What Are Quant Funds? Strategies, Performance & Risks Explained

What Is a Quant Fund?

A quant fund is an investment fund that uses quantitative analysis for its investment selection process. It relies more on algorithmic, data-driven strategies than human judgment. Such non-traditional and passive funds use customized software models for investment decisions. The history of quant funds is rooted in decades-old quantitative analysis principles, with notable early influences from influential works like "Security Analysis" by Benjamin Graham and David Dodd. Supporters of quant funds believe that using computer programs reduces risks and losses compared to human fund managers. Yet they carry unique risks, such as high trading costs and the potential for failures due to unpredictable market events or excessive reliance on historical data

How Quant Funds Operate

Quant funds rely on algorithmic or systematically programmed investment strategies. As such, they don't use the experience, judgment, or opinions of human managers to make investment decisions. They use quantitative analysis rather than fundamental analysis, which is why they're also called quantitative funds. Not only can they be one of many investment offerings supported by asset managers, but they may also be part of the central management focus of specialized investment managers.

Increased access to diverse market data and solutions using big data has driven quant fund growth. Advances in financial technology and automation have expanded data sets for quant fund managers, providing richer data for broader analysis. 

Large asset managers have increased investment in quantitative strategies as fund managers struggle to beat market benchmarks. Smaller hedge fund managers also contribute to the quant fund offerings in the market. Overall, quant fund managers seek talented individuals with accredited academic degrees and highly technical experience in mathematics and programming.

Assessing Quant Fund Performance

Quant fund programming and quantitative algorithms have thousands of trading signals they can rely on, ranging from economic data points to trending global asset values and real-time company news. Quant funds are also known for building sophisticated models around momentum, quality, value, and financial strength using proprietary algorithms developed through advanced software programs.

Quant funds draw a lot of interest and investment due to the returns they've made over the years. But, a report by Institutional Investor says they've been underperforming since 2016. In the five years leading up to 2021, the report said the MSCI World index and the equity quant index generated annualized returns of 11.6% and 0.88%, respectively.

Institutional Investor claimed that the equity quant index was up 10.2% in 2010, 15.3% in 2011, 8.8% in 2012, 14.7% in 2013, 10.4% in 2014, and 9.2% in 2015.

The Evolution of Quantitative Investing

The basis for quantitative analysis and, therefore, quant funds, has a history that dates back eight decades, with the publishing of a 1934 book called Security Analysis. Written by Benjamin Graham and David Dodd, the book advocated investing based on the rigorous measurement of objective financial metrics related to specific stocks.

Security Analysis has been followed by further publications related to quantitative investment strategies, such as Joel Greenblatt’s The Little Book that Beats the Market and James O'Shaughnessy’s What Works on Wall Street. 

Essential Factors for Investing in Quant Funds

Quant funds are often classified as alternative investments since their management styles differ from more traditional fund managers.

Quant funds usually have lower costs because they need fewer traditional analysts and managers. However, their trading costs tend to be higher than traditional funds, due to a higher turnover of securities. Their offerings are also generally more complex than standard funds, and it is common for some of them to target high-net-worth investors or have high fund entrance requirements.

Some investors consider quant funds to be among the most innovative and highly technical offerings in the investment universe. They encompass a wide range of thematic investment styles and often deploy some of the industry’s most groundbreaking technologies.

Successful quant funds keep a close eye on risk control due to the nature of their models. Most strategies start with a universe or benchmark and use sector and industry weightings in their models. This allows the funds to control the diversification to a certain extent without compromising the model itself.

Risks Inherent in Quant Funds

Some argue that quant funds are risky and disagree with letting a "black box" manage investments. For all the successful quant funds out there, just as many seem to be unsuccessful. Unfortunately, for the quants' reputation, when they fail, they often fail big time.

Long-Term Capital Management (LTCM) was one of the most famous quant hedge funds, as it was run by some of the most respected academic leaders and two Nobel Memorial Prize-winning economists, Myron S. Scholes and Robert C. Merton. During the 1990s, their team generated above-average returns and attracted capital from all types of investors. They were famous for not only exploiting inefficiencies but using easy access to capital to create enormous leveraged bets on market directions.

Their disciplined strategy was a weakness that led to their collapse. LTCM was closed and dissolved in early 2000. Its models did not include the possibility that the Russian government could default on some of its own debt. This one event triggered events, and a chain reaction magnified by leverage created havoc. LTCM was so heavily involved with other investment operations that its collapse affected the world markets, triggering dramatic events. In the end, the Federal Reserve (Fed) stepped in to help, and other banks and investment funds supported LTCM to prevent any further damage.

While a strong quant team will be constantly adding new aspects to the models to predict future events, it's impossible to predict the future every time. Quant funds can also become overwhelmed when the economy and markets are experiencing greater than average volatility. The buy and sell signals can come so quickly that high turnover can create high commissions and taxable events.

Quant funds can also pose a danger when they are marketed as bear-proof or are based on short strategies. Predicting downturns using derivatives and combining leverage can be dangerous. One wrong turn can lead to implosions, which often make the news.

The Bottom Line

Quant funds use advanced mathematical models and algorithms to make investment decisions, and require technology-advanced portfolio managers. Quant funds are considered alternative investments and typically aim to achieve diversification through sector and industry weightings in their models, which helps manage risk without compromising their systematic approach. Despite their cutting-edge technology and data-driven approach, quant funds have faced performance challenges, notably underperforming traditional benchmarks in recent years. Other risks associated with quant funds include their performance in volatile markets and an over-reliance on historical data, which can lead to significant failures, such as the collapse of Long-Term Capital Management (LTCM).