Hui Guo

English

Research Papers in Economics

August 2005 NationalEconomicTrends
Views expressed do not necessarily reflect official positions of the Federal Reserve System.
M
odern economic theory of foreign exchange rates
stipulates that the Deutsche mark/U.S. dollar rate,
for example, is equal to discounted future funda-
mentals—e.g., aggregate income, interest rates, and monetary
aggregates—in both the United States and Germany. A substan-
tial portion of the variation in these fundamental macroeconomic
variables is predictable across time; therefore, fundamentals
should provide important information about future movements
in exchange rates. In an influential paper, Meese and Rogoff
(1983), however, find that a simple random walk model, in which
the forecasted value is the most recent realization, outperforms
various forecasting models, including those using economic
fundamentals as predictors.1
Meese and Rogoff’s result has inspired numerous empirical
investigations of exchange rate predictability, and their conclusion
has proven to be strikingly robust after 20 years of fresh data
and intensive academic research. In light of seemingly compell-
ing evidence, some recent authors argue that exchange rates are
indeed unpredictable—possibly because some shocks have a
permanent effect on economic fundamentals. In particular, if
people discount the future very little relative to the present, then
exchange rates could follow a process close to a random walk.
Other economists, however, argue that exchange rates are
predictable and that existing empirical studies suffer from vari-
ous misspecifications. For example, some crucial fundamental
determinants of exchange rates may have been omitted. Also,
many macroeconomic variables are subject to periodic revisions;
therefore, the current vintage data, which have been commonly
used in the literature, do not contain the same information as
that available to investors at the time of forecast. To address
these issues, Guo and Savickas (2005) propose using financial
variables, which are broad measures of business conditions and
never revised, to predict exchange rates.2
Guo and Savickas find that a measure of U.S. aggregate idio-
syncratic volatility (IV) is a strong predictor of the exchange rates
of the U.S. dollar against major foreign currencies, especially at
relatively long horizons. An idiosyncratic shock to a stock is the
part of the stock return that is not explained by asset pricing
models. To measure IV, Guo and Savickas first estimate idiosyn-
cratic shocks to all (U.S.) common stocks included in the CRSP
(Center for Research in Security Prices) database; they then
aggregate the realized variance of idiosyncratic shocks across
stocks using the share of market capitalization as the weight.
The accompanying chart plots IV from the last quarter of
each year (in natural logarithms, solid line) along with one-year-
ahead changes (December 31 to December 31 of the following
year, dashed line) in the Deutsche mark/U.S. dollar rate over the
period 1973 to 1998 and the Euro/U.S. dollar rate over the period
1999 to 2003. The chart reveals a strong positive relation between
IV and changes in the price of the U.S. dollar over the next year.
For example, recent depreciation of the U.S. dollar was preceded
by a sharp decline in IV in the year 2001. Overall, IV accounts
for more than 30 percent of the variation of the Deutsche mark/
U.S. dollar rate; IV also outperforms the random walk model
in out-of-sample forecasting.
The forecasting power of IV is consistent with economic
theory. In particular, many early authors have argued that IV
is a proxy for the dispersion of shocks across different sectors;
and a high level of dispersion induces costly sectoral resource
reallocation, which reduces output and employment. Indeed,
Guo and Savickas show that IV is a strong predictor of GDP
growth, fixed private business investment, and unemployment
rates. Moreover, they find that a measure of aggregate IV con-
structed using German stock price data is also positively related
to future dollar prices of the Deutsche mark. Therefore, although
we cannot completely rule out the possibility of data mining,
the forecasting power of IV appears to provide support for the
conjecture that economic fundamentals are important determi-
nants of foreign exchange rates.
—Hui Guo
1 Meese, Richard A. and Rogoff, Kenneth. “Empirical Exchange Rate Models
of the Seventies: Do They Fit Out of Sample?” Journal of International
Economics, February 1983, 14(1), pp. 3-24.
2 Guo, Hui and Savickas, Robert. “Foreign Exchange Rates Don’t Follow a
Random Walk.” Working Paper 2005-025A, Federal Reserve Bank of St. Louis,
April 2005.
research.stlouisfed.org
Foreign Exchange Rates Are Predictable!
0.3
0
–0.3
–2
–3.5
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1973 1978 1983 1988 1993 1998 2003
Changes in Exchange Rates (dashed line) Log IV (solid line)
Log IV vs. Changes in Deutsche Mark (1973-98)
and Euro Rates (1999-2003) One Year Forward  

Foreign exchange rates are predictable!

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Foreign exchange rates are predictable!

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