Fundamental Lessons in Trading

How universities are preparing a new generation

Originally published in the June 2013 issue

Research is the quest for knowledge, an empirical investigation to discover the truth, establish factual evidence opinions aside, solve existing problems and provide insight into new theories. Research is the process by which science investigates and analyses information to yield conclusions. As Francis Bacon once said, “Science is but an image of the truth.” Research is based on the classic scientific method of empirical evidence, a thorough study of the information, facts and data at hand.

With technological automation advancing rapidly in the financial industry, the need to understand market dynamics, market micro-structure, the influences of geopolitical economics and central bank policy is more important than ever. The accelerated pace of global events and technology has created a new normal within financial markets. Such conditions result in thinning margins and a lower risk appetite for trading firms of all stripes.

The tumultuous market turmoil from events such as the Associated Press Twitter hack and Knight Capital’s software glitch has sent jitters through market participants, fuelling the regulatory debate with calls to act punitively. Such a mindset of guilty until proven innocent is wrongheaded. But hidden behind all that media cacophony is the quiet voice of reason. In universities across the US and Europe academic researchers are immersing themselves in analyzing market structure and educating future generations of traders, quants and regulators.

Financial market research examines the causal effects behind price formation and transaction costs resulting from trading behavior. Prediction is not the Holy Grail, but calculating future probabilities better than the next guy is the driving force behind quantitative analysis for profitable trading. The next generation of quants are the product of university programmes specifically tuned to address this rapidly accelerating new normal. Academics have heard the call, responding with MS degree programmes in financial engineering, quantitative finance and operations research.

The role of the quant has evolved beyond that of mathematician to encompass a much broader set of responsibilities. They are required to be well versed in the business processes of the trade life-cycle. It is the intersection of technology, finance and mathematics for investment decisions, portfolio management, cost controls and trading automation. The ideal quant has a blend of skills in finance, mathematics and computer science.

And university programmes are responding with curricula focused on financial criteria and the enabling technology. These programmes are designed specifically for a new breed of quants covering numerical analysis and stochastic processes to understand order in seemingly random data. Curricula cover algorithmic trading and portfolio analysis. They delve into options pricing models, interest rate models and how those affect equity and currency markets. But that’s not all.

Today’s quants are learning that computer science, programming skills and database systems are foundational elements behind the accelerated pace of trading. Prominent universities across the globe, from Oxford University and Columbia University, to U.C. Berkeley and numerous others, have recognized this and are incorporating the same state of the art technology used by industry into their curricula. Courses in data structures, database systems, probability and statistical market data analysis are leveraging time-series tick database and Complex Event Processing (CEP) technology. This ultimately reflects a trend on how higher education is evolving to prepare students for careers in finance.

University faculties and graduate students within financial engineering departments are engaged in a quest to understand the multitude of factors that influence our market behaviors – both its successes and failures. They look to move beyond the anecdotal to discover hard evidence. They seek to lay bare the empirical truth of what forces – however subtle – shape the yield curve, determine the microeconomic aftermath of macroeconomic policy decisions such as quantitative easing and factors driving market efficiency. Richard Holowczak, Professor of Computer Information Systems at Baruch College, City University of New York, has researched the impact of the Options Penny Pilot, a programme begun a number of years ago, but which had a profound influence on the options industry’s growth.

Analytical research looks for the determinate forces of market microstructure, the goal of which is to rationalize the interplay of those forces – the participants’ influence on price formation, price discovery and transaction costs. Over the past few years many research studies have lasered in on high-frequency trading (HFT) and its impact on volume, spreads and market quality. That is a hot research topic as HFT has matured and the industry wrestles with coming to terms with the proliferation of automated and algorithmic trading across all asset classes.

What of the market impact of recent regulations? There are trade halting rules like circuit breakers and limit up/limit down. While it may be too soon to fully understand their fallout, research is underway to understand their reverberating effects not just within the fragmented equities markets, but also across the landscape of other assets classes.

Professor Dale Rosenthal from the University of Illinois at Chicago is using theoretical models to demonstrate and ultimately demystify price movements. As Rosenthal describes it, this is the “particle physics of finance.” These are guiding principles in trading and trading technology, vital lessons as students make that transition from the classroom to industry.

University professors use research projects to challenge graduate students to understand market mechanics, explore and optimize trading behaviors, solve optimal execution problems and better understand modern portfolio theory. For this they have created mock trading floors, stores of deep equity and options data and mastered analytical tools. University faculties strive to educate and groom the next generation of quantitative analysts, economists, even future regulators, and prepare them for eventual leadership roles in the financial marketplace. The economics of world markets will be better off for it.

The quest for the truth is a noble and lofty goal. As author Sylvia Nasar says of John Maynard Keynes, a confidence in the “apparatus of the mind” is of utmost importance for wrestling with economic catastrophe. When markets are strained, it causes far too many to wield anecdotal opinions and too few armed with evidential facts as to why such distressing conditions happen. While they have pressed the SEC to accelerate its regulatory efforts, universities across North America and Europe have been pressing ahead to reveal the truthful image through studied research.

Louis Lovas is the director of solutions at OneMarketData where his responsibilities include strategic business development and delivering targeted solutions for quantitative research and trading systems.