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The Transformational Influence of “Big Data” on the 21st Century Global Financial System

wall street bull data


Big data has arrived. The cheering din grows louder. Supporting the idea of a monumental data-stimulated change ahead in

many disciplines, especially finance, information flows are rising at an exponential pace. A Google search on April 15, 2013,

for big data revealed a gargantuan 2.2 billion entries, shrunk by using an advanced filter to a “paltry” 30.2 million items. Big

data conferences, books, and articles proliferate. This essay defines big data, highlights its vast potential, acknowledges

its limitations, sketches its transformational influence on the 21st century global financial system, mainly from an asset

management perspective, and lists key capital market inquiries that might be well addressed by big data methods.


Green eyeshade finance perished little more than a generation ago. A small group

of grizzled veterans from the Great Depression still inhabited financial institutions

as recently as the late 1970s. Performing more forensic archaeology on historical

measures of economic and corporate vitality, these “statistical clerks” (as security

analysts used to be known) were outfitted with pencils, spreadsheets, and adding

machines the size of giant dictionaries in lieu of computers. These prototype modern

capital-market soldiers engaged mainly in retrospective comparative analyses

rather than forecasting. To satisfy the demand for prognostications, the illusion of

forecasting was created by the manufacture of modified extrapolations of the past

into the future. Like the medical and pharmaceutical fields, competition atomized

research to cater to sponsoring institutions to the disadvantage of perhaps more

rapid coordinated progress.

The past four decades wrought prodigious change to the practice, principles, and

technology of finance. Monroe calculators replaced printed bond yield tables. In

turn, computers quickly superseded Monroe calculators. Bloomberg terminals and

broadcast financial media introduced near real-time simultaneous dissemination of

important financial market information. High-frequency trading advanced into the

machine realm via APIs (Application Program Interfaces), with client servers co-

located next to exchange servers to expedite processing speed. Asset management

and dealer scale ballooned. Quantitative methods blossomed beyond simple

statistics to sophisticated models.

Graduate programs in financial engineering began to sprout up in the in the early

1990s. Empirical analyses surpassed qualitative, subjective techniques. Investment

and planning horizons both shortened (along with the burgeoning hedge fund

industry) and extended for plan sponsors, endowments, and sovereign wealth funds.

Globalization, disintermediation, and derivatization recast the financial system.

Regulatory oversight converged more regionally than globally and could not fully

keep pace with all the new products, new markets, and new techniques of the rapidly

evolving global financial system. Many of the best and brightest students elected

to pursue lucrative careers in finance over manufacturing, management consulting,

science, medicine, law, and other professional fields.

Despite numerous welcome advances in economics and finance in the late 20th and

early 21st centuries, the forecasting prowess of these social science disciplines has

not been distinguished, as evidenced by the general capital market shock that greeted

the arrival of the partially predictable “Great Recession” and the extended policy

uncertainties as to how to best cope with its long aftermath. Like seismologists who

can calculate the probability but not the timing of earthquakes, financial market

prognosticators can articulate possible stresses but usually not their timing, magnitude,

or implications. These shortcomings may be addressed in the 21st century.

This early third millennium already has posted an impressive list of milestone

scientific achievements. The human genome has been decoded (2001). Earth-like

planets have been discovered in other solar systems (2007). The Higgs-Boson

particle (2012) presumably has been confirmed.

And the best advances are yet to come, especially in better understanding and forecasting

the path of the incredibly complex global financial system that serves the needs of more

than 7 billion human beings currently populating approximately 200 nations. Under the

auspices of big data, substantial aid is on the way to better decipher and navigate the

intertwined financial system realms of economics, regulation, corporate finance, asset

management, risk, product innovation, insurance, technology, and marketing.

As shown in Exhibit 1, world curiosity about big data has skyrocketed. Since mid-2012, big data has partially been credited with U.S. President Obama’s re-election. And big data has been featured at the World Economic Forum in Davos in 2012 and the Council of Foreign Relations in 2013 as well as in such publications as The Wall Street Journal, the Financial Times, The New York Times, Harvard Business Review, CFA Institute Magazine, Fortune, Foreign Affairs, and spawned conferences around the world like “Big Data in Africa.”

In addition to abetting actuarial methods, cosmological inquiries,

meteorological predictions, unraveling quantum and criminology mysteries, aiding

epidemiological studies, advancing life sciences, and expediting business logistics,

these articles envision the construction of more accurate economic and business

predictions as well as improved decision-making processes thanks to big data.

The swift amplification of the big data din may foster doubts by some seasoned

capital market veterans. After all, evanescent market fads are common. And

“catchy-phraseology hype” sells in futurology. False prophets of revolution litter

the prediction landscapes of economics, capital markets, and technology. Recall

the excessively enthusiastic expectations for fractal market analysis in the early

1990s as well as “B2B” and “e-commerce” in the late 1990s. For example, “horror

of horrors,” shopping mall obsolescence was presumed by the inevitable surrender

by consumers to the glories of online shopping. But in our view, the forthcoming

successful application of big data methods will disappoint jaundiced cynics.

The concept of big data, including the search for regular signals to better predict

the future, has been around since the dawn of humanity. Effectively, big data

is simply a new name for an old and universal undertaking: the acquisition and

application of new information confer competitive advantage throughout the

economic system and speed progress in all fields.

Through history, these data surges are a series of stochastic jumps rather than

continuous flows. And each can be characterized by a different source of information

expansion. The seafaring “Age of Discovery” in the 15th and 16th centuries was

predicated on new navigation information. The accumulation of data spurred the

Scientific Revolution in the 15th-17th centuries, which in turn begot the Industrial

Revolution of the 18th and 19th centuries. Under the tutelage of such business

luminaries as Alfred Sloan, W. Edwards Deming, and Peter Drucker, modern corporate

management came to rely upon the systematic acquisition and interpretation of new

information. For decades, successful firms have set out to learn as much as possible

about their political environment, customers, products, costs, and competitors. And

all major sports now routinely prowl for fresh data-driven guidance on legitimate

performance enhancement.

Despite exponential technological advance over the past century with attendant

societal benefits, information harvests, information analyses, and information-

based transformation of many institutional practices in financial services still

remain in an adolescent phase in the early 21st century. Historical records have

not been fully converted into computer-manipulated forms and awaiting the

installation of “new measurement sensors,” the “datafication” of much pertinent

financial market information has not been completed. To pick one field, the

complete transcription of financial market reality into interpretative computer-

friendly components lies over the long horizon. New analytical and visualization

methodologies await invention.

Over the long run, big data may come to be viewed as the successor to the Internet

in terms of revolutionary impact. For financial markets, this implies the creation of a

whole new set of questions, and original data-supported insights (see accompanying

list of potential big data inquiries), and hopefully better performance. This shift

may not be uniform. For cultural, ideological, and institutional purposes, full and

even partial acceptance of new methods often varies and extends over many years.

(In Hicks’ Capital and Growth , these long-term processes are called “information

diffusion” and “capital transmutation.”)

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