauses changes during high volatility weeks.
Volatility Regime Switcher
Switches between risk-on and defensive allocations based on volatility. If 20 day volatility exceeds a threshold, it reduces exposure. Restores exposure after a cooldown period.
MA Crossover with Volume Filter
Buys when MA20 crosses above MA50 and volume is above its 10 day average. Sells on the reverse cross or a fixed stop. Designed for trend confirmation.
Optimised RSI and MA Strategy
Enters when RSI drops below 35 while price stays above MA200. Takes profit when RSI exceeds 65. Adds a time stop to exit after 20 sessions if momentum stalls.
Buy the Dips
Adds in tranches on pullbacks. Buys 1 percent after a 3 percent drop, then another 1 percent after 6 percent. Stops adding if drawdown exceeds a defined limit.
DCA Accumulator
Invests a fixed amount on a schedule, such as $125 each week. Skips buys if price is above a chosen moving average by more than 5 percent. Tracks average entry automatically.
Stop Loss and Trailing Take Profit
Sets a hard stop, then trails profits once price moves in your favor. Example: stop at 4 percent, trail at 2 percent after a 6 percent gain. Helps lock in trends without constant monitoring.
Risk-On/Risk-Off Macro Switch
Rotates exposure based on a simple macro proxy like drawdown or trend. Reduces risk after a 7 percent peak to trough move. Re-enters after recovery and a confirmation window.
Unlike one time buys, thematic ETFs often need maintenance as volatility changes. You can set a monthly rebalance, cap exposure at 30 percent, and add a rule to reduce risk if drawdown hits 10 percent. This keeps your plan aligned with your risk tolerance instead of the latest narrative.
For an ai etf approach, simple triggers often beat complex models. Try a rule that buys only after a 5 day pullback of 3 percent and a recovery close above yesterday high. Add a cooldown of 48 hours to avoid rapid fire trades. Keep the logic readable so you can audit why each order happened.
Every action is logged with the condition that triggered it, the order type and the timestamp. You can review missed signals, adjust thresholds and relaunch without rewriting everything. If you manage multiple accounts, separate strategies by goal, such as accumulation, trimming and protection. See /automated-trading for more on rule design.
Risk controls should be part of the workflow, not an afterthought. Set max daily orders, max position size and portfolio level stops. Add an emergency pause that disables all strategies if a threshold is hit. These guardrails help keep automation predictable during fast markets.
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Traders often pair a thematic ETF with broader holdings to avoid concentration. Use a basket approach with weights like 15 percent theme, 60 percent core index, and 25 percent defensive. Then automate monthly rebalances so drift does not silently change your risk profile.
When volatility spikes, short timeframes can generate false signals. Consider daily candles for trend rules and weekly schedules for rebalancing. A simple filter like require two consecutive closes above MA50 can reduce churn. You can still keep a protective stop for sudden drops.
Sizing is where many plans break down. Define a fixed percent per entry, such as 1 to 2 percent, and add a max total allocation. If you scale in, use a ladder like 1 percent, 1 percent, then stop. Mechanical sizing makes results easier to evaluate.
Rules can conflict, such as a buy trigger and a risk off trigger on the same day. Use priority logic, cooldowns and max orders per day to keep behavior predictable. Review the event log after volatile sessions to confirm the engine acted as intended. This is how you turn automation into a process, not a mystery.
Paper testing helps you validate assumptions without pressure. Track how often signals fire, average holding time and worst drawdown. Adjust one variable at a time, such as RSI threshold from 35 to 30, and compare. Once stable, go live with small size and scale gradually.
Start with one simple rule set, then add complexity only if it improves outcomes. Many users run a scheduled accumulator plus a separate protection rule, rather than one giant strategy. Keep notes on why you changed thresholds so you can learn over time. See /templates to explore more building blocks.
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