In a 2009 letter to investors, legendary investor Warren Buffett cautioned against strategies based solely on quantitative models: “Beware of geeks bearing formulas.” However, investors didn’t quite get the memo. The ‘geeks’ have since taken over. In the US, quant funds now control 35% of the market, significantly surpassing humanmanaged funds. Mathematician and investor Jim Simons popularised quant-driven investing, achieving unparalleled success by trading on patterns hidden within vast amounts of data. Many investment firms now leverage data to generate substantial profits.
Back home in India, quant funds are still nascent, but growing rapidly. Asset management companies (AMCs) are lining up offerings, with ABSL Quant Fund currently available and SBI Quant Fund set to launch soon. Motilal Oswal Quant Fund made a splash earlier this month. Currently, eight quant funds are up and running. “These adopt a rule-based, datadriven approach to build a portfolio of stocks,” says Santosh Joseph, Founder and CEO, Germinate Investor Services. These funds offer an alternative to fund manager-led strategies, which can be influenced by human impulses and biases. Quant funds aim to cut through the noise, replacing gut feelings with clearly defined rules and statistics. However, index funds and their factor-based variants make similar promises. So, what sets quant funds apart?
Quant funds have shown widely varying outcomes
Most funds have struggled to beat the broader market.
Quant funds are far more complex in their workings. Unfortunately, this complexity isn’t always beneficial. The success of any quant strategy hinges entirely on the intricacies of its model. Each quant fund follows its own set of rules for making buy and sell decisions, responding to a complex array of business metrics, market signals and patterns. Consequently, they tend to trade frequently in response to high-frequency indicators.
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For instance, Nippon Quant Fund, the oldest in this category, uses a proprietary model based on valuations, earnings, price, momentum, and quality. ICICI Prudential Quant Fund employs a three-step model, which combines macro, fundamental and technical variables to screen and identify stocks. Tata Quant Fund uses a machinelearning algorithm to find the optimal factor combination for driving future returns. Quant Quantamental Fund relies on a blend of fundamental, quantitative, predictive and cognitive insights to build its portfolio.
However, besides the broader outlines, very little is known about how these models work. AMCs closely guard their proprietary frameworks and never disclose the exact details. Due to this secrecy, these strategies are often referred to as ‘black box’. Joseph remarks, “There is very little clarity on the working of quant funds and how the underlying rules are enforced.” Without a clearly defined investing style, betting on a particular quant strategy is akin to throwing darts in the dark. The complex interplay of underlying variables often makes it difficult to pinpoint the exact factors influencing portfolio outcomes at any given time. Roopali Prabhu, CIO and Head of Products and Solutions, Sanctum Wealth, remains unconvinced about quant funds owing to this opacity. “Not many of us know how to evaluate a quant fund,” she says.
The demonstrated success of Jim Simons’ Renaissance Fund certainly proves that quant funds hold promise. However, while it set a benchmark for quant strategies, its secretive model does not lend itself to imitation. “In almost every way, this tale is the strangest in the world of investments,” wrote Dhirendra Kumar, CEO, Value Research, about Simons’ investing feats. “Simon and his team’s success holds no real lessons for you and me in our investing lives. Unlike Buffett, Charles Munger, or so many other successful investors, there is nothing we can emulate,” he said. Kumar further observed that Simons’ reliance on advanced mathematical models and statistical analysis was not just innovative but almost exclusive to his firm’s unique skill set. This is why, despite his phenomenal success, his methods remain largely inaccessible to everyday investor.
Performance is the sole yardstick for assessing the success of a quant fund. On this measure, investors face limited information. Most quant funds in India have a track record of only 3-4 years, which is too short to reliably judge their execution capabilities. Within this limited time frame, significant variance can be observed. Despite a few exceptions, most funds have struggled to outperform the market. However, Quant AMC, which utilises its data crunching capabilities across a range of funds, has consistently delivered impressive results.
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Despite the short track record, experts insist that quant funds cannot be ignored for long. Joseph argues, “Quant has become an integral part of today’s life, and those who can connect the dots harnessing data can potentially make outsized gains.” Vidya Bala, Head, Research, Primeinvestor.in, says, “We agree that quant funds are high-risk strategies and cannot form part of the core portfolio. However, it is hard to ignore these funds as an investment option as long as they show consistent performance.”