TigerData continuously scans 9 cross-asset correlations (indices, rates, volatility, crypto) scored on real backtests, and sends you every morning the ones that crossed their movement threshold — with the method, sample size and reliability track record for each.
One email a day. Active correlations, expected direction, historical reliability. Cancel anytime.
Daily email digest of active correlations (NQ→BTC, ETH→VIX, VIX→SOL, etc.), with confidence, track record and expected amplitude for each.
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The source code of the 50 bots (11,600+ lines) that power the correlation engine, plus the backtester. For those who want to audit or extend the method themselves.
Every correlation comes from a backtest on real prices (Yahoo Finance), 60-day window, June 2026. Only those above 51% historical accuracy and a 0.28 score are kept. None is presented as a guarantee.
| Pair | Tier | Score | 60d accuracy | Amplitude | Lag |
|---|---|---|---|---|---|
| NQ → BTC | A | 0.44 | 64% | 1.65× | D+1 |
| BTC → VIX | A | 0.42 | 53% | 3.58× | D+3 |
| ETH → VIX | A | 0.38 | 61% | 2.65× | D+0 |
| NQ → ETH | A | 0.38 | 56% | 2.25× | D+0 |
| NQ → SOL | A | 0.35 | 56% | 2.45× | D+0 |
| SP500 → BTC | B | 0.35 | 55% | 2.67× | D+0 |
| VIX → ETH | B | 0.34 | 62% | 0.38× | D+0 |
| VIX → SOL | B | 0.30 | 64% | 0.41× | D+0 |
| GOLD → BTC | B | 0.28 | 44% | 0.48× | D+3 |
Score = historical correlation strength (0-1) · Accuracy = % of times the expected direction held over 60 days · Amplitude = expected move ratio on the lagging asset. Short sample — to be verified over time, not a guarantee of future performance.
Point of comparison: a random guess (coin flip on direction) would average 50%. Our 9 correlations range from 44% to 64% on this sample — above chance for most, but not by a margin that justifies betting heavily on any single one.
The correlation engine is just one part of the framework. 50 bots in total: market making, pairs trading, arbitrage, mean-reversion, momentum, risk parity, a backtest engine.
| File | Role | Lines |
|---|---|---|
| backtester_v2.py | Backtest engine | 641 |
| cross_asset_correlations.py | Correlation engine (this site) | 508 |
| signal_engine_v2.py | Signal generation | 477 |
| market_making_bot.py | Market making | — |
| pairs_trading_bot.py | Pairs trading | — |
| + 45 more bots | Risk parity, momentum, arbitrage, regime detection... | — |
Not a trial of the signals product — an independent sample to judge the method's rigor: 3 real datasets (flu, weather, ER visits, France), with a README detailing sources and limits.