Quantitative analysts and the strategies they develop are often called alpha generators. Alpha is an investment’s ability to beat the market, exploiting market inefficiencies and thereby generating excess returns relative to a benchmark index. For as long as markets have existed, investors have been motivated to make an abnormal rate of return.
Historically, that was achieved with human-led strategies and manual number crunching. The advent of networked communications and inexpensive high-powered computation opened the door to strategies based on real-time data and complex mathematical models.
Quantitative investing is the use of quantitative strategies to beat the market. It combines the expertise of analysts, statisticians, and developers to create mathematical models that ingest quantitative data from market feeds and other sources. The data is analyzed by a computational model designed to exploit inefficiencies. When the code spots a positive trend or locates an inefficiency, it automatically triggers the appropriate buys and sells.
Quantitative Investing vs. Fundamental Investing
Quantitative analysis may be compared to fundamental analysis, the traditional investment approach. In fundamental analysis, investors are concerned with factors that directly impact the value of underlying assets, such as the company’s profit margins, the health of the business, assets owned, and the quality and experience of the management team.
Warren Buffet is the most prominent adherent of fundamental analysis. His approach is to examine a stock’s fundamentals—performance, debt, profit margins—and compare them to its price. If he perceives that the stock is undervalued based on the fundamentals, he invests, typically over the long term.
Quantitative investing takes a different tack. Quants create multi-factor models and use them to survey a large number of potential investments. The models range from those based on the ratios and relationships of a handful of well-understood metrics to enormously complex models that work with thousands of factors.
Determining which quantitative metrics to focus on and predicting how their behavior affects an investment’s value and risk is the complex art and science of quantitative analysis.
This “scientific” approach aims at the same outcomes as fundamental analysis, identifying and exploiting market inefficiencies to outperform the market. But, instead of going deep on a handful of businesses, it goes broad, analyzing the behavior of relevant factors to identify market inefficiencies, which it then exploits with a pre-determined investment strategy.
Unlike fundamentals investing, quantitative investing works at the pace of technology. This allows investors to exploit short-term inefficiencies that would go unobserved and unexploited by investors relying on brain matter rather than silicon, fiber optics, and code.
The Benefits of Quantitative Investing?
There are several advantages to the quantitative investing approach:
- Breadth: Quantitative strategies can survey a vast number of potential investments, while even the best analysts are limited to focusing on a handful of securities at a time.
- Speed: Quantitative investing strategies can exploit opportunities on much shorter timescales. They can make thousands of transactions per second, allowing investors to take advantage of novel strategies that would once have been impossible.
- Discipline: Quantitative investment systems consistently apply the rules as programmed. They don’t deviate for emotional or psychological reasons, and they don’t miss opportunities.
- Cost: Quantitative funds are typically less expensive to run because they require fewer analysts and managers. However, quantitative trading may have higher technology costs and usually requires a larger capital base, although that is less of a problem for institutional investors and hedge funds.
These advantages are why quantitative strategy has become significantly more widespread in recent years, as investors seek to exploit new technologies and the strategies they enable.
The Potential Drawbacks of Quantitative Investing
We’ve explored the advantages of quantitative trading, but it isn’t all upside. The success of a quantitative trading strategy depends mainly on the quality of the model. If it doesn’t accurately map market behavior, it can’t form the basis of successful investments. Although quantitative investing relies heavily on technology, the strategies depend on the analysts and developers who devise and implement them.
Another disadvantage is that quantitative trading depends on vast volumes of real-time and historical trading data and the network and computational resources that ingest and analyze it. At SpiderRock, we help investors access the quantitative data they need in the most useful formats. In addition to raw and normalized, real-time, low-latency, multicast stock, option, and future feeds, we offer comprehensive historical datasets for backtesting, risk management solutions, and FIX Gateways for low-latency, high-throughput order entry, management, and execution.
To learn more, contact our data and quantitative trading specialists today.