Alumni Spotlight: John B. Guerard (B.A. '75)

Friday, June 23, 2017
Alumni Spotlight: John B. Guerard (B.A. '75)

In just 25 years, alumnus John B. Guerard (B.A. '75) already has had a storied career as an academic, author, and financial economist.

"John is one of our eminent Duke undergraduate alumni. He’s become highly respected in his profession and has published in top journals," said Professor Edward Tower.

Within the world of finance, he has worked with such firms as Drexel Burnham Lambert, the DAIS Group at Drexel, Daiwa Securities Trust Company, and Vantage Global Advisors. While at Daiwa, Guerard co-managed a Japanese equity portfolio with esteemed economist Harry Markowitz, winner of the 1990 Nobel Prize in Economics for his theory of portfolio choice.

Guerard counts Markowitz as one of his professional mentors, and they have worked together for nearly three decades, publishing two papers together — along with third co-author Ganlin Xu — in the International Journal of Forecasting and the IBM Journal of Research and Development on efficient portfolio construction and management.

Guerard currently serves as the Director of Quantitative research at McKinley Capital Management in Anchorage, Alaska, located in the geographic center of the world's financial capitals of New York, London, and Tokyo. In this role, he and a team of analysts apply quantitative methods and models to investment strategies that produce 80 percent of their clients' return enhancements.

“At McKinley Capital we use forecasted earnings acceleration in all of our models. It is our most statistically significant variable for stock selection. I have worked on earnings forecasting, and its applications, since 1985,” he said. “Every day, I try to build a better model with the objective of applying it in a newer market or with a better-estimated risk model.”

In his free time — Saturday afternoons and Sunday evenings — Guerard writes books about finance, had edited books published by Springer to honor Harry Markowitz and Jack Treynor, and serves as an associate editor for the Journal of Investing and the International Journal of Forecasting.

Guerard's interest in economics and financial economics developed at a young age. His father, an economics major at the University of Virginia, encouraged him to read works by economist John Kenneth Galbraith. While at Duke, he further cultivated this interest by taking courses with Professors Tom Havrilesky, Lloyd Saville, and Tower, and attending department seminars featuring economists Allan Meltzer (B.A. ’48) and Robert Fogel.

He holds master's degrees in economics and industrial management from the University of Virginia and the Georgia Institute of Technology, respectively, as well as a Ph.D. in finance from the University of Texas at Austin; and he has taught at several institutions, including Lehigh University, New York University (NYU), Rutgers University, the University of Pennsylvania, and the University of Virginia’s McIntire School of Commerce.

Whom do you consider to be your academic and/or professional mentors, and why?
My academic mentors were Jim Vander Weide, Henry Latane, Bernell Stone, and Jan Mossin. I truly believe that I received an excellent education from studying with each of them. I took my first finance class from Jim Vander Weide at Duke. Jim was a great teacher and wrote me letters of recommendations for over 20 years. When I was at Duke I drove to Chapel Hill on Thursday afternoons to take Henry Latane’s Portfolio Theory course. Latane was brilliant. Bernell Stone taught me cash management at Georgia Tech when I was earning a master’s degree. Since then, Bernell and I have done research for The Institute for Quantitative Research in Finance and published several papers together. At Texas, I took my doctoral seminars from Jan Mossin, of the capital asset pricing fame. Jan was outstanding as a truly innovative mind.

My professional mentors are and have been Harry Markowitz, Eli Schwartz of Lehigh University, William Ziemba of the University of British Columbia, and Martin Gruber of NYU. Harry, because he is the father of Portfolio Selection; Eli, because he was a great friend, colleague, and co-author; Bill Ziemba, because we worked on U.S. and Japanese portfolio strategies at the same time for different organizations and produced very similar results (he was brilliant); and Marty, because he has been a great friend since 1980, and in my mind, the ultimate professor and academic consultant. My co-authors, Bernell Stone (Brigham Young University), Mustafa Gultekin (University of North Carolina), Ganlin Xu (GuidedChoice and McKinley Capital Management, LLC Scientific Advisory Board), Shijie Deng (Georgia Tech), Rick Ashley (Virginia Tech), Rochester Cahan (McKinley Capital Management, LLC Scientific Advisory Board), and Anureet Saxena (McKinley Capital Management, LLC Scientific Advisory Board) continue to educate me.

How did you meet and start working with Harry Markowitz? How has his work impacted the work that you do?           
Much of Wall Street exists because of Harry Markowitz. In the beginning, Benjamin Graham and David Dodd published Security Analysis (McGraw-Hill, 1934) and John Burr Williams published The Theory of Investment Valuation (Harvard University Press, 1939). These were the primary investment texts prior to Harry Markowitz’s Portfolio Selection (Wiley, 1959). Graham and Dodd and Williams believed in the low price-to-earnings (P/E) effect: One should buy stocks with the lowest P/E multiples, preferably at a 33 percent discount to the average market P/E. There was no concept of risk in portfolio construction; one merely bought attractive stocks. What Harry created was a framework of the efficient frontier, buying stocks with the highest return relative to risk or the lowest risk relative to return. Today, almost every Wall Street firm has a research group that implements a form of Markowitz’s analysis. A strong fundamental understanding of Markowitz’s theories is necessary to succeed in equity or portfolio analysis.

Harry Markowitz is the most brilliant person I have ever met. I worked at Drexel Burnham Lambert after teaching at the University of Virginia and Lehigh. In February 1990, Drexel declared bankruptcy. I was among 10,000 employees fired from Drexel in one day via fax. Around that time, Harry was starting a research department at Daiwa Securities. We spoke on a Tuesday night, and I flew to New York on Saturday morning to interview with him at the Grand Central Oyster Bar. I joined Harry at Daiwa six weeks later. Six months after that, I presented a paper on our joint research at the Berkeley Program in Finance at Santa Barbara, and six months after that, Harry won the Nobel Prize. Daiwa Securities launched Fund Academy in January 1991, based on my composite model of expected returns and the Markowitz optimization system. Fund Academy had a four-year, fixed life and outperformed the market by over 3000 basis points in its life, which we documented in a footnote in one of our professional publications.

How has the finance industry evolved over the last few decades? How do you think it will change in the coming years?
Twenty-five years ago, there were three research databases: Compustat (balance sheet, income statement, and sources and uses of funds data), CRSP (the University of Chicago database of monthly stock prices, returns, and dividends), and the Institutional Brokerage Estimation Services (otherwise known as I/B/E/S, an earnings forecasting database). Now, we have earnings transcripts database, social media sources, and other “Fancy Dan” data sources.

Twenty-five years ago, I used SAS. Now you can use SAS on the cloud. Python, R, AdaBoost for machine learning, and other languages are also available. Personally, I believe that SAS with the regression model that addresses outliers and multicollinearity, still reigns supreme in Japan relative to 35 other models and compiles about 85 percent of the excess returns of AdaBoost in optimal markets.

Twenty-five years ago, I cranked the composite model to create optimal portfolios with the Markowitz mean-variance risk as well as enhanced index weighting and equal active weighting procedures. The new optimization techniques, emphasizing tail loss, pioneered by Zari Rachev, enhance performance relative to the Markowitz mean-variance risk by about 15 percent.

Twenty years ago, Barra, Inc., and APT were the only risk model firms in existence. Now there are several additional firms, including Axioma, which specialize in robust risk modeling, custom risk models, and the alpha alignment factor analysis. We hold an annual McKinley Capital Horse Race to test for the most effective risk models, and we find that Axioma has crushed most of its competitors in the past four out of five years. APT continues to be very good.

What do I expect 25 years from now? I expect finance in the United States will be dominated by small, 10- to 12-people firms that charge performance-incentive fees; earnings forecasting models will still be relevant; Shanghai will be as important as New York City; and London will have descended into the “Middle Ages” financially. Quantitative analysis will still be highly relevant, and graduate students will make pilgrimages to the graves of Harry Markowitz and William F. Sharpe.

You’ve had a diverse background in academia and finance, and in addition to your role at McKinley Capital, you’re an author and published researcher. What motivates your research and your writing?
Personally, I believe it is in the best interest of Wall Street firms to employ people with Ph.D. graduates who have the ability and capability to publish applied research. Publications help differentiate a firm’s research, and they establish intellectual credibility and recognized expertise. In terms of balancing academia and real-world finance, we at McKinley Capital seek to publish in journals that stress applied investment research, such as the IBM Journal of Research and Development, the Annals of Operations Research, the International Journal of Forecasting, and the Journal of Investing. With Harry, we sought to model all stocks with all available models. As a “global growth” specialist, McKinley Capital’s research concentrates on earnings and price momentum studies. We seek to use forecasted earnings acceleration and price momentum variables to outperform the market. We have done a very good job of publishing, particularly with our Scientific Advisory group, such that we can compete on an intellectual level with far larger firms in terms of assets under management and Ph.D. graduates employed.

You were awarded the 1996 Moskowitz Prize for research in socially responsible investing? What is socially responsible investing, and why is it important?
I was director of research at Vantage Global Advisors (which no longer exists) when I won the first Moskowitz Prize. In its 20-year history, the Moskowitz Prize has been awarded to faculty from Boston College, Oregon, Cal-Irvine, Notre Dame, Maastricht, Cornell, Syndey, Eramus, Stanford, Cal-Davis, London Business School, Geneva, and Harvard Law School.

I was awarded the prize for research on socially responsible investing (SRI). My work, published in the Journal of Forecasting in its technical form and in the Journal of Investing, addressed the most relevant question in my mind: Is there a cost to being socially responsible in investing? The answer is “no”; SRI says that you can invest with the aim of “doing good” and still do well financially. If one screened out businesses involved in nuclear power, sin (alcohol, gambling and tobacco), military, and fossil fuel from one’s portfolios, returns went down slightly, but the decrease was not statistically significant. One can eliminate stocks that do not pass the Kinder, Lydenberg, and Domini (KLD) social choice investment screens and still not sacrifice rewards.

Are you currently working on anything that you find particularly exciting and interesting?
I am working on an extension on my SRI analysis with Chris Geczy, of the Wharton Jacobs Levy Equity Management Center. We again found only modest portfolio return reductions imposing SRI criteria, in an aggregate level, in portfolio construction, with the KLD criteria for 1997-2014. However, if one uses disaggregated, normalized KLD data and the five-factor Fama-French model, then one finds that the largest excess returns are produced by total KLD criteria, diversity, and human rights.

I am working with Shijie Deng at Georgia Tech on a book on quantitative finance to be published by Peking University Press in 2018.

Markowitz and I are working on timing (forecasting) growth, momentum, and value factors, a so-called Holy Grail of finance. Most risk-factor returns follow a random walk with drift process. We have found, however, that global momentum factor returns are statistically associated with six- and nine-month changes in the Eurozone leading economic indicators.

On a personal, weekend research note, I am very interested in the minimum wage. I worked with Bill Alpert on the minimum wage and its effects on unemployment and employment using Granger causality. We presented the paper at the 1983 AEA meeting and published it in Applied Economics. In my opinion, few questions are as relevant as the minimum wage.

What advice do you have to future generations of Duke students who want to pursue careers in finance?
Failure is a likely scenario in finance. In 1990, the average person at Drexel Burnham had worked 20-25 years on Wall Street with five firms: Merrill Lynch, Goldman, Salomon Brothers, Lehman, or Kidder Peabody. People stayed four to five years at a firm and left for better compensation or were fired. Research analyst budgets continually expand and contract with market conditions. You can be fired for being a prima donna, an idiot, or insubordinate, in your boss’s mind. Most people I know on Wall Street have been fired at least once for such causes. Even Harry Markowitz was fired in 1969 and discussed the situation in his Risk-Return Analysis (McGraw-Hill, volume one, 2013). Being fired hurts, but it can also propel you to pursue greater success. The best comeback for being fired is future success and much higher compensation!