The Resurgence of Quantitative Investing

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The following is a guest article from Hui Wang, Partner of AlphaLetters LLC, a service which monitors new quantitative finance research from universities, finance journals associations and other sources.

2017 marks the tenth anniversary since the so-called “Quant Quake” of August 2007. As a research firm serving quantitative communities since 2005, we have witnessed several important changes in quantitative research over these past years.

Increasing popularity of quant funds

A quick Google trend search using key word “quant funds” clearly delivers two messages.  First, in spite of the rising popularity of passive investing, the August 2007 meltdown cast a long shadow among investors regarding the validity of active quantitative investing as an investment style. Interest in quantitative funds declined, as shown in results from Google Trends.

Source: Google Trends

In the most recent 2-3 years, however, quantitative investing has been picking up attention. This is evidenced in the high profile integration of quantitative techniques into fundamental investment processes by industry bellwethers such as BlackRock, SAC, Bridgwater, etc, which are all seeking to replace some fundamental managers with quantitaitve  stock-selection models. In fact, Institutional Investors claims that “quants rule” in the top 100 hedge fund list.

The head of Canada’s largest pension fund argued that quant investing adds value as an orthogonal investment style: “In a highly efficient market like U.S. large-cap stocks, it’s hard to deliver value to clients through traditional means of investing.”

Thirst for novel quant strategies

With August 2007 in mind, practitioners we talk with are not sure the increasing popularity of quant funds is necessarily a good thing. Journalists have started to air similar concerns.   The Financial Times quoted Richard Bookstaber, a former risk manager at Morgan Stanley and Moore Capital, now an advisor to the University of California’s $100bn investment office: “What is going on now is not just the growth of quant hedge funds, like before the crisis. Now it’s system-wide across the investment world.”

Indeed, the overlapping portfolios of quant fund holdings does look worrisome to many:

Source: https://www.novus.com/blog/rise-quant-hedge-funds/

As a consequence, at AlphaLetters we have seen the renewed efforts of quantitative researchers to differentiate their models in the following directions:

  • New alternative data
  • New risk models
  • New international markets

The rise of alternative data

Within the quantitative research community, new data sources have become critical. . The rationale is simple: the classic sources of financial data such as stock prices, volumes, and accounting data have been mined by too many PhDs for too long a time. To avoid the next quant meltdown, one needs new alpha based on new data.

The last five years has witnessed a mushrooming of alternative data, including the following varieties:

  • Social media sentiment (for example, iSentium for investor sentiment)
  • Corporate/central bank sentiment (for example, Prattle for sentiment derived from central bank communiqués)
  • App Usage (for example, AppAnnie for gaming stocks)
  • Consumer Receipts (for example, Slice Intelligence for consumer stocks)
  • Credit card usage:(for example, Yodlee for consumer stocks)
  • Geo-location (for example, PlaceIQ for consumer stocks)
  • Satellite (for example, Orbital Insights for shipping/commodity stocks or retailers)

Because many of the alternative data sources are sector-specific in nature, they present challenges for quantitative funds that generally prefer broad data sets. It is not easy to find alternative data sources with large investment capacities and high efficacy.

New risk models

One theory is that high correlations between quantitative investors was caused the popularity of few risk model (most notably Barra) rather than the models themselves.

As a result, we have also seen alternative risk models being adopted by quant practitioners, among which are Axioma, APT, etc. Academic research, however, seems to be lagging on this front as there are still only limited number of papers published on this topic.

Growing interest in international markets and emerging markets

Fundamental managers are not the only ones to complain that it gets more challenging to make profits in the US stock universe. Similar comments are made by many US focused quant managers. In fact, some researchers have found that publishing academic research can destroy stock strategies in the US markets.

Consequently, many investors have been looking at international markets and emerging markets. Academia studies, such as this paper by German researchers, have shown that many cross-sectional trading signals work in international financial markets including European, Asian, and Emerging Markets.

In the past five years we have seen an increase in quant funds focused on international markets, for example in Asia. Several leading US quant funds, notably WorldQuant/Millennium, take pride in their success in international markets and emerging markets in particular.

Conclusion

The creativity of academia seems to know no boundaries. Many of the most important security selection models such as value, momentum, and the accrual anomaly can be traced back to academia. In addition, many quant researchers publish their research in financial journals or academic publications, despite competitive pressures. Academic research has been, and will continue to be, critical to help many quant funds build profitable strategies and meanwhile reduce the risk of a repeat of the Quant Quake.

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About Author

Hui Wang is a Partner at AlphaLetters LLC, a service which has been helping quant investors identify top-quality research and build profitable strategies since 2005. Before this Hui worked as a senior quantitative equity researcher with the Vanguard Group. She is the co-author of "Trading against anchoring" published in the Review of Behavioral Finance in 2017.

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