Discovering Alpha Through Automation

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VenkatHeadshotIn this special guest feature, Dr. Venkat Srinivasan of Rage Frameworks, Inc.,  outlines how big data can help active investment managers see success in financial markets in pursuit of Alpha. Dr. Venkat Srinivasan is chairman and CEO of Rage Frameworks, Inc., which enables the creation of intelligent, live, business process automation solutions. He has incubated several ventures, namely eCredit, Brightleaf, EnglishHelper, Teranode & Corporate Fundamentals. He is an expert in knowledge-based system architectures, computational linguistics and natural language processing.

Consistently discovering alpha is the holy grail of investment management, and is an arena populated by two primary schools of thought. The first consists of active managers who proactively try to uncover investment opportunities that can generate higher returns, and the other consists of passive managers who believe markets are efficient and invest in a diversified portfolio of securities mirroring the market.

While there is growing acceptance even amongst die-hard efficient market finance theorists that financial markets are not efficient to the level originally hypothesized, active managers have not consistently outperformed their passive counterparts in many asset classes in recent times. However, can investment managers systematically uncover pockets of market inefficiencies using Big Data analytics?

The short answer is yes. How this is achieved takes more time to explain.

Keeping Up with the Information Deluge

Of late, many academic researchers have found several anomalies in security price behavior that point to the presence of market inefficiencies in those contexts. For example, using the portfolios of the best and worst performing companies over the previous three years, and by comparing their performance over the following five years, researchers found that while long-term trends tend to reverse, short-term trends tend to persist. Thus, stocks that went up last year have a likelihood of going up again this year. This is attributed to a positive sentiment bias amongst investors. Many studies have reported similar findings of under- and over-reaction by investors in financial markets.

Clearly, with the mounting evidence that markets are not information efficient, active managers should be able to outperform passive funds. Yet, active managers on the whole did much worse than passive funds during the last few years in certain asset classes. Compounding issues is the fact that the explosive growth in information on the Internet has made the task of active managers much more difficult. The inability of active managers to outperform index funds is not just due to the current monetary policy, wherein most stocks are moving along with the index.

In sum, active managers may be finding it difficult to process all the information that is becoming available on a continuous basis. While most seem to argue that active managers tend to do well when individual stocks perform differently than indices, there has been no work that attempts to isolate whether an improved ability to systematically access, identify and analyze relevant information can intelligently assist active managers find alpha consistently.

Active versus Passive Advising

Within this discussion exists considerable debate on the merits of Active vs Passive Investing. Passive investing is when money is invested in securities proportionally to their weight in a market capitalization weighted index. As the market moves, so does an investor’s portfolio. If a specific security’s weight increases in the market portfolio, so does its proportion in the portfolio. If an investor believes that markets are information-efficient, then passive investing is a no brainer.

On the other hand, if the investor believes that markets are not information efficient, then active investing is a viable option. The challenge is that active investing requires trust in the manager’s ability to systematically process all relevant information, and accurately interpret and predict the future.

Will systematic and intelligent processing of all the information arriving in the market aid fund managers with a greater disposition to active investing outperform their benchmarks? If information inefficiencies persist in markets, then evidence suggests processing all the available information will help managers find such inefficiencies more consistently. Superior skill and care will still distinguish managers because even after processing all the information, managers still need to integrate the results of such processing with their investment process effectively.

Putting Big Data to Work

In this era of pervasive digital information flows, enterprises realize that they cannot afford not to capture and analyze the enormous amount of information that is being generated on a real time basis. The tidal wave of Big Data – very large data sets both structured and unstructured – is unlikely to stop as enterprises and individuals alike continue to contribute to today’s worldwide data torrent. The ability to instantly and consistently analyze vast amounts of data and rapidly customize, experiment and embrace new business models will be the way companies compete in the future and move closer in their pursuit of Alpha.


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