Forward-looking quant models across thousands of instruments — built for decision workflows.
Hedgtrade publishes a unified “forecast surface” for multi-asset markets: projections, regimes, scenarios, reversal zones, and explainable drivers — consistently framed across your universe.
What “plethora of models” means in practice
Many platforms drown you in indicators. Hedgtrade organizes models into a small number of families that map directly to real decisions: when to add risk, when to hedge, what breaks the thesis, and what’s actually driving outcomes.
Model families
Each family answers a specific question. Together, they form a decision-ready layer you can review in meetings and operationalize with boundaries.
1) Regime & risk state
“What environment are we in — and what posture fits it?”
- Trend / chop / transition framing for posture and timing.
- Volatility state to avoid sizing mistakes during expansion.
- Correlation & fragility flags when diversification collapses.
2) Projections & scenario paths
“What are the plausible paths from here — and what must happen first?”
- Base / alternative / stress paths with explicit conditions.
- Horizon-aware bands to frame expectations, not certainties.
- Decision points that map cleanly to actions.
3) Seasonality & cohorts
“What tends to happen in similar windows — and how strong is that tendency?”
- Calendar overlays for context (month/quarter/event windows).
- Cohort comparisons to reduce small-sample confidence.
- Rhythm recognition that supports consistent cadence reviews.
4) Reversal zones & risk boundaries
“Where is the thesis invalidated — and what do we do if we get there?”
- Reversal / invalidation zones for disciplined TP/SL planning.
- Boundary-based sizing tied to levels (not headlines).
- Stress outcomes that translate into hedging triggers.
5) Attribution & overlap
“What’s actually driving P&L and risk — and where are we double-counted?”
- Driver attribution to reduce narrative drift.
- Overlap visibility across correlated assets and clusters.
- Contribution framing for committee-ready decisions.
6) Liquidity & positioning context
“If this moves, how does it move — and how quickly can risk cascade?”
- Liquidity-aware context when markets gap or cascade.
- Crowding / reflexivity signals to avoid crowded pain trades.
- Execution-aware framing without requiring OMS/EMS change.
How teams use the model surface
Weekly committee cadence
Start at regime + top scenarios, confirm boundaries, then agree actions and governance notes in one pass.
Risk-on / risk-off tilts
Make tilts only when scenario conditions are met — with explicit invalidation levels.
Cross-asset monitoring
Track correlation shifts, overlap, and combined stress outcomes before “diversified” becomes “one trade.”
What improves immediately
- Less ad-hoc talk → shared regime + scenarios language.
- Cleaner actions → boundaries and decision points are explicit.
- Faster attribution → know what’s driving risk immediately.
- Less hidden concentration → overlap + correlation visibility.
Delivery modes
Dashboards
Visual, repeatable layouts for desks, risk, and committees.
Email briefs
Daily/weekly summaries with “what changed” framing and links back to context.
API / exports
Programmatic access and audit-friendly exports for downstream workflows.
See it on your universe
We’ll run the end-to-end workflow on representative assets: regime snapshot → scenario map → risk boundaries → attribution drivers.