Practitioners’ Insights: Investing in Indian Equities: Understanding Quant Investing and Risk Modelling for Asset Allocation

Overview

Use of factors in investing and asset allocation has been around for decades, but the use of artificial intelligence (AI) and machine learning models to forecast risks and rewards in the market is making them more efficient. It is not surprising that systematic approaches to equity investing are gaining significant traction around the world, including in India. As data availability continues to expand, computational tools have become more powerful, and as AI-enabled research workflows mature, the barriers to building these investment models will become lower than ever. In this webinar, the speaker will draw on her fifteen years of experience in quant investing to explore how investments are made using quantitative strategies covering factor labels like value, quality, and momentum. 

The speaker will also show how the quant models work as investment decision inputs and risk-modelling tools along with how their underlying principles can be applied more broadly to open additional areas of investment research. Why the Indian equity context offers a particularly interesting lens for these ideas will also be discussed. The session will cover a forward-looking perspective on how modern data and AI-enabled tooling are accelerating the research workflow while investment judgment remains at the centre. To attend this webinar, no coding experience is needed, nor is prior exposure to quantitative investing required. The session is designed to be accessible and relevant to investment professionals across all backgrounds.

This webinar is worth 1 PL credit. If you are a CFA Institute member and attended live or watched the recording on your own time, you may self-report this activity in your tracker.

Learning Outcomes

• Understand how systematic equity investing connects to fundamental investment philosophy, and how quant models work.
• Develop an appreciation for why the investment definitions and choices underneath factor labels drive meaningful differences in portfolio outcomes.
• Understand how algorithms operate as an investment tool  and how their principles can be applied more broadly by practitioners.
• Explore how advances in data and AI-enabled tooling are lowering the barriers to systematic implementation and accelerating the decision usefulness of these inputs.

Date and Time

Speakers