The Swiss Franc-Euro Relationship: A Time Series-Based Correlation Study of

Economic Factors in Switzerland and the Eurozone Joe Barber and Peter Kraus1

JoeBarber@letu.edu; PeterKraus@letu.edu

LeTourneau University

School of Business

February 2015

ABSTRACT: This work analyzes historical time series data for the EUR/CHF exchange rate along with several

other predictor variables in order to study the correlated effects these variables have on one another. As the

Swiss Franc has for many years been viewed as a stable standard by which European nations judge currencies,

the authors attempt to discover what impact the recent removal of the peg linking the CHF to the Euro has on

relevant variables in Switzerland and the Eurozone. Using regression equations designed to find correlation

between these variables, the authors seek to show any significant effects changing exchange rates can have on a

nation’s own economy as well as the economies of surrounding nations. The significance of other variables

affected by monetary policies are also studied, with specific focus on inflation and interest rate levels. This

study operates under the current popular belief that recent appreciation in the value of the Swiss franc will have

negative effects on the nation’s overall economy. Results indicate that exchange rate decreases can indeed have

adverse effects on export levels and GDP, but that the economic variable most impacted is that of foreign

reserve holdings.

Keywords: Swiss Franc, Euro, Exchange Rates, Exports

JEL Classifications: F31, F37, F47

This paper was written and prepared under the guidance and instruction of Juan R. Castro, Professor of

Economics and Finance, School of Business, LeTourneau University

Prepared for the 2015 Economics Scholar Program

Dallas Federal Reserve

A Time-Series Based Correlation Study of Economic Factors in Switzerland and the Eurozone

Introduction and Literature Review

In January 2015, over three years after implementing a peg that prevented the Swiss franc from

appreciating beyond CHF1.20 per euro, the Swiss National Bank suddenly and unexpectedly removed the peg

and allowed the franc to float freely in the exchange market. As should have been expected, the franc

appreciated drastically over a short time period and has only recently settled at a more stable, yet much stronger

level compared to the euro. One of the major concerns now facing the nation of Switzerland is the risk of losing

substantial amounts of exports, a significant portion of Swiss GDP. Moreover, since over half of all Swiss

exports go to countries within the European Union, a shifting exchange rate could severely lessen the

competitiveness of Swiss exports within the European market. Due to the apparent correlation between

exchange rates, inflation levels, and interest rates within a nation, Switzerland faces a series of systemic results

that could impact the country’s macro-economy on a variety of levels.

This study examines the actual effect exchange rates have on Swiss GDP both during the existence of

the currency peg and a time period before the peg was implemented in order to determine possible future results

1 Research conducted under the instruction and guidance of Juan R. Castro Ph.D. Professor of Finance and Economics, School of Business, LeTourneau University (JuanCastro@letu.edu)

Barber and Kraus 2

of the franc’s recent appreciation. It is the authors’ belief that such a study will provide relevant data to be used

in assessing 1) how the peg itself changed the Swiss economy and 2) how such economic variables might be

affected in the future. By forecasting alternative data for recent years assuming the peg had never been

implemented, the authors derive information that is used to indicate how the peg’s removal can impact the

Swiss economy in the future.

In a working paper published in the Paradoks Economics, Sociology & Politics Journal, authors

Cambazoglu, Karaalp, and Vergos study how exchange rates impact key variables in the macro-economy. The

analysis focuses on two countries in particular—Turkey and Argentina—in order to determine how the recent

adoption of floating exchange rates by these nations has changed overall economic growth as well as internal

market policies. The authors’ conclusion “indicate[s] that the operation of the exchange rate channel is

effective” in both nations (Cambazoglu, Karaalp, and Vergos, 7). As a channel by which monetary policies can

be influenced, exchange rate control measures can have significant effect on lowering inflation levels and

controlling a country’s level of exports. According to this work, both countries analyzed were able to achieve

reduced inflation levels through such policies.

The authors focus heavily on the relationship between exchange rates and net exports for a few key

reasons, the first being the fact that net exports are decent macro-economic variables, and the second being the

significant impact an increase or decrease in exchange rates can have on exports. This article also describes

how interest rate manipulation—another monetary policy tool—can effect exchange rates which in turn impact

export levels. In short, a decrease in domestic real interest rates result in lower demand (and therefore lower

value) of domestic currency, which tends to increase export levels as export goods are deemed more desirable to

foreign consumers. The opposite is true of rising interest rates; such a situation results in excess amounts of

available foreign currency that leads to depreciation of that currency and a subsequent decrease in exports as

domestic consumers purchase imported goods.

The authors state that Turkey and Argentina switched from fixed exchange rates to flexible exchange

rates in 2001 and 2002, respectively. In Turkey, the government has gradually shifted from following an

intervention policy designed to influence the exchange rate through foreign currency purchases to a much

decreased level of involvement in the market itself. While initial results of this policy shift showed depreciation

for the nation’s currency, the situation is now more stable and the country has been able to keep inflation at an

acceptable level. For Argentina, the nation adopted floating exchange rate policies in direct response to high

levels of inflation present throughout the 1990s as well as the appreciation of the U.S. dollar during the latter

half of that decade. The country’s exchange rate system can best be described as a managed floating system

due to the presence of government intervention when required (DoS, qtd. in Cambazoglu et al., 11) The policy

has seen overall success as Argentina is reported to have been less impacted by the negative economy following

the recent economic crisis in 2009.

The paper concludes with an empirical study based on a vector auto-regression (VAR) model that

studies the “relative effect of the monetary transmission mechanism exchange rate channel on macro-economic

variables” (Cambazoglu et al., 19). According to the authors, this model shows a high level of effectiveness of

the exchange rate channel when used in both Argentina and Turkey.

Published by the Federal Reserve Bank of Cleveland, Owen F. Humpage’s paper entitled “The

Limitations of Foreign-Exchange Intervention: Lessons from Switzerland” studies how Swiss intervention

policies have negatively affected that nation since the recent economic crisis. Humpage uses two intervention

categories—nonsterilized and sterilized—as benchmarks for use in analyzing the Swiss National Bank’s

policies from the period following the recession to the implementation of the currency peg in September of

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2011. Nonsterilized interventions are defined as “interventions that alter a nation’s monetary base” and that

affect items like inflation and unemployment rates in addition to exchange rates (Humpage, 2). Humpage states

that these interventions differ from more traditional forms of monetary policy since only the former uses foreign

exchange as the sole instrument. Sterilized interventions, however, are described in the work as interventions

that attempt to offset negative aspects of other interventions on the monetary base of a nation. Humpage states

that these sterilized interventions do not always have positive results.

The paper outlines three phases of Swiss policies marked by the presence of nonsterilized intervention,

the implementation of sterilized intervention to offset these policies, and then the return of nonsterilized

intervention. The first period began with the franc’s appreciation in 2009; because of this and the perception

that Swiss monetary policies were too tight the SNB began to loosen such policies and increase its foreign

reserve holdings of euros. For a time, the Swiss franc ceased to appreciate, but little actual depreciation was

seen. By early 2010, the Swiss monetary base decreased by thirty percent as a result of losses sustained through

foreign exchange currency swaps. This year was also marked by franc appreciation due to the instability of

European countries and their respective currencies. Although the SNB ceased its interventions in mid-2010, the

franc reached a historic high level later that year, thus proving the ineffectiveness of policies from the very start.

Finally, later in 2011, the SNB began to use currency swaps to depreciate the franc, but initial depreciation was

reversed in September after the franc’s value increased substantially. In response, the Bank implemented a

currency peg on September 6, 2011 designed to prevent the franc from appreciating below SF1.20 per euro.

The SNB also stated it was prepared to purchase as much foreign currency as necessary to maintain this peg.

Although Humpage’s paper was written before the currency peg was removed in January 2015, his work

provides three distinct lessons regarding intervention policies in Switzerland and the general economic market.

As stated, the first lesson is that “sterilized transactions—that is, interventions that leave the monetary base

unchanged—do not provide central banks with a way to systematically influence their exchange rates

independent of their monetary policies” (Humpage, 3). This can best be seen in the manner in which the franc

was ultimately prevented from appreciating despite numerous intervention attempts. Secondly, Humpage states

that the SNB’s decision proves “nonsterilized intervention can create policy dilemmas” (Humpage, 4). Since

the SNB operated under stringent price stability targets, its intervention policies risked adversely impacting

inflation and other variables deemed important as well. Humpage’s third lesson concerns the potential for

collateral damage, mainly in the form of losses sustained by the SNB in its foreign reserve portfolios as the

franc continued to appreciate. Humpage concludes his paper with a recommendation that central banks use

monetary policies rather than foreign-exchange intervention to change monetary policies.

In “Swiss Franc Lending in Europe,” authors Brown, Peter, and Wehrmuller analyze the level of Swiss

franc borrowing existing throughout Europe through the end of 2007. Focusing on the nature of lending levels

in a combination of European countries allows the authors to discover the nature of these loans as well as how

involved in refinancing such loans the Swiss financial sector appears to be. By revealing the high franc lending

levels throughout Europe, this work lays the framework for future studies analyzing possible correlation

between exchange rates, the economy of Switzerland, and the economic well-being of the rest of Europe.

From 1997 to 2007, the “value of CHF loans [by euro area banks] has more than trebled” (Brown, Peter,

and Wehrmuller, 3). The authors estimate that, at the end of 2007, “CHF 238 billion in Swiss franc

denominated loans were outstanding in the euro area, and another CHF 122 billion in other European countries”

(Brown et al., 1). The nature of borrowers across Europe varies—many Western European nations borrow

francs through businesses, whereas countries such as Hungary and Poland hold Swiss franc loans as individual

household mortgages. This paper serves as a valuable framework on which to base recent developments, as the

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sovereign debt crisis in Europe further increased franc borrowing and has now resulting in increased

vulnerability across Europe due to the renewed appreciation of the franc.

Data

This study makes use of numerous variables designed to show correlation between macro-economic

conditions of a nation or economic region and internal conditions influenced through intervention and monetary

policies. All data is obtained using time-series databases from both the Swiss National Bank and the European

Central Bank. Six separate data variables are used: exchange rate, interest rate, inflation, net exports, GDP, and

foreign reserves. The exchange rate utilized is the historical rate between the euro and the Swiss franc; the

interest rates are listed by the Swiss National Bank as official rates and inflation levels are measured using

consumer prices. Net exports are divided into two categories, with one representing overall Swiss export levels

and the other showing Swiss exports only to nations within the European Union that currently use the euro as

the official currency (cumulatively labeled the Eurozone). GDP is also subdivided into two categories—overall

GDP for the Eurozone and the same for Switzerland. Finally, Swiss foreign reserves are listed as an overall

value and also as the amount of foreign reserves held in euros, thus again making two separate data sub-

categories.

Data used for this study is listed in quarterly format, with initial monthly values for exchange rate,

interest rate, and inflation being averaged every three months to create quarterly data that matches observation

periods for the other variables. While mostly original data is used directly in the regression equations, in some

instances percentage change values are used instead. The first data period extends from the beginning of 1999

through the second quarter of 2011, as the currency peg was implemented in September of 2011. The second

period coincides with the existence of the peg and includes data starting in the third quarter of 2011 and

extending through the last quarter of 2014. Since the currency peg was removed on January 15, 2015 and no

data for 2015 exists at the time of this writing, this study does not include any data after the end of 2014. The

first data set is extended back to 1999 in an effort to provide an accurate number of data points for use in

running the regression equations for this study.

Methodology

Correlation and Regression Equations

Three separate models are used in this study, the first of which is a test for correlation between all variables:

Equation (1)

where mean values are subtracted from data points and then divided by the standard deviation in order to

determine the level of correlation between any two variables. Any correlations deemed significant (either

positive or negative) are recorded between exchange rates and other economic variables included in the paper.

Level of significance is determined on the basis of p-values of less than 0.05 in a 95% confidence level.

Correlation is measured on a scale of -1 to 0 and 0 to 1, with -1 indicating a high negative correlation, 0

meaning no correlation exists, and 1 meaning a high positive correlation is present between the variables

compared.

The second equation makes use of a simple regression format to correlate each variable to the other

variables in the data set. The results indicate the significance of the correlation for each pair of variables:

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Equation (2)

For this equation, β represents the slope of the equation and α stands for the y-intercept value. The equation is

used to determine the impact of exchange rate on other economic factors. In this case, xi represents the

exchange rate, and y are all the economic variables listed previously in the data section. (Interest rate, inflation,

net exports, GDPs, and foreign reserves)

The final equation makes use of a multiple regression format that uses interest rate, exchange rate, and

inflation as independent variables and the chosen economic factors as the response variable. A separate

equation is run for each economic variable, thus totaling six regressions using the following response variables:

net exports, net exports to the Eurozone, Swiss GDP, Eurozone GDP, Swiss foreign reserves, and Swiss foreign

reserves held in euros. The following format is used as a guideline for these equations:

Equation (3)

In this case, three independent variables exist, and the results show correlation results for both the overall

equation and each predictor variable. It can thus be seen which general equations prove most significant and

which variables have the most impact on the response.

Forecast – Double Exponential Smoothing Model

In order to forecast the EUR/CHF exchange rate assuming the currency peg had never been adopted, the

double exponential smoothing method is utilized. This model is used because the data studied appears to be

trended but not seasonal. The resulting forecasted data provides an estimation of the exchange rate without the

existence of the peg; this data is then used to determine the systemic effects such exchange rates would have

had on Swiss overall net exports, Swiss GDP, total foreign reserves, and reserves held in euros. Using existing

regression equations deemed significant in earlier models, the forecasted exchange rate data is inputted,

resulting in predicted values for these other variables, assuming the absence of a currency peg. Finally, the

difference between actual and predicted values is then divided by actual values in order to determine how much

the given variables would have changed had not the currency peg been implemented. The average of these

changes is computed to show how the changed exchange rates would have impacted other economic variables

during the time the peg was actually in place.

Results

Correlation and Regression Equations

The results of the correlation model differ between the time period before and during the currency peg.

During the former timeframe, several of the economic variables tested exhibited significance and moderate to

high levels of correlation. Interest rate levels, reserve amounts held in euros, and total foreign reserve amounts

all show significance; the former is mildly positively correlated to exchange rates, while the latter two show

strong negative correlation to the same. For the period during the peg, however, no correlation equations prove

significant and only mild correlation is exhibited. These results make sense considering the fact that the

currency peg resulted in artificially low exchange rates made possible by foreign currency purchases and the

ability of Switzerland to print large amounts of currency without experiencing severe inflation. Tables A-1 and

B-1 in the appendices provide summaries of these results.

The simple regression model for both periods yield almost identical results to those obtained for the

correlation model. Using the exchange rate as the response variable and the listed economic variables as

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predictors, the unpegged period once again highlights interest rate levels and the two foreign reserve categories

as significant. These regression equations have moderate to high R-squared values that indicate a high

explanation level concerning exchange rates. Once again, the models used for the pegged period yield no

significant results. Tables showing data for these models include Table A-2 and Table B-2 in the appendices.

The multiple regression model used in this study provide varied results, but results for the pegged time

period only indicate one equation that has both a significant overall p-value and a high R-squared value. As

Table B-3 in Appendix B indicates, an equation using Swiss net exports to the Eurozone as the dependent

variable and exchange rate, interest rate, and inflation as predictors yields a significant p-value of 0.008 and an

R-squared value of 71.26%. The other equations for this time period lack significance. For the unpegged

period, all equations are significant overall, with some individual variables exhibiting higher levels of

significance than others. Results for these multiple regression models can be seen in Table A-4.

Forecast – Double Exponential Smoothing Model

Using the double exponential smoothing method, forecasted exchange rates (assuming the absence of a

currency peg) are calculated; the table below shows how these values compare to actual values during the

existence of the peg:

Exchange rates (Euro/CHF)

Time Period Actual Forecasted

2011Q3 1.166433 1.22444

2011Q4 1.229633 1.19567

2012Q1 1.2082 1.1669

2012Q2 1.201467 1.13813

2012Q3 1.203667 1.10937

2012Q4 1.208033 1.0806

2013Q1 1.228067 1.05183

2013Q2 1.231 1.02306

2013Q3 1.234533 0.9943

2013Q4 1.2294 0.96553

2014Q1 1.223433 0.93676

2014Q2 1.2192 0.908

2014Q3 1.211533 0.87923

These results can be viewed in graphical format in Appendix C. While the actual exchange rate remains

relatively constant, a general downward trend can be observed with the forecasted rates that corresponds to a

theoretical appreciation of the franc without the currency peg in place to halt such a rate decrease.

Barber and Kraus 7

The forecasted values are then inputted with regression equations previously deemed significant in order

to forecast how other variables would be effected by the different exchange rates. The results can be seen

below:

Variables

Average

Difference

Net Exports 2.41%

GDP (Swiss) 1.69%

Euro Reserve 11.62%

Total Foreign

Reserve 25.97%

These results represent the absolute value of the average difference, as all variables would have actually

decreased based on the forecasted exchange rates. For example, based on forecasted exchange rates, Swiss net

exports would have experienced an average 2.41% decrease annually during the timeframe marked by the peg’s

actual existence, given the forecasted corresponding change in the exchange rate. These results both estimate

the effect on economic variables without the presence of the peg and reveal which of our original variables are

most impacted by changing exchange rates.

Conclusion

The results of this study indicate merely moderate significant effect of exchange rates on various

economic variables, with foreign reserves showing the highest consistent level of correlation and regression

significance. As indicated by the data, foreign reserve amounts tend to decrease as exchange rates rise; such a

conclusion is understandable considering the fact that depreciation of the Swiss franc reduced the need for the

nation to increase its foreign reserve holdings in an effort to keep the franc from gaining strength against the

euro. The study also shows a lack of significant results during the period the peg was in place, most likely due

to the fact that exchange rates varied only slightly despite normal fluctuations among the other economic

variables. Concerning the forecasting model, results indicate a substantial appreciation of the Swiss franc had

the peg not been implemented. Assuming these new conditions, many of the economic variables studied would

have decreased in size, with foreign reserves predicted as sustaining the greatest reduction in size. While

perhaps not substantial, results also indicate that both Swiss exports and GDP would have been adversely

affected, thus in a small way validating the currently-held belief that the franc’s appreciation will hurt Swiss

export levels and therefore the general economy of that nation.

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References Brown, M., Peter, M., & Wehrmuller, S. (2009). Swiss Franc Lending in Europe. Swiss National Bank. Retrieved from

http://www.snb.ch/n/mmr/reference/sem_2008_09_22_background/source/sem_2008_09_22_background.pd

f

Cambazoglu, Birgul; Karaalp, Hacer; Vergos, Konstantinos. (2014, July). The Effects of Exchange Rates on Macroeconomic

Variables: A Study of the Selected Emerging Market Economies. Paradoks Economics, Sociology and Policy

Journal, 10(2), 5-29. Retrieved from http://web.a.ebscohost.com.research-

db.letu.edu/ehost/pdfviewer/pdfviewer?vid=7&sid=1bdc44d6-dd5c-42ff-a2c9-

36e2e5e5d182%40sessionmgr4002&hid=4112

Humpage, O. F. (2013, October 18). The Limitations of Foreign-Exchange Intervention: Lessons from Switzerland.

Economic Commentary(2013-13). Retrieved from http://web.b.ebscohost.com.research-

db.letu.edu/ehost/pdfviewer/pdfviewer?vid=10&sid=d1af9b54-e0c2-4e9f-b42a-

c273d742d090%40sessionmgr114&hid=105

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Appendix A – Unpegged Currency

Table A-1: Correlations between exchange rate and other variables

Unpegged Currency Exchange Rate

P-value Correlation

Interest Rate 0.000 0.592

Inflation 0.024 0.319

Net Exports (to Euro regions) 0.583 0.080 NS

Total Net Exports 0.028 -0.312

GDP (Euro) 0.108 -0.230 NS

GDP (Swiss) 0.035 -0.299

Reserves in Euro 0.000 -0.783

Total Foreign Reserves 0.000 -0.814

NS = not significant

Table A-2: Exchange rate regressions (testing for significant impacts)

Unpegged Currency Exchange Rate

95% confidence interval P-value R-Sq

Interest Rate 0.0000 35.0%

Inflation 0.0240 10.2%

Net Exports (to Euro) 0.5830 0.6% NS

Net Exports 0.0140 9.6%

GDP (Euro) 0.1080 5.3% NS

GDP (Swiss) 0.0350 8.9%

Euro Reserves 0.0000 61.3%

Total Foreign Reserves 0.0000 66.2%

NS = not significant

Table A-3: reserve regressions

GDP (Swiss) GDP (Euro)

P-value R-Sq P-value R-Sq

Euro Reserves 0.000 34.0% 0.000 24.6%

Total Foreign Reserves 0.000 32.0% 0.001 22.5%

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Table A-4: Multiple Regression

Dependent Variable Exchange

Rate Interest Rate Inflation Regression

P-value p-value p-value p-value R-sq

Net Exports (to Euro) 0.676 0.168 0.006 0.046 15.85%

Net Exports 0.369 0.000 0.073 0.000 48.43%

GDP (Euro) 0.391 0.000 0.000 0.000 37.41%

GDP (Swiss) 0.890 0.000 0.023 0.000 36.10%

Euro Reserves 0.000 0.001 0.155 0.000 69.68%

Total Foreign Reserves 0.000 0.003 0.162 0.000 71.97%

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Appendix B – Pegged Currency

Table B-1: Correlations between exchange rates and other variables

Pegged to the Euro Exchange Rate

P-value Corrolation

Interest Rate 0.108 -0.467 NS

Inflation 0.714 -0.113 NS

Net Exports (to Euro regions) 0.267 0.332 NS

Total Net Exports 0.251 0.343 NS

GDP (Euro) 0.205 0.376 NS

GDP (Swiss) 0.103 0.473 NS

Reserves in Euro 0.236 0.353 NS

Total Foreign Reserves 0.207 0.375 NS

NS = not significant

Table B-2: exchange rate regressions (testing for significant impact)

95% confidence interval Exchange Rate

P-value R-Sq

Interest Rate 0.1080 21.8%

Inflation 0.7140 1.3%

Net Exports (to Euro) 0.2670 11.0%

Net Exports 0.2510 11.8%

GDP (Euro) 0.2050 14.2%

GDP (Swiss) 0.1030 22.4%

Euro Reserves 0.2360 12.5%

Total Foreign Reserves 0.2070 14.0%

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Table B-3: reserve regressions

Exchange

Rate Interest

Rate Inflation Regression

P-value p-value p-value p-

value R-sq

Net Exports (to Euro) 0.828 0.002 0.218 0.008 71.26%

Net Exports 0.767 0.071 0.448 0.170 41.21%

GDP (Euro) 0.294 0.219 0.028 0.061 54.15%

GDP (Swiss) 0.062 0.772 0.059 0.087 50.08%

Euro Reserves 0.288 0.930 0.547 0.638 16.37%

Total Foreign Reserves 0.293 0.607 0.157 0.289 32.78%

Appendix C – Forecast Model Data

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0 2 4 6 8 10 12 14

Exchange Rate: Actual vs Forecasted

Actual Forcasted