EventHorizonIQ

The call, before it's in the price
— and the analyst on your names.

Structural conviction delivered ahead of consensus : the thesis, the invalidation triggers, and a standing line to pressure-test it.

Performance Summary

Strategy CAGR (Jul 2021 – Mar 2026)
+25.88%
Sharpe Ratio
0.743
Max Drawdown
−46.1%
Drawdown Catch Rate
92% (12/13)
Walk-Forward OOS
8/10 windows positive
Monte Carlo (3yr, 1000 sims)
77.7% P(profit)
Signal Validation
39 of 450K+ survived FDR
BTC Regime NW p-value
0.0003

All figures computed on out-of-sample data unless otherwise noted. Past performance is not indicative of future results.

Cross-Asset Extension

15
Equities tracked
92%
Avg catch rate
0.09–0.28
BTC–equity correlation
12/13
Drawdowns caught

Coverage spans Mag 7 (AAPL, MSFT, GOOGL, AMZN, NVDA, META, TSLA), PLTR, and 7 BTC miners (MARA, RIOT, CLSK, HUT, BITF, IREN, WULF). The regime signal operates despite low BTC-to-equity correlation because it captures macro structural shifts upstream of asset-specific moves.

Bitcoin reacts first. Equities follow.

Data Delivery

REST API

<100ms latency, JSON response

WebSocket

Real-time regime state changes

Daily Scores

Regime probability scores, updated daily

Historical Backfill

Full history available on request

Audit Trail

Compliance-ready timestamped records

Documentation

Interactive API reference

Use Cases

Corporate Treasury Risk Management

Regime-aware monitoring for BTC and ETH balance sheet exposure. Early warning before drawdowns propagate to treasury valuations.

Crypto Fund Regime Overlay

Overlay regime state on existing long/short strategies. Reduce gross exposure during STRESS transitions, increase during NORMAL confirmation.

Cross-Asset Tail Risk Detection

Detect macro structural deterioration 30-60 days before equity impact. Signal validated across 7 bank failures and 13 drawdown events.

Options Vol Surface Conditioning

Regime probability scores condition volatility surface models. Separate NORMAL-regime vol dynamics from STRESS-regime skew behavior.

Research Foundation

Built on 20 years of published research from Columbia University on what predicts corporate performance and what predicts failure.

Eric Jackson, PhD

Columbia University — Upper Echelons Theory (Hambrick)

Director equity stakes and corporate performance divergence

California Management Review, 2000

Certification prestige and substantive involvement in IPO outcomes

Journal of Business Venturing, 2009

Early warning systems: Survivors vs. implosions

Ivey Business Journal, 2005

Institutional access is structured on a custom basis.

Coverage scope, delivery format, and integration depth are tailored to each allocator's existing infrastructure and compliance requirements.

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Past performance is not indicative of future results. Statistical validation does not guarantee future signal accuracy. EventHorizonIQ provides regime intelligence and diagnostic observations, not investment advice. All performance metrics are computed on out-of-sample data unless otherwise noted. Monte Carlo simulations assume no transaction costs. Sharpe ratios and CAGR figures reflect strategy-level returns before fees. This material is intended for qualified institutional investors and is not a solicitation to invest.

Institutional | EventHorizonIQ