Methodology

How the models and indicators on this platform are constructed.

Data Sources

Ansaar aggregates data from NSE (National Stock Exchange of India), BSE, and cryptocurrency exchanges. Data includes daily OHLCV prices, F&O open interest, delivery volumes, institutional trade data (FII/DII), sector flows, and fundamental ratios such as P/E, P/B, ROE, and debt-to-equity.

Crypto data is sourced from major exchanges via aggregated APIs. Global macro data (VIX, DXY, oil, copper) is sourced from market data providers.

Equity Quantitative Research Model

The equity model (ADR-0061) is a LightGBM gradient-boosting model trained on ~150–180 features derived from price, volume, F&O, institutional flow, and fundamental data. It produces return estimates across 1-day, 5-day, and 21-day horizons.

Model outputs are scaled to a standardized range and combined using a Forecast Diversification Multiplier (FDM) following the framework in Robert Carver's “Systematic Trading”. The combined score represents the relative conviction of the model — descriptive, not an absolute return estimate.

Training information coefficient (IC): 0.35–0.61
Retrained bi-weekly on rolling historical data
Position sizing via Half Kelly criterion with volatility targeting

Crypto Quantitative Research Model

The crypto model uses a relaxed LightGBM architecture trained on ~77 features including price-derived statistics, funding rates, global market metrics, and liquidity indicators. It targets 5-day risk-adjusted returns.

Training IC: 0.08–0.30
Retrained bi-weekly
Stablecoin and low-liquidity pairs filtered out

ETF Carver Model

ETF quantitative research combines rule-based signals following Carver's methodology: EWMAC trend indicators (16/64 and 32/128 crossovers), Donchian channel breakout indicators, and NAV arbitrage signals. Signals are scaled to the same –20 to +20 range and blended using an FDM.

Macro Regime Classification

Market regime is classified using a Hidden Markov Model or threshold-based classifier applied to price momentum, volatility, and breadth indicators. The three classes are: Bull Trend, Bear Trend, and Sideways. Regime probability represents the model's confidence in the current classification.

Institutional Activity Indicators

The institutional activity view tracks delivery volume trends and F&O open interest patterns to surface potential accumulation or distribution at the institutional level. These are statistical indicators derived from public NSE data — not confirmed insider or institutional trade data, and not buy/sell calls.

Why some signals are not shown yet

Under the SEBI (Research Analysts) Regulations, 2014, forward-looking opinions on specific Indian securities may only be published by a registered Research Analyst. Ansaar's registration is in progress, so while it completes we have paused the display of those model outputs rather than show them without registration.

Paused for now: equity and ETF ML return predictions, signal scores and buy/sell calls, whale accumulation and distribution scores, liquidity-risk scores, and suggested position sizing.

Unaffected: all factual market data — prices, NAV, premium/discount, fundamentals, FII/DII flows, bulk deals and halal/zakat status — index-level market regime and sector rotation, all country macro on the Ansaar Desk, the entire Learn hub, and all crypto signals (crypto assets sit outside the Research Analyst regime).

These features are built and will switch back on once our SEBI Research Analyst registration is complete.

Limitations

All models have limitations. Model outputs degrade during regime changes, low-liquidity periods, or when market structure shifts significantly. Backtested performance is calculated on historical data and may not reflect live trading outcomes due to transaction costs, slippage, and look-ahead bias.

This platform publishes research outputs as-is. See our full disclaimer.