Equity
Large-cap, next 50, mid-cap, and small-cap building blocks.
Adaptive Portfolio Methodology
A systematic framework for evaluating assets, measuring risk and constructing multi-asset portfolios.
The investment process combines quantitative asset evaluation, multi-horizon return and risk analysis, allocation constraints and periodic portfolio review. The objective is to follow a consistent research framework rather than rely on short-term market predictions.
Research by Arindam Samanta, SEBI Registered Research Analyst (Registration No. INH000031462). Registration granted by SEBI and certification from NISM in no way guarantee performance of the intermediary or provide any assurance of returns to investors. Investments in securities market are subject to market risks. Read all related documents carefully before investing.
Research philosophy
Financial research is often influenced by short-term market movements and recent performance trends. The Adaptive research process is designed to focus instead on:
- Structure over noise
- Process over prediction
- Discipline over reaction
- Long-term perspective
The framework emphasises consistency, context, and rational decision making across changing market conditions.
Investment universe
Eligible instruments are evaluated within five asset clusters. Inclusion in the investible universe is subject to data availability and eligibility requirements and does not imply a recommendation.
Metals
Gold and silver exposure via liquid listed proxies.
REITs
Listed real estate investment trusts.
InvITs
Listed infrastructure investment trusts.
Debt and liquid instruments
Debt-oriented and liquidity instruments.
How these clusters are combined into a portfolio architecture is described on the Adaptive Multi-Asset Strategy page.
Two complementary evaluation frameworks
Assets are evaluated through two complementary lenses. Core evaluation supports strategic allocation over longer horizons. Tactical evaluation supports shorter-horizon allocation adjustments. Exact signal parameters used in client-facing model portfolio reports are stated in those reports.
| Dimension | Core evaluation | Tactical evaluation |
|---|---|---|
| Orientation | Long-term | Short/medium-term |
| Return horizons | 36 and 60 months | 3, 6 and 12 months |
| Risk measure | Historical drawdown | Annualised volatility |
| Scoring | Weighted return-to-drawdown | Return-to-volatility |
| Purpose | Strategic asset allocation | Tactical allocation |
Core measurement notes
Core evaluation emphasises multi-year return horizons (36 and 60 months) relative to historical drawdown experience. Scoring is expressed as a weighted return-to-drawdown relationship so that assets with comparatively stronger long-horizon outcomes per unit of drawdown receive higher relative emphasis within the core process rules.
Drawdown measures used in the research process may include current drawdown and rolling multi-year drawdown windows. Exact weights and eligibility filters are versioned in the client research report.
Tactical measurement notes
Tactical evaluation emphasises shorter return horizons (3, 6 and 12 months) relative to annualised volatility. Scoring is expressed as a return-to-volatility relationship so that comparatively stronger risk-adjusted shorter-horizon signals can influence tactical sleeve weights.
Tactical allocations are formed through positive-score normalisation and instrument-level rules within the tactical sleeve. Full parameter packs appear in the model portfolio research report.
Asset and cluster evaluation
Allocation signals are produced through a fixed progression:
- Calculate individual asset scores.
- Aggregate eligible asset scores into cluster scores.
- Convert cluster scores into allocation signals.
- Apply the applicable allocation constraints.
- Generate sleeve-level asset weights.
Sleeve-level weights are then available for the portfolio architecture described on the Adaptive Multi-Asset Strategy page.
Risk measurement
The research process distinguishes several risk concepts rather than relying on a single volatility statistic:
- Historical volatility — dispersion of returns over a defined lookback, used primarily in tactical evaluation.
- Current drawdown — distance from a prior peak at the evaluation date.
- Rolling 36-month drawdown — drawdown experience measured over a three-year window.
- Rolling 60-month drawdown — drawdown experience measured over a five-year window.
Core scoring emphasises drawdown-based risk; tactical scoring emphasises annualised volatility. Neither measure eliminates the possibility of larger future losses.
Allocation constraints and liquidity considerations
The core sleeve applies specific allocation controls to listed REITs and InvITs because these instruments can combine equity-like price variability with trust-specific liquidity, distribution, and market-depth characteristics. Individual REIT and InvIT positions in the core sleeve are capped at 7.5% each.
Allocation limits in the model are process controls. They are not the same as actual market liquidity. An instrument may receive a model weight and still be difficult or costly to trade at size; conversely, liquid instruments may be constrained by methodology rules even when markets are deep.
How core constraints interact with the tactical sleeve and the final blended portfolio is explained on the strategy page — the 7.5% figures are core-sleeve controls, not portfolio-wide caps.
Portfolio validation and governance
The research process incorporates operational checks intended to keep outputs auditable:
- Data validation for prices, distributions, and eligibility inputs
- Weight reconciliation so sleeve and blended outputs sum to 100% within tolerance
- Eligibility checks before an instrument can receive a positive model weight
- Methodology versioning when measurement parameters or constraints change
- Periodic review aligned with the quarterly rebalance cadence
Scope of research services
Research services under the SEBI Research Analyst framework may include macroeconomic and market-context analysis, industry evaluation, company and security-level research where published, portfolio construction and model portfolio research, and quantitative investment frameworks.
This methodology page describes the Adaptive research process. It is not a substitute for the prescribed client-facing model portfolio research report, factsheet, or risk disclosures.
Investment risks and limitations
All model portfolios and research frameworks involve uncertainty. Material risks include:
- Market risk and general price variability across asset classes
- Volatility and drawdown risk, including larger losses than observed historically
- Asset-class and cluster concentration
- Liquidity and market-depth constraints, particularly for some REITs and InvITs
- Execution and transaction costs when translating model weights into holdings
- Model and estimation risk, including misspecification of signals or constraints
- The possibility that historical return and risk relationships may not persist
Research does not assure or guarantee returns. Past model behaviour does not predict future results.