Build rule-based ETF orders with Coinrule. Automate entries, exits, DCA and rebalancing across brokers like Tradier, Alpaca, E*TRADE and Robinhood.
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Instead of watching charts all day, Coinrule turns ETF trading automation into simple if-this-then-that rules you can test and run. For example, buy 25% of your planned size if SPY drops 2% in a day, then add the remaining 75% only if it falls another 3% within 5 days.
Your account stays at your broker while the platform sends orders through secure connections. Link Alpaca, Robinhood, TradeStation, WeBull or Charles Schwab, then choose which symbols, order types and position limits each strategy can use. You can pause, edit or clone rules any time, and every action is recorded for review.
Traders often start with one liquid fund, then expand to a basket with shared risk limits. You might run a trend rule on QQQ, a defensive rotation rule between TLT and SHY, and a cash-protection stop that reduces exposure after a 6% portfolio drawdown. The system keeps sizing consistent so one idea cannot dominate the account.
Risk Guardrails
Risk controls are first-class settings, not afterthoughts. Set a hard stop like 1.8% below entry, then trail by 1.2% once profit exceeds 3%. Add a time stop that exits after 10 trading days if price never reaches your target, so capital does not get stuck.
Execution Discipline
Rules run the same way every session, which helps remove hesitation and revenge trading. You can schedule checks at market open, mid-day and close, or only place orders during a defined window like 10:00 to 15:30 ET to avoid thin prints.
Portfolio Rebalance
Rebalances a basket back to target weights weekly. Triggers when any holding drifts more than 3%. Uses max order size caps to reduce slippage.
DCA Accumulator
Splits a monthly budget into weekly buys. Adds an extra tranche if price dips 4% from the 20-day high. Pauses buys if volatility spikes above a set threshold.
MA Crossover with Volume Filter
Buys when the fast MA crosses above the slow MA and volume is above its 20-day average. Sells on the reverse cross. Designed for daily timeframes.
Volatility Regime Switcher
Switches between risk-on and defensive assets when realized volatility crosses a threshold. Example: move from equities to bonds if 10-day vol rises above 22%. Rechecks daily.
Minimum Variance Rebalance
Targets lower portfolio variance by adjusting weights on a schedule. Adds constraints like max 35% per ETF. Uses a rebalance band to avoid overtrading.
Portfolio Rebalance
Rebalances a basket back to target weights weekly. Triggers when any holding drifts more than 3%. Uses max order size caps to reduce slippage.
DCA Accumulator
Splits a monthly budget into weekly buys. Adds an extra tranche if price dips 4% from the 20-day high. Pauses buys if volatility spikes above a set threshold.
MA Crossover with Volume Filter
Buys when the fast MA crosses above the slow MA and volume is above its 20-day average. Sells on the reverse cross. Designed for daily timeframes.
Volatility Regime Switcher
Switches between risk-on and defensive assets when realized volatility crosses a threshold. Example: move from equities to bonds if 10-day vol rises above 22%. Rechecks daily.
Minimum Variance Rebalance
Targets lower portfolio variance by adjusting weights on a schedule. Adds constraints like max 35% per ETF. Uses a rebalance band to avoid overtrading.
Sharpe Targeting Rebalance
Adjusts exposure to keep a target risk-adjusted profile. Reduces allocation after a losing streak of 3 periods. Increases slowly after new equity highs.
Stop Loss and Trailing Take Profit
Sets an initial stop after entry, then trails profits once price moves in your favor. Example: stop at -2%, trail at 1% after +3%. Helps lock gains during trends.
Breakout + Retest
Buys after a breakout above resistance, then waits for a retest to confirm. Places a stop just below the retest low. Exits on a failed retest or target hit.
Bollinger Band Mean Reversion
Buys when price closes below the lower band and RSI is under 35. Sells near the middle or upper band. Works best in range-bound conditions.
Risk Parity Allocator
Balances positions so each contributes similar risk. Uses volatility estimates to size trades. Rebalances monthly and applies a max leverage and max drawdown rule.
Templates are starting points you can adapt to your own watchlist and risk rules. ETF trading automation works best when you define clear triggers, sizing and an exit plan before you go live. A common setup is trend-following on SPY with a defensive switch into TLT when momentum weakens, plus a weekly rebalance to keep allocations on track.
Users often begin with three simple conditions. Example 1: buy if RSI(14) on 4-hour candles drops below 30, then sell half when RSI rises above 55. Example 2: add 10% more exposure only after price closes above the 50-day MA for 3 consecutive sessions. Example 3: if the position is up 8%, tighten the trailing stop from 2% to 1% to protect gains.
Unlike a spreadsheet plan, live execution needs guardrails for gaps, partial fills and changing spreads. Coinrule lets you set order types, cooldowns and max trades per day so a noisy session does not trigger a cascade. You can require confirmation like two closes above a level, or a minimum distance of 0.5% from the last fill before adding again. Logs make it easy to audit what happened and why.
After a week or two, review the trade log and adjust one variable at a time. Tighten stops, widen entry bands, or reduce frequency if the rule is too reactive. Scaling becomes straightforward once the process is stable.
Launch BotFAQ
Emma T.
Lars H.
Priya K.
Diego R.
Hiroshi Y.
Amara N.
Every rule has visible conditions, actions and limits, so you can explain what the bot will do before it does it. Use notifications for fills, errors and threshold breaches. That transparency matters when markets gap at the open.
Position sizing can be fixed, percentage-based, or tied to available cash. Add constraints like max 20% in any single ETF and max 2 new entries per day. These limits help keep a good idea from becoming an oversized bet.
Schedule checks around the session you care about, and avoid placing orders outside your preferred window. Many users run signals after the open, then allow exits any time. This keeps behavior predictable across days.
Clone a strategy, adjust one parameter, and run it side by side with smaller size. Compare logs to see which version behaves better in the same regime. Iteration becomes a controlled process, not guesswork.
Start with a template, add your constraints, then go live with conservative sizing. Once you trust the behavior, expand to more symbols or a rebalance basket. The goal is repeatable execution you can maintain.
Connect a broker, pick a template, and define your risk limits before the next session. You will spend less time clicking and more time improving the rules that drive decisions. When you are ready, scale gradually and keep reviewing the logs.
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