Moore’s Law Vs. Murphy’s Law In The Financial System: Who’s Winning?

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Moore’s Law vs. Murphy’s Law in the Financial System: Who’s Winning?

Andrew W. Lo

Massachusetts Institute of Technology (MIT) – Sloan School of Management; National Bureau of Economic Research (NBER)

January 22, 2016

Abstract:

Breakthroughs in computing hardware, software, telecommunications, and data analytics have transformed the financial industry, enabling a host of new products and services such as automated trading algorithms, crypto-currencies, mobile banking, crowdfunding, and robo-advisors. However, the unintended consequences of technology-leveraged finance include firesales, flash crashes, botched initial public offerings, cybersecurity breaches, catastrophic algorithmic trading errors, and a technological arms race that has created new winners, losers, and systemic risk in the financial ecosystem. These challenges are an unavoidable aspect of the growing importance of finance in an increasingly digital society. Rather than fighting this trend or forswearing technology, the ultimate solution is to develop more robust technology capable of adapting to the foibles in human behavior so users can employ these tools safely, effectively, and effortlessly. Examples of such technology are provided.

Moore’s Law Vs. Murphy’s Law In The Financial System: Who’s Winning? – Introduction

In 1965—three years before he co-founded Intel, now the largest semiconductor chip manufacturer in the world—Gordon Moore published an article in Electronics Magazine in which he observed that the number of transistors that could be placed onto a chip seemed to double every year. This simple observation, implying a constant rate of growth, led Moore to extrapolate an increase in computing potential from sixty transistors per chip in 1965 to sixty thousand in 1975. This number seemed absurd at the time, but it was realized on schedule a decade later. Later revised by Moore to a doubling every two years, “Moore’s Law” has been a remarkably prescient forecast of the growth of the semiconductor industry over the last 40 years, as Figure 1 confirms.

Technological change is often accompanied by unintended consequences. The Industrial Revolution of the 19th century greatly increased the standard of living, but it also increased air and water pollution. The introduction of chemical pesticides greatly increased the food supply, but it increased a number of birth defects before we understood their properties. And the emergence of an interconnected global financial system greatly lowered the cost and increased the availability of capital to businesses and consumers around the world, but those same interconnections also served as vectors of financial contagion that facilitated the Financial Crisis of 2007–2009. As a result, the financial industry must weigh Moore’s Law against Murphy’s Law, “whatever can go wrong, will go wrong,” as well as Kirilenko and Lo’s (2013) technology-specific corollary, “whatever can go wrong, will go wrong faster and bigger when computers are involved.”

Some of the unintended consequences of financial technology include firesales, flash crashes, botched initial public offerings, cybersecurity breaches, catastrophic algorithmic trading errors, and a technological arms race that has created new winners, losers, and systemic risk in the financial ecosystem. The inherent paradox of modern financial markets is that technology is both the problem and, ultimately, the solution. Markets cannot forswear financial technology—the competitive advantages of algorithmic trading and electronic markets are simply too great for any firm to forgo—but rather must demand better, more robust technology, technology so advanced it becomes foolproof and invisible to the human operator. Every successful technology has gone through such a process of maturation: the rotary telephone versus the iPhone, paper road maps versus the voice-controlled touchscreen GPS, and the kindly reference librarian versus Google and Wikipedia. Financial technology is no different. To resolve the paradox of Moore’s Law versus Murphy’s Law, we need version 2.0 of the financial system.

Moore’s Law and Finance

Moore’s Law now influences a broad spectrum of modern life. It affects everything from household appliances to biomedicine to national defense, and its impact is no less evident in the financial industry. As computing has become faster, cheaper, and better at automating a variety of tasks, financial institutions have been able to greatly increase the scale and sophistication of their services. The emergence of automated algorithmic trading, online trading, mobile banking, crypto-currencies like Bitcoin, crowdfunding, and robo-advisors are all consequences of Moore’s Law.

At the same time, the combination of population growth and the complexity of modern society has greatly increased the demand for financial services. In 1900, the total human population was estimated to be 1.5 billion, but little more than a century later—a blink of an eye in the evolutionary timescale—the world’s population has grown to 7 billion (see Figure 2). The vast majority of these 7 billion individuals are born into this world without savings, income, housing, food, education, or employment. All of these necessities today require financial transactions of one sort or another, well beyond the capacity of the financial industry in 1900. Therefore, it should come as no surprise that innovations in computer hardware, software, telecommunications, and storage continue to shape Wall Street as a necessary part of its growth.

Moore's Law
Figure 2. Semi-logarithmic plot of estimated world population from 10,000 B.C. to 2011 A.D. Source: U.S. Census Bureau (International Data Base) and author’s calculation.

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