Build AI-inspired, rule-based automation on Coinrule for crypto across OKX, Kraken, Binance and Coinbase, with clear logic, logs and risk controls.
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If you are evaluating a neural network trading platform, start by defining the behavior in plain conditions. Coinrule turns those ideas into transparent rules you can test, monitor and refine across Binance, Kraken and Coinbase.
Rather than trusting an opaque prediction, express signals as indicator and price logic. For example, buy when RSI drops below 30 on 1-hour candles and price is above MA200, then sell when RSI rises above 60. Every trigger is logged so you can review what happened and why.
Traders often split liquidity across venues, and manual execution creates drift. The platform connects via API keys and can run the same strategy on OKX, Bybit, KuCoin or Bitget with consistent sizing rules. You can pause, clone or schedule bots without touching your funds.
AI-Inspired Automation
Once you find an edge, convert it into a rule set with entries, exits and safeguards. Example: if BTC drops 5 percent within 4 hours, buy 2 percent of available balance, then place a 3 percent stop loss and a 6 percent take profit. This keeps decisions consistent during fast markets.
Risk-First Controls
Risk controls can include position limits, cooldown timers and max daily loss rules to keep automation bounded. Add trailing stops that tighten as profit grows, and set alerts when volatility spikes so you can intervene quickly.
Buy the Dips
Buys after a defined pullback, such as -3% to -7% from a recent high. Confirms with RSI below a threshold. Exits on a rebound target or trailing take profit.
Grid Trading
Places staggered buys and sells inside a price range to capture chop. Uses fixed or percentage spacing. Stops the grid if price breaks out beyond a set band.
Volatility Breakout
Enters when price closes above a breakout level and ATR expands. Adds a time stop if momentum fades. Exits with a trailing stop to ride trends.
Stop Loss and Trailing Take Profit
Opens a position on your chosen trigger, then attaches a hard stop loss. Switches to a trailing take profit after a gain, like 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 average. Sells on the crossback or when momentum weakens. Works well on 4-hour or daily charts.
Buy the Dips
Buys after a defined pullback, such as -3% to -7% from a recent high. Confirms with RSI below a threshold. Exits on a rebound target or trailing take profit.
Grid Trading
Places staggered buys and sells inside a price range to capture chop. Uses fixed or percentage spacing. Stops the grid if price breaks out beyond a set band.
Volatility Breakout
Enters when price closes above a breakout level and ATR expands. Adds a time stop if momentum fades. Exits with a trailing stop to ride trends.
Stop Loss and Trailing Take Profit
Opens a position on your chosen trigger, then attaches a hard stop loss. Switches to a trailing take profit after a gain, like 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 average. Sells on the crossback or when momentum weakens. Works well on 4-hour or daily charts.
Bollinger Band Mean Reversion
Buys when price closes below the lower band and RSI confirms oversold. Takes profit near the middle or upper band. Adds a time stop to avoid dead money trades.
Supertrend Momentum
Enters when Supertrend flips bullish and price holds above the line. Exits when Supertrend turns bearish or a trailing stop hits. Designed for trend phases.
DCA Accumulator
Splits a budget into scheduled buys, such as $500 per month as four $125 weekly orders. Can add extra buys on dips like -5%. Reduces timing risk with steady accumulation.
RSI Divergence Hunter
Looks for bullish divergence where price makes a lower low but RSI makes a higher low. Enters on confirmation and exits at a defined reward target. Useful for reversal setups.
Portfolio Rebalance
Rebalances allocations back to targets, like 50% BTC and 50% ETH, on a schedule. Adds drift thresholds such as 3% before trading. Helps keep risk aligned over time.
Before you deploy real capital, validate the logic on historical data and then run it in demo conditions. Compare results across timeframes, like 1-hour versus 4-hour candles, and track drawdowns, not just returns. Once stable, scale position size gradually and keep a kill switch ready.
A neural network trading platform is only as good as its inputs and constraints, and the same is true for rule-based automation. Combine indicators, price levels and time filters, then layer guardrails like max exposure per coin. Example: only trade when funding is below 0.01% and spread is under 0.05%, otherwise wait. This keeps execution closer to the conditions you designed.
Your funds stay on your exchange account while Coinrule sends orders through API permissions you control. Use read and trade keys, disable withdrawals, and rotate keys anytime. For on-chain automation, smart accounts and session keys can limit what a bot is allowed to do.
After you go live, monitoring matters as much as entries. Use logs, alerts and rule health checks to spot missed fills, slippage or unusual volatility. Keep a simple playbook: pause, adjust thresholds, or switch to a safer template during choppy regimes.
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Some traders use automation to hedge, not just to speculate. You can reduce exposure when volatility rises, rotate into stablecoins after a drawdown, or rebalance a basket weekly. These workflows are easier to maintain when rules run on schedule.
Markets alternate between trend and chop. Keep separate bots for each regime and switch based on a filter like ADX above 25 for trend or below 20 for range. This avoids forcing one strategy to do everything.
Define order types and sizing up front. For example, use limit orders inside a grid, but market orders for breakout confirmation. Add a minimum volume filter so thin pairs do not trigger noisy signals.
Set a max position size per asset, a max number of open trades, and a daily loss cap. Combine that with stop loss rules like 2.5% on intraday bots and 6% on swing bots. Consistency comes from constraints.
Once a bot performs, clone it for new pairs and adjust only the parameters. Keep naming conventions and notes so you can audit changes later. Small, controlled iterations beat constant rewrites.
Connect a single venue, pick a template, and run it with small size until you trust the process. Then expand to more pairs or add a second exchange for redundancy. The goal is repeatable execution you can explain.
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