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it may be sensible for less skilled or infrequent forecasters to mimic the consensus, they often don't. Laster, Bennett, and Geoum also find that nonwinners in the Blue Chip survey herd more often to the forecasts of winners than to the consensus forecast.

      Success Factors: Why Some Forecasters Excel

      Both successful and unsuccessful forecast histories offer valuable lessons. In subsequent chapters we review many of both. What follows here is an example of what one can learn from studying relatively successful forecasters of U.S. Federal Reserve monetary policy – a key input to all financial forecasting.

      European Central Bank (ECB) economists analyzed the accuracy and characteristics of forecasters seeking to predict to what extent the Federal Reserve System, in its Federal Open Market Committee (FOMC) meetings between February 1999 and September 2005, would alter the Federal funds rate target.30 Specifically, they studied how forecasters' accuracy was related to their education, professional experience, type of employer, and geographic location relative to Washington, D.C., where the FOMC meets. Here's what they learned:

      • Education matters, but you don't need a PhD to be a relatively accurate forecaster of Fed actions. Forecasters with a master's degree were more accurate than those with other degrees. However, having a PhD was not associated with superior accuracy.

      • A forecaster's geographic location and local environment influence monetary policy forecast accuracy. Prognosticators working in regions where local economic circumstances – inflation and job growth – deviated most from the national conditions influencing U.S. monetary policy recorded larger errors than others. This finding reminds us that forecasters should ask themselves if their everyday environment is conditioning their judgment. My experience is that investors and analysts in relatively depressed U.S. regions are sometimes too pessimistic about overall U.S. economic conditions, while residents of comparatively strong regions can be too optimistic.

      • In forecasting, specialized knowledge of institutional behavior complements statistical skills. Individuals who had worked for the Federal Reserve Board of Governors recorded relatively fewer errors in forecasting Fed policy. During the period studied, monetary policy forecasters often estimated statistical “reaction functions,” attempting to assign numerical values to actions the Fed had taken in the past in response to various economic statistics (such as inflation and unemployment). However, the Fed can be influenced by variables that are not easily quantifiable. Moreover, the Fed's response to economic statistics can be altered over time by changes in its internal policy making procedures and FOMC membership.

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      1

      Tom Herman, “How to Profit from Economists' Forecasts,” Wall Street Journal, January 22, 1992.

      2

      Timothy R. Homan, “The World's Top Forecasters,” Bloomberg Markets, January 2012.

      3

      Alan Murray, “Greenspan Met with GOP Senators to Hear Concerns About Credit Crunch,” Wall Street Journal, July 11, 1990.

      4

      Paul Duke Jr., “Greenspan Says Fed Poised to Ease Rates

1

Tom Herman, “How to Profit from Economists' Forecasts,” Wall Street Journal, January 22, 1992.

2

Timothy R. Homan, “The World's Top Forecasters,” Bloomberg Markets, January 2012.

3

Alan Murray, “Greenspan Met with GOP Senators to Hear Concerns About Credit Crunch,” Wall Street Journal, July 11, 1990.

4

Paul Duke Jr., “Greenspan Says Fed Poised to Ease Rates Amid Signs of a Credit Crunch,” Wall Street Journal, July 13, 1990.

5

Tom Herman, “How to Profit from Economists' Forecasts,” Wall Street Journal, January 22, 1993.

6

Tim Nudd, “Ad of the Day: Ally Bank – Nobel Prize-winning economist Thomas Sargent lends his expertise, or not, to Grey's theatrical campaign,” Adweek, September 17, 2012.

7

Michael F. Bryan and Linsey Molloy, “Mirror, Mirror, Who's the Best Forecaster of Them All?” Federal Reserve Bank of Cleveland, Economic Commentary, March 15, 2007.

8

David Laster, Paul Bennett, and In Sun Geoum, “Rational Bias in Macroeconomic Forecasts,” Federal Reserve Bank of New York Research Papers, July 1996.

9

Andy Bruce and Anooja Debnath, “Bad Habits Plague Economic Forecasts,” Reuters, June 29, 2011.

10

Herman, “How to Profit from Economists' Forecasts.”

11

Milton Friedman, “The Role of Monetary Policy,” American Economic Review, March 1968.

12

Carmen Reinhart and Kenneth Rogoff, This Time Is Different: Eight Centuries of Financial Follies (Princeton, NJ: Princeton University Press, 2010).

13

Henry Hazlitt, “Pitfalls of Forecasting,” Newsweek, November 22, 1948.

14

Takatoshi Ito, “Foreign Exchange Rate Expectations: Micro Survey Data,” American Economic Review (June 1990): 434–449.

15

Boris Groysberg, Paul Healy, Greg Chapman, and Yang Gui, “Do Buy-Side Analysts Out-Perform the Sell-Side?” Division of Research at Harvard Business School, July 13, 2005.

16

Andrew Leone and Joanna Shuang Wu, “What Does It Take to Become a Superstar? Evidence from Institutional Investor Rankings of Financial Analysts,” William E. Simon Graduate School of Business Administration – University of Rochester, May 23, 2007.

17

Phillip E. Tetlock, Expert Political Judgment – How Good Is It? How Can We Know? (Princeton, NJ: Princeton University Press, 2005).

18

Jerker Denrell and Christina Fang, “Predicting the Next Big Thing: Success as a Signal of Poor Judgment,” Management Science 56, no. 10 (2010): 1653–1667.

19

G. Hilary and L. Menzly, “Does Past Success Lead Analysts to Become Overconfident?” Management Science 52, no. 4 (2006): 489–500.

20

J. Chevalier and G. Ellison, “Risk Taking by Mutual Funds in Response to Incentives,” Journal of Political Economy 105, no. 6 (1997): 1167–1200.

21

Leone

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<p>30</p>

Helge Berger, Michael Ehrmann, and Marcel Fratzscher, “Geography or Stills: What Explains Fed Watchers' Forecast Accuracy of US Monetary Policy?” European Central Bank Working Paper Series 695 (November 2006).