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 pooling risk , 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 was also 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, but 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 pretenured 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.
In addition to being the coauthor of the first major financial econometrics
textbook, Lo had 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 due 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.
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