Turn ideas into automated stock rules with Coinrule. Build a WeBull-focused bot, backtest logic, and run entries, exits and risk controls with clear logs and alerts.
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Instead of watching every tick, build a webull ai trading bot in Coinrule that follows your plan with consistent execution. Set triggers like RSI below 30 on 1-hour candles, then buy a fixed dollar amount and place a 2.5% stop loss. Connect to WeBull, Alpaca, Robinhood, or E*TRADE and keep the same logic across accounts.
Traders use the rule builder to translate signals into actions without writing scripts. Combine indicators, price levels and time windows, then map them to market or limit orders. For example, buy when price breaks yesterday high by 0.8% and volume is above its 20-day average, then take profit in two steps at 3% and 6%. Every run is logged so you can review what fired and why.
Every bot needs guardrails, especially in fast markets. Add position sizing like 1% of equity per entry, daily loss limits, and cooldown timers after a stop. You can also cap exposure per ticker and pause automation during earnings week. Alerts help you stay informed without staring at charts.
Broker-ready automation
Link supported brokers and run the same strategy logic across multiple accounts. Many users start with WeBull for active trading, then mirror a calmer version on Charles Schwab or Tradier. You can separate long-term allocations from short-term rules while keeping one dashboard for monitoring.
Transparent execution logs
See each trigger, order and outcome in a clean activity feed. If a rule did not place an order, the system shows which condition failed so you can adjust thresholds. This makes iteration faster than guessing from chart screenshots.
Grid Trading
Places staggered buy and sell limits inside a defined range. Re-centers the grid if price moves beyond the band. Best for sideways periods with tight risk caps.
Moving Average Scalper
Enters when fast MA crosses above slow MA on 5-15 minute candles. Exits on crossback or a fixed 0.8-1.5% stop. Adds a time stop to avoid chop.
Optimised RSI and MA Strategy
Buys when RSI dips below 35 while price holds above MA100. Sells when RSI exceeds 65 or price closes below MA100. Designed for trend-friendly pullbacks.
Volatility Breakout
Triggers a buy when price breaks an ATR-based channel by 1.0x ATR. Sets an initial stop at 1.2x ATR and trails after +2x ATR profit. Targets expansion days.
Stop Loss and Trailing Take Profit
Opens a position on your chosen signal, then attaches a hard stop. Activates a trailing take profit after price gains 2-4%. Helps lock in winners without constant monitoring.
Grid Trading
Places staggered buy and sell limits inside a defined range. Re-centers the grid if price moves beyond the band. Best for sideways periods with tight risk caps.
Moving Average Scalper
Enters when fast MA crosses above slow MA on 5-15 minute candles. Exits on crossback or a fixed 0.8-1.5% stop. Adds a time stop to avoid chop.
Optimised RSI and MA Strategy
Buys when RSI dips below 35 while price holds above MA100. Sells when RSI exceeds 65 or price closes below MA100. Designed for trend-friendly pullbacks.
Volatility Breakout
Triggers a buy when price breaks an ATR-based channel by 1.0x ATR. Sets an initial stop at 1.2x ATR and trails after +2x ATR profit. Targets expansion days.
Stop Loss and Trailing Take Profit
Opens a position on your chosen signal, then attaches a hard stop. Activates a trailing take profit after price gains 2-4%. Helps lock in winners without constant monitoring.
MA Crossover with Volume Filter
Buys on MA cross only if volume is above its 20-period average. Exits when volume fades and the fast MA turns down. Reduces false signals in thin sessions.
Range Bound Reversal
Buys near support after a 2-3% pullback and a bullish close. Sells near resistance or after a fixed 1.5-3% bounce. Adds a tight stop below the range floor.
ATR Channel Breakout
Uses ATR channels to define dynamic support and resistance. Enters on a close outside the channel and exits on a return inside. Works well with a max-loss per trade rule.
Opening Range Breakout
Defines the first 15-30 minutes as the opening range. Buys on a break above that high with a stop below the range low. Takes profit at 1R and 2R targets.
Portfolio Rebalance
Rebalances holdings back to target weights on a schedule. Adds drift bands like 3-5% before trading to reduce churn. Useful for steady ETF or stock baskets.
Unlike black-box tools, Coinrule keeps your logic readable: IF conditions, THEN actions, plus risk limits. You can start from templates, then adjust thresholds to match your style. A typical setup might be: if price drops 5% in 4 hours, buy $200, then wait 24 hours before the next entry. Add a second rule that sells 25% at +4% and the rest at +8% to scale out. This is where a webull ai trading bot approach becomes practical: you iterate the rules, not the code.
Before you run automation, test the idea on historical data and sanity-check trade frequency. Look for overtrading, long flat periods and drawdowns that exceed your comfort zone. Then paper trade to confirm the rule triggers match your intent. Once live, start small and increase size only after consistent behavior.
Some users run one account for active swing rules and another for long-term investing. You might connect WeBull for faster iteration, then replicate a lower-frequency version on Trading212 or Tastytrade. Keeping strategies separated by goal makes performance easier to evaluate. It also prevents a short-term bot from interfering with a long-term allocation plan.
When conditions change, you can pause a single rule or halt everything. Set alerts for events like a 2% gap at the open, a daily loss limit hit, or an order rejection. These controls keep automation predictable. You remain the decision maker.
Launch BotFAQ
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Avoid stacking too many indicators that all say the same thing. Start with one entry signal, one exit signal and one risk rule, then expand. Watch for rules that trigger too often in choppy markets. Add a cooldown like 6-24 hours to reduce noise.
Pick a sizing method you can stick to, such as 0.5-1.5% of equity per trade. If you use fixed dollars, tie it to account size and rebalance monthly. Keep a max exposure per ticker so one name cannot dominate. Consistency matters more than precision.
Earnings can break technical setups with gaps and spreads. Many traders pause automation 24 hours before results and resume after the first post-earnings close. Another option is to require a wider stop on those days, like 4% instead of 2%. Choose one policy and apply it consistently.
Measure results per strategy, not per day. Track win rate, average win versus loss, and maximum drawdown. Compare live fills to expected triggers to spot slippage. Small improvements in exits often matter more than new entries.
Once a rule behaves well, scale slowly. Increase size in steps, for example 10% per week, while monitoring drawdowns and order rejections. Keep a rollback plan: clone the last stable version before edits. Treat changes like releases, not impulses.
Build a rule, test it, and let the system execute with discipline. Start with one ticker and one timeframe, then expand to a small basket. When you can explain every trigger in one sentence, you are ready to run it live.
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