Build an AI-guided stock selection workflow with Coinrule. Automate screening, entries, exits and rebalancing across brokers using clear, testable rules.
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Instead of juggling watchlists and alerts, an AI stock picker workflow on Coinrule turns your signals into rules you can run. Connect Alpaca, Robinhood, Charles Schwab, TradeStation and more, then automate entries, exits and position sizing. Example: if price breaks above the 50-day MA and volume is 1.5x the 20-day average, buy 2% of cash and set a 3% stop. You keep control because every condition is explicit, logged and easy to adjust.
Traders often confuse a good idea with a repeatable process. The platform helps you translate screening logic into rule-based execution so you can compare outcomes across timeframes and symbols. Run the same playbook on a basket of tickers, or restrict it to ETFs for smoother exposure. When results drift, tweak one variable at a time instead of reinventing the whole approach.
Risk controls matter more than clever signals. Add max allocation per ticker, daily loss limits and cooldown timers so the system does not overtrade. For example, stop new entries after 3 losses in a day, or cap any single position at 7% of equity. You can also require confirmation like RSI above 50 before adding to winners. These constraints keep your process consistent when markets get noisy.
Broker-Connected Automation
Coinrule connects to stock and ETF venues through supported brokers, so your workflow stays in one place. Run strategies on WeBull, Trading212, Tradier and Charles Schwab while keeping a unified view of rules and activity. Start with paper-style sizing, then move to live execution once you trust the logic. Alerts and logs make it easy to audit every decision.
Transparent Rules, Not Black Boxes
If you use AI-style signals, Coinrule helps you wrap them in clear conditions and risk limits. That means you can pause, clone and iterate without guessing why a trade happened. The goal is disciplined execution, not mystery predictions.
MA Crossover with Volume Filter
Buys when MA20 crosses above MA50 and volume is above a set threshold. Exits on a bearish cross or a stop. Built for liquid large caps.
Stop Loss and Trailing Take Profit
Enters on your chosen trigger and sets a fixed stop. Trails profit after a defined gain to lock in upside. Useful in fast reversals.
Portfolio Rebalance
Rebalances a stock and ETF basket back to target weights on a schedule. Adds to underweights and trims overweights. Uses a drift threshold to reduce churn.
Volatility Regime Switcher
Uses ATR to detect high-volatility regimes and reduces position size. In calmer periods, restores normal sizing. Adds a cooldown to avoid rapid flip-flops.
Opening Range Breakout
Defines the first 30-minute range, then buys on a break above the high. Uses a tight stop and staged exits. Designed for active sessions.
MA Crossover with Volume Filter
Buys when MA20 crosses above MA50 and volume is above a set threshold. Exits on a bearish cross or a stop. Built for liquid large caps.
Stop Loss and Trailing Take Profit
Enters on your chosen trigger and sets a fixed stop. Trails profit after a defined gain to lock in upside. Useful in fast reversals.
Portfolio Rebalance
Rebalances a stock and ETF basket back to target weights on a schedule. Adds to underweights and trims overweights. Uses a drift threshold to reduce churn.
Volatility Regime Switcher
Uses ATR to detect high-volatility regimes and reduces position size. In calmer periods, restores normal sizing. Adds a cooldown to avoid rapid flip-flops.
Opening Range Breakout
Defines the first 30-minute range, then buys on a break above the high. Uses a tight stop and staged exits. Designed for active sessions.
Mean Reversion with Z-Score
Buys when price deviates below a moving average by a negative Z-score. Exits near the mean or on a time stop. Fits range-bound periods.
ADX Trend Strength Filter
Takes trend entries only when ADX is above a threshold to avoid chop. Exits when ADX weakens or on a stop. Helps filter false breakouts.
Minimum Variance Rebalance
Maintains a defensive basket by rebalancing toward lower-volatility holdings. Rechecks weights monthly and caps single-name exposure. Aims for smoother swings.
Earnings Drift Rider
After earnings, enters if price holds above the post-release high for multiple sessions. Exits on a moving average break or after a time limit. Targets continuation moves.
Range Bound Reversal
Buys near support when RSI is low and price rejects the range floor. Sells near resistance or when momentum fades. Uses a stop just below support.
Unlike a black-box model, Coinrule lets you combine simple signals into a robust decision stack. You might require trend alignment (price above MA200), momentum confirmation (RSI above 55) and a volatility check (ATR below a threshold) before entering. Example: buy 1.5% of equity when MA50 is above MA200 and the last close breaks the 20-day high, then place a 2.5% stop. Because each step is explicit, you can review performance and refine without overfitting.
Many investors use AI tools to summarize news, rank fundamentals or surface unusual activity. The mistake is letting that output become an unbounded trading impulse. With Coinrule, you can turn those insights into constraints: only trade top-5 ranked tickers, only during market hours, and only if spread and volume meet your minimums. This keeps the process measurable and reduces decision fatigue.
Risk controls include bracket-style logic, trailing exits and time stops. Here is a concrete setup: enter with 2% size, take 50% profit at +4%, trail the remainder by 2%, and exit fully if the position is still flat after 10 trading days. You can also scale in: add 1% more only after a close above the prior swing high. These mechanics matter as much as the entry signal.
Once a first strategy is stable, you can run separate rules for trend, mean reversion and rebalancing. Keep them isolated by ticker groups so they do not fight each other. A simple naming convention and scheduled reviews make the system easier to manage. The activity log shows what fired and why.
Launch BotFAQ
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Your account stays with your broker, and the platform focuses on execution and monitoring. Pause rules instantly, set trading windows and require confirmations before adding risk. This separation helps you stay systematic without giving up oversight.
Slippage, gaps and news shocks happen. Build rules that assume imperfect fills by using limit logic where appropriate and adding time-based exits. A safeguard like no new entries in the last 15 minutes can reduce end-of-day noise. Robust beats clever.
If you invest in themes, rebalancing can prevent one winner from dominating your portfolio. Set a monthly schedule and a drift threshold like 1% to avoid constant trading. This approach can complement trend rules that focus on entries and exits.
Alerts should lead to decisions, not anxiety. Configure notifications for drawdown, exposure and rule triggers so you know when to intervene. Review the log weekly to spot repeated false signals and tighten filters. Small improvements compound.
As you add more tickers, use groups and caps to keep complexity manageable. For example, limit total sector exposure to 25% and any single position to 7%. Add a cooldown like one trade per symbol per day to reduce churn. Structure keeps the system stable.
Pick one simple edge, define the exact trigger, then wrap it with sizing and exits. Start small, measure results and iterate. When you are ready, expand into multiple playbooks and scheduled rebalancing for broader coverage.
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