Let’s start with your personal story
I was born and raised in Mumbai, the financial capital of India. Growing up in a family deeply rooted in financial services, my interest in the markets developed almost instinctively, shaped over years of dinner table conversations. I pursued CA, CFA, and an MSc in Management for Business Excellence, along with a double diploma in World Politics from the University of Warwick. I’ve also completed CMT Level 2 and am a SEBI-registered Research Analyst, Investment Advisor, and Portfolio Manager. To further hone my skills, I have completed programmes at Harvard, the London School of Economics, and Cornell.
How did you land up in this job?
After completing my articleship at EY, I joined PL’s Institutional Equities research team in 2016, later moving into Investment Strategy and Advisory. While gaining deep exposure on the research side, I saw a clear opportunity to innovate and differentiate, which led me to the world of quantitative investing.
I spearheaded PL’s foray into the Quantitative Asset Management space. This decision not only fortified PL’s position with a distinct moat but also introduced more sophisticated and systematic strategies to India’s investment landscape.
Over the past five-plus years, I have built and led a multi-disciplinary team of experts to introduce groundbreaking strategies and have completely transitioned to quant-based asset management. I am currently the Head – Quant Investment Strategies and Fund Manager at PL Asset Management.
Which funds are you currently managing?
I manage PL’s flagship equity strategy AQUA, Adaptive; Quantitative; Unbiased; Alpha, India’s pioneering style-agnostic and style-adaptive flexicap PMS. I also manage MADP – Multi Asset Dynamic Portfolio – a first-of-its-kind multi-asset PMS that employs quant models for tactical asset allocation using only passive instruments. Together, AQUA and MADP have surpassed INR 500 crore in AUM and exemplify our differentiated ‘Man with Machine’ approach — a synergy between PL’s traditional investment wisdom and cutting-edge quantitative techniques.
AQUA, PL Capital’s flagship equity PMS, has completed two successful years. As of 30th June, AQUA delivered a TWRR of 28.14%, outperforming the benchmark BSE 500 by 7.61%. This milestone strongly validates AQUA’s systematic, data-driven investment framework, powered by robust quantitative models, adaptive strategy, and disciplined execution.
What is your investment philosophy and how would you describe your investment strategy?
We have designed adaptive investment strategies that rely on data-driven models and systematic processes to switch between investment styles, sectors, and risk levels based on market and macro cycles. Technically, it’s a quantitative, rules-based, dynamic multifactor strategy. The core philosophy is built on the pillars of adaptability, flexibility, agility, and totality – providing a sustainable, repeatable, and holistic method for investing across changing market regimes.We follow a “Quantamental” investment approach, integrating Fundamental, Alternative, Technical, and Quantitative analytics. Our team has built 25+ proprietary factors, using over 1,000 indicators, and tested more than 7,500 strategies to power our models. Every decision is guided by structured rules and systematic processes.
What gives you the kick while managing other people’s money?
Making machines that can make money — that’s what truly excites me. We build models using sophisticated technology and statistics. At the same time, we create synergies by translating human investing understanding into rules, which we rigorously test across multiple market cycles. Simply put, it’s about blending art and science, where human intelligence is amplified by machine rigor and accuracy. This approach makes investing scientific, sophisticated, and systematic.
I believe there’s always scope to improve and explore the boundless possibilities of the man-with-machine approach. This includes finding smarter solutions, building new features, and making systems more robust in investment decision-making.
