Strategy examples

These examples live only in the documentation. Copy a JSON block into a local file, change one concern at a time, then submit the complete file to the validator described in Write your own strategy.

Examples demonstrate the file contract; they are not investment advice or claims of profitability. Parameters and fee assumptions require independent testing before paper or live use.

What each example teaches

Example	Trigger	Filters	Risk	Execution lesson
ZEC 4h maker breakout	`donchian_breakout`	`ema_trend`, `volume_surge`	`atr_bracket`	Maker entry/routine exit with taker hard stop
BTC 1h RSI reversion	`rsi_reversion`	`ema_trend`	`atr_bracket`	Conservative all-taker baseline
ETH 4h trend trailing	`trend_continuation`	`atr_expansion`	`atr_trailing`	Maker entry with taker exits

ZEC 4h maker breakout

This example combines a four-hour Donchian trigger with a daily trend gate, volume confirmation, an ATR bracket, and post-only routine orders. Hard stops remain taker orders.

{
  "name": "ZEC 4h maker breakout example",
  "thesis": "Trade confirmed four-hour ZEC Donchian breakouts in the daily trend with volume confirmation, an ATR bracket, and post-only routine execution.",
  "frequency": "medium",
  "definition": {
    "schemaVersion": 1,
    "slug": "example-zec-4h-breakout-maker",
    "symbol": "ZEC-USD",
    "trigger": {
      "kind": "donchian_breakout",
      "timeframe": "base",
      "lookback": 36,
      "thresholdBps": 5,
      "clock": "4h"
    },
    "filters": [
      {
        "kind": "ema_trend",
        "timeframe": "high",
        "fast": 20,
        "slow": 50,
        "clock": "1d"
      },
      {
        "kind": "volume_surge",
        "timeframe": "base",
        "window": 20,
        "multiplier": 1.15,
        "clock": "4h"
      }
    ],
    "risk": {
      "kind": "atr_bracket",
      "timeframe": "base",
      "atrPeriod": 14,
      "atrStopMult": 3,
      "riskReward": 4,
      "maxHoldHours": 20
    },
    "sizing": { "riskFraction": 0.15, "leverage": 1 },
    "entryPolicy": { "maxEntriesPerUtcDay": 1 },
    "feeBps": 13,
    "allowLong": true,
    "allowShort": true,
    "reverseOnOpposite": false
  },
  "data": {
    "provider": "pyth",
    "frames": {
      "base": {
        "interval": "4h",
        "lookbackDays": 600,
        "ticker": "Crypto.ZEC/USD"
      },
      "high": {
        "interval": "1d",
        "lookbackDays": 600,
        "ticker": "Crypto.ZEC/USD"
      }
    }
  },
  "executionPolicy": {
    "schemaVersion": 1,
    "entryMode": "maker",
    "routineExitMode": "maker",
    "emergencyExitMode": "taker",
    "emergencyExitReasons": ["stop"],
    "maker": {
      "ttlSeconds": 180,
      "offsetBps": 0,
      "entryMaxAttempts": 2,
      "routineExitMaxAttempts": 2,
      "routineExitFallbackSeconds": 420
    },
    "costs": {
      "hizzFeeBps": 5,
      "strikeMakerFeeBps": 0,
      "strikeTakerFeeBps": 8
    }
  }
}

BTC 1h RSI reversion

This example trades one-hour RSI extremes only when the daily EMA trend permits that side. It uses an all-taker execution baseline so the cost assumption does not depend on passive fills.

{
  "name": "BTC 1h RSI reversion example",
  "thesis": "Trade one-hour BTC RSI extremes only in the direction permitted by the daily EMA trend, using a fixed ATR stop and target.",
  "frequency": "medium",
  "definition": {
    "schemaVersion": 1,
    "slug": "example-btc-1h-rsi-reversion",
    "symbol": "BTC-USD",
    "trigger": {
      "kind": "rsi_reversion",
      "timeframe": "base",
      "period": 14,
      "oversold": 28,
      "overbought": 72,
      "clock": "1h"
    },
    "filters": [
      {
        "kind": "ema_trend",
        "timeframe": "high",
        "fast": 20,
        "slow": 50,
        "clock": "1d"
      }
    ],
    "risk": {
      "kind": "atr_bracket",
      "timeframe": "base",
      "atrPeriod": 14,
      "atrStopMult": 1.5,
      "riskReward": 1.8,
      "maxHoldHours": 36
    },
    "sizing": { "riskFraction": 0.1, "leverage": 1 },
    "entryPolicy": { "maxEntriesPerUtcDay": 2 },
    "feeBps": 13,
    "allowLong": true,
    "allowShort": true,
    "reverseOnOpposite": false
  },
  "data": {
    "provider": "pyth",
    "frames": {
      "base": {
        "interval": "1h",
        "lookbackDays": 600,
        "ticker": "Crypto.BTC/USD"
      },
      "high": {
        "interval": "1d",
        "lookbackDays": 600,
        "ticker": "Crypto.BTC/USD"
      }
    }
  },
  "executionPolicy": {
    "schemaVersion": 1,
    "entryMode": "taker",
    "routineExitMode": "taker",
    "emergencyExitMode": "taker",
    "emergencyExitReasons": ["stop"],
    "maker": {
      "ttlSeconds": 180,
      "offsetBps": 0,
      "entryMaxAttempts": 2,
      "routineExitMaxAttempts": 2,
      "routineExitFallbackSeconds": 420
    },
    "costs": {
      "hizzFeeBps": 5,
      "strikeMakerFeeBps": 0,
      "strikeTakerFeeBps": 8
    }
  }
}

ETH 4h trend trailing

This example follows established four-hour EMA separation only during expanding volatility. Entries are passive; both routine and emergency exits are taker orders so a trailing exit is not left waiting in the book.

{
  "name": "ETH 4h trend trailing example",
  "thesis": "Follow established four-hour ETH trends only during expanding volatility and manage exits with ATR-scaled initial and trailing stops.",
  "frequency": "medium",
  "definition": {
    "schemaVersion": 1,
    "slug": "example-eth-4h-trend-trailing",
    "symbol": "ETH-USD",
    "trigger": {
      "kind": "trend_continuation",
      "timeframe": "base",
      "fast": 20,
      "slow": 50,
      "thresholdBps": 12,
      "clock": "4h"
    },
    "filters": [
      {
        "kind": "atr_expansion",
        "timeframe": "base",
        "atrPeriod": 14,
        "slowPeriod": 50,
        "clock": "4h"
      }
    ],
    "risk": {
      "kind": "atr_trailing",
      "timeframe": "base",
      "atrPeriod": 14,
      "atrStopMult": 2.5,
      "trailAtrMult": 3,
      "maxHoldHours": 240
    },
    "sizing": { "riskFraction": 0.15, "leverage": 1 },
    "entryPolicy": { "maxEntriesPerUtcDay": 1 },
    "feeBps": 13,
    "allowLong": true,
    "allowShort": true,
    "reverseOnOpposite": true
  },
  "data": {
    "provider": "pyth",
    "frames": {
      "base": {
        "interval": "4h",
        "lookbackDays": 600,
        "ticker": "Crypto.ETH/USD"
      }
    }
  },
  "executionPolicy": {
    "schemaVersion": 1,
    "entryMode": "maker",
    "routineExitMode": "taker",
    "emergencyExitMode": "taker",
    "emergencyExitReasons": ["stop"],
    "maker": {
      "ttlSeconds": 180,
      "offsetBps": 0,
      "entryMaxAttempts": 2,
      "routineExitMaxAttempts": 2,
      "routineExitFallbackSeconds": 420
    },
    "costs": {
      "hizzFeeBps": 5,
      "strikeMakerFeeBps": 0,
      "strikeTakerFeeBps": 8
    }
  }
}

Validate a copied example

Use the code-block copy button, save the JSON as a local file, then validate it:

curl -X POST https://hizz.io/api/v1/ai-trading/strategies/validate \
  -H "Content-Type: application/json" \
  --data-binary @my-strategy.json

The validator returns the normalized strategy and the exact node graph. Inspect the graph before changing the file so you can see which module and cable each JSON section creates.

Safe modifications to try first

Change the market without inventing a ticker

Change definition.symbol and every direct historical ticker together. Use a market/provider pair returned by Hizz coverage rather than guessing a Pyth namespace.

Change one timeframe

Update the frame interval, the trigger/filter clock labels, and any holding period that was expressed for the old cadence. Then validate and retest; changing 1h to 4h creates a different strategy.

Stress costs

Increase feeBps for a uniform stress test, or update the maker/taker cost fields in executionPolicy. Do not count maker rebates on exits that are configured as taker orders.

Reduce exposure

Lower sizing.riskFraction or leverage. Remember that riskFraction is allocated margin, not a guaranteed maximum loss percentage.

Keep an experiment log

For every variant, record the JSON version, data provider, timeframe, date range, fee assumptions, symbol, trade count, return, realized payoff, maximum drawdown, and whether the result was in-sample, walk-forward, or paper. That record makes a result reproducible and reduces selection bias.

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Strategy examples

What each example teaches

ZEC 4h maker breakout

BTC 1h RSI reversion

ETH 4h trend trailing

Validate a copied example

Safe modifications to try first

Keep an experiment log

​What each example teaches

​ZEC 4h maker breakout

​BTC 1h RSI reversion

​ETH 4h trend trailing

​Validate a copied example

​Safe modifications to try first

​Keep an experiment log

What each example teaches

ZEC 4h maker breakout

BTC 1h RSI reversion

ETH 4h trend trailing

Validate a copied example

Safe modifications to try first

Keep an experiment log