---
id: HKUDS/Vibe-Trading/cross-market-strategy
version: "89c9dce8"
license: MIT
install: manual
updated: 2026-07-27
---

# cross-market-strategy — Cross-Market Strategy generates trading signals for portfolios spanning different asset classes and exchanges. It automatically detects market type, applies tailored indicator parameters, and adjusts position sizes by volatility so crypto or forex positions don't dominate your risk budget. The underlying engine handles calendar shifts, market rules, and capital allocation per symbol.

Publisher: HKUDS · Stars: 28096 · Updated: 2026-07-27

Install (manual): `git clone https://github.com/HKUDS/Vibe-Trading`

## SKILL.md

## When to Use

When the user requests a backtest with codes from **different markets** — e.g. `["000001.SZ", "BTC-USDT"]` or `["AAPL.US", "EUR/USD", "600519.SH"]`.

The `CompositeEngine` handles calendar alignment, shared capital, and market rules automatically. The strategy only needs to output per-symbol signals.

## Key Concepts

### 1. Market Classification in generate()

Group symbols by market type and apply market-specific indicator parameters:

```python
def generate(self, data_map):
    groups = {}
    for code, df in data_map.items():
        market = self._detect_market(code)
        groups.setdefault(market, {})[code] = df

    signals = {}
    for market, market_data in groups.items():
        params = MARKET_PARAMS[market]
        for code, df in market_data.items():
            signals[code] = self._market_signal(df, params)
    return signals
```

### 2. Per-Market Parameter Tables

Different markets have very different dynamics. Using the same parameters everywhere produces poor results.

| Parameter | A-Share | Crypto | US Equity | Forex |
|-----------|---------|--------|-----------|-------|
| MA fast | 5 | 7 | 10 | 10 |
| MA slow | 20 | 25 | 50 | 30 |
| RSI period | 14 | 10 | 14 | 14 |
| Vol lookback | 20 | 14 | 20 | 20 |
| Typical daily vol | 1-2% | 3-8% | 1-2% | 0.3-0.8% |

### 3. Volatility-Adjusted Weights (Critical)

BTC daily vol ~ 5%, A-share daily vol ~ 1.5%. Without vol-adjustment, crypto eats the entire risk budget.

```python
def _vol_adjust(self, signals, data_map):
    vols = {}
    for code, df in data_map.items():
        ret = df["close"].pct_change().dropna()
        vols[code] = ret.rolling(20).std().iloc[-1] if len(ret) > 20 else ret.std()

    inv_vols = {c: 1.0 / (v + 1e-10) for c, v in vols.items()}
    total_inv = sum(inv_vols.values())

    adjusted = {}
    for code, sig in signals.items():
        weight = inv_vols[code] / total_inv * len(signals)
        adjusted[code] = (sig * weight).clip(-1.0, 1.0)
    return adjusted
```

### 4. Cross-Market Signal Patterns

1. **Momentum spillover**: BTC 7-day momentum as overlay for A-share tech sectors
2. **Risk-on/Risk-off**: USD/CNH rate + VIX proxy to reduce equity exposure
3. **Hedging**: Long A-shares + short crypto delta as tail hedge
4. **Correlation regime**: When rolling correlation > 0.6, reduce to single-market exposure; when < 0.2, maximize diversification

### 5. What the Engine Handles (Don't Worry About)

- **Trading calendar alignment**: signals are shifted on each symbol's own calendar, then ffill'd to unified dates
- **Market rules**: T+1 for A-shares, funding fees for crypto, swap for forex — all per-symbol
- **Capital allocation**: shared pool, strategy just sets target weights via signals
- **Commission/slippage**: dispatched to correct sub-engine per symbol

## config.json for Cross-Market

```json
{
  "source": "auto",
  "codes": ["000001.SZ", "BTC-USDT"],
  "start_date": "2024-01-01",
  "end_date": "2025-03-31",
  "interval": "1D",
  "initial_cash": 1000000,
  "engine": "daily"
}
```

- `source` **must** be `"auto"` for cross-market (routes each symbol to its loader)
- `extra_fields` should be `null` (not all markets support fundamentals)
- `leverage` defaults to 1.0 (CompositeEngine inherits from config)

## Market Detection Heuristics

| Pattern | Market |
|---------|--------|
| `000001.SZ`, `600519.SH` | A-share |
| `AAPL.US` | US equity |
| `700.HK` | HK equity |
| `BTC-USDT` | Crypto |
| `IF2406.CFFEX` | China futures |
| `ESZ4` | Global futures |
| `EUR/USD` | Forex |

## Supporting Files

- [example_signal_engine.py](example_signal_engine.py) — complete cross-market strategy example


[View on SkillFed](https://skillfed.io/HKUDS/Vibe-Trading/cross-market-strategy) · [View on GitHub](https://github.com/HKUDS/Vibe-Trading)