Methodology
Every signal at QuantTau Research is derived from a fixed multi factor architecture evaluating market structure across dimensions, with no discretionary overrides or manual intervention.
Philosophy
Momentum as a factor has decades of empirical evidence across global markets. Our flagship Guha™ algorithm operationalises momentum through a structured architecture designed to capture persistence, continuation, and regime shifts in market behaviour.
Signals emerge only when underlying conditions align within this architecture, ensuring a focused and internally consistent output set.
A daily systematic algorithm identifying stocks aligned with our defined momentum framework for positional trading across multiple timeframes.
A price target generator, a buy/sell recommendation engine, or a portfolio management service. Signals indicate momentum structure, not outcomes.
Factor Structure
01 — Directional Velocity
Evaluates the short-to-intermediate term rate of price change to ensure positive structural drift.
02 — Normalized Momentum Dynamics
Quantifies the magnitude of recent gains against historical drawdowns to identify persistent buying pressure.
03 — Secular Regime Confluence
Establishes the baseline market regime by verifying price positioning against clustered historical distribution means.
04 — Vector Robustness
Measures the strength of the directional vector alongside institutional accumulation metrics.
Daily Process
7:45 PM
The algorithm is prepared for execution once all end of day data is available post market close.
8:15 PM
The algorithm processes the full equity universe across four segments, applying its internal math engine to identify instruments aligned with defined conditions.
9:00 PM
Model outputs are published to the client portal. Email delivery is used only as a backup during system downtime. IST daily.
Limitations
Transparency about limitations is part of our research standard. The following are inherent constraints of our systematic momentum approach.
| Limitation | Notes |
|---|---|
| No price targets | Our model identifies momentum, not where price will go |
| No stop-loss levels | Risk management is the subscriber's responsibility |
| IT incompatibility | Precision exceeds 90% outside the IT sector but falls below 30% within it |
| Not a portfolio | Position sizing and allocation are outside scope |
| Past signals ≠ future results | Momentum conditions change with market regimes |
The number of stocks the model selects varies significantly by market condition. In strong trending markets, output may be 10–15 stocks per day. In choppy or correcting markets, output may be zero. A zero-signal day is a valid and informative output, and it means current conditions do not support momentum entries in that universe.