Build systematic crypto strategies with Coinrule. Create no-code rules, test ideas, and automate execution across major exchanges with built-in risk controls.
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Instead of turning every hypothesis into a coding project, Coinrule helps you validate it fast. Use the AI quant trading platform to translate signals into rules, then deploy them with consistent execution on Binance, Kraken, Bybit and OKX.
Traders start with templates, then refine conditions like RSI, moving averages and time windows. Combine triggers, position sizing and exits in one flow so the system behaves consistently across regimes. Logs and alerts make it easy to review what happened and why.
Risk controls are first-class: define max allocation per asset, cap daily trades, and add stop loss plus trailing take profit. For example, risk 1 percent per trade, stop out at 2.5 percent, then trail by 1.2 percent after price moves 4 percent. These constraints help prevent good logic from being ruined by bad execution.
Quant Templates And Blocks
Templates cover mean reversion, trend following, breakouts and rebalancing so you can start from a working baseline. Clone a template, change one variable at a time, and compare results before going live. This keeps iteration disciplined and measurable.
Non-Custodial By Design
Your funds stay on your exchange accounts while Coinrule connects via API keys, so you keep control. For on-chain automation, you can use smart accounts with limited permissions and route trades via Li.fi. That separation reduces operational risk while keeping execution flexible.
Buy the Dips
Buys after a 5 percent drop within 4 hours and confirms with RSI below 35. Adds a second entry if price falls another 3 percent. Exits on a 6 percent rebound or a trailing take profit.
Grid Trading
Places a grid of buys and sells inside a defined range, like plus or minus 4 percent around a mid price. Re-centers if price breaks out for 2 hours. Uses a hard stop if range expands beyond 10 percent.
Volatility Breakout
Enters when price closes above the prior day high and ATR expands by 20 percent. Sets stop loss at 1.8x ATR and takes partial profit at 1x ATR. Trails the remainder until momentum fades.
Bollinger Band Mean Reversion
Buys when price closes below the lower band and RSI is under 40 on 1-hour candles. Sells at the middle band, then exits at the upper band. Adds a time stop if no reversion occurs in 12 hours.
Supertrend Momentum
Goes long when Supertrend flips bullish on 4-hour candles and volume is above its 20-period average. Exits on the first bearish flip. Adds a trailing stop to protect gains during strong trends.
Buy the Dips
Buys after a 5 percent drop within 4 hours and confirms with RSI below 35. Adds a second entry if price falls another 3 percent. Exits on a 6 percent rebound or a trailing take profit.
Grid Trading
Places a grid of buys and sells inside a defined range, like plus or minus 4 percent around a mid price. Re-centers if price breaks out for 2 hours. Uses a hard stop if range expands beyond 10 percent.
Volatility Breakout
Enters when price closes above the prior day high and ATR expands by 20 percent. Sets stop loss at 1.8x ATR and takes partial profit at 1x ATR. Trails the remainder until momentum fades.
Bollinger Band Mean Reversion
Buys when price closes below the lower band and RSI is under 40 on 1-hour candles. Sells at the middle band, then exits at the upper band. Adds a time stop if no reversion occurs in 12 hours.
Supertrend Momentum
Goes long when Supertrend flips bullish on 4-hour candles and volume is above its 20-period average. Exits on the first bearish flip. Adds a trailing stop to protect gains during strong trends.
MA Crossover with Volume Filter
Buys when MA20 crosses above MA50 and volume is 15 percent above its 30-day average. Exits when MA20 crosses back below MA50. Skips entries if spread widens beyond a set threshold.
RSI Divergence Hunter
Looks for bullish divergence: price makes a lower low while RSI makes a higher low on 1-hour charts. Enters after a close above the prior candle high. Exits at a fixed 3 percent target or on RSI above 65.
Donchian Channel Turtle
Enters on a breakout above the 20-period Donchian high and adds on new highs. Exits on a close below the 10-period Donchian low. Caps exposure to avoid over-leveraging in choppy periods.
Portfolio Rebalance
Rebalances weekly to target weights, such as 50 percent BTC, 30 percent ETH and 20 percent SOL. Trades only if drift exceeds 3 percent to reduce fees. Adds a risk-off rule if volatility spikes.
Funding Rate Hedge
When funding turns strongly positive, opens a hedge to reduce carry risk. Closes the hedge when funding normalizes for 6 hours. Useful for smoothing returns during crowded long periods.
Users treat the platform as a research-to-execution bridge. You might set: if BTC drops 5 percent in 6 hours and RSI is below 30, buy 2 percent of balance, then sell 50 percent at plus 3 percent and trail the rest by 1 percent. Those rules are easy to audit, improve and repeat.
Once you connect venues like Coinbase, KuCoin and Bitget, the same strategy logic can run wherever you trade. Separate bots by exchange, asset or timeframe, then monitor positions in one place. This reduces tool sprawl and makes risk easier to manage.
For decentralized execution, Coinrule supports smart accounts and session keys for limited permissions. Automate swaps on Base or Arbitrum without handing over custody, and routing can seek better liquidity across pools. This makes it practical to run systematic rules beyond centralized venues.
After a run, review triggers, fills and exits to see which conditions mattered. Set real-time alerts for drawdown, missed signals or unusual volatility so you can intervene when needed. The goal is a feedback loop that improves the strategy, not just more trades.
Build StrategyFAQ
Lars H.
Priya K.
Michael R.
Giulia C.
Kenji M.
Valentina C.
Traders who think in probabilities need tools that respect process. Coinrule focuses on repeatable rules, transparent triggers and clean monitoring, so you can evaluate decisions after the fact. That is closer to a quant workflow than manual clicking.
Use indicators like MA crossovers, Supertrend flips or Bollinger touches as triggers, then define what happens next. Add confirmations such as volume thresholds or time-of-day filters. This turns a chart idea into a testable playbook.
As you add more bots, central limits matter more than individual entries. Set portfolio exposure caps, per-asset limits and cooldowns after losses. These controls help keep a strategy set stable when correlations rise.
A good model can fail if execution is inconsistent or emotional. Automation applies the same logic every time, while you focus on research and review. That separation makes performance analysis cleaner.
Change one parameter, run it, and compare results to the prior version. Keep notes on why you changed it and what you expect to improve. Over time you build a library of strategies you actually understand.
Create a rule, test it, and deploy it with the same discipline you would expect from a professional workflow. Keep custody, control risk, and scale across venues as your process matures.
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