Financial Engineering  (posted 27 Feb 99)

Financial engineering is, in essence, the phenomenon of product and/or process innovation in the financial industries - the development of new financial instruments and processes that will enhance shareholders', issuers' or intermediaries' wealth. In the New Palgrave finance dictionary, John Finnerty lists countless recent financial innovations - from adjustable rate preferred stock to zero-coupon convertible debt - but these all can be classified into three principal types of activities: securities innovation; innovative financial processes; and creative solutions to corporate finance problems.

All these innovations are implemented using a few basic techniques, such as increasing or reducing risk (options, futures and other more exotic derivatives - see RISK MANAGEMENT), pooling risk (see MUTUAL FUNDS), swapping income streams (interest rate swaps), splitting income streams ('stripped' bonds), and converting long-term obligations into shorter-term ones or vice versa (maturity transformation). But to be truly innovative, a new security or process must enable issuers or investors to accomplish something they could not do previously, in a sense making markets more efficient or complete.

Finnerty describes ten forces that stimulate financial engineering. These include risk management, tax advantages, agency and issuance cost reduction, regulation compliance or evasion, interest and exchange rate changes, technological advances, accounting gimmicks and academic research.

The emergence of financial engineering has also been influenced by the realization on Wall Street in the early to mid-1990s that there was a need for a new kind of graduate training. The financial institutions wanted people with heavy mathematics skills and some finance training, and had previously been fed from a haphazard network of different programs. Universities began to respond to the demand by setting up masters programs in financial engineering - and they were helped by the fact that the physics job market was at an all-time low due to the end of the Cold War.

Financial engineering guru: Andrew Lo

Where else but the Massachusetts Institute of Technology (MIT) would you expect to find a course track called financial engineering? For a while the Sloan School of Management was not really accepted at MIT though its graduates were among the most sought after in the job market for newly minted MBAs. But within the science-oriented faculty, business education was hardly taken as seriously as Alfred Sloan, the donor of the facilities, hoped it would be.

Now that has changed. Finance has gone quant: higher mathematics is a regular feature of security pricing, risk management and business strategy. Professor Andrew Lo is one of the key people responsible. He is a first rate scholar who, like others in this volume, can straddle academe and business. His research output is huge, often in collaboration with other leading lights who appear in the Journal of Finance, the Journal of Financial Economics, the Journal of Econometrics, the Review of Financial Studies and the many other publications still being added to the reading lists of professors and practitioners.

The burgeoning field of financial economics has produced a group of young professors who now hold endowed chairs. Just a decade or so ago, they were pre-tenured stars full of research ideas sprung from the basic efficient market hypothesis. They were going on to the next level or two, testing and applying these theories to specific valuation, portfolio strategy and risk problems. They showed their students, who were to become the star practitioners in institutions, how to do investments the modern way. Many of this group won a coveted Batterymarch Fellowship for research when little other funding was available. Andrew Lo, of course, was one of the most promising of that group as a winner in 1989.

Lo's research interests run the gamut of today's financial interests and his papers are among the most thoroughly researched of the field. Students call him an inspired teacher perhaps because he believes in the worth of his subject matter. And in addition to his heavy teaching load, he carries an administrative burden as the director of the Laboratory for Financial Engineering, in fact its founder, at MIT. Somehow, he also finds time to help leading investment firms through consulting projects as well as steadily maintaining active parenting of a young toddler.

In addition to being the co-author of the first major financial econometrics textbook, Lo has a book published in early 1999 entitled A Non-Random Walk Down Wall Street, an obvious counterpoint to Burton Malkiel's classic book of almost the same name (see MARKET EFFICIENCY). As his title suggests, Lo's research indicates that there are some elements of short-term predictability in stock returns and that it may be possible for disciplined active managers to seek them out, exploit them and 'beat the market'.

Financial engineering is the key to superior performance. Lo uses the analogy of the exceptional profitability of a pharmaceutical company, which may be associated with the development of new drugs via breakthroughs in biochemical technology. Similarly, even in efficient financial markets, there can be exceptional returns to breakthroughs in financial technology. Of course, barriers to entry are typically lower, the degree of competition much higher and most financial technologies are not as yet patentable - so the 'half-life' of profitability of financial innovation is considerably smaller.

Clearly, it is difficult to beat an efficient market but, according to Lo, not impossible. So what are the sources of superior performance an active manager can draw on: better mathematical models of the markets? More accurate statistical methods? More timely data in a market where minute delays can mean the difference between profit and loss? All can contribute: as Lo concludes, 'By better understanding the sources of value-added of active managers, rather than focusing purely on past performance, the chances of obtaining consistently superior investment returns can be increased dramatically.'

Counterpoint

Counterpoints to financial engineering include traditional market efficiency arguments against active management, such as Bill Sharpe's arithmetic (see ACTIVE PORTFOLIO MANAGEMENT). And even if it is possible to beat the market, and notwithstanding the fact that past performance should not be the sole criterion for judging investment managers, the riskiness of active strategies can be very different from passive strategies (see INDEXING). Such risks do not necessarily average out over time, and investors' risk tolerance should be part of the process of selecting an investment strategy to match their goals (see INVESTMENT POLICY).

A second counterpoint is the set of arguments against quantitative investing, and notably its reliance on backtesting and 'data mining' (see QUANTITATIVE INVESTING). Engineering, by the very nature of its development and application, builds on whatever is accepted theory at any given stage of the cycle. Investment theories tend to lurch forward in leaps, usually after the disappointment of a prolonged bear market. New theories emerge, correcting the ills exposed by a calamitous decline and engineering applies the new wisdoms.

It should not surprise us that the applications of today's financial engineer seem internally consistent, sound and almost unassailable. That would always be found after decades of reconfirmation of market and portfolio theory. But we should not be lulled into complacency by a catechism built on data of only a few decades. Nor should we imagine that portfolio theory, as we know it today, is the end of investment knowledge. There will be new theory and new engineering to apply it. But it may have a different label than the contemporary 'financial engineering'.

Finally, one of the consequences of the development of computer and financial technologies (as well as the long bull market) is the incredible growth in electronic trading. This has both good and bad implications for ordinary investors. On the positive side, the tools developed by cutting edge financial institutions over two decades ago are now available to the individual household. Yet as with most technologies, the tools are more advanced than the general population's understanding of how to use them properly. Although trading costs have come down dramatically for the individual investor, the possibility of doing serious damage to your nest egg is even greater.

Guru response

Andrew Lo comments: 'These are exciting times for financial engineering, a discipline that has coalesced only within the last decade or so. Despite the recent turmoil in financial markets, or perhaps because of it, quantitative methods have become indispensable to even the most hardened fundamental investment manager. Indeed, the distinctions between fundamental, technical and quantitative have become blurred - all three approaches to financial decision-making are now subsumed by the term financial engineering'.

'The enormous popularity of financial engineering can be attributed to three factors. The first is the simple fact that the financial system is becoming more complex over time, not less. This is an obvious consequence of general economic growth and development in which the number of market participants, the variety of financial transactions, and the sums and risks involved also grow. And as the financial system becomes more complex, financial technology must develop in tandem to keep pace with such complexity.'

'The second factor is, of course, the set of breakthroughs in the quantitative modeling of financial markets, for example, 'financial technology', pioneered over the past three decades by the giants of financial economics: Black, Cox, Lintner, Markowitz, Merton, Modigliani, Miller, Ross, Samuelson, Scholes, Sharpe and others. Their contributions laid the remarkably durable foundations on which all of modern quantitative financial analysis is built.'

'The third factor is an almost parallel set of breakthroughs in computer technology, including hardware, software, and data collection and organization. Without these breakthroughs, much of the financial technology developed over the past thirty years would be irrelevant academic musings, condemned to the moldy oblivion of unread finance journals in university library basements. The advent of affordable desktop microcomputers and machine-readable real-time and historical data have irrevocably changed the way financial markets function. The outcome is nothing short of an industrial revolution in which the old-boys network has been replaced by the computer network; where what matters more is what you know, not who you know; and where graduates of Harvard and Yale suddenly find themselves less employable than graduates of MIT and Caltech. It is, in short, the revenge of the nerds!'

'Of course, this is not to say that technology will replace human judgment altogether. As with other successful technologies, financial technology will succeed by 'leveraging' human abilities, allowing us to do far more efficiently what we have been doing all along and liberating us from the more menial tasks that can be readily automated and delegated. But this suggests that the biggest challenges over the next few decades for financial engineering will not lie in improving existing technologies, but rather in focusing on aspects of human judgment that are now considered impossible to mimic computationally: fear, greed and other emotional aspects of decision-making. Recent advances in the cognitive sciences, neurobiology and computer science may provide some clues to solving these tantalizing problems in financial contexts.'

'In this respect, financial engineering is following a path not unlike those of the engineering disciplines in their formative stages: applications tend to drive the technology, yet research and development are characterized by an intellectual entrepreneurialism that cuts across many different methodologies. Although some of the mathematical and statistical machinery displayed at the cutting edge of the field may seem foreign to the financial community, rest assured that if they prove their worth, they will quickly become absorbed into the mainstream of financial practice.'

'No one has illustrated this entrepreneurialism more eloquently than Harry Markowitz, the father of modern portfolio theory and a joint winner of the 1990 Nobel Prize in economics. In his Nobel address, he described his experience as a PhD student on the eve of his graduation: 'When I defended my dissertation as a student in the Economics Department of the University of Chicago, Professor Milton Friedman argued that portfolio theory was not Economics, and that they could not award me a PhD degree in Economics for a dissertation which was not Economics. I assume that he was only half serious, since they did award me the degree without long debate. As to the merits of his arguments, at this point I am quite willing to concede: at the time I defended my dissertation, portfolio theory was not part of Economics. But now it is.''

Where next?

Andrew Lo's research results and the implication that there are pockets of predictability in the stock market lend support to contrarian strategies of buying 'losers' and selling 'winners' (see CONTRARIAN INVESTING). But he is less convinced by investment strategies based on the insights of behavioral finance into psychological biases inherent in human cognition, which aim to take advantage of individual 'irrationality' (see INVESTOR PSYCHOLOGY).

As financial engineering attempts to define itself as a field with connections closer to the engineering disciplines than more traditional finance, associations are being set up, and the general engineering community does not quite know what to do. Patenting is a becoming a big issue. Recent changes in patent laws and interpretations, along with encouragements for universities to do more patenting have led to an explosion of new patents. Some of these are in financial engineering but it is not clear which can be defended. Certainly, financial patents will have an impact on the efficiency of markets and the rate of financial innovation.

Financial engineering is also having an impact on banking. Innovation in combination with electronic technology is creating a world in which maturity transformation - turning short-term deposits into long-term loans, the central function of banks - is unnecessary. Economic agents - individuals, households, companies - will no longer require this service. Their portfolios of assets and liabilities will be broadly matched in maturity terms: short-term assets will match short-term liabilities, longer-term liabilities will offset longer-term assets. As a result, as Peter Martin of the Financial Times suggests, 'traditional banking is dying. But the grieving throng around the deathbed face a long and expensive vigil.'

Finally, what about market innovations? Financial innovations have been fast and furious over the past two decades. But why are market innovations so slow in coming? We have known for a long time what to do: integrate global markets electronically; pay shares in decimals not fractions; open the specialist books and stock exchanges like the New York Stock Exchange; record and display publicly the questions and answers exchanged by companies and analysts. Indeed, we could even go further and encourage insider trading, bringing insiders' wisdom into the market sooner rather than holding out, waiting for culprits to take advantage of us. It could be done, merely by identifying fewer insiders and letting them trade at which point they would identify themselves. All of these things and more could be done in a stroke.

Read on

In print

John Campbell, Andrew Lo and Craig Mackinlay, The Econometrics of Financial Markets
Andrew Lo and Craig Mackinlay, A Non-Random Walk Down Wall Street
Burton Malkiel, A Random Walk Down Wall Street
Peter Newman, Murray Milgate and John Eatwell, The New Palgrave Dictionary of Money and Finance

Online

linux.agsm.ucla.edu/dir/ - an international directory of financial economists
web.mit.edu/lfe/www - website of the Laboratory for Financial Engineering