Build a quant-style workflow without code. Turn signals into rule-based execution across Binance, Kraken, OKX and more, with clear risk controls and logs.
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Instead of rewriting the same checklist every trade, a Quant AI platform on Coinrule turns your logic into reusable rules. Set triggers like RSI below 30 on 1-hour candles, buy 2% of balance, then place a 3% stop and a 6% take profit.
Traders use the visual builder to combine indicators, price moves and time filters into one workflow. Chain conditions like MA50 above MA200, volume up 20% versus the prior day and price breaking yesterday high. The system executes entries, exits and alerts exactly as defined.
Run one strategy across multiple venues while keeping a unified view of exposure. Connect accounts via API keys for centralized exchanges, then route orders where liquidity and fees make sense. For on-chain execution, automate via smart accounts while keeping self-custody.
Risk Controls First
Risk controls include max position size, daily loss limits and rule-level cooldowns so a bot cannot overtrade. Stop new entries after a 4% drawdown in 24 hours, or require 2 confirmations before buying. Logs and alerts help you audit what happened and why.
Templates And Building Blocks
Start from templates, then adapt them to your market, timeframe and risk budget. Clone a strategy, change the candle interval from 4H to 1H, tighten stops from 3% to 1.5%, and compare results cleanly.
Buy the Dips
Buys after a defined pullback like -5% in 6 hours with MA200 rising. Adds one extra entry if price drops another 3%. Exits on a rebound target or trailing stop.
Grid Trading
Places a ladder of buys and sells inside a defined range. Uses equal spacing or ATR-based spacing for choppy markets. Stops the grid if price breaks beyond the range.
Volatility Breakout
Enters on a recent high break while ATR expands. Confirms with volume or trend strength to reduce false moves. Exits with a trailing take profit and a hard stop.
Stop Loss and Trailing Take Profit
Adds a fixed stop and a trailing exit to any entry signal. Example: stop at -2.5%, trail after +4%. Helps protect downside while letting winners run.
MA Crossover with Volume Filter
Buys when a fast MA crosses above a slow MA and volume is above its 20-period average. Sells on the cross back or when RSI exceeds a ceiling. Fits 1H to 1D charts.
Buy the Dips
Buys after a defined pullback like -5% in 6 hours with MA200 rising. Adds one extra entry if price drops another 3%. Exits on a rebound target or trailing stop.
Grid Trading
Places a ladder of buys and sells inside a defined range. Uses equal spacing or ATR-based spacing for choppy markets. Stops the grid if price breaks beyond the range.
Volatility Breakout
Enters on a recent high break while ATR expands. Confirms with volume or trend strength to reduce false moves. Exits with a trailing take profit and a hard stop.
Stop Loss and Trailing Take Profit
Adds a fixed stop and a trailing exit to any entry signal. Example: stop at -2.5%, trail after +4%. Helps protect downside while letting winners run.
MA Crossover with Volume Filter
Buys when a fast MA crosses above a slow MA and volume is above its 20-period average. Sells on the cross back or when RSI exceeds a ceiling. Fits 1H to 1D charts.
Bollinger Band Mean Reversion
Buys when price closes below the lower band and RSI is oversold. Takes profit at the mid-band or upper band based on volatility. Uses a time stop if the bounce fails.
RSI Divergence Hunter
Looks for bullish divergence where price makes a lower low and RSI makes a higher low. Enters on a confirmation close with a stop under the swing low. Exits at prior resistance or on RSI rollover.
Portfolio Rebalance
Rebalances back to target weights on a schedule like weekly. Sells overweight assets and buys underweight ones to control drift. Can pause during extreme volatility spikes.
Perps Trend Follower
Trades perpetuals when signals align, such as Supertrend up and ADX above a threshold. Uses smaller sizing and strict stops to manage leverage risk. Can reduce exposure when funding is expensive.
TWAP Execution Accumulator
Splits a larger order into smaller slices over time to reduce slippage. Example: buy $1,000 over 2 hours in 20 orders. Pauses if price moves beyond a set percent.
Users typically start by linking Binance, Bybit, KuCoin or Bitget, then deploying the same rule set across accounts. A Quant AI platform setup keeps spot bots, hedges and long-term DCA organized in one dashboard with clear status and logs.
Rather than guessing, test conditions on historical data to see how a rule behaves in different regimes. Compare variants where only one parameter changes, like RSI 30 versus RSI 35, to avoid overfitting. Then paper trade or go live with small sizing.
Once a first bot is stable, treat it like a versioned model. Duplicate it, change one variable, and track performance over a fixed window such as 30 days. Schedule rotations, for example switching from breakout rules to mean reversion when volatility compresses.
For decentralized execution, smart accounts keep control in your hands while enabling limited permissions via session keys. Orders can route through Li.fi to find efficient liquidity across pools. This helps you automate without handing over custody.
Explore ToolsFAQ
Lars H.
Priya K.
Diego R.
Sakura O.
Michael R.
Giulia C.
Separate signal generation from execution so you can see what each condition contributes. Keep rules readable, name them well and document assumptions. When performance changes, you will know what to adjust.
Use smaller size when ATR expands and scale up only when conditions stabilize. A simple rule is to risk 0.5% per trade with a 2% stop, then cap total open risk at 3%. These constraints prevent one idea from dominating the portfolio.
Add protective logic like: if BTC drops 3% in 30 minutes, reduce alt exposure by 25% and pause new longs for 2 hours. Set global kill switches and alert thresholds so automation reacts to sudden regime shifts.
Run spot accumulation and leveraged trend systems as separate strategies with different limits. Keep leverage modest, define liquidation-aware stops and avoid stacking correlated positions. Clear separation makes risk reporting simpler.
Review weekly, not hourly. Track a small set of metrics like win rate, average loss, max drawdown and time in market. Change one parameter at a time so you can attribute improvements.
Start with one template, set three rules you can explain, and run it with conservative sizing for two weeks. Then add a second strategy that diversifies the logic, such as mean reversion plus trend following. Consistency comes from process, not prediction.
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