A structure-driven intraday model rewriting how the tape is read.
QuantEdge Technologies develops physics-inspired, intraday models that read tick-by-tick microstructure, capture structural inflection points, and adapt to changing regimes in real time.
ENGINE ARCHITECTURE
From raw ticks to adaptive execution — a layered system built around structure, not hope.
Market-structure first. Indicators second.
The QuantEdge Engine treats the market like a complex dynamic system, not a sequence of candles. We focus on microstructure, curvature, and regime shifts using indicators only as a language to express underlying structure, not as a crutch.
- Multi-timeframe compression: micro/meso → 1m → 3m → 5m → 15m.
- Curvature / inflection points in price dynamics.
- Order-flow pressure and tape-speed context.
- State machine for trend, range, and volatility regimes.
The engine is designed from day one to be understandable by a risk manager, not just a coder. Every decision path is loggable, auditable, and rooted in observable structure.
- L1 – Tape & Microstructure: tick/quote stream, micro-bursts, curvature.
- L2 – Signal Engine: price-inflection models, regime-awareness, confirmation logic.
- L3 – Risk & Structure: stop architecture, structure exits, filters.
- L4 – Broker Layer: execution routing, throttles, and safeguards.
A simplified view of how the QuantEdge Engine processes the tape in real time – from raw ticks to risk-aware execution.
Market Data Ingest
Ticks, quotes, and higher-timeframe bars streamed into a unified feed.
MicroTape & Micro Hook
1s micro-bursts, price delta shock, and tape overrides watching each print.
Signal Engine
Price inflection models, flow filters, and regime context framing each decision.
Risk & Structure Layer
TSL, structure exits, and micro exits guarding downside in real time.
Execution & Logging
Broker-agnostic routing, fills, and full-session diagnostics for review.
Research notes & internal experiments.
QuantEdge runs continuous experiments on microstructure behavior, intraday regime transitions, and signal robustness across instruments and timeframes. This work is exploratory, iterative, and entirely data-driven.
Over time, selected insights will be summarized here as short research notes not as trade calls, but as documentation of how the engine learns and how different components behave under stress.
- Price inflection detection vs. traditional indicator crossovers.
- Regime-aware execution vs. static rule sets.
- Microstructure changes around sessions / volatility events.
- Behavior of the stack under different market environments.
This area is under active development. Public research notes will be added once internal experiments reach stable, repeatable conclusions that can be communicated responsibly.
From rockets to tape.
Samuel Banahene is an aerospace engineer by training, working on complex systems and high-stakes environments before building QuantEdge. That same mindset precision, redundancy, and respect for risk is what underpins the engine.