Latest news with #Quantitative
Economic Times
4 days ago
- Business
- Economic Times
Siddharth Vora, Head - Investment Strategy & Fund Manager, PL Capital
With a strong background in finance and advanced credentials, the fund manager leads PL Capital's quant-driven investment strategies, including the flagship AQUA and MADP funds. Combining human insight with data-driven models, their adaptive 'Quantamental' approach dynamically adjusts across market cycles, delivering consistent outperformance. Passionate about blending art and science, they continually innovate to enhance systematic, rule-based investing for long-term success. Let's start with your personal story Tired of too many ads? Remove Ads How did you land up in this job? Which funds are you currently managing? Tired of too many ads? Remove Ads What is your investment philosophy and how would you describe your investment strategy? What gives you the kick while managing other people's money? 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 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 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.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 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 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 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 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.
Channel Post MEA
16-04-2025
- Business
- Channel Post MEA
SandboxAQ Leverages NVIDIA DGX Cloud To Fuel Scientific Discovery
SandboxAQ has announced a collaboration with NVIDIA to accelerate breakthrough innovations across biopharma, chemicals, advanced materials, financial services, cybersecurity, navigation, and medical imaging. SandboxAQ, a member of the NVIDIA Inception program, is leveraging the NVIDIA DGX Cloud AI platform on Google Cloud to build a state-of-the-art Large Quantitative Model (LQM) platform, fueling AI-driven scientific discovery. SandboxAQ is now uniquely positioned to help customers tackle the most complex and consequential business challenges through its LQMs – delivering breakthroughs where traditional models have fallen short – while offering unparalleled speed, scalability, and precision. This collaboration enables SandboxAQ to unlock critical breakthroughs specifically designed to transform customer outcomes, including: Up to 4x Faster Discovery Across Drug, Chemical, and Materials Pipelines: Accelerated by NVIDIA DGX Cloud, SandboxAQ replaces slow, resource-intensive design-make-test cycles with high-performance, equation-based simulations – reducing discovery timelines from months to weeks. Enhanced modeling capabilities support simultaneous optimization across multiple parameters, enabling faster validation of promising candidates and accelerating breakthroughs with greater confidence. Accelerated by NVIDIA DGX Cloud, SandboxAQ replaces slow, resource-intensive design-make-test cycles with high-performance, equation-based simulations – reducing discovery timelines from months to weeks. Enhanced modeling capabilities support simultaneous optimization across multiple parameters, enabling faster validation of promising candidates and accelerating breakthroughs with greater confidence. Breakthrough Datasets, Curated with DGX Cloud: SandboxAQ is generating high-fidelity scientific datasets, combining chemical and biological simulations. These methods leverage equation-based LQM models to reveal interactions between small molecules and complex biological targets that were previously difficult to detect including conformer libraries for generative chemistry and synthetic affinity data for training predictive models. By powering causal knowledge graphs and more accurate molecular design, these datasets reduce false positives and improve success rates across the R&D pipeline. SandboxAQ is generating high-fidelity scientific datasets, combining chemical and biological simulations. These methods leverage equation-based LQM models to reveal interactions between small molecules and complex biological targets that were previously difficult to detect including conformer libraries for generative chemistry and synthetic affinity data for training predictive models. By powering causal knowledge graphs and more accurate molecular design, these datasets reduce false positives and improve success rates across the R&D pipeline. Agentic AI Chemist – A New Era of Autonomous Discovery: SandboxAQ's AI Chemist combines and orchestrates multiple LQMs to transform the scale of the research and development process. It autonomously explores millions of potential chemical pathways, far beyond what a human chemist could evaluate, enabling the discovery of novel molecules and the optimization of compounds for clinical and scale up success. Research Breakthroughs Today's announcement builds on previous collaboration between SandboxAQ and NVIDIA: 2024 Breakthrough : SandboxAQ and NVIDIA achieved an 80x acceleration in quantum chemistry calculations using CUDA-accelerated Density Matrix Renormalization Group (DMRG), enabling accurate simulation of enzyme active sites and complex catalysts previously impossible due to computational limitations. : SandboxAQ and NVIDIA achieved an using CUDA-accelerated Density Matrix Renormalization Group (DMRG), enabling accurate simulation of enzyme active sites and complex catalysts previously impossible due to computational limitations. 2025 Breakthrough : In the newly published joint research paper, 'Orbital Optimization of Large Active Spaces via AI-Accelerators,' for the first time, researchers successfully performed orbital optimization on a system with 82 electrons in 82 orbitals – more than doubling the size of simulations compared to previous works. This groundbreaking advance for GPU accelerated quantum chemistry calculations pushes the capabilities for molecular simulations into a regime that has thus far been entirely out of reach, with potentially far-reaching implications in catalysis, material science and high-dimensional parameter optimization. Transformative Impact Across Key Customer Domains SandboxAQ's enhanced capabilities deliver strategic outcomes across customer innovation and critical workflows: Biopharma and Healthcare : Proven track record of accelerating preclinical pipelines for pharma companies by rapidly generating and optimizing therapeutic candidates based on significantly improved predictability of drug efficacy and safety. : Proven track record of accelerating preclinical pipelines for pharma companies by rapidly generating and optimizing therapeutic candidates based on significantly improved predictability of drug efficacy and safety. Chemicals and Materials : Enabling deeper, faster exploration and validation of sustainable chemical processes to unlock carbon and hydrogen utilization as well as next-generation energy storage technologies. : Enabling deeper, faster exploration and validation of sustainable chemical processes to unlock carbon and hydrogen utilization as well as next-generation energy storage technologies. Cybersecurity and Strategic Infrastructure: Leveraging advanced modeling and predictive capabilities to enhance agility, strengthen resilience, and support proactive cybersecurity postures. Pioneering How Organizations Can Effectively Leverage AI SandboxAQ is pioneering a new category of enterprise AI through its proprietary Large Quantitative Models (LQMs), a platform specifically engineered to solve massively complex, high-stakes problems where precision and deterministic outputs are critical. Unlike generalized frontier models, SandboxAQ's LQMs are designed to reflect the underlying laws of physics, chemistry, biology, and economics – enabling outcomes that are not just predictive, but scientifically reliable. In fields like drug discovery, SandboxAQ trains LQMs on high-fidelity, domain-specific datasets to dramatically improve accuracy, reduce false positives, and accelerate the path from hypothesis to therapeutic insight. This focus on scientifically grounded, application-specific modeling sets SandboxAQ apart, empowering organizations to unlock value in areas where conventional AI simply cannot deliver. 'Our expanded work with NVIDIA accelerates our customers' ability to innovate and lead in their fields,' said Jack Hidary , CEO of SandboxAQ. 'By developing our platform on NVIDIA DGX Cloud and continuing our research collaboration, SandboxAQ will deliver a level of performance and insight that gives our customers a clear edge in accelerating innovation.' 'SandboxAQ is pushing the boundaries of AI-native science,' said Alexis Bjorlin , Vice President of NVIDIA DGX Cloud. 'NVIDIA DGX Cloud provides an AI development platform with essential scale and optimized application performance, empowering SandboxAQ to deliver cutting-edge capabilities and drive real-world impact for organizations tackling society's most critical challenges.' 0 0
