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A quant hedge fund uses quantitative analysis and computer modeling to pick securities.

A quant hedge fund is a pooled investment vehicle that uses quantitative analysis to select securities. This means that the fund relies on research and mathematical and statistical modeling to predict how an investment will perform. While investing in hedge funds is reserved only for accredited investors, anyone can work with a financial advisor to build an investment portfolio and meet their money goals.

Understanding Hedge Funds

Before diving into how quant funds work, it’s important to have a general understanding of hedge funds and what sets them apart from other investment vehicles. A hedge fund pools money from high net worth investors and uses a variety of speculative investment strategies, including short selling and leverage, to generate significant returns.

Hedge funds typically invest in a wide array of assets, from equities and real estate to currencies and commodities.

While they are both pooled investment vehicles, hedge funds differ from mutual funds in several notable ways. First, hedge funds are only available to accredited investors — individuals who have earned income exceeding $200,000 in each of the last two calendar years or have a net worth of at least $1 million (not including their primary residence).

Hedge funds are also not subject to many of the same government regulations that protect those who invest in mutual funds. And while hedge funds often seek higher returns through speculative strategies, they also charge hefty performance-based fees on top of management fees.

How Does a Quant Hedge Fund Work?

A quant hedge fund uses quantitative analysis and computer modeling to pick securities.

Traditional hedge funds, often referred to as “fundamental hedge funds,” base their investment strategies on fundamental research and human intuition. A quant fund, on the other hand, removes the human element and relies entirely on mathematical and statistical modeling.

A fun comparison can be drawn by examining the proliferation of sabermetrics and analytics in baseball. While teams had always evaluated players based on traditional statistics and the subjective analysis of coaches and scouts, the advent of fast, automated computer-based analytics has ushered in a new wave of advanced metrics that teams use to make decisions in a more objective, data-driven manner.

While it’s not a perfect apples-to-apples comparison, a quant hedge fund is a little like a baseball team that relies solely on analytics. Portfolio managers typically have mathematics or computer science backgrounds. Investment decisions are often dictated by algorithms and patterns in historical data. Quantitative analysts may examine the same data as their counterparts at other funds, but they’ll use it in a systematic, automated way that does not include human judgement.

Quant Hedge Fund Performance

A quant hedge fund uses quantitative analysis and computer modeling to pick securities.

So what’s the better investment, a fundamental hedge fund or one that uses quantitative analysis? Well, it depends. Quant funds appear to have struggled through the late 2010s, following a string of strong performances earlier in the decade.

Data from PivotalPath, the hedge fund research firm, shows that its Equity Quant Index posted -1.60% returns in the three years leading up to April 2021. PivotalPath’s Hedge Fund Composite Index, however, was up 7.1% during that same timespan. The composite index comprises all hedge fund strategies, including quants.

It’s important to point out that the Equity Quant Index’s recent rough patch came after several years that saw double-digit gains. According to Institutional Investor, the index was up 10.2%, 15.3%, 8.8%, 14.7%, 10.4% and 9.2% between 2010 and 2015.

Bottom Line

While most investors won’t qualify to invest with hedge funds, those who can choose between funds that use fundamental analysis, quantitative analysis, or perhaps a blend of the two. A quantitative hedge fund, however, uses sophisticated mathematics and algorithms to develop an investment strategy that is then implemented automatically. A more traditional fund relies on fundamental research — and the discretion of its managers — to find undervalued and overpriced securities.

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Patrick Villanova, CEPF® Patrick Villanova is a writer for SmartAsset, covering a variety of personal finance topics, including retirement and investing. Before joining SmartAsset, Patrick worked as an editor at The Jersey Journal. His work has also appeared on and in The Star-Ledger. Patrick is a graduate of the University of New Hampshire, where he studied English and developed his love of writing. In his free time, he enjoys hiking, trying out new recipes in the kitchen and watching his beloved New York sports teams. A New Jersey native, he currently lives in Jersey City.
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