80%
Core allocation
Long-term asset evaluation, strategic allocation, and core-specific constraints.
PureRational Adaptive Multi-Asset Strategy
A rules-based multi-asset portfolio combining strategic allocation with measured tactical flexibility.
The strategy combines a long-term core allocation with a separate tactical allocation process. Both sleeves are evaluated independently and blended at the individual asset level.
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.
Strategy overview
The Adaptive Multi-Asset Strategy is a research model portfolio that allocates across five asset clusters — equity, metals, REITs, InvITs, and debt/liquid instruments — using a repeatable process.
Investment horizon: Medium- to long-term; not designed as a short-term trading framework.
Intended role: a structured multi-asset research framework for understanding how strategic and tactical sleeves can be combined under explicit constraints. It is not portfolio management, execution, custody, or personalised advice for a client account.
How assets are scored and risk is measured is described in the Adaptive Portfolio Methodology.
The 80:20 portfolio architecture
Final model weights are an asset-level blend of two independently evaluated sleeves.
20%
Tactical allocation
Shorter-horizon return and volatility signals, with positive-score allocation normalisation.
100%
Final portfolio
Asset-level weighted combination of both sleeves, reconciled to 100%.
Five asset clusters
Each cluster has a defined role in the portfolio. Instrument eligibility and evaluation details sit in the methodology; the list below summarises portfolio architecture.
Equity
Primary growth exposure across listed Indian equity market segments.
Large-cap, next 50, mid-cap, and small-cap building blocks.
Metals
Diversifying exposure to precious metals as a distinct risk sleeve.
Gold and silver exposure via liquid listed proxies.
REITs
Listed real-estate cash-flow and property-linked exposure.
Listed real estate investment trusts.
InvITs
Listed infrastructure cash-flow and asset-linked exposure.
Listed infrastructure investment trusts.
Debt and liquid instruments
Stability and liquidity relative to risk assets in the model.
Debt-oriented and liquidity instruments.
How the portfolio is constructed
Construction follows a fixed sequence from sleeve engines to the blended book. Evaluation frameworks that feed each engine are documented on the methodology page.
- Core allocation engine
- Strategic asset weights
- Tactical allocation engine
- Tactical asset weights
- 80:20 asset-level blending
- Final multi-asset portfolio reconciled to 100%
Allocation constraints
Constraint application differs by sleeve. The important distinction is:
- Core sleeve: REIT and InvIT allocations are individually capped at 7.5%.
- Tactical sleeve: allocations are determined by its own positive-score normalisation and instrument-level allocation process.
- Blended portfolio: final REIT and InvIT exposure can exceed the core-sleeve limits because the tactical sleeve is not bound by those same individual caps.
The 7.5% figures are therefore core-sleeve controls — not final portfolio-wide caps.
Portfolio review and rebalancing
The research model follows a quarterly review framework. At each scheduled review, input data are refreshed, sleeve weights are recomputed, the 80:20 blend is formed, and outputs are reconciled.
Material methodology or constraint changes are versioned. When a client-facing model portfolio research report is published or updated, launch and update dates, rationale, and parameters are stated in that report as required for model portfolio disclosures.
Historical portfolio composition
The chart below shows how the five cluster weights in the research model have evolved across twenty quarterly observations. It is labelled as historical model allocation only — not performance, and not a current recommendation.
- Equity
- Metals
- REITs
- InvITs
- Debt / liquid
Historical model allocation from the Adaptive Multi-Asset research workbook (blend construction). 20 quarterly observations (2021-03-31 to 2025-12-31). Figures are research-model cluster weights at quarterly rebalance dates. They are not validated performance, not a recommendation of current holdings, and may differ from any executable portfolio after liquidity, costs, and implementation constraints.
Risk and implementation considerations
Model allocation is not the same as actual execution. Translating research weights into holdings can involve:
- Liquidity and market-depth limits for individual instruments
- Concentration at both instrument and cluster level
- Transaction costs, bid–ask spreads, and timing differences
- Deviations from model weights during implementation or between review dates
Investors should also consider market risk, volatility, drawdown, and the possibility that historical relationships embedded in the model may not persist. See the Adaptive Portfolio Methodology for process-level risk measurement and Disclosures for regulatory statements.
Strategy factsheet and disclosures
Public webpages describe the research process and portfolio architecture. They are not substitutes for the prescribed client-facing model portfolio research report.
- Adaptive Portfolio Methodology — evaluation frameworks and risk measurement
- Disclosures — registration, conflicts, AI use, and liability statements
- Risk disclosure — general investment risk language
- Latest model portfolio research report / factsheet — published to eligible clients when available (includes launch and update dates, parameters, benchmark information, and required risk disclosures)
No returns are assured. Past model allocation or research output does not predict future results.