The primary objective of INVasset’s PMS is to generate superior risk-adjusted returns over the long term by investing in fundamentally robust companies with strong earnings potential. By leveraging the power of technology and quantitative analysis, the firm seeks to deliver consistent alpha while maintaining capital protection. INVasset aims to help investors navigate market volatility through a rules-based framework that ensures objective, bias-free decision-making.

INVasset follows a multi-factor, quantitative investment strategy that integrates fundamental, technical, and behavioral data to identify market-leading opportunities. Its proprietary algorithm continuously monitors market data to capture asymmetric risk-reward setups. A research team of 10+ analysts oversees the strategy to ensure quality control and conviction in stock selection.

Key highlights of the strategy include:

• Real-time screening of 1,500+ listed stocks
• Evaluation across 170+ proprietary parameters
• Blend of value, momentum, and quality factors
• Dynamic portfolio rebalancing based on market triggers
• Elimination of emotional bias through algorithmic execution

The result is a data-driven, scalable, and disciplined investment process that adapts to changing market conditions.

INVasset’s core philosophy revolves around Data. Discipline. Direction.

• Data-Driven: Every investment decision is anchored in real-time, quantifiable data, ensuring an evidence-based approach to portfolio construction.
• Discipline-Led: By removing emotional interference, the strategy maintains consistency across market cycles, ensuring systematic adherence to the model.
• Directionally Aligned with India’s Growth: INVasset believes in the long-term India opportunity and structures its portfolios to benefit from the country’s macroeconomic tailwinds and sectoral shifts.

Through its philosophy, INVasset strives to deliver predictable, repeatable, and scalable outcomes, ensuring long-term wealth creation for investors in a transparent and accountable manner.