What are Quant Funds, and why are they NOT an outright success?

Automation is taking over many highly paid jobs around the world and money management may be no exception. One illustration of this phenomenon is Quant funds.

What are Quant Funds?

A quantitative fund (or Quant Funds, in short) is an investment fund in which investment decisions are determined by numerical methods rather than by human judgment.
A quant fund, is therefore, a mutual fund in which the investment decision (or the stock buy and sell decisions) is done according to a set of predetermined rules based on a statistical or mathematical model. 
They rely entirely on algorithmic or systematically programmed investment strategies. Unlike actively managed mutual funds, where a fund manager chooses his investments and the timing of entry and exit, quant funds rely on an automated program to make these decisions.

Quant funds use these advanced mathematical models to select stocks based on parameters such as fundamentals, valuations, price trends etc, but these are not limited to just these. Globally, it is also called multi-factor (smart beta) investing strategy where various factors, which result into out-performance and reduce downward risks are identified and a mathematical model is built based on these. The propagators of quant funds say the scope of human error is significantly reduced in Quant Funds since there is almost negligible human intervention, and hence they are likely to perform significantly better than active funds.

What was the need for Quant Funds?

Quant Funds came into existence with the objective of removing human intervention from the investment process. This helps to eliminate various behavioural biases (which are inherent to humans) such as herd mentality, loss aversion, recency bias, anchoring, confirmation bias, overconfidence etc. which may lead to sub-optimal decision-making. Quant Rules effectively act as a mechanism to have better rationality, predictability and control in the way portfolios are managed.

Quant Funds Vs Index Funds Vs Active Funds

Decision making is pretty much automated in Quant Funds, but a quant fund does have a fund manager, and the fund manager may not be entirely hands off, unlike an index fund manager. He often designs and monitors the quantitative model that throws up the portfolio choices. The Quant Fund Manager also monitors the selection for accuracy of the model.

Quant funds basically lie somewhere in the middle of index and active funds.

Index funds replicate the index constituents and the performance by minimising the tracking error while in quant funds, stock selection is done just like an active fund but nothing is left to the discretion of the fund manager.

Read this --> Index Funds Vs Active Mutual Funds

Quant Funds in India?

Globally, quant funds are quite popular and have built up a decent track record while in India, such quantitative strategies are still at a very nascent stage.

DSP has a quant fund running for some time now. And DSP is not the first to be launched in India. Reliance Quant fund has been in the market for many years now.

What are some of the Quant Fund Mathematical Models?
Different Quant Funds work on different mathematical models. The model is designed by experienced fund managers and implemented by expert programmers. Let us look at two of the Mathematical Models being used by two fund houses in India:
1/ DSP Quant Fund Model
The DSP Quant Fund works on a model which eliminates stocks, which are over-leveraged and volatile. The selection of stocks is be done based on various quality, growth and valuations factors derived from EPS growth, return of equity and earnings growth variability and PE, PB numbers etc. There is a stock and sector-specific cap of 10 per cent. The re-balancing of the portfolio is done every six months.

2/ Reliance Quant Fund Model
Reliance Quant Fund model selects stock on the basis of value, growth and momentum indicators.  The model  identifies around 30 stocks from BSE-200 index where growth and fundamentals are improving, valuations are acceptable and momentum is favourable. The mathematical model has been assigned highest weight (approximately 50 per cent) to quality/fundamentals factors, followed by high quality momentum factors along with two value factors to make it a diversified style driven strategy.

Triggers creating interest towards Quant Funds

With advancement in technology and big data explosion, there are many factors that are triggering interest towards Quant Funds.
Fueling the growth of quant funds has been increasingly higher access to a broader range of market data and the growing number of solutions surrounding big data. 

Developments in financial technology and increasing innovation around automation have vastly broadened the data sets quant fund managers can work with, giving them even more robust data feeds for broader analysis of scenarios and time horizons. 

Thus, 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.

Benefits of Quant Fund investments

1/ The most important advantage of using a pre-programmed model to select stocks is that it eliminates the human bias and subjectivity that often trip human investors. 

2/ Using a proven model also allows consistency in strategy across market conditions.

3/ Often, in bearish or volatile markets, active fund managers are forced or tempted to cut positions in certain stocks or shift their investment styles. Quant Fund does not allow for the same.

4/ Since a quant fund follows a somewhat passive strategy, expenses are lower here than active funds. Reliance Quant fund (regular plan), for example, has an expense ratio of 0.98 per cent, which is lower than the 2-2.9 per cent the fund house charges on its other equity funds. 

5/ Quant funds can also have built in checks on sector and stock concentration, something which passive funds (index funds) that mirror the index do not do.

6/ You don’t have to worry about the manager quitting, making mistakes or going off the rails on the fund mandate. 

Performance of Quant Funds in India so far

With so many unique advantages, you would expect Quant Funds to vastly outperform the Active or Index Funds. But elimination of human bias doesn’t automatically guarantee that the fund will be a top performer. 
Reliance Quant fund, for instance, has logged only 8 per cent return over the last five years and about 10.8 per cent over the last ten years — lower than the average returns of large-cap funds in this period. It has also under-performed the benchmark — the BSE 200 TRI — over short and long time-frames.

Why Quant Funds are not exceptional performers?

1/ Quant funds use models that are tested based on historical data and the past is not always a good indicator of the future. Benchmark-beating returns or higher returns than active funds are not a given. 

2/ Since Quant funds are managed on a rule-based approach, they may not incorporate, or may be slow in incorporating elements like market sentiment, news flows and nuanced manager views on certain industries/businesses.

3/ Quant funds work on various assumptions and do a back-testing on historical data. Hence, it may not be able to account for unexpected events. For example, the market crash of 2008 and the quick recovery in 2009 were slightly unexpected events and quant funds globally struggled during these times. 2018 was also a bad year for quant fund globally. 

4/ Markets are a complex system. Hence, it becomes extremely difficult to factor in all variables in the quantitative model. Therefore, quant models may not be very effective over short-term horizons, where events usually define market trends.

5/ If the holdings are re-balanced often, as it is done in many Quant Funds, higher churn may push up costs and thereby eat into returns.

6/ Each quant fund needs to be judged on the work-ability of its own model. This needs time in the market. Maturity of these funds (essentially their models) will come only with time.

7/ Various models were already being used (though not in a fully automated manner) by active fund managers. So, beating active funds is never going to be easy for quant funds.

8/ At the end of the day, the model of a fund is also prepared by humans - which is prone to errors. Garbage in Garbage Out.

Is there a Balanced Approach?

India is still a stock-picker's market and sensitive to many factors, which may not be captured in a quant. A balanced approach where you mix quant process with people's intelligence is likely to deliver better results. Many active funds used a balanced approach, wherein the quant process is followed for filtering out poor quality stocks and then the fund manager's inputs are used to arrive at the final portfolio.

Summary

Quant Funds do eliminate human bias - which is definitely a big plus. 
But Quant funds may be more suited for long-term investors as it may take time for the strategy to play out in full. Hence investors who want to ride on momentum or book profits regularly may need to keep away from it. 

Quantitative strategies are likely to perform better in relatively efficient markets, where the probability of unexpected event sis lower, while in India, a more balanced approach is expected to deliver better results.

Investors can invest in quant funds to an extent, to diversify their risk. But, like any other theme, the exposure should be limited and actively managed funds should be the core of any portfolio in India.