Forecaster Rationality and Expectation Formation in Foreign Exchange Markets: Do Emerging Countries Differ from Industrialized Economies?

ABSTRACT

This paper uses the Consensus Economic Forecast poll to investigate how forecasters in the foreign exchange market form expectations and whether the expectation formation process differs between industrialized and emerging countries. In order to explain the expectation formation of forecasters in countries and country groups, we analyze around 50,000 forecasts for 22 OECD member currencies. We find that differences between the way forecasters in industrialized countries and emerging countries form exchange rate expectations. However, we show that one important difference is due to a difference in forecasting behavior of emerging countries. Controlling for this feature lets the forecasting behavior in emerging countries resemble more the ones found for industrialized countries, but not for all forecast horizons.

KEYWORDS:

• Foreign exchange markets
• forecasts
• chartists
• fundamentalists

JEL CLASSIFICATIONS:

• F31
• D84
• C33

Acknowledgments

We are grateful to two anonymous referees and the editor for the referees' valuable comments and suggestions.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 The participants of the poll are working for investment banks, commercial banks, and consultancies. Not all institutes forecast all currencies, resulting in 30–40 institutes to forecast a given currency. A complete list of participants for each exchange rate pair is available upon request.

2 They include forecasts of the Australian dollar, Brazilian real, Canadian dollar, Chilean peso, Chinese renminbi, euro, Japanese yen, Mexican peso, New Zealand dollar, Russian ruble, South African rand, South Korean won, Turkish lira, and the UK pound sterling vis-à-vis the US dollar. In addition, the data set includes forecasts of Czech koruna, Danish krona, Hungarian forint, Norwegian krone, Polish zloty, Slovakian koruna, Swedish krona and Swiss franc vis-à-vis the euro.

3 In order to determine the PPP, the OECD (Eurostat and OECD 2012) first calculates relative prices at the lowest possible level (i.e. product level), where relative group prices are calculated for individual goods and services. The prices of goods are then combined at the product group level, where the averages of the respective prices are calculated and averaged to obtain the PPP level for the respective group. Lastly, the PPP for the product groups covered are weighted and averaged to obtain weighted PPP for the aggregation level up to GDP, where weights are derived from relative expenditure shares in the economy. Similarly, we also applied means as an alternative representation of actual exchange rates, which did not alter the results. The results are available on request.

4 Tsuchiya (2015) investigates whether forecasters hold asymmetric loss functions in South Africa and Pierdzioch, Rülke, and Stadtmann (2012a) provide some evidence on general forecasting behavior in emerging countries.

5 The paper follows the studies of Ito (1990), MacDonald and Marsh (1996) and Elliott and Ito (1999) are commonly used as a yardstick for the analysis and were developed further by Frenkel, Rülke, and Stadtmann (2009), Rülke, Frenkel, and Stadtmann (2010) and ter Ellen, Verschoor, and Zwinkels (2013).

6 Note: 16 ($24\mathrm{\%}$) regressions did not show significant results for the analysis of trends and were thus excluded.

7 Note: 15 ($23\mathrm{\%}$) regressions did not show significant results for the analysis of fundamentals and were thus excluded.

8 The only currency showing a change from bandwagon behavior to contrarian behavior with increasing forecasting horizon is the Chinese renminbi. A potential reason therefore may be found in the credible peg of renminbi to the US dollar.

9 The South Korean won is the only currency of an industrialized economy showing destabilizing expectations. As a result of the Asian crisis, the won deviated strongly from the fundamental values thus offering a potential explanation for destabilizing expectations.

10 In 27 of 66 forecast, at least one of the estimated parameters -- β or γ -- was not significant leading to an exclusion of the observation.