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US Macro Announcements and the Euro/Dollar Exchange Rate

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:

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US Macro Announcements and the Euro/Dollar Exchange Rate

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  1. US Macro Announcements and the Euro/Dollar Exchange Rate MSc Student: Simona A. Popa Supervisor: ProfessorMoisa Altar, PhD Bucharest, 2007

  2. 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). • The analysis of whether market news about fundamentals are capable of explaining the behavior of exchange rate movements. • 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.

  3. 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) • 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) • 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

  4. 2001- 2005 USA Preview • 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) • The US macroeconomic announcements 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: • the greater importance of the US economy than that of euro zone; • the usually earlier release of the US announcements than that of comparable euro area announcements; • the release times of US announcements are known exactly (day and time) but only inexactly (day but not the time) for euro area.

  5. 3. Data used • January 2, 2001 - December 30, 2005 daily EUR/USD Reuters close quotation (1301 observations). • 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. • With the help of a forecastsurvey 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. • 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)

  6. 4. Methodology (1) • 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. • 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.

  7. Methodology (2) • 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. • 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.

  8. 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. • 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. • 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 quatationand 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. • 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

  9. Conclusion (2): • 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 standarddeviation 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.

  10. 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. • 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. • 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. • 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. • 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.

  11. Methodology (3) • 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 two-variable 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.

  12. Conclusion (4)

  13. Conclusion (5) • 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 R-squared 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.

  14. Methodology (4) • 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).

  15. 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 isthe 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.

  16. Conclusion (6)

  17. 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) • 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).

  18. 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.

  19. 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.

  20. 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.

  21. 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 alltogether and not separately, showing the interaction results of the two markets.

  22. Bibliography: • 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. • Baumohl, B. (2005). The secrets of economic indicators. Hidden clues to future economic trends and investment opportunities. Pearson Education Limited. • Ehrmann, M. and Fratzscher (2004). Exchange rates and fundamentals: new evidence from real time data. ECB Working Paper no. 365. • 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. • Galati, G. and C. Ho (2001). Macroeconomic news and the euro/dollar exchange rate. BIS Working Paper no. 105. • Cheung Yin Wong, Chinn Menzie (2000). Empirical Exchange Rates Models of the Nineties: Are Any Fit to Survive? • Martin Evans, Richard Lyons (2001): Order Flow and Exchange Rate Dynamics • Jesus Crespo Cuaresma, Jarki Fidrmuc, Maria Antoinette Silgoner: Exchange rates developments and fundamentals in 4 EU accession and candidate countries, Bulgaria, Croatia, Romania and Turcia. • Meese Richard, Kenneth Rogoff (1983): Empirical Exchange Rate Models of the Seventies: Do they fit out of sample? • Chris Brooks – Introductory Econometrics for Finance • Documentation from the Federal Reserve Bank of Philadelphia regarding the market surveys, given with the amability of Mr. Tom Stark, Macroeconomic Database and Policy Support Manager • Croushore Dean, Stark Tom- Research Department Federal Reserve Bank of Philadelphia, Working Paper No.99-4, June 1999: A real time data set for macroeconomists. • Faust, J., Rogers, J.H., Wang, S.B. şi 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. • Berder David, Chaboud Alain, Chernenko Sergey, Howorka Edward, Krishnamasi Raj Iyer, Liu David, Wright Jonathan: Order Flow and Exchange Rate Dynamics in Electronic Brokerage System Data; Board of Governors of the Federal Reserve System International Finance Discussion Paper no. 830, April 2005. • Chaboud Alain, Chernenko Sergey, Howorka Edward, Krishnamasi Raj Iyer, Liu David, Wright Jonathan: The High Frequency Effects of US Macroeconomic Data Release on Prices and Trading Activity in the Global Interdealer Foreign Exchange Market; Board of Governors of the Federal Reserve System International Finance Discussion Paper no. 823, November 2004. • Schubert Michael, Praefcke Antje, Kramer Jorg, Commerzbank Analysts: Research Notes: Is the euro-dollar exchange rate driven by surprise data? January 2007 • http://biz.yahoo.com/c/e.html; www.bloomberg.com; • http://www.briefing.com/Investor/Public/Calendars/EconomicCalendar.htm • http://www.consensuseconomics.com/ • http://www.federalreserve.gov/- US Depart. of Commerce Bureau of Economic Analysis • http://www.bea.gov/scb/index.htm • http://www.reuters.com/; http://www.bloomberg.com/index.html?Intro=intro3 • http://www.phil.frb.org/econ/spf/; Federal Reserve Bank of Philadelphia; • http://www.ecb.int/home/html/index.en.html- European Central Bank • http://www.eviews.com/eviews5/eviews5/censusx11.htm

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