Transcript US Macro Announcements and the Euro/Dollar Exchange Rate MSc Student: Simona A. Popa

US Macro Announcements and
the Euro/Dollar Exchange Rate
MSc Student:
Simona A. Popa
Supervisor:
Professor Moisa Altar, PhD
Bucharest, 2007
1. Purpose of the paper:

The analysis of the relationship between macroeconomic
fundamentals and exchange rate EUR/USD in the period 2001-2005
in the USA, based on real-time data for macroeconomic
announcements (true information market participants have when
making trading decisions).
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The analysis of whether market news about fundamentals are
capable of explaining the behavior of exchange rate movements.
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The market news about fundamentals are surprises of
macroeconomic announcements, that means parts of the actual
values of the macroeconomic indicators remained after the
subtractions from these of the market participants’ expectations.
2. Literature:

Economic literature that approached the purpose of my paper :

Andersen, T.G., Bollerslev, T., Diebold, F.X. and C. Vega (2002). Micro effects of macro
announcements: real-time price discovery in foreign exchange. PIER Working Paper no. 02-011
(Department of Finance, Kellogg School, Northwestern University and NBER, Departments of Economics
and Finance, Duke University and NBER, Departments of Economics, Finance and Statistics, University
of Pennsylvania and NBER, Graduate Group in Economics, University of Pennsylvania)

Ehrmann, M. and Fratzscher (2004). Exchange rates and fundamentals: new evidence from real time
data. ECB Working Paper no. 365. (European Central Bank economists)
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Faust, J., Rogers, J.H., Wang, S.B. and J.H Wright (2003). The high-frequency response of exchange
rates and interest rates to macroeconomic announcements. Board of Governors of the Federal Reserve
System International Finance Discussion Paper no. 784. (Assistant Director, International Finance
Division, Board of Governors of the Federal Reserve System; Chief, Trade and Financial Studies,
International Finance Division, Board of Governors of the Federal Reserve System; Graduate Student,
Department of Economics, Yale University; Chief, Monetary and Financial Market Analysis, Division of
Monetary Affairs, Board of Governors of the Federal Reserve System)

Galati, G. and C. Ho (2001). Macroeconomic news and the euro/dollar exchange rate. BIS Working
Paper no. 105 (Bank for International Settlements economists)
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Baumohl, B. (2005). The secrets of economic indicators. Hidden clues to future economic trends and
investment opportunities. Pearson Education Limited. (Director of The Economic Outlook Group,
consulting firm that evaluates global trends and risks, professor at New York University and Duke
University
2001- 2005 USA Preview
1.2
6/10/2005
28/12/2005
15/7/2005
the release times of US announcements are known exactly (day
and time) but only inexactly (day but not the time) for euro area.
1/2/2005
•
25/4/2005
the usually earlier release of the US announcements than that of
comparable euro area announcements;
19/8/2004
•
10/11/2004
the greater importance of the US economy than that of euro
zone;
8/3/2004
•
28/5/2004
0.2
0
15/12/2003
It was proved that news about US economy have a greater
impact on EUR/USD exchange rate than that of euro zone
news. The explanations for this fact are the followings:
2/7/2003
0.6
0.4
23/9/2003
The US macroeconomic announcements
10/4/2003
1
0.8
17/1/2003

1.6
1.4
5/8/2002
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EUR/USD Exchange rate
25/10/2002

14/5/2002
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20/2/2002
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6/9/2001
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28/11/2001
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15/6/2001
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2/1/2001
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In the period 2001-2005, the economy of the USA was
characterized by the following:
Terrorist attacks from September 11, 2001.
A lower trend of economic growth compared with other zones.
Interest rate differentials.
The reorientation of international capital inflows to assets more
safer and efficient.
The low level of confidence on the financial markets from the USA
(a lower growth rate than the anticipated one, the low level of
confidence on the financial statements of the biggest American
corporations due to lack in accounting controlling).
The exchange rate regime in Asia.
The massive trade deficit due to restrictive changes in the
commercial policy of the USA.(2006: 60 billion USD)
The massive current account deficit - the main determinant of the
USD depreciation in 2004.(2006: 226 billion USD due to petrol
price appreciation and increasing China imports of goods)
26/3/2001
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3. Data used
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January 2, 2001 - December 30, 2005 daily EUR/USD Reuters close quotation (1301 observations).
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16 macroeconomic announcements from USA economy: Gross Domestic Product (GDP) Advanced;
Nonfarm Payrolls; Retail Sales; Industrial Production; Capacity Utilization; Personal Spending; New Home
Sales; Durable Goods Orders; Construction Spending; Factory Orders; Trade Balance; Producer Price
Index; Consumer Price Index; Consumer Confidence Index; ISM Index for Manufacturing; Housing Starts.
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With the help of a forecast survey data on market participants’ expectations of announcements from
the United States (made by Federal Reserve Bank of Philadelphia), it was extracted the “surprise” or
the “news” component of each variable and then it was tested if these are capable to explain the
behavior of the daily EUR/USD exchange rate for the period 2001 – 2005.

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S k ,t 
Ak ,t  E k ,t
Ùt
At moment t+1, the announcement takes place as follows:
Ak,t= the effective announcement (the effective value of the indicator at moment t) made by the owners of
the macroeconomic indicators: Federal Reserve Board, Bureau of Labour Statistics, Bureau of Economic
Analysis, Bureau of Census, Institute for Supply Management (ISM), Conference Board.
Ek,t= the market expectation regarding a macroeconomic indicator at moment t (mean of the 36
participants at the market survey expectations made by Federal Reserve Bank of Philadelphia), given to
publicity with almost 5 quarters before the effective annoucement of the owners of the indicators.
Ut= the sample standard deviation for each announcement.
The difference is normalised by dividing by the sample standard deviation of each announcement in order
to allow a comparison of the relative size of the coefficients in the econometric model.
The table below shows the summary of the data used in the paper (table 1)
Announcement
Obs.1
Souce2
Period3
Time of
announcemen
t4
Announcement date in the month
Min
Max
12:30
25
31
12:30
1
10
Quarterly Annoucements
1- GDP-adv
20
BEA
31/01/01-28/10/05
Monthly Announcements
Real Activity
2- Nonfarm payrolls
60
BLS
05/01/01-02/12/05
3- Retail Sales
60
BC
12/01/01-13/10/05
12:30
11
15
4- Industrial Production
60
FRB
17/01/01-15/10/05
13:15
14
17
5- Capacity utilization
60
FRB
17/01/01-15/10/05
13:15
14
17
Consumption
6-Personal Spending
60
BEA
01/02/01-22/12/05
12:30
215
3
7- New home sales
61
BC
05/01/01-23/12/05
14:00
235
5
Investment
8- Durable goods orders
60
BC
26/01/01-23/12/05
12:30
23
29
9-Construction Spending
60
BC
03/01/01-01/12/05
14:00
1
5
10- Factory Orders
60
BC
04/01/01-06/12/05
14:00
305
8
19/01/01-14/12/05
12:30
10
21
12/01/01-20/12/05
12:30
1
22
17/01/01-15/12/05
12:30
14
23
Trade Balance
11- Trade Balance
60
BEA; CB
Prices
12-Producer Price Index
60
BLS
13-Consumer Price Index
60
BLS
Forward-Looking
14-Consumer Confidence Index
586
CB
30/01/01-28/12/05
14:00
22
31
15- ISM Index
60
ISM
02/01/01-01/12/05
14:00
1
4
16- Housing starts
60
BC
18/01/01-20/12/05
12:30
16
21
4. Methodology (1)
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The forecasts used in this paper are provided by the Federal Reserve Bank of
Philadelphia, formerly conducted by the American Statistical Association (ASA) and the
National Bureau of Economic Research (NBER). In the surveys conducted since the
Philadelphia Fed took over, the forecasters provide quarterly projections for five
quarters ahead and annual projections for the current year and the following years.
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It is produced quarterly and is available to the public at no charge. It is released at the
end of the second month of each quarter (or early the next month). Currently, there are 27
different forecast variables included in the survey.

This survey has proven to be valuable both for informing business firms and policymakers
about the future direction of the economy and aiding economic researchers studying
forecasting. The forecasters in the Survey of Professional Forecasters come largely
from the business world and Wall Street. For example, out of 36 participants in a recent
survey, 13 were from Wall Street financial firms, eight from banks, five from economic
consulting firms, three from university research centers, and seven from other private firms,
including chief economists at many Fortune 500 companies. This diverse group of
forecasters shares one thing in common: they forecast as part of their current jobs.
And they do so, according to Zarnowitz and Braun (1992) (NBER and University of
Chicago), using statistical (econometric) models, other people’s forecasts, leading
indicators, and surveys such as the Consumer Confidence Index.
Methodology (2)
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Initially, we analyzed in Eviews program, the standardized news for each
macroeconomic indicator for the time in which the announcement was made in the
period 2001-2005, inclusive for the first difference in logarithm of the daily exchange
rate EUR/USD.
The series are not normal distributed (as resulting from the analysis of the
skewness and kurtosis, the series show left/right asymmetry, being leptokurtic/
platykurtic).
All series are stationary as per Augmented Dickey Fuller test at any
significance level.
To focus on the importance of news during announcements periods, it were
estimated two-variable regression model for each type of announcement
studied based on only those observations when such an announcement was
made.

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Δ(ln et) = α + βk Sk,t + εt ,
(1)
where et is the daily exchange rate EUR/USD, Δ (ln et) represents the first difference
in logarithm of the daily exchange rate EUR/USD, Δ (ln et) = ln et - ln et-1 and Sk,t
is the standardized news for the macroeconomic announcement k (k = 1,…,16)
at the time t, and the forecasts are based only on those observations (Δ (ln et ), Sk,t)
for which an announcement was made at the time t. In this paper, we used the first
difference of the daily logarithm of EUR/USD exchange rate in order to show the
variation of the profitability.
There has been found five announcements (please see next table) statistically
significant. The econometric results of these variables have the greatest R-squared.
Conclusion (1):
Results (see Table 1):
- there has been found five announcements statistically significant;
- the econometric results of these variables have the greatest R2 values;
- the signs of the regression coefficients of these variables are in line with the economic intuition.
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The most significant announcements that have an influence over the exchange rate are: GDP,
non farm payrolls, trade balance, ISM index, consumer confidence index. (influence coming from
the highest values of regression coefficients, R-squared, t-statistic and the probability of t-statistic).
Andersen, Diebold, Bollerslev and Vega (2002) considered these variables to be statistically
significant in the period 1992-1998 using univariate regressions with dependent variable being the
exchange rate EUR/USD at 5 minutes intervals. Also, Faust, Rogers, Wang and Wright (2003)
obtained regression coefficients statistically significant using univariate regression, having as dependent
variable the exchange rate EUR/USD at 20 minutes intervals in the period 1987-2002 and independent
variables GDP, non farmpayrolls and trade balance.
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The following regression coefficients of the independent variables (GDP, non farmpayrolls, trade
balance, ISM index, consumer confidence index) have negative signs, thus reducing the EUR/USD
exchange rate quatation and improving the value of USD on the market. An improvement in the
economic conditions from USA, meaning an increase of the GDP, non farmpayrolls, ISM index,
consumer confidence index, all higher than the estimated/forecasted value and a lower value of the
trade balance deficit than the estimated/forecasted value, lead to the reduction of EUR/USD exchange
rate, thus improving the performance of USD on the market.
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The sign of the regression coefficients of statistically significant variables is in line with the economic
intuition that says better than expected news about a country’s economic condition (USA) are
supportive for its currency (leads to the dollar appreciation so to euro/dollar exchange rate falls).
Numbers in brackets are t-statistics
βk
Announcement
r2
Advance GDP
-0,003608
(-3,077248)
0,344727
Nonfarm payrolls
-0,003710
(-3,634648)
0,185515
ISM Index for manufacturing
-0,002665
(-3,205883)
0,150528
Trade balance
-0,001892
(-2,694176)
0,111228
Consumer confidence index
-0,001413
(-1,744282)
0,051531
Conclusion (2):
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A surprise/news of one standard deviation of GDP, will lead to a reduction of EUR/USD exchange rate with
0.003608%, meaning the appreciation of USD with 0.003608% compared to EUR.
A surprise/news of one standard deviation of the nonfarm payrolls, will lead to the reduction of EUR/USD
exchange rate with 0.003710%, meaning the appreciation of USD with 0.003710% compared to EUR.
A surprise/news of one standard deviation of the consumer confidence index, will lead to the reduction of
EUR/USD exchange rate 0.001413%, meaning the appreciation of USD with 0.001413% compared to EUR.
A surprise/news of one standard deviation of ISM (Institue for Supply Management) index, will lead to the
reduction of EUR/USD exchange rate with 0.002665%, meaning the appreciation of USD 0.002665%
compared to EUR.
A surprise/news of one standard deviation of the trade balance, will lead to the reduction fo EUR/USD
exchange rate with 0.001892%, meaning the appreciation of USD with 0.001892% compared to EUR.
The surprise time series are adjusted for heteroschedasticity using the option from Eviews “LS & TSLS
Heteroskedasticity Consistent Convariance”. Applying White test on the residuals obtained from the regression
models, it can be concluded that the regressors do not explain the residuals, meaning that the residuals’
variance is constant in time (homoschedasticity).
The most known test for the autocorrelation of errors is Durbin Watson test, whose value should be around 2
in order to conclude for the lack of autocorrelation between residuals regression. Null hypothesis: residuals are not
autocorrelated.
Residuals are not normal distributed, the probability attached to Jarque-Bera has high values, but are adjusted
for heteroschedasticity using the option “LS & TSLS Heteroskedasticity Consistent Convariance”.
Due to the fact that the series have a long number of observations, we might conclude that the estimations
are not affected by the residuals, even if they are not normal distributed. So, we accept the regression
models results and continue with the analysis.
Conclusion (3):

Nonfarm payrolls:
Employment news can greatly influence the dollar’s value in currency markets.
A vigorous jobs report - drive interest rates higher - makes the dollar more attractive to foreign investors - earn more interest income by
owning US Treasury securities.
An anemic jobs report softens demand for US currency - it spells trouble for American stocks and puts downward pressure on rates making the dollar less appealing for foreigners.
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Consumer Confidence Index:
A depressed consumer makes foreign investors with exposure in the US markets a bit nervous - raises the prospects of falling interest
rates and a weakening business climate. Foreign investors might sell the US currency in search for higher yields and a stronger economy
elsewhere.
An upbeat consumer can lift US interest rates and stock market returns to levels that promise a higher return relative to other regions in
the world and this normally has the effect of increasing demand for dollars.
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GDP:
To foreign investors, a strong American economy is viewed more favorably than a weak one. Robust economic activity in the US
motivates corporate profits and firms interest rates; foreign investors see opportunities to make money in the stock market and from
higher-yielding Treasury bills and bonds. All this will increase the demand for dollars. If the Federal Reserve moves quickly to preempt
inflation by driving up short term rates, odds are it would also lead to an appreciation of the dollar because of the perception that the US
central bank is ahead of the curve in containing price pressures. However, if inflation acceleates and stays at a high level, it would lower
US competitiveness in the world and worsen the country’s foreign trade deficit, a scenario that can make US currency far less appealing.
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ISM Index:
If the economy is fundamentally healthy and inflation is in check, the dollar will likely bounce higher with a Purchasing Managers Index
above 50. Conversely, should the ISM report portray a manufacturing sector moving unsteady on recession, foreigners might sell some of
their dollar linked investments, depressing the dollar’s value against other key currencies.
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Trade Balance:
While investors in the bond and stock markets agonize over how to respond to the latest international trade figures, currency traders take
a more direct approach. Unless caused by a deep recession in the US, any improvement in the trade balance is viewed favorably for the
dollar. The more goods and services foreigners buy from the US, the more dollars they will need to pay for these American products. In
contrast, a worsening trade deficit can undermine the dollar. To purchase foreign goods and services, Americans have to sell dollars so
they can pay for these products in local currencies. The problem is that foreign exchange traders are already swimming in a sea of
surplus dollars. Flooding the market with even more dollars can only further depress the dollar’s value.
Methodology (3)
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To explain EUR/USD daily exchange rate movements during the entire period 2001 - 2005 it was estimated a multiple
regression model with all the 16 selected announcements and one lag of the dependent variable as independent
variables. (K lags for announcements and J for exchange rate)
I
K J
Δ (ln et) = α + ∑ βi Δ (ln et-i) + ∑ ∑ βkj Sk,t-j + εt , t = 1,…,T
(2)
i=1
k=1 j=0
16
Δ (ln et) = α + β1 Δ (ln et-1) + ∑ βk Sk,t + εt , t = 1,…,1.301
(2’)
k=1
Results (see table below):
- this model has the same statistically significant variables as those of the before mentioned two-variables regression
model 1, with the same correct sign of the regression coefficients. The single difference from the results of twovariable regression models is the lower significance level of advance GDP and trade balance.
- the model’s coefficient of determination has a small value for an econometric model (R2 = 0.046282) but this result
is in line with results obtained by other empirical models which try to explain the exchange rates’ movements.
- the signs of the regression coefficients are in line with economic intuition.
The reason for using model (2’) is based on the results obtained by Andersen, Bollerslev, Diebold and Vega
(2002) who consider that the the most part of the explanatory power of the model for conditional mean
comes from the laged dependent variables and from the current values of the announcements and Ehrmann
and Fratzscher (2004) consider the fact that in 99% of the cases one lag for the exchange rate variation is
sufficient.
βk
Announcement
Advance GDP
-0.00343
(-2.551904)
Nonfarm payrolls
-0.00366
(-3.575308)
Trade balance
-0.00191
(-2.815763)
Consumer confidence index
-0.00149
(-1.897579)
ISM Index for manufacturing
-0.00254
(-2.609994)
R2=0.046282, F-statistic = 3.662436
Conclusion (4)
Dependent Variable: LN_ET
Method: Least Squares
Date: 06/25/07 Time: 12:39
Sample: 1 1301
Included observations: 1301
White Heteroskedasticity-Consistent Standard Errors & Covariance
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
0.000104
0.000176
0.592771
0.5534
ANT_LN_ET
-0.068313
0.027695
-2.466596
0.0138
CAPACITYU
0.001737
0.001149
1.51172
0.1309
CONSTRUCTIONS
0.000456
0.000749
0.609315
0.5424
CONSUMERC
-0.001493
0.000787
-1.897579
0.058
CPI
-0.001109
0.00089
-1.24649
0.2128
DURABLEO
0.00059
0.000679
0.867594
0.3858
FACTORYO
0.000519
0.001216
0.426992
0.6695
GDP
-0.003432
0.001345
-2.551904
0.0108
0.001
0.000887
1.127568
0.2597
INDUSTRIALP
-0.001806
0.001228
-1.471172
0.1415
ISM_IND
-0.002541
0.000974
-2.609994
0.0092
NEWHOMES
0.000154
0.000581
0.26558
0.7906
NONFARMP
-0.003661
0.001024
-3.575308
0.0004
PERSONALS
-0.000777
0.000548
-1.418805
0.1562
PPI
0.000554
0.000653
0.848491
0.3963
RETAILS
-0.000694
0.00094
-0.738455
0.4604
TRADEB
-0.00191
0.000678
-2.815763
0.0049
HOUSINGS
R-squared
0.046282
Mean dependent var
0.000176
Adjusted R-squared
0.033645
S.D. dependent var
0.006354
S.E. of regression
0.006246
Akaike info criterion
-7.29994
Sum squared resid
0.050057
Schwarz criterion
Log likelihood
4766.611
F-statistic
3.662436
Durbin-Watson stat
2.008637
Prob(F-statistic)
0.000001
-7.228399
Conclusion (5)
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
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In Galati and Ho (2001), the variation
of the exchange rate using regressions
with daily data is not so big, this model
having a reduced R-squared of 10%.
Andersen, Bollerslev, Diebold and
Vega (2002) consider that the Rsquared values for model regression
(2) are very small. Copeland (2000)
considers that the ”news” variables
explain between 5 and 20% of the
monthly variation of the most important
currencies. Evans and Lyons (2003)
consider that econometric models
based on fundamentals
macroeconomics determinants explain
in less than 5% of the exchange rate
variation.
The same result is obtained regressing
the macroeconomics indicators with
the most significant results in model
(1), reaching a R2= 3.97% (the highest
regression coefficients, the highest
values R-squared and the probabilities
attached to t-statistic): GDP, non
farmpayrolls, trade balance, ISM index
and consumer confidence index.
Dependent Variable: LN_ET
Method: Least Squares
Date: 06/25/07 Time: 12:39
Sample: 1 1301
Included observations: 1301
White Heteroskedasticity-Consistent Standard Errors & Covariance
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
0.000129
0.000174
0.743839
0.4571
ANT_LN_ET
-0.06805
0.027544
-2.470621
0.0136
CONSUMERC
-0.001449
0.000771
-1.87892
0.0605
GDP
-0.003448
0.00134
-2.573301
0.0102
ISM_IND
-0.002632
0.00091
-2.891463
0.0039
NONFARMP
-0.003642
0.00102
-3.572164
0.0004
TRADEB
-0.001947
0.000672
-2.897815
0.0038
R-squared
0.039714
Mean dependent var
0.000176
Adjusted Rsquared
0.035261
S.D. dependent var
0.006354
S.E. of regression
0.006241
Akaike info criterion
-7.309987
Sum squared
resid
0.050401
Schwarz criterion
-7.282166
Log likelihood
4762.147
F-statistic
Durbin-Watson
stat
2.002555
Prob(F-statistic)
8.919215
0
Methodology (4)
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Due to the fact that the R-squared of model (2’) has a low value, it was estimated another type of model (2) inspired
from Galati and Ho model (2001), which R-squared was of 10%.
We continued to identify the number of lags of the exchange rate and of the macroeconomic announcements ”news”,
based on the results obtained using the informational criterion Akaike and Schwarz. For all the macroeconomic
news, the lowest values for AIK and SCH were obtained for the lag number 12, while for the exchange rate the AIK
showed the lag of 9 and SCH the lag of 12. We choose the lag of 12, due to the fact that it showed the highest value
of R-squared.
12
7 12
Δ (ln et) = α + ∑ β1 Δ (ln et-i) + ∑ ∑ βkj Sk,t-j + εt , t = 1,…,1.297
(2“)
i=1
k=1 j=0
So, in search of a model with a greater value of the coefficient of determination, thus having a greater
explanatory power, it was estimated another multiple regression model with the values of 7 announcements
and 12 lags of each one of these, and 12 lags of the dependent variable as explanatory variables. The 7
announcements are the variables most statistically significant from the two-variable regression model and
whose models have the greatest R2 values (model 1) in each of the 7 groups in which announcements were
divided. This approach has been done also by Galati and Ho.
It was obtained a R-squared of 10.3%, similar result obtained by Galati and Ho (2001), these using 5 number of lags
for the exchange rate and 4 number of lags for the macroeconomic announcements “news”.
It was obtained a greater coefficient of determination (R2 = 10.3154%) than that of the first multiple regression
model (model 2’). From the announcement variables were found statistically significant over the entire studied period
only the contemporaneous variables for four announcements (GDP, nonfarm payroll, trade balance, ISM index) with,
again, a correct sign of the correspondent coefficients of regression (see table below - numbers in brackets are
t-statistics ).
βk
Announcement
1- GDP-adv
-0.00357
(-2.852383)
2- Nonfarm payrolls
-0.0042
(-4.326059)
3- Personal Spending
-0.00067
(-1.186616)
4-Durable goods orders
0.000778
1.037427
5- Trade Balance
-0.00224
(-2.665470)
6-Consumer Price Index
-0.00103
(-1.179608)
7- ISM Index
-0.00249
(-2.388373)
R-squared
0.103154
Mean dependent
var
0.000182
Adjusted R-squared
0.024936
S.D. dependent
var
0.006266
S.E. of regression
0.006187
Akaike info
criterion
-7.255177
Sum squared resid
0.045211
Schwarz criterion
-6.837679
Log likelihood
4765.451
F-statistic
1.318799
Durbin-Watson stat
1.992986
Prob(F-statistic)
0.021729
Methodology (5)

This paper also analyses the importance of announcement timing, whether news released
earlier tend to have greater impact than those released later.
To evaluate, the US indicators were grouped into six types: real activity, consumption,
investment, prices, trade balance and forward-looking. GDP was kept separately. Within each
group the announcements were arranged in the chronological order of the release time. (as in
table 1)

We regressed the absolute values of the regression coefficients and t-statistics obtained
from the first multiple regression model (model 2’) on the average announcement delay,
which is the average number of days which passed from the end of the quarter to which de
announcement refers and the date of its release. The coefficients of regression obtained were not
statistically significant.

The hypothesis is generally verified. The two-variable regression model with the earlier
released announcements have the most statistically significant coefficients and the highest
R2 values.
Based on the results of the two-variable regression model it was verified if within the same
category of macroeconomic indicators, news released earlier tend to have a greater impact
than that of the later released news.

The results obtained show that the intensity and the significance of the regression
coefficients are only weak correlated with the medium announcement delay for each
announcement.

Comparing these results, Ehrmann and Fratzscher (2004) used the same approach for the
analysis of the exchange rate EUR/USD for the period 1993-2003, obtaining also a weak
connection between the value of the coefficients and the medium announcement delay for each
announcement.
Conclusion (6)
Dependent Variable: BETA
Dependent Variable: T_STAT
Method: Least Squares
Method: Least Squares
Date: 06/25/07 Time: 12:42
Date: 06/25/07 Time: 12:42
Sample: 1 16
Sample: 1 16
Included observations: 16
Included observations: 16
White Heteroskedasticity-Consistent Standard Errors & Covariance
White Heteroskedasticity-Consistent Standard Errors & Covariance
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
-0.001327
0.000715
-1.857078
0.0845
DK_MED
2.91E-05
3.27E-05
0.890908
0.388
0.051975
Mean dependent var
R-squared
Adjusted Rsquared
S.E. of
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
-1.657931
0.879732
-1.884587
0.0804
DK_MED
0.043058
0.040593
1.060724
0.3068
R-squared
0.097568
Mean dependent var
-0.842513
Adjusted Rsquared
0.033109
S.D. dependent var
1.732345
S.E. of
1.703426
Akaike info criterion
4.019629
Sum squared
resid
40.62324
Schwarz criterion
4.116202
Log likelihood
-30.15703
F-statistic
1.513639
Durbin-Watson
stat
2.022725
Prob(F-statistic)
0.238857
-0.000776
-0.015741
S.D. dependent var
0.001605
0.001617
Akaike info criterion
-9.899412
regressio
n
Sum squared
resid
3.66E-05
Schwarz criterion
-9.802838
Log likelihood
81.19529
F-statistic
0.767542
Durbin-Watson
stat
1.75056
Prob(F-statistic)
0.395762
regressio
n
Methodology (6)


Finally it were searched evidences of sign effects (the
asymmetric reaction of the markets to news characterized
by a greater impact of the bad news than that of the good
news), in the EUR/USD exchange rate’s movements for the
period 2001 – 2005.
Δ (ln et) = α + βi Δ (ln et-1) + (βPDP,t + βNDN,t) It + εt ,
(3)
Dependent Variable: VAR_LN_ET
Method: Least Squares
Date: 06/25/07 Time: 12:43
Sample: 1 1301
Included observations: 1301




where DP,t=1 if the news is positive (It=1) and DN,t=-1 if the
news is negative (It=-1), both dummy variables having 0 value
otherwise.
There were developed two dummy aggregate indicators,
one for good news and another for bad news based on
the results of the first multiple regression model (2’)
before mentioned. The indicator of good news has the value
1 if the day’s US news are favorable to the US dollar
appreciation and 0 otherwise and the indicator for bad news
takes the -1 if the day’s US news are leading to US dollar
depreciation and 0 otherwise, both of them taking the 0
value if there are no news.
We estimated the model with the two dummy variables and
one lag of the dependent variable as independent
variables.
The results confirmed the sign’ effect, the coefficient of
regression for bad news indicator was statistically
significant while that of good news indicator was not
statistically significant over the entire studied period, 2001 2005. However the coefficient of determination of this model
was again very low (R2 = 0.013445).
White Heteroskedasticity-Consistent Standard Errors & Covariance
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
-9.54E-05
0.000222
-0.42992
0.6673
VAR_ANT_LN_ET
-0.066331
0.027827
-2.38368
0.0173
DUMMY_P
-1.02E-05
0.000488
-0.021
0.9832
DUMMY_N
-0.001518
0.000439
-3.46224
0.0006
R-squared
0.013445
Mean dependent var
0.000196
Adjusted R-squared
0.011163
S.D. dependent var
0.006356
S.E. of regression
0.006321
Akaike info criterion
-7.28694
Sum squared resid
0.051815
Schwarz criterion
-7.27104
Log likelihood
4744.155
F-statistic
5.892031
Durbin-Watson stat
2.008291
Prob(F-statistic)
0.000541
Methodology (7)


The analysis of the relationship between the level
(not variation) of the exchange rate EUR/USD and
the macroeconomic announcements in USA.
It was consider useful the analysis of the below
regression model (4) in order to analyze the
influence of the macroeconomic news’ signs
over the level of the exchange rate EUR/USD
(direction) and not the variation of the exchange
rate EUR/USD in the period analyzed:

ln et = α + β1 ln et-1 + (βPDP,t + βNDN,t) It + εt
(4)

This time, it was obtained a R-squared of
0.998075, much higher than the previous coefficient
of determination, which means the regression
model (4) explains in a percentage of 99% the
evolution of the exchange rate EUR/USD in the
period 2001-2005. The regression coefficient of the
negative news is also significant compared to the
previous model (-0.001514), when the positive news
do not have a significant impact (the regression
coefficient -0.00003).

It is confirmed in this way the fact that
macroeconomic news explains very well the
direction, but not the intensity of the exchange
rates’ movements.
Dependent Variable: LN_ET
Method: Least Squares
Date: 06/25/07 Time: 12:44
Sample: 1 1301
Included observations: 1301
White Heteroskedasticity-Consistent Standard Errors & Covariance
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
-3.15E-05
0.000247
-0.127755
0.8984
ANT_LN_ET
0.998802
0.001199
833.1570
0.0000
DUMMY_P
-3.00E-05
0.000491
-0.061159
0.9512
DUMMY_N
-0.001514
0.000438
-3.460351
0.0006
R-squared
0.998075
Mean dependent var
0.078383
Adjusted R-squared
0.998071
S.D. dependent var
0.144102
S.E. of regression
0.006330
Akaike info criterion
-7.284080
Sum squared resid
0.051963
Schwarz criterion
-7.268181
Log likelihood
4742.294
F-statistic
224163.8
Durbin-Watson stat
2.141320
Prob(F-statistic)
0.000000
Conclusions

Taking into consideration the information found at our disposal and the fact that the difference between
the macroeconomic indicators announcements given to public by the USA Federal Organizations and
the market expectations surveys (Federal Reserve Bank of Philadelphia) is equal to 0 in only 8% of the
cases, any regression model can efficiently estimate the relationship between EUR/USD exchange
rate intensity and the macroeconomic news at only 8% efficiency level (the level of R-squared).

In conclusion there were found five announcements that statistically significant influenced the
EUR/USD exchange rate‘s movements over the entire period analyzed, 2001-2005, according to all
the econometric models from this paper in which they were included. These announcements are:
advanced GDP, nonfarm payrolls, trade balance, ISM index for manufacturing and consumer
confidence index.

It was found evidence that the announcement timing matters for the impact on EUR/USD exchange
rate of US macroeconomic announcements in the analyzed period, the earlier released news tend
to have a greater impact than those released later.

Finally, there was confirmed for the period analyzed and for the EUR/USD exchange rate the sign effect,
the greater impact of the bad news than that of the good news from the United States.

The low explanatory power for the intensity (variation) of the exchange rate was once again confirmed
in spite of a showed high explanatory power for the direction (level) of the exchange rate’s movement.

The explanatory power of the econometric models used in this paper is very low. This confirmed
also the conclusion drawn from the research made by specialists that the models that use real
time data for the analysis of the exchange rate evolution obtain good results for the analysis of
the direction (level), but not for the intensity (variation) of the EUR/USD exchange rate
variations/movements.
2006 USA Economic Environment









The first half of 2006…
During the first half of 2006, market participants apparently focused on the question of how
long the Federal Reserve would continue to raise rates.
At that time, US employment figures played a greater role. The markets were probably
keen to obtain a picture of wage pressure, income and the sustainability of private
consumption.
The markets were also paying close attention at the start of the year to industrial
production and capacity utilization as a means of estimating US growth, which was robust
at the time, and a possible capacity shortage.
… and the second half
As of the summer, when the slowdown in US growth was becoming apparent and the Fed
took a break from its rate hikes, the currency markets came to focus more again on
economic performance.
The EUR/USD exchange rate clearly responded to unexpected (negative) Chicago PMI
(the business barometer in Midwest region of USA, based on production, new orders, and
order backlogs, employment, prices paid, buying policy) figures, for example, because the
market saw a threat of a hard landing and early rate cuts.
At the same time, real-estate figures were also commanding greater attention, and these
deteriorated steadily. The result was fears of a property-market crash with adverse effects
for assets, private consumption and thus the US economy as a whole. The strongest
reaction on the part of the exchange rate came in the wake of surprise figures for housing
permits.
As of the summer, as growth was slowing down, but concern about inflation grew, more
attention started to be paid to the unemployment rate. The change in focus was also due in
part to the market finding it increasingly difficult to asses how high ‘neutral’ growth in
employment might be.
Proposal and further research direction

A future direction of study for this paper is the study of the exchange
rate with an approach that combines the three recent approaches
from the literature of explaining the exchange rates dynamics at
short to medium term horizons: the order flow approach, the chartist
behavior approach and the approach based on the real-time data.

A combined focus that includes the equity market, the bond market
and the currency market could also lead to good results. Also the
inclusion of unscheduled news about political and social events
could be a promising direction of study too.

Another direction of study might be the analysis of the
macroeconomic surprise announcements over the financial and
foreign exchange market all together and not separately, showing
the interaction results of the two markets.
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