If you're interested in working for a quant fund, you'll be interested to know that Morgan Stanley's equity strategists have produced a big new 65 page report on factor and quant-based investing globally.
We can't reproduce the whole thing here, but can pull out some of the most salient - and simpler - points. If you aspire to work for a quant fund, this is (some of) what Morgan Stanley's strategists have to tell you...
Morgan Stanley's strategists have produced a chart showing trends in investing dating back to 1950. Quant-based investing is the new-new thing.
Quant investing grew out of the mean variance model of investing from the 1990s in which portfolios were assembled so that returns were maximized for a particular level of risk. These led to covariance matrices that generated beta values representing each asset class's sensitivity to equity movements. Today's quant funds, which use factor analysis (see below) can be seen as a more granular attempt to summarize the risk factors that influence returns in a market where risk seems to have been subdued..
For all the talk, quant funds are still a tiny subset of the market. Right now, they only represent 7% of assets under management in the market, despite growing at a compound average growth rate of 17% over the past six years.
Morgan Stanley's strategists note that a lot of quant funds are active funds. In other words, they've taken over the stock-picking function of human fund managers and use complex mathematical models to pick stocks instead.
Just like the human analysts who went before them, these funds can use various strategies to make investment decisions, including event-driven, trend-following (momentum), economic data-driven or price inefficiency seeking.
Other quant funds follow so-called 'factor-based' strategies. These are strategies that try improve investment outcomes (eg. enhanced returns, improved diversification, reduced risk) by targeting exposure to specific drivers of risk and return which are referred to as factors.
The five key factors targeted by quant funds are typically: value, momentum, size, quality and low volatility.
Quant funds following factor-based strategies typically employ quantitative/algorithmic approaches that automatically and dynamically adjust their portfolio holdings based on a given factor on an ongoing basis. One example would be a value-oriented factor strategy buys stocks that are trading at a discount to fair value or the broader market.
Factor-based strategies are not exactly active, nor exactly passive - they sit at the intersection between passive and active investing.
A subset of factor-based investing is "smart beta" investing. This is investing which uses clearly stated factor-based rules, but which then tries to derive extra returns by creating portfolios weighted towards particular securities instead of simply constructing the portfolio or index according to the relative market capitalization of the companies invested in.
Smart beta strategies can typically be separated into three categories: return-oriented (value, growth, quality), risk-oriented (minimum volatility, risk parity) and other (equal-weighted, multi-asset). A lot of smart beta strategies are built around exchange traded funds (ETFs) (see below).
Morgan Stanley's strategists note that quant and factor-based net flows accounted for 208% of the total US-domiciled mutual fund industry flows, and there has been a similar trend so far in 2017. Quant and factor-based mutual funds are on pace to set record net inflows, growing at about a 9.5% annualized organic growth rate through July.
BlackRock, the world's largest asset manager, announced in March that it would overlay a quantitative strategy to some of its active equity funds in search of alpha. Other mutual funds are expected to do the same.
The other big growth area are smart beta ETFs, where Morgan Stanley's analysts calculate that assets under management have grown at a CAGR of 25% from 2010-17 YTD - well above the 18% CAGR for the ETF industry as a whole over the same period.
This year, Charles Schwab, BlackRock, WisdomTree, Franklin Templeton, Virtus and Goldman Sachs are launching smart beta products in ETF wrappers. In future, Morgan Stanley predicts growth in fixed income ETFs, environmental, social and governance (ESG)-related ETFs and emerging market ETFs.
For all the excitement, Morgan Stanley notes that quant funds haven't done that well. Factors are becoming less good at generating returns and in the U.S. only one factor - enterprise value/EBITDA, has an annualized spread (i.e., performance of the top versus bottom quintile of a metric) of at least 5% since 2012. This is in contrast to the past, where factors had much larger spreads.
The decline in factor efficacy is thought to be due: increased competition between funds, the strange macro economic environment (eg. ultra-low interest rates), or regulations which have hampered the ability of quant funds to perform properly.
Many quants funds are looking into alternative data sources ("big data") as sources of competitive advantage. These can include anything and everything from checkout scanner readings to parking lot traffic, credit card transactions, etc. The hope is that these data sets will produce uncorrelated returns and introduce previously untapped excess returns. If you want to get in on the next big quant trend, these big data providers may be the best place to situate yourself.