Build rule-based stock bots for WeBull with Coinrule. Automate entries, exits and risk controls from a visual builder, then monitor performance with clear logs.
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Most traders start with alerts and manual orders, then realize consistency matters more than speed. With Coinrule, webull algo trading becomes a set of clear if-then rules you can test, launch and monitor from one dashboard.
Link your brokerage via supported integrations and run strategies across WeBull, Alpaca, TradeStation and Robinhood from the same interface. You stay in charge of position sizing, symbols and limits, while the engine handles repeatable execution and tracking.
Every action is logged with timestamps, triggers and order outcomes so you can review what happened and why. That audit trail makes it easier to refine conditions, compare variants and avoid changing a strategy mid-stream.
Broker-ready automation
Use time windows for market hours, avoid low-liquidity periods and add guardrails like max daily trades. You can run separate rule sets for long-only ETFs and higher-volatility single names, then pause or clone them as your plan evolves.
Risk-first defaults
Position sizing, stop logic and exposure caps are first-class settings, not afterthoughts. Set a max allocation per ticker, a portfolio drawdown limit and a cooldown after a stop so the system does not overtrade.
Opening Range Breakout
Trades the first 15 minutes range. Buys on a break above the high with volume confirmation. Exits on a 1.5x ATR stop or a timed close before the session ends.
MA Crossover with Volume Filter
Enters when a fast MA crosses above a slow MA and volume is above its 20-day average. Exits on the reverse cross or a trailing stop once profit exceeds 4 percent.
RSI Oversold Rebound
Buys when RSI drops below 30 on 1-hour candles and price holds above a longer-term MA. Sells when RSI recovers above 55 or after a 2 percent take profit.
Stop Loss and Trailing Take Profit
Adds a fixed stop, then switches to a trailing take profit after price moves in your favor. Example: 2 percent stop, then trail by 1 percent once up 3 percent. Helps protect gains.
Grid Trading
Places staggered buy and sell levels inside a defined range. Buys every 1 percent drop and sells every 1 percent rise. Best for sideways periods with strict exposure limits.
Opening Range Breakout
Trades the first 15 minutes range. Buys on a break above the high with volume confirmation. Exits on a 1.5x ATR stop or a timed close before the session ends.
MA Crossover with Volume Filter
Enters when a fast MA crosses above a slow MA and volume is above its 20-day average. Exits on the reverse cross or a trailing stop once profit exceeds 4 percent.
RSI Oversold Rebound
Buys when RSI drops below 30 on 1-hour candles and price holds above a longer-term MA. Sells when RSI recovers above 55 or after a 2 percent take profit.
Stop Loss and Trailing Take Profit
Adds a fixed stop, then switches to a trailing take profit after price moves in your favor. Example: 2 percent stop, then trail by 1 percent once up 3 percent. Helps protect gains.
Grid Trading
Places staggered buy and sell levels inside a defined range. Buys every 1 percent drop and sells every 1 percent rise. Best for sideways periods with strict exposure limits.
Volatility Breakout
Enters when price breaks above the prior day high and ATR expands. Uses a tight initial stop and scales out at 1R and 2R targets. Avoids chop with a volatility filter.
DCA Accumulator
Splits a fixed budget into scheduled buys, such as $500 per month as four $125 weekly orders. Adds a pause rule if price is 8 percent above the 30-day average. Smooths entries.
Bollinger Band Mean Reversion
Buys when price closes below the lower band and RSI is below 40. Sells at the middle band or on a time stop after 3 days. Targets snapbacks, not trends.
Support and Resistance Bounce
Buys near a defined support zone after a rejection candle and improving volume. Exits at the next resistance level or if support breaks by 1 percent. Works well with clear levels.
Portfolio Rebalance
Rebalances a basket back to target weights on a schedule, such as weekly. Adds a drift threshold like 3 percent before trading. Keeps risk aligned without constant manual tweaks.
Instead of running 24-7, stock automation should respect session structure. Set rules like: only trade between 9:35 and 15:45 ET, ignore signals in the first 5 minutes, and stop after 3 trades per symbol per day. Add a volatility gate such as ATR above its 14-day average to avoid dead tape. These constraints reduce noise and make results easier to interpret.
Traders using webull algo trading often start with three simple conditions. Example 1: buy when RSI(14) < 30 on 1-hour candles, then sell when RSI > 55. Example 2: enter on a 20/50 MA cross only if volume is 20 percent above the 20-day average, then trail by 1 percent after a 3 percent move. Example 3: cut risk with a hard stop at 2 percent and a cooldown of 60 minutes after a stop-out.
Run the same playbook across accounts without duplicating work. You can keep a conservative ETF bot on Charles Schwab while testing a faster strategy on Tradier or Tastytrade, then compare logs side by side. Exposure caps help prevent accidental concentration when multiple rules target the same ticker. When you change a parameter, clone the rule first so you can measure the impact cleanly.
Unlike discretionary trading, a bot will do exactly what you told it to do. Use small sizing at first, set max position limits and review the order history weekly. Treat every change as a new version and keep notes on why you adjusted it. Consistency comes from process, not constant tinkering.
Launch BotFAQ
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Priya K.
Michael R.
Giulia C.
Kenji M.
Valentina C.
Start with one indicator and one risk rule, then add complexity only if it improves results across different periods. A common mistake is stacking too many filters until the strategy only works on the last month of data. Keep a baseline version running so you always have a control to compare against.
Set notifications for large fills, repeated rejections and drawdown thresholds so you can intervene quickly. If a symbol gaps beyond your stop, you want to know immediately. Alerts also help you learn which market regimes break your assumptions.
Schedule a weekly review: check win rate, average loss, slippage and the number of trades taken. If a rule deviates from expectations, pause it and inspect the trigger sequence. Small operational habits often improve outcomes more than new indicators.
Increase size in steps, such as 25 percent increments, only after stable behavior over at least 20-30 trades. Keep the same symbols and time window while scaling so you can attribute changes correctly. When you expand to new tickers, treat it like a new deployment.
If you want a broader overview of systematic execution, see /automated-trading. For indicator-driven ideas and ready templates, explore /trading-strategies. Use those resources to turn a thesis into a rule you can test and monitor.
Build one rule, run it small, and let the data tell you what to change. Coinrule is built for traders who want repeatable execution, clear controls and an audit trail they can trust.
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