This bachelor’s thesis investigates the relationship between economic exchange rate exposure and firm value through a literature review. It explains how exposure is defined and measured (including market-based regression approaches) and traces how academic findings evolved from early mixed evidence (“exposure puzzle”) to more recent studies reporting statistically significant sensitivity of firm value to exchange rate movements. A key reviewed study (Parlapiano et al., 2017) on European firms highlights how exposure differs by international involvement, industry, and country of origin, and the thesis also summarizes hedging strategies (financial and operational) that reduce—though do not fully eliminate—currency exposure.
Table of Contents
Abstract
Listof Abbreviations
1. Introduction
2. Exchange Rate Exposure: Definition, Measurement and Link to Firm Value
3. Results
3.1 Exchange Rate Exposure and Firm Value
3.2 HedgingStrategiesand TheirEffectiveness
4. Discussion
5. Conclusion
References
Documentation of the Use of AI Tools
List of Abbreviations
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Abstract
In an increasingly globalized economy, exchange rates play a critical role in shaping firm performance as revenues, costs and ultimately firm value are sensitive to exchange rate changes. This thesis investigates the relationship between economic exchange rate exposure and firm value. Unlike accounting exposure, economic exposure captures the sensitivity of a firm’s future cash flows and market valuation to exchange rate movements. Drawing on a comprehensive literature review, the study explores the evolution of academic understanding, from early inconsistent findings to more recent empirical studies that show statistically significant sensitivity of firm value to exchange rate changes. Special emphasis is placed on the study by Parlapiano et al. (2017), which examines the exchange rate exposure of European firms using an advanced orthogonalized regression model. The analysis highlights how firm characteristics, such as international involvement, industry type and country of origin, influence exposure levels. Additionally, the role of hedging strategies is reviewed, showing that firms employ financial and operational tools to reduce their exposure to currency risk, though not fully eliminate it. The thesis concludes with recommendations for future research, particularly regarding domestic firms, exposure measurement based on firm characteristics and firms with small and mid-sized market capitalization.
1. Introduction
Globalization has made the world more interconnected than ever before, intensifying international trade across the globe. Since countries trade in different currencies, exchange rates have become increasingly important. Unexpected changes in exchange rates can significantly affect the value of cross-border revenues, costs and ultimately, firm value. Furthermore, according to Aggarwal and Harper (2010), exchange rates also matter for purely domestic firms due to global competition, as currency fluctuations directly impact the price competitiveness of imported goods. As a result, all firms are exposed to exchange rate risk, either directly or indirectly. This thesis investigates the relationship between exchange rate exposure and firm value, with an exclusive focus on economic exposure, rather than an accounting exposure. According to Shapiro et al. (2024), accounting exchange rate exposure refers to the impact of exchange rate fluctuations on a firm's financial statements, often resulting in paper gains or losses without affecting actual cash flows. In contrast, economic exchange rate exposure captures the effect of exchange rate changes on a firm’s future cash flows and overall market value (Shapiro et al., 2024). Furthermore, Adler and Dumas (1984) argue that only economic exposure can capture the exchange rate risk faced by domestic firms, whereas accounting exposure fails to reflect such risks. With no foreign currency accounts on their books, domestic firms do not have any exchange rate exposure from an accounting perspective (Adler & Dumas, 1984). Thus, the thesis is about the relationship between economic exchange rate risk exposure and firm value. Furthermore, it is based on a literature review. To guide this analysis, the thesis is driven by the central research question of how academic understanding ofthe relationship between economic exchange rate exposure and firm value evolved over time and what insights can be drawn from the available empirical studies and practical developments in risk management.1 The primary aim is to trace the evolution in academic understanding of the relationship between economic exchange rate exposure and firm value, from the earliest theoretical developments to the recent empirical contributions. As part of this investigation, the thesis examines a contemporary study on the exchange rate exposure of European firms as a representative example, highlighting key dimensions such as advanced exposure measurement techniques and the role of firm-specific characteristics, including industry, degree of international involvement and country of origin. Its findings are compared with other empirical studies to assess consistency and identify open questions in the literature. Finally, the thesis presents the latest findings on hedging strategies and their effectiveness in reducing such exposure. The remainder of this thesis is structured as follows. Section 2 provides background information on the concept of exchange rate exposure, including its definition, methods of measurement and the theoretical link to firm value. Section 3 presents the results of the literature review, summarizing key findings on the relationship between economic exchange rate exposure and firm value. Section 4 offers a critical discussion of these findings. Section 5 concludes the thesis.
2. Exchange Rate Exposure: Definition, Measurement and Link to Firm Value
According to Shapiro et al. (2024), a firm’s value is equal to the sum of the present values of its expected future cash flows. Since economic exchange rate exposure captures both the direct and indirect (competitive) sensitivity of future cash flows to exchange rate movements, it is economic, rather than accounting, exposure that is relevant for assessing the relationship between exchange rate changes and firm value. According to Adler and Dumas (1984), economic exchange rate exposure is the sensitivity of a firm’s cash flows to unexpected changes in real exchange rates. According to Shapiro et al. (2024), economic exposure consists of two components. These are transaction exposure and operating exposure. Transaction exposure stems from exchange rate gains and losses on foreign currency denominated contractual agreements. Operating exposure arises because exchange rate fluctuations can affect a firm’s future revenues and costs, and therefore its operating cash flows. Thus, measuring a firm’s operating exposure requires a long-term perspective that views the firm as an ongoing concern, whose cost and price competitiveness may be influenced by changes in exchange rates (Shapiro et al., 2024). According to Adler and Dumas (1984), the implementation ofthe definition of economic exchange rate exposure is a regression of the changes in actual home currency denominated cash flows from past periods on changes in the exchange rate during the corresponding period. Specifically, this involves running the following regression:
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where A CFt = CFt - CFt_n and CFt equals the home currency value of total cash flows during period t. a is the regression constant. p is the foreign exchange coefficient, which measures the sensitivity of home currency cash flows to exchnage rate changes. Ae“t = et - et-i, and et equals nominal exchange rate (home currency value of one foreign currency unit) during period t. ut is a random error term with mean 0 (Adler & Dumas, 1984). In empirical studies on the relationship between exchange rate exposure and firm value, one period may refer to a day, a week, a month, a quarter or a year. It is important to note that although the definition of economic exchange rate exposure refers to real exchange rates, the above regression relies on nominal exchange rates. Adler and Dumas (1984) explain in their second footnote that for the purpose of measuring the sensitivity of cash flows to exchange rate changes, distinguishing between nominal and real exchange rates is not necessary. Moreover, according to Shapiro et al. (2024) such a regression may include lagged values of Ae"t since sales and costs often respond with a lag to exchange rate changes. Furthermore, the validity of this method depends on the assumption that the sensitivity of future cash flows to exchange rate changes is similar to their historical sensitivity. In the absence of additional information, this assumption appears to be reasonable. However, a firm may have a reason to modify the implementation of the above procedure. For instance, if a firm has recently entered into a large purchase or sales contract fixed in terms of a foreign currency, it might need to consider the resulting transaction exposure separately. Moreover, the above method can only be used if one has detailed information on a firm’s cash flows, which is something that outsiders rarely possess. However, it is possible to identify changes in the present value of future cash flows without access to detailed cash flow data. This can be done by applying the insight that in an efficient market, a firm’s stock price reflects the present value of its expected future cash flows per share. Therefore, the percentage change in the present value of future cash flows is equal to the percentage change in the firm’s stock price, or its stock return (Shapiro et al., 2024). If a stock pays dividends, then dividends are included in the calculation of stock returns. The literature on the relationship between economic exchange rate exposure and firm value primarily measures firms’ exchange rate risk exposure using stock returns, rather than the present value of future cash flows. Additionally, Jorion (1990) improved the above-mentioned regression technique by introducing a market control variable, which should help isolate stock price movements that are attributable only to exchange rate changes. The improved regression equation is as follows:
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where rt is a firm’s stock return during period t. a is the regression constant. rmt represents the return on an index of the overall stock market during period t, while ret denotes the percentage exchange rate change, expressed as the home currency value of one unit of foreign currency, during the same period. The coefficients pe and pm represent the sensitivity of the stock return to changes in the exchange rate and the market index, respectively. ut is a random error term with mean 0. It is important to note that a regression for the purpose of exposure measurement does not imply a causal relationship between exchange rates and stock prices (Jorion, 1990). This is because stock prices and exchange rates are determined jointly (Adler & Dumas, 1984). Without keeping this point in mind, commonly used phrases in the literature such as the impact of exchange rate changes on firm value may be misinterpreted as implying causality. However, an exposure measurement regression is a statistical decomposition similar to others used to study the relationship between the value of an asset and inflation rates, interest rates and market movements (Jorion, 1990). If stock returns of a firm exhibit positive sensitivity to changes in an exchange rate, then the value of the firm exhibits positive sensitivity to the changes in the exchange rate. On the other hand, if stock returns of a firm exhibit negative sensitivity to changes in an exchange rate, then the value ofthe firm exhibits negative sensitivity to the changes in the exchange rate.
3. Results
Over the past several decades, a substantial body of academic literature has examined the relationship between exchange rate risk exposure and firm value. This research trajectory shows a clear evolution in understanding. According to the seminal work by Adler and Dumas (1984), economic exchange rate exposure is the sensitivity of a firm’s cash flows to unexpected changes in real exchange rates. They further proposed a method for measuring economic exposure, which was by regressing a firm’s equity returns on changes in the exchange rate. Building on earlier theoretical work, Jorion (1990) introduced a time-series two-factor regression model in which individual firm stock returns were explained by both stock market returns and exchange rate changes. This regression technique became standard in the exchange rate exposure literature. Applying this model to a sample of U.S. multinational corporations (MNCs), he found that only a small proportion of firms exhibited statistically significant exchange rate exposure, as measured by the sensitivity of their stock returns to exchange rate changes. This study laid the empirical foundation for firm-level analysis of exchange rate risk exposure. Subsequent empirical studies tended to point out weak or even non-existent relations between exchange rate changes and firms’ stock returns. These studies were, among others, Bartov and Bodnar (1994), Bodnar and Gentry (1993), Choi and Prasad (1995) and Ami- hud (1994). According to Levi (1994), the difficulty in empirically estimating exposure was due to changing elasticity of demand, variations in the profitability of operations over the business cycle, changes in effective tax rates, shifts in required shareholder returns, and most importantly, hedging activities, which were based on many factors that firms could neither manage nor precisely predict. Consequently, the phenomenon commonly referred to as the “exposure puzzle” raised concerns about the strength of the relationship between exchange rate movements and firm value. In response, subsequent research progressively refined its methodologies and expanded its scope by the mid-1990s through the 2000s. For example, Bartov and Bodnar (1994), Bodnar and Wong (2003), Dominguez and Tesar (2001,2006) and Priestley and 0degaard (2007), among others, examined implications of differences in research designs, such as sample selection, return measurement horizon, model specification and choice of the exchange rate, on exposure measurement. Emerging studies increasingly employed larger, cross-country firm samples and introduced panel data techniques that allowed for better control over firmlevel heterogeneity. This resulted in empirical studies which showed statistically significant sensitivity of firm value to changes in exchange rates. For instance, Doidge et al. (2006) found evidence for economically sizable exposure. Furthermore, Doukas et al. (2003) persuasively argued that at least part of the lack of evidence for the significant sensitivity of individual stock returns to changes in exchange rates arose from the commonly implemented modelling assumption that aggregate stock returns were independent from exchange rates.2 Even during those years, there was substantial evidence of a relationship between aggregate stock markets and exchange rates as demonstrated, for example, by Roll (1992) and Granger et al. (2000).3 Thus, Doukas et al. (2003) introduced an orthogonalized model approach that helped reduce multicollinearity between exchange rate movements and equity market returns. According to Shrestha (2020), multicollinearity can distort the estimation of coefficients because when two or more independent variables are highly correlated, they carry overlapping or redundant information. This overlap makes it difficult for the regression model to determine how much of the change in the dependent variable is uniquely explained by each independent variable (Shrestha, 2020). Furthermore, Doukas et al. (2003) used macroeconomic control variables to filter out common external influences, which helped isolate firm-specific exchange risk exposure more effectively. The progression from basic linear regression models to these increasingly structured and purified approaches reflects the field’s growing consensus that exchange rate exposure is complex, heterogeneous, and best understood through firm-level, context-sensitive analysis. Nevertheless, as the literature has expanded over the last two decades, a growing consensus has emerged that firm value does have a statistically significant sensitivity to changes in exchange rates. However, the direction and magnitude of this sensitivity remain subject to considerable debate, especially when comparing exposure levels across different industries, countries of origin and levels of international involvement. This overview lays the groundwork for the detailed results presented in the remainder of the section. The following subsections are organized to reflect the key dimensions emphasized by the literature. In the first subsection, a recent empirical study is reviewed. This review serves three main purposes. Firstly, it demonstrates an advanced technique for exposure measurement and thereby gives a solid idea of what exposure measurement techniques are employed in the current research. Secondly, this review should demonstrate what firm characteristics are at the core of academic research interest for the purpose of understanding the exchange rate exposure of firms. Thirdly, the findings of this paper will be compared with the results of other similar studies to provide a clearer understanding of the current state of literature on the relationship between exchange rate exposure and firm value. The second subsection summarizes findings on hedging strategies and their effectiveness, emphasizing how the use of pass-through, operational, and financial hedges has been shown to influence exchange rate exposure. The results section delineates the historical evolution of research on exchange rate exposure and provides an overview of the key dimensions emphasized in the recent literature.
3.1 Exchange Rate Exposure and Firm Value
One ofthe most recent empirical studies on firm exposure to exchange rate fluctuations is by Parlapiano et al. (2017). This paper presents an assessment of the relationship between exchange rate changes and the value of European firms for the period 1999 - 2011 using the orthogonalized model approach of Doukas et al. (2003). Additionally, the study examines the exchange rate exposure of the firms based on firm-specific characteristics such as the level of international involvement, industry classification and country of origin. Firstly, the study divides the firm sample into three groups depending on their level of international involvement, meaning non-Eurozone operations. This division is based on the Foreign Exchange Exposure (FEE) index threshold as in Doukas et al. (2003), which is, in this empirical study by Parlapiano et al. (2017), the ratio of each firm’s non-Eurozone revenues to total revenues. The resulting groups are MNCs, low-export firms, and domestic firms. This way of assessing exposure serves the purpose of understanding the relationship between a firm’s level of exporting and its exposure to exchange rate risk. Secondly, the paper assesses the exposure of the sample firms based on their classification as either financial or non-financial industry firms. This is a common classification in the recent literature since initial academic research focus was primarily on nonfinancial industrial firms, assuming that the exposure of financial firms might be driven by diverse aims and factors, such as the possibility of taking advantage of better forecasts of future exchange rates by financial institutions. Finally, this research paper divides the sample of firms based on their respective countries of origin. This should reflect the importance of sovereignty within a currency union. Although it is well documented that the European common currency area has resulted in a reduction of exchange rate risk for firms in the member states, according to Hutson and O’Driscoll (2010), significant exchange rate risk remains. The exposure measurement technique used in this paper examines European firms within a framework that accounts for the common factors affecting both exchange rates and equity markets. According to Chen et al. (1986) and Doukas et al. (2003), these macroeconomic factors include unexpected inflation (UI), industrial production (IP), term premium (TP), money supply (MS), interest rate spread (IRS), and trade balance (XM), all of which influence exchange rate movements and equity market fluctuations. Except for the UI, all the control variables are selected and computed following Chen et al. (1986) and Doukas et al. (2003) specifications.[4] Parlapiano et al. (2017) evaluates the impact of unexpected fluctuations in the Euro exchange rate against the United States Dollar (USD), Japanese Yen (JPY), British Pound Sterling (GBP) and Swiss Franc (CHF), meaning that its focus is on Eurozone firms. Specifically, the paper considers all 600 firms of a broad market index called Euro Stoxx Total Market Index (TMI) and 50 firms of a large capitalization index called Euro Stoxx 50. Both indices have a diverse coverage ofthe Eurozone countries and sectors. While Euro Stoxx TMI presents an economic performance benchmark of the Eurozone, Euro Stoxx 50 is focused on large capitalization and value weighted selection of firms.4 The paper uses monthly data obtained from Bloomberg and Stoxx Ltd. According to Par- lapiano et al. (2017), the exposure literature discusses two biases associated with the inclusion of large stocks in market indices. The size or positive bias affects the estimation of exchange rate exposure due to the higher proportion of exports of large firms (Bodnar & Wong, 2003). On the other hand, the success bias inflates the market risk premium estimation when stocks included in the value weighted indices experienced a sustained growth path (Dimson et al., 2002). Parlapiano et al. (2017) account for the mentioned size and success biases by using a broad market index, specifically the Euro Stoxx TMI. Monthly data for the set of economic variables and nominal bilateral exchange rates are derived from the ECB Statistical Data Warehouse. The study adopts indirect exchange rate quotation from the view ofthe Eurozone. Thus, positive exchange rate returns imply appreciation of the Euro. This means that the study expresses all exchange rates in terms of the foreign currency cost of one Euro. The study points out that the standard model used in the literature is the one of Jorion (1990), which is a direct regression of contemporaneous exchange rate changes on individual firm stock returns. It controls for market conditions by using a common market indicator. The model is an augmented capital asset pricing model (CAPM) and is as follows:
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where rit represents the stock return for a firm i at time t and is regressed on contemporaneous exchange rate return (rst) and the market portfolio return (rmt). pli represents the exposure of the firm i to exchange rate movements. Because of the previously mentioned problem of multicollinearity, Parlapiano et al. (2017) uses a three stage orthogonalization approach of Doukas et al (2003). This approach separates or “orthogonalizes” the market and exchange rate risk factors. The initial step serves the purpose of removing from the exchange rate returns the effect of common macroeconomic fundamental influences which might potentially influence both equity markets and exchange rates. These variables correspond to the previously mentioned macroeconomic factors.
Regressing these control variables on the exchange rate returns, we derive the unexpected exchange rate returns from
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where CVj,t_I represents lagged control variables and rst_i serves the purpose of controlling for any autocorrelation in exchange rate returns. According to Schaffer et al. (2021), autocorrelation means that past values of a variable, in this case exchange rate returns, are correlated with current values and thus are not independently distributed. According to Ludlow (2018), if this is not taken into account, the results of the analysis can be misleading. The unexpected exchange rate returns are the fitted residuals from Equation (2), denoted as ¿St- The second step is to orthogonalize equity market returns to the same set of common control variables and the unexpected exchange rate returns derived from Equation (2), while controlling for autocorrelation in the market returns as follows:
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Where r"t stands for the stock market return. The orthogonalized indicator of the market return will be provided by the estimated residuals, eJJt. Finally, the third step is to estimate the sensitivity of individual firm stock returns to the unexpected exchange rate and unexpected market returns. This is done as follows:
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where we now take into consideration the effect of the economic factors and the unexpected components of the exchange rate and market returns. The coefficient stands for the sensitivity of the stock returns of an individual firm, rit, to unexpected exchange rate movements. We now turn to the results of this study. Although the study reports results of all the three stages of the regression analysis, only the results of the third regression stage are presented here to conserve space. Moreover, the third stage results represent the final outcomes of the analysis and are central to the study’s conclusions. Table 1 reports the outcomes of the third stage of the described regression procedure. The first panel of Table 1 shows the results for the unexpected changes in the exchange rate of the JPY against Euro. Slightly over 27 % of the Euro Stoxx TMI constituents have a significant response to unexpected changes in the value of the JPY against the Euro, with an average appreciation of 8.2 % in stock returns for every 10 % appreciation ofthe Euro. The second and third panel of Table 1 show that the impact of an appreciation of the Euro against the USD and GBP is positive with an average of about 7 %. However, the proportion of firms with significant impact is fewer than half that
Table 1. Exchange rate exposure of European firms (orthogonalized market model)
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Notes: Equation (4) estimated using monthly data from 1999 to 2011. Heteroskedasticity robust OLS estimates of the exchange rate exposure, pis, are reported. Figures show the percentage of firms significantly affected by exchange rate fluctuations, the average magnitude of significant exposure coefficients and the number of firms positively, N+, and negatively, N; affected bycurrencyvariations.
<a> Average of significant pis from Equation (4).
<b) Number of significant and positive pis from Equation (4).
<c> Number of significant and negative pis from Equation (4).
Source: Parlapiano etal. (2017)
in the case of the Japanese currency. An astonishing 52% of firms in the Euro Stoxx TMI are significantly affected by fluctuations in the CHF, with as many as 72% of affected firms belonging to the financial sector. On average, a 10% appreciation of the Euro against the CHF corresponds to an 18.8% increase in stock returns. The large proportion of European firms exposed to the CHF may be a reflection of a speculative demand for the CFH in the form of a foreign debt. Keloharju and Niskanen (2001) provide insight into this from the case of Finland. Parlapiano et al. (2017) point out that this demand for CHF might be driven by the interest rate differential between the Eurozone and Switzerland. The interest rate differential makes it attractive to borrow funds denominated in CHF. The increase in stock returns as a result of an appreciation ofthe Euro is consistent with the reported results in Muller and Verschoor (2006). According to Muller and Verschoor (2006), appreciating Euro against other currencies has a positive effect on the returns of European stocks. Their argument is that European firms are primarily net importers and therefore benefit from a strong euro, which enhances domestic consumption and increases the competitiveness of exports that incorporate imported inputs. According to Table 1, the percentage of firms with a significant response to unexpected exchange rate fluctuations in the Euro Stoxx 50 sample is substantially higher than for the Euro Stoxx TMI. However, the estimated pis of the two market indices cannot be directly meaningfully compared with each other since they are constructed for two diverse indices. According to Table 1, the highest average impact on the Euro Stoxx 50 constituents comes from unexpected changes in the Euro against the CHF, which is about 16.4 % for each 10 % exchange rate variation, followed by the GBP (9.5%), JPY (6.7%) and USD (5.9%). Traditionally, a firm’s level of international involvement has been widely recognized as a determinant of its exchange rate exposure (Parlapiano et al., 2017). According to Choi and Jiang (2009), empirically, exchange rate risk exposure of MNCs is smaller and less significant than the exposure of non-MNCs, which is not consistent with theoretical predictions. This might be due to operational hedging of MNCs (Choi and Jiang (2009)). According to Davies et al. (2006), Bartram (2008) and Bartram et al. (2009), there is strong evidence that firms with a higher proportion of international sales are likely to hedge FEE. Furthermore, Amiti et al. (2014) provide an alternative explanation for a smaller and less significant exposure of MNCs, which is a theoretical framework where a typical large importer is simultaneously a large exporter and thus manages both sides of exchange rate fluctuation so that the exposure of such a large MNC is smaller than the exposure of firms with a lower level of international involvement. Table 2, which comes from Parlapiano et al. (2017), shows the exposure coefficients classified by the level of international involvement approximated by the FEE index. There is a clear pattern that emerges from Table 2. Low exporters and domestic firms are more sensitive to unexpected exchange rate changes than MNCs. Furthermore, the magnitude of the average exposure coefficient for low exporters and domestic firms is greater than that for MNCs, confirming the findings of Davies et al. (2006) and Choi and Jiang (2009). Moreover, these results are consistent with Amiti et al. (2014), who provide evidence that internationally active firms experience lower exchange rate risk. Because Amiti et al. (2014) provide evidence from Belgian data, it has high Euro relevance. On the other side, this result is a contradiction to the theoretical prediction that the higher a firm’s level of international involvement, the greater the impact of currency fluctuations on the firm’s market value. One can make two additional observations from Table 2. Firstly, the exposure of MNCs to unexpected changes in the value of the USD and GBP is smaller than their exposure to the JPY and CHF. One possible explanation is that
MNCs focus their hedging activities on exchange rate risks arising from the currencies of their main trading partners. In this case, these currencies are USD and GBP (Parlapiano et al., 2017). Another possible explanation is that the MNCs in the firm sample take advantage of the interest rate differentials between the Eurozone and Japan as well
Table 2: Exchange rate exposure of European firms with a breakdown by international involvement
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Notes: Equation (4) estimated using monthly data from 1999 to 2011. Heteroskedasticity robust OLS estimates of the exchange rate exposure, pis, for the Euro Stoxx TMI and the Euro Stoxx 50 constituents are reported along with the percentage of firms significantly affected by exchange rate fluctuations, the average magnitude of significant exposure coefficients and the number of firms positively, N+, and negatively , N-, affected by currency variations. Firms are categorized as multinational corporations (MNCs), low exporters (Low Exp.) or domestic firms (Dom.) based on the ratio oftheir non-Eurozone revenues to total revenues.
<a)Average of significant |is from Equation (4).
<b>Number of significant and positive pis from Equation (4).
<c>Number of significant and negative pis from Equation (4).
Source: Parlapiano et al. (2017)
as between the Eurozone and Switzerland (Brunnermeieret al., 2008; Galati et al., 2007; Hattori & Shin, 2009). According to Parlapiano et al. (2017), the second observation is that large-capitalization firms are more likely to be exposed to exchange rate risk. For instance, 43% of Euro Stoxx 50 MNCs are significantly affected by exchange rate fluctuations. This percentage is considerably higher than that of significantly affected MNCs in the Euro Stoxx TMI, which stands at only 27%. Table 3 reports the results of the assessment of exchange rate exposure based on firm industry. Table 3 reports that firms in the financial industry experienced a much bigger positive impact of exchange rate fluctuations than firms outside the financial industry. The proportion of financial firms significantly affected is larger and, in some cases, more than double the proportion of non-financial firms. Additionally, the magnitude of exposure coefficients is greater on average. However, this is not consistent with the results of the study by Mozumder et al. (2014), which is based on 100 European blue chip companies. According to Mozumder et al. (2014), there is no significant difference between the exposure of financial and non-financial firms. This indicates that there is no strong consensus in the literature
Table 3. Exchange rate exposure of European firms with a breakdown by industry.
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Notes: Equation (4) estimated using monthly data from 1999 to 2011. Heteroskedasticity robust OLS estimates of the exchange rate exposure, pis, for the Euro Stoxx TMI and the Euro Stoxx 50 constituents are reported along with the percentage of firms significantly affected by exchange rate fluctuations, the average magnitude of significant exposure coefficients and the number of firms positively, N+, and negatively, N“, affected by currency variations. Each firm is grouped as financial or non-financial according to the Bloomberg Industry Classification system.
(a) "Fin." is an abbreviation for "Financials". Financials include firms in financial, banking, and insurance sectors.
(b) “Non-Fin.” is an abbreviation for “Non-Financials”. Non-Financials include firms in the Industrial, Utility and Real Estate Investment Trust (REIT) sectors.
(c) The sample size is 529 firms from Euro Stoxx TMI. Securities with less than 70 observations have been excluded from the analysis.
(d) Average of significant pis from Equation (4).
(e) Numberofsignificantand positive pis from Equation (4).
(f) Number of significant and negative pis from Equation (4).
Source: Parlapiano etal. (2017)
regarding the differences in the exposure of financial and non-financial firms. Furthermore, Parlapiano et al. (2017) examine the sensitivity of the firms in the sample to exchange rate fluctuations based on their countries of origin. Table 4 shows the results. The list of countries with relatively higher exposure to exchange rate fluctuations includes Greece, Ireland, Italy, Portugal, Spain and Belgium. These countries experienced sovereign debt crisis late in the sample period. According to Chaieb & Mazzotta (2013) and Mozumder et al. (2014), firms become more sensitive to exchange rate exposure during a period of crisis, which confirms the increased sensitivity of the firms based in the above countries. Furthermore, these countries have the largest concentration of financial firms in comparison to other countries in the sample. As discussed earlier and shown in Table 3, firms in the financial industry appear more exposed to exchange rate risk, although the literature does not show strong consensus on whether financial and non-financial firms differ in this regard. Finally, Parlapiano et al. (2017) implements the Jorion model using the data sample. Specifically, the study reports the results for the
Table 4. Exchange rate exposure of European firms with a breakdown by country.
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Notes: Equation (4) estimated using monthly data from 1999 to 2011. Heteroskedasticity robust OLS estimates of the exchange rate exposure, pis, for the Euro Stoxx TMI and the Euro Stoxx 50 constituents are reported along with the percentage of firms significantly affected by exchange rate fluctuations. Each firm is grouped according to the country of origin. Furthermore, country abbreviations correspond to the following: AT(Austria), BE (Belgium), DE (Germany), ES (Spain), FI (Finland), GR (Greece), IE (Irland), IT (Italy), NL (Netherlands), PT (Portugal).
(a) Countries with less than five firms.
(b) Average of significant pis from Equation (4).
Source: Parlapiano et al. (2017)
Euro Stoxx TMI. Table 5 clearly presents these results. These results can be compared with the outcomes of the third stage of the orthogonalized approach. For the JPY and CHF, the estimated proportion of firms significantly affected by exchange rate risk using the Jorion (1990) model is significantly lower than the proportion estimated using the orthogonalized approach, whereas the proportions are almost identical for the USD and GBP. Moreover, the average estimated relationship between individual firm equity returns and exchange rate risk is larger when using the orthogonalized approach compared to the Jorion (1990) model in all cases. Remarkably, the average of the significant coefficients in the orthogonal market approach is always positive. This is not the case with the Jorion (1990) approach since the average ofthe significant coefficients is negative in the case of the GBP. The body of evidence on the common factors affecting
Table 5. Exchange rate exposure of European firms (augmented market model ofJorion (1990))
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Notes: Equations (1) estimated using monthly data from 1999 to 2011. Average p represents the average of significant P-j. from Equation (1). OLS estimates of the exchange rate exposure for the Euro Stoxx TMI constituents are reported along with the percentage of firms significantly affected by exchange rate fluctuations, the average magnitude of significant exposure coefficients and the number of firms positively, (N+), and negatively, (N-), affected by currency variations.
Source: Parlapiano etal. (2017)
exchange rates and equity market conditions, combined with the observed differences when exchange rate and market shocks are not orthogonalized, underscores the importance of controlling for potential multicollinearity by using an orthogonalized model. Finally, the review of this study fulfilled effectively all the three of its intended purposes. Firstly, it demonstrated an advanced technique for exposure measurement and thereby gave a solid idea of what exposure measurement techniques are employed in the current research. Secondly, this review demonstrated which firm characteristics are at the core of academic research interest for the purpose of understanding the impact of exchange rate exposure. Specifically, these characteristics are the level of international involvement, industry classification and country of origin. Thirdly, the findings of this paper were compared with other similar studies to provide a clearer understanding of the current state of literature on the relationship between exchange rate exposure and firm value. This review effectively sets the stage for the next subsection, which addresses the hedging of exchange rate risk exposure.
3.2 Hedging Strategies and Their Effectiveness
According to Shapiro et al. (2024), firms actively manage their exchange rate exposure. Research by Bartram et al. (2010), based on a sample of 1,150 MNCsfrom 16 countries, has shown that firms do face significant currency exposure but mitigate it through three separate methods. First, firms use pricing strategies to pass through at least some of the additional costs caused by currency movements to their customers. This allows them to reduce the impact of currency fluctuations on revenues. Second, firms adapt their sourcing of parts and products by shifting manufacturing activities among factories in different countries in response to exchange rate changes. This is also called operational hedging. Third, firms employ a variety of financial instruments and techniques, such as debt denominated in different foreign currencies and foreign exchange derivatives, to hedge against currency risk. Together, these three strategies explain the reduced sensitivity of stock returns to exchange rate changes. Pricing pass-through and operational hedging each reduce exposure by about 10% to 15%, while financial hedging with foreign debt and, to a lesser extent, foreign exchange derivatives accounts for an additional 37% to 43% reduction. As a result, the combined effect of these strategies reduces gross economic exposure by approximately 70% to the levels measured from equity prices (Bartram et al., 2010). However, according to Shapiro et al. (2024), these three methods are only part of a broader set of tools available to firms to manage their exposure. Since exchange rate risk affects all aspects of a firm’s operations, it should not be only the concern of financial managers. Operating managers should develop marketing and production initiatives that aim to ensure long-term profitability. The focus on the economic effects of exchange rate changes and the related risks shows that a good exchange risk management strategy should aim to protect a firm’s earning power in its home currency. While firms can easily hedge transaction exposures, the economic exchange exposure from competitors operating in other currencies is longer term and cannot be managed through financial hedging alone. Instead, it requires long-term operational adjustments, especially in marketing and production management. The design of a firm’s marketing strategy under home currency fluctuations presents a significant opportunity for gaining a competitive advantage. For this reason, one of the main tasks of an international marketing manager should be to identify the likely effects of an exchange rate change and adjust pricing and product policies. Furthermore, one of the most important strategic marketing considerations for an exporter is market selection and the relative marketing support to devote to each market. As mentioned, pricing is an essential strategic marketing area for exchange risk management. When it comes to the pricing strategy of a MNC, the key consideration is whether to emphasize market share or profit margin. Following a home currency depreciation, an exporter can either raise its home currency price and boost its profit margin or keep its home currency price constant, which will lead to a lower foreign currency price and expand its market share. This decision depends on multiple factors, such as whether this change in the exchange rate will persist, economies of scale, the cost structure of expanding output, consumer price sensitivity and the likelihood of future competition. The greater the price elasticity of demand, which is the change in demand for a given change in price, the bigger the incentive to hold down the foreign price and expand sales and revenue. In this case, it would be wiser to gain more market share. Similarly, if significant economies of scale exist, it is generally worth holding the foreign price down, expanding demand, and thereby lowering production costs per unit. The opposite is true if economies of scale do not exist or if price elasticity is low. Turning now to domestic pricing after a fall in the home currency, a domestic firm facing import competition has similar options. It can raise prices consistent with import price increases or hold prices constant to gain market share. The strategy depends on factors such as economies of scale and price elasticity of demand. For instance, the sharp rise in the value of the JPY and Deutsche Mark (DM) against the USD during the 1990s led Japanese and German automakers to raise their dollar prices. This allowed Ford and General Motors to raise their prices on competing models. The price increases by the U.S. auto manufacturers, which were not as high as the sharp rises in import prices, improved their profit margins and kept U.S. cars competitive with their foreign rivals. The competitive situation is reversed following an appreciation of the USD. When considering whether to raise prices following a foreign currency depreciation, firms must take into consideration not only sales that will be lost today but also the probability of losing future sales. A customer that is lost might be lost forever. Product strategy is also essential when it comes to the marketing management of exchange risk. Product strategy deals with areas such as new product development, product line decisions, and product innovation. One practical way of coping with exchange rate fluctuations is to change the timing of the introduction of new products. For instance, due to the competitive price advantage, the period after a home currency depreciation may be the perfect time to develop a brand franchise. Furthermore, exchange rate fluctuations also affect product line decisions. Following home currency devaluation, a firm will potentially be able to expand its product line and cover a wider spectrum of consumers both at home and overseas. On the other hand, home currency appreciation may force a firm to reorient its product line and target it to a higher-income, more quality-conscious customer base. For example, Volkswagen attained its export prominence on the basis of low-priced, low-maintenance cars. However, the appreciation of the DM in the early 1970s effectively ended Volkswagen’s ability to compete mainly on the basis of price. The German car manufacturer was forced to revise its product line and sell relatively high-priced cars from an extended product line to middle-income consumers based on quality and styling rather than cost. The equivalent strategy for firms selling to the industrial rather than consumer market and facing a strong home currency is product innovation, financed by an expanded research and development budget. Firms can differentiate their product offerings by adding service features that customers find valuable. For this to be a viable strategy, the premium that customers are prepared to pay for additional features must exceed the cost of adding those service features. However, exchange rates sometimes fluctuate so much that pricing or other marketing strategies cannot save the product or the home currency earnings of a firm. Firms facing such a situation must either drop uncompetitive products or cut their costs. This is part of the production management of exchange risk. Product sourcing and plant location are the main production management channels of influence that firms have in order to manage exchange rate risks arising from competition when these risks cannot be mitigated through marketing changes alone. The basic strategy is to shift a firm’s manufacturing base overseas. This can be done in more than one way. Building new factories overseas is a direct manufacturing shift. A more flexible solution is to change the input mix by purchasing more components overseas. However, one strategy that is unlikely to improve competitiveness is to force suppliers to invoice in a different currency. Suppliers are likely to simply take their local currency prices and convert them into the desired currency at the forward rate, which will not result in any cost savings for the firm. Moreover, MNCs with worldwide production systems can allocate production among their various plants depending on home currency costs of production. They can increase production in a country whose currency has devalued and decrease production in a country where there has been a currency revaluation. Thus, contrary to conventional wisdom, MNCs face less exchange risk exposure than an exporter due to their greater ability to adjust production operations globally, depending on relative production costs (Shapiro et al., 2024). According to Hagerty (2010), for global companies based in the U.S., the impact of currency swings can be muted because they have factories in many countries and costs in a variety of currencies. However, Shapiro et al. (2024) explain that the theoretical ability to shift production is limited in reality. One reason is the power of local labor unions involved. On the other hand, since MNCs are typically innovative, they frequently develop new products. These products can be sourced from the firm’s various plants based on cost considerations. A strategy of product shifting is based on the assumption that a MNC has already created a portfolio of plants worldwide. This large network of plants can lead to manufacturing redundancies and impede cost-cutting. The cost of multiple sourcing is particularly great when the establishment of only one or two plants to serve the global market would be especially profitable due to economies of scale. However, due to increased uncertainty, most firms find that production diversification is significantly beneficial. Having redundant capacities means the ability to execute volume shifts fairly easily. The greater the volatility of relevant exchange rates, the more valuable it is to be able to shift manufacturing quickly. Another important aspect of production management of exchange risk is raising productivity. Firms can raise their productivity by closing inefficient plants, automating processes, and negotiating wage and benefit cutbacks with unions. They can also increase productivity by launching special programs to boost employee motivation. Furthermore, firms can revise their product offerings and consider discontinuing products that do not significantly contribute to revenue generation. It is important to mention that the above marketing and production strategies rely on knowledge of exchange rate changes. Although exchange rate fluctuations are unpredictable, contingency plans can still be prepared. This involves developing several plausible exchange rate scenarios, analyzing the effects of each scenario on the firm’s competitiveness and profitability, and deciding on strategies to address these possibilities. Part of the competitive analysis includes assessing the effects of a given currency scenario on foreign competitors. Since exchange rates are volatile and the only constant is change, firms must be able to react within a short time horizon. Therefore, they must develop competitive options such as outsourcing, flexible manufacturing systems, a global network of production facilities, and shorter product cycles. Because of this constant state of change, investments in flexibility often yield the highest returns. For instance, foreign production facilities, even if not currently profitable, can be valuable by allowing firms to shift production in response to changing exchange rates or other relative cost shocks. Strategic marketing and production adjustments are timeconsuming. Therefore, the role of financial management in this process is to structure a firm’s liabilities so that, during the time that strategic operational adjustments are being made, the reduction in asset earnings is matched by a corresponding decrease in the cost of servicing these liabilities. One possibility is to finance the portion of a firm’s assets that generate export profits in such a way that any shortfall in operating cash flows caused by an exchange rate change is offset by a reduction in debt servicing expenses. For instance, a firm that has developed a sizable export market should hold a portion of its liabilities in that country’s currency. The portion to be held in the foreign currency depends on the size of the loss in profitability associated with a given currency change. Since currency effects vary from one firm to another, it is not possible to give a more precise recommendation. A numerical example of the application of this financial hedging strategy can be found in Chapter 10 of Shapiro et al. (2024). The implementation of a hedging policy is quite challenging in practice. One reason is that it is hard to predict the specific cash-flow effects of a given exchange rate change. Firms need trained personnel to implement and monitor an active hedging program. Thus, hedging should be undertaken only when the effects of anticipated exchange rate changes are expected to be considerable. The key to effective exposure management is to integrate currency considerations into the general management process. One possible approach used by MNCs to develop coordination among executives responsible for various aspects of exchange risk management is the establishment of a committee for managing foreign currency exposure. In addition to financial executives, such committees include senior officers of the firm, such as the chief executive officer, vice president, director of corporate planning, and top marketing and production executives. This arrangement is important because it exposes top executives to the challenges of exchange risk management, allowing them to incorporate currency expectations into their own decisions. In this type of integrated exchange risk program, the role of a financial executive consists of four main tasks. First, the financial executive should provide operating management with forecasts of inflation and exchange rates. Second, they should identify and highlight the risks that exchange rate changes pose to competitiveness. Third, they should structure evaluation criteria so that operating managers are not rewarded or penalized for the effects of unanticipated exchange rate changes. Fourth, the financial executive should estimate and hedge any remaining operating exposure after the appropriate marketing and production strategies have been put in place (Shapiro et al., 2024). Finally, although hedging significantly reduces exchange rate exposure, it does not fully eliminate it, as demonstrated in the study by Parlapiano et al. (2017).
4. Discussion
There is a vast amount of literature on the topic of exchange rate exposure and firm value. However, the results of empirical studies in this area are not always consistent. In fact, many studies contradict one another, which even led to the term “exposure puzzle” in the early stages of research. Based on the reviewed studies and the current state of the literature, several conclusions about the relationship between exchange rate exposure and firm value can be drawn. First, stock returns show a statistically significant sensitivity to exchange rate changes, which implies a significant relationship between firm value and exchange rate changes. This conclusion is supported by several recent empirical studies, including Parlapiano et al. (2017), Chaieb and Mazzotta (2013), Mo- zumder et al. (2014) and Aggarwal and Harper (2010). The consistent findings across these studies indicate that the exposure puzzle has been solved. This is an important observation as many recent studies begin by addressing this issue. Such an approach is no longer necessary given the current consensus in the literature. As shown in the reviewed empirical study, the value of European firms has a statistically significant positive sensitivity to changes in exchange rates between the Euro and the four selected foreign currencies. However, these results should not be generalized globally as firms in other regions may exhibit different sensitivity of firm value to exchange rate changes between their domestic currency and the currencies of their trading partners. Nevertheless, it can be stated that firm value generally exhibits a statistically significant sensitivity to exchange rate changes although the majority of existing research focuses primarily on U.S. and European firms. The reviewed empirical study is representative in terms of its exposure measurement technique and the selected firm characteristics used for exposure measurement. Second, based on the above findings, firms actively hedge exchange rate risk exposure using a combination of financial and operational strategies. These approaches substantially reduce exposure, though they do not fully eliminate it. Third, according to Aggarwal and Harper (2010) and Parlapiano et al. (2017), domestic firms are significantly exposed to exchange rate risk. However, these studies differ in their conclusions regarding whether domestic firms are more exposed than internationally active firms. Furthermore, the majority of existing literature focuses on internationally involved firms while studies on the exchange rate exposure of domestic firms remain limited. In fact, the first studies on the exchange rate exposure of firms, such as Jorion (1990) and Bartov and Bodnar (1994), focused exclusively on internationally active firms. The first study addressing the exposure of domestic firms, Aggarwal and Harper (2010), appeared approximately two decades after research on exposure measurement began.
This indicates that the study of exchange rate exposure of domestic firms is still at an early stage and further research may yield valuable insights. Fourth, there is widespread agreement in the literature that exchange rate exposure increases during periods of economic contraction, such as recessions or financial crises. This conclusion is consistently supported by empirical studies, such as Parlapiano et al. (2017), Chaieb and Mazzotta (2013), Mozumder et al. (2014) and Sikarwar (2018). Fifth, MNCs are not necessarily more exposed than other firms, which contradicts purely theoretical predictions. This is supported by several empirical studies, such as Parlapiano et al. (2017), Choi and Jiang (2009) and Bartram et al. (2010). Any further general statements regarding the relationship between firm value and exchange rate exposure are unlikely to be supported academically. The literature is particularly inconsistent concerning the measurement of exposure based on firm characteristics, such as industry, level of international involvement and country of origin. This highlights a clear need for further research in this area. Moreover, it suggests that it is premature for policymakers to develop policies based on firm characteristics and exchange rate exposure. A promising direction for future research could also be the examination of exchange rate exposure of firms with small and midlevel capitalization as well as the development of appropriate hedging strategies for them.
5. Conclusion
This thesis explored the evolving academic understanding of the relationship between economic exchange rate exposure and firm value. By focusing exclusively on economic, rather than accounting, exposure, it emphasized the relevance of exchange rate movements for a firm's future cash flows and valuation. A comprehensive literature review demonstrated that while early empirical research produced inconsistent results, often referred to as the “exposure puzzle”, more recent studies have significantly refined exposure measurement techniques, leading to a growing consensus that firm value is indeed sensitive to exchange rate changes. The review of the empirical study by Parlapiano et al. (2017) confirmed that a large number of European firms exhibit statistically significant sensitivity to exchange rate fluctuations. However, the direction and magnitude of this sensitivity cannot be generalized globally, as economic exposure varies substantially based on firm characteristics and the methodology used. Comparing this study with others revealed both consensus points and inconsistencies. Most inconsistencies arise when exposure is measured across firm subgroups—such as by industry, level of international involvement, or country of origin. Nonetheless, this approach remains valuable for identifying patterns and gaps in the literature. In addition, the thesis reviewed the role of hedging strategies, concluding that while many firms employ both financial and operational methods to reduce their currency exposure, complete elimination of it remains difficult. This underlines the strategic importance of exposure management across different functional areas of the firm. Based on the literature review, three promising directions for future research were identified. First, future research should focus more on the economic exposure of domestic firms and explore tailored hedging strategies for them. Second, further efforts are needed to bring greater consistency to exposure measurement based on firm characteristics. Due to a lack of consistency in this area, it is premature to introduce policies on the basis of economic exposure and firm characteristics. Third, more attention should be given to small- and mid-cap firms, whose economic exposure is under-researched despite their central role in most economies. Advancing research in these areas will deepen our understanding of how diverse firms can protect their value in an increasingly volatile global financial environment.
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1 ChatGPT was used to facilitate the preparation of the research question.
2 Another critical point regarding Jorion's model assumption comes from Agyei-Ampomah et al. (2013). According to their recent study, the weak evidence of foreign exchange exposure found in most previous studies may be due to Jorion's assumption that exposure remains constant over time. In reality, however, a firm's “circumstances”, including its international operations and risk management activities, change continuously, which should logically cause its currency risk exposure to vary over time as well.
3 There is also recent evidence of bi-directional Granger causality between exchange rates and stock market returns in Inci and Lee (2014). Furthermore, you can also see Phylaktis and Ravazzolo (2005) for evidence that aggregate equity market returns are related to exchange rate movements via common factors. Moreover, you can see Chordia and Shivakumar (2002) as well as Flannery and Protopapadakis (2002) on macro fundamentals in forecasting and announcement effects on stock returns. You can see Beckmann et al. (2011) for evidence on macro variables and the Euro.
4 According to Parlapiano et al. (2017), The number of constituents ofthe Euro Stoxx TMI varies to coverage of approximately 95% of the free-float market capitalization of the European Monetary Union, while the Euro Stoxx 50 covers 60% of the free-float market capitalization of the Euro Stoxx TMI super sector index.
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- Mukhammadzhon Bekhbudov (Autor:in), 2025, Exchange Rate Risk Exposure and Firm Value, München, GRIN Verlag, https://www.grin.com/document/1700281
