The impact of headquarters location on stock returns

Table of Contents

List of Abbreviations

List of Symbols

Index of Figures

Index of Tables

1 Introduction
1.1 Motivation and Problem Definition
1.2 Course of the Analysis

2 The Fundamentals of International Capital Markets
2.1 The Concept of Portfolio Theory
2.1.1 Portfolio Optimization
2.1.2 International Diversification
2.2 Integration versus Segmentation of Capital Markets
2.3 The Concept of Market Efficiency
2.3.1 Operational and Informational Market Efficiency
2.3.2 Market Efficiency and Behavioral Finance

3 Home Bias and Local Bias in Equities
3.1 Definition of Home Bias and Local Bias
3.2 Different Explanations to the Bias Puzzle
3.2.1 National Barriers to International Investments
3.2.2 Hedging of Country-specific Risks
3.2.3 Information Advantages of Local Investors
3.2.4 Familiarity
3.2.5 Social Interaction of Investors and Trading Patterns
3.3 Home Bias from a German Perspective
3.3.1 Benefits from International Diversification for German Investors
3.3.2 Actual Portfolio Holdings of German Investors

4 Geographic Component of Asset Pricing
4.1 Location of Corporate Headquarters
4.2 Agglomeration of Headquarters
4.3 Geographic Implications on Stock Returns
4.3.1 Fundamentals and Geographic Segmentation
4.3.2 Hypothesis of Local Asset Pricing

5 Description of the Data Set
5.1 Data Selection
5.2 Descriptive Statistics

6 Empirical Analysis
6.1 Comovement of Local Stocks
6.1.1 Methodology – Time-series Regressions
6.1.2 Results
6.2 Robustness Test
6.2.1 Resampling Method
6.2.2 Local Comovement versus Non-local Comovement
6.3 Local Comovement Attributable to Fundamentals
6.3.1 Methodology – Time-series Regressions
6.3.2 Results
6.4 Firm-specific and Regional Determinants
6.4.1 Methodology – Cross-sectional and Panel Regressions
6.4.2 Results
6.5 Limitations of the Model

7 Summary and Conclusion

Index of Appendices

References

List of Abbreviations

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List of Symbols

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Index of Figures

Figure 1: Local vs. Non-local Comovement for the Time Period from 1986 to 2005

Index of Tables

Table 1: Correlation of the DAX with Major Stock Indices from 1997 to 2005

Table 2: Descriptive Statistics

Table 3: Local Comovement

Table 4: Local Comovement and Fundamentals

Table 5: Local Comovement and Firm Characteristics

Table 6: Firm and Regional Determinants of Local Comovement

1 Introduction

1.1 Motivation and Problem Definition

In a time of tremendous advances in technology, it seems striking why the location of corporate headquarters should matter for the firm’s stock return. At first glance, low information and communication costs are thought to facilitate the interaction between market participants all around the world and, thus, deem the role of geographical location as marginal. This reasoning, however, does not take investors’ behavior into account.

Even if over the past decades, international capital markets have widely been liberalized and the variety of investment opportunities across countries has grown substantially, many investors do not take the risk reduction potential of foreign assets into consideration. Despite the extensive benefits of international diversification, investors still overweight domestic and local assets in their portfolios. Although this home bias has drawn much academic attention and its existence is commonly accepted, a satisfactory rationale could not yet be obtained. Further, the resulting economic implications for asset pricing remain unexplored. Yet, locality could be highly relevant for cost of capital calculation, asset allocation and performance evaluation.^[1]

As a result, it is of crucial importance to investigate the relationship between portfolio holdings of investors and stock pricing patterns to shed light on a potential geographical component of asset pricing. The lack of academic research motivates to explore this area in greater detail. The purpose of this thesis is to fill the existing gap and establish a link between local bias and asset pricing. Therefore, a detailed overview of the home bias puzzle as well as of local asset pricing is presented. The economic impact of local bias on stock returns is empirically investigated. Thus, the key question of the analysis is whether the location of corporate headquarters has an impact on stock returns attributable to the local bias of investors.

1.2 Course of the Analysis

In section 2, the underlying financial theories of international capital market integration are introduced. The portfolio theory points out that an investor can eliminate the idiosyncratic risk with international diversification and, hence, increase the efficiency of his portfolio. Thereby, the concept of market efficiency provides the foundation of portfolio optimization which assumes that stock prices reflect all available information. Alongside with this informational market efficiency, capital markets are also well integrated and operationally efficient. Thus, there should be no rational explanation why an investor should not invest in a certain market.

In spite of the compelling evidence of the benefits of international diversification, section 3 emphasizes the underdiversification of investors. A substantial body of empirical studies observed an overweighting of domestic assets in investor portfolios, exhibiting a so-called home bias. In addition, recent studies revealed a preference for geographically proximate assets in the context of national markets which is of particular interest for this thesis. The phenomena of home and local bias are not yet thoroughly understood and remain puzzling in academic literature. Thus, different explanation approaches, ranging from informational advantages of local investors to hedging of local risks, are considered in this section. Moreover, international diversification and home bias from the perspective of German investors are described in more detail, which serve as a foundation for the subsequent empirical work on the German market. The reasons for choosing Germany are twofold. First, the German market satisfies the framework of a developed capital market system. Second, the market is not thoroughly explored with respect to locality which makes it particularly challenging.

Turning to the economic implications of local bias, section 4 analyzes the impact of headquarters’ location on stock returns. The role of headquarters and the determinants of the choice of location are presented. Several hypotheses are formulated with regard to the geographic impact on stock returns.

Section 5 presents a description of the data set that is subsequently used for the empirical analysis. Afterwards, section 6 explains the applied methodology and interprets the results. This section closes with a critical assessment of the findings and the limitations of the applied analysis. Finally, a brief summary and concluding remarks are given. An illustrative overview of the elaboration is given in Appendix 1.

2 The Fundamentals of International Capital Markets

2.1 The Concept of Portfolio Theory

2.1.1 Portfolio Optimization

The most important work in the context of portfolio selection stems from Markowitz (1952). The focus of asset allocation is set on rational investors who seek to maximize their utility function. Thereby, investment decisions are solely based on two criteria: expected return and risk of the portfolio. Investors desire expected returns but regard the variance of returns as undesirable. As investors tend to avoid risk, they demand compensation in terms of returns, a so-called risk premium, for investing in risky assets. In order to control for risk, investors can diversify their portfolio, meaning to invest in a large variety of assets. In this way, the risk exposure to an individual security in the portfolio is lowered. In terms of risk, assets in the portfolio can offset each other and reduce the portfolio risk if the assets are less than perfectly correlated. The idiosyncratic risk, the firm-specific risk, of the assets can be eliminated with the naïve diversification strategy which leaves only the systematic risk of the assets.^[2]

The portfolio optimization process can be summarized in three steps. As a first step, the expected return and the standard deviation of all feasible portfolios are computed.^[3] For every level of expected portfolio return, the minimum variance is determined. All mean-variance optimal portfolios form the efficient frontier, implying that these portfolios offer the lowest variance for any target return and are superior to all other feasible portfolios. The second step involves the risk-free asset as it is the intercept of the capital allocation line (CAL). The CAL represents different mixtures of risky and risk-free assets. In this step, the weights of assets in the optimal portfolio of risky assets are derived. This is performed by determining the CAL which contacts the tangential portfolio on the efficient frontier. The Sharpe ratio examines the slope coefficient of the CAL and is a measure of risk-adjusted returns. The greater the Sharpe ratio, which means the steeper the CAL, the better is the risk-return relationship of the portfolio.^[4] Third, the investor selects the optimal risk-return portfolio on the CAL in accordance with his utility function by mixing the risky assets with the risk-free one.^[5]

The early work on portfolio diversification focuses solely on national markets. The trend of capital market liberalization raised the attention of researchers to extend their models and take the internationality of investments into consideration, which provides great potential for diversification. Thus, a brief overview of international portfolio selection is content of the next section.

2.1.2 International Diversification

The portfolio approach of Markowitz was transferred to the international context at the end of the 1960s. Assuming rational investors and identically distributed random returns, all investors should hold the same portfolio. However, investors living in different countries have different mean-variance efficient frontiers. As a result, the diversification potential varies depending on the home country of the investor.^[6]

A major issue arising in the international setting is the exposure to exchange rate fluctuations, which makes foreign investments more risky and is highly associated with estimation risk. Since the uncertainty of exchange rates is to a large extent non-diversifiable, the performance of international portfolios can be negatively affected. In order to capture the gains from international diversification, it is important to control for this uncertainty with hedging. Yet, it highly impedes the ex ante estimation of international returns because the differences between the actual returns and the historical returns, which serve as proxies for expected returns, could be severe. Thus, the gains from international diversification are only maximized under full information. For this reason, it is important that the efficient market hypothesis (EMH), presented in section 2.3.1, holds. In case of incomplete information, the costs of obtaining the information could be prohibitively high so that investors choose to deviate from the optimal international portfolio and prefer domestic assets. If the number of stocks in the portfolio is large, the estimation risk is high and the costs of estimation errors could exceed the marginal benefits of additional diversification. This is highly relevant for investors in large diversified economies with low levels of risk aversion. The study of Hasan and Simaan (2000) shows that the benefits of international diversification are less attractive for German and Japanese investors. Only U.S. investors with high levels of risk aversion regard international diversification strategies as superior to domestic portfolio strategies.^[7] Although the gains from international diversification are higher for small economies, their institutional barriers often hamper investors’ ability to invest in foreign assets.^[8]

The first studies of international diversification focus on ex post comparisons of risk and return characteristics of international portfolio strategies to pure national strategies. Regarding the methodology, these ex post studies identify efficient portfolios from a retro perspective, meaning that the actual realized returns and covariances are known. Leading the way, Grubel (1968) analyzes realized rates of return from investing in the major eleven industrialized equity markets from the U.S. perspective and found that diversification among these countries would result in higher rates of return.^[9] The benefits of international diversification are supported by a substantial body of research.^[10] The main opportunity of open capital markets is the variety of different risk-return combinations. The correlation between domestic and foreign asset returns is usually lower than the correlation of asset returns within the national market enhancing the gains from diversification. Yet, the correlation between domestic and foreign assets has to be carefully investigated as only assets with low correlations can offset each other in terms of risk.^[11]

All of these ex post studies simplify their analysis by assuming that future returns are, at least to some extent, predictable. By design, the studies failed to account for estimation risk. As a result, the findings have to be interpreted with caution. In this respect, it is much more interesting whether the benefits of international diversification are also evident on an ex ante level. Recent studies improved the methodology by estimating risk and returns on the basis of historical data. For instance, Eun and Resnick (1988) show that investors can benefit from unhedged international diversification strategies as long as estimation risk is adequately controlled for. Hedged international strategies, which additionally control for the exchange risk via the forward exchange market, performed extremely well.^[12] Contrary, Levy and Lim (1994) observe that unhedged international strategies outperformed hedged strategies, which they attributed to the biasedness of forward rates.^[13] Therefore, forwards can help to control for exchange rate risk but at the same time potentially lower the expected return. This underlines the complexity of international investment strategies. The implicit notion of all this empirical evidence is the superiority of international diversification strategies.

Remarkably, the majority of research focuses on the U.S. viewpoint while the perspective of non-U.S. investors is largely neglected. The German perspective, which is highly relevant for this thesis, is therefore outlined in greater detail in section 3.3. Subsequently, the financial framework on international capital markets is completed by introducing the concept of integration of capital markets and market efficiency.

2.2 Integration versus Segmentation of Capital Markets

In the context of international diversification, it is important to consider the integration of international markets. Generally, capital markets are described as integrated if identical assets are equally priced on these markets.^[14] This means that investors have identical expectations about the risk-return relationship of assets irrespective of the market. The growing integration of markets facilitates the acquisition of information about foreign stocks. As a result, investors attain a greater potential to diversify their stocks among different capital markets. Yet, the theoretical assumption of capital market integration does not correspond to the actual situation. Even though a complete segmentation can be ruled out as domestic returns correlate with foreign returns,^[15] the markets are perceived to be partially segmented into domestic markets which operate to some extent separately from each other. For instance, it is intuitive that the U.S. market is more efficient than emerging markets in terms of accounting standards and coverage of analysts and, hence, these markets cannot be deemed to be fully integrated. Legal as well as indirect barriers are the major impediments of international investments.^[16] The former category includes apparent constraints such as regulatory and monetary restrictions of foreign investments or transaction costs. Consequently, the variety of international investment opportunities is not uniform for investors from different countries. Alternatively, indirect barriers result from differences in culture, language or psychological aversion to foreign investment. The acquisition of information about foreign assets, differences in the financial reporting standards, and disclosure rules could hamper investors to hold foreign assets. In the light of indirect constraints, investors from different countries value identical investment opportunities differently. Knowing these international effects enables to get a clear picture of the complexity investors are confronted with when investing internationally.

2.3 The Concept of Market Efficiency

2.3.1 Operational and Informational Market Efficiency

A key role in finance plays the concept of market efficiency. It is primarily used to describe that all relevant information is impounded in stock prices. Besides this information-based aspect of market efficiency, it can also be referred to the operation of international capital markets. Operational market efficiency addresses the optimal microstructure of capital markets and reviews the resources employed to facilitate the market operations. Operationally efficient markets are liquid and bear only low costs of trading. Moreover, a fast execution of stock activities is feasible.^[17]

With regard to informational efficiency, the EMH states that markets are efficient if stock prices reflect all available information at any time.^[18] Hence, new information is impounded immediately into the stock prices and investors are not able to earn excess returns in the long-run. Even though stocks are fairly priced, each stock bears idiosyncratic risk which can only be eliminated by diversification and, thus, is not compensated by the market. Moreover, the task of portfolio management in efficient markets is to tailor the portfolios according to the preferences of investors rather than to outperform the market. This underlines the importance of the portfolio optimization presented above even in efficient markets.^[19]

In order to test market efficiency, “all available information” has to be unambiguously defined. Fama (1970) develops a classification on the basis of a categorization into three market efficiency forms. In the weak form, only past prices are reflected in the stock prices. A market is considered to be semi-strong efficient if historical prices and all publicly available information is impounded in the stock prices. Finally, the definition of “all available information” in the strong form includes past prices, public information as well as private information. This implies that investors cannot generate abnormal returns as stocks move randomly.^[20]

The level of market efficiency is highly relevant as it determines what information investors may use to predict future stock prices and earn abnormal returns.^[21] Thereby, information which is already reflected in the prices is not valuable. The predictability of stock returns indicates that the market is not fully efficient. Despite the lack of unanimity, empirical studies predominantly support the semi-strong form of market efficiency.^[22] As a result, only private information can be used to predict future stock returns because all other information is fully reflected in the stock prices and, hence, not value-enhancing. In the context of home bias and local asset pricing, the semi-strong efficiency form suggests that local as well as non-local investors cannot earn excess returns as long as private information does not come into play. But exactly this reasoning is viewed critically in the home bias literature. One rationale for the geographical investment preference rests upon information asymmetries between local and distant investors which are not necessarily associated with private information. Rather, the diffusion process of new released information is described as proceeding gradually, meaning that distant investors obtain the information to a later point in time as it was actually revealed and obvious to local investors.^[23]

Generally speaking, such deviations from market efficiency imply an inefficient resource allocation which could be burdensome for the overall economy. If mispriced, asset prices lose their guidance function and induce the wrong investment incentives.^[24] In the case of local asset pricing, it would result in a different asset valuation depending on the headquarters’ location of a company. These anomalies are also often referred to be the outcome of irrational decisions of investors. Behavioral finance deals with this issue in greater detail in the next section.

2.3.2 Market Efficiency and Behavioral Finance

Traditional finance theory assumes rational investors. However, this assumption is doubted by representatives of the behavioral finance approach.^[25] Irrationality can arise either from incorrect processing of information or from systematically suboptimal decision-making. This does not necessarily threat the EMH. If irrational investor decisions result in mispriced assets, arbitrageurs are expected to intervene and push the prices back to their fair level. In practice, the benefits of arbitrage are limited and, thus, there are no opportunities for easy profits.^[26] In sum, this suggests that if stocks are priced fairly, markets are efficient and no excess return opportunities exist. But if prices do not reflect the intrinsic value of the stocks, this absence of excess return opportunities does not necessarily mean that markets are efficient. In essence, the guidance function of stock prices is distorted which may result in a misallocation of resources. For this reason, it is extremely important to understand the interrelation of EMH and behavioral finance, which is not well documented in research yet.^[27]

With regard to the second premise of irrationality, systematically suboptimal decision-making, investors exhibit behavioral biases and make irrational risk-return trade-offs. Apart from a variety of biases defined in the finance literature, this thesis focuses on the geographical impact on investment decisions. The so-called home bias is a costly behavioral bias as the portfolios of these investors are, by design, underdiversifed and, hence, carry idiosyncratic risk. Looking at the underdiversification related to the employment income or real estate holdings, investors should virtually be encouraged to diversify at least their stock portfolio in order to compensate the risks arising from other underdiversifications. In reality, the picture looks quite different. The bias towards local stocks increases the dependency on the local area, which might hint at the irrationality of investors.^[28]

While the existence of this home bias is well established, the extent to which it influences asset pricing is not thoroughly researched yet.^[29] Thus, the subsequent sections provide an extensive overview of the bias and its implications on stock returns.

3 Home Bias and Local Bias in Equities

3.1 Definition of Home Bias and Local Bias

Despite the commonly accepted gains from international diversification, the portfolios of investors are often biased towards their home country. The preference for domestic assets, also known as domestic bias, infers the existence of other determinants in investors’ asset allocation decision than standard portfolio theory predicts. This observation is not limited to the setting of equity markets but also widely seen in international trade and consumption.^[30] With regard to equities, French and Poterba (1991) notably document that U.S. investors held approximately 94 percent of their portfolio domestically at the end of the 1980s.^[31] Such estimations violate the fundamentals of portfolio theory since the actual portfolios do not lie on the efficient frontier and, hence, bear idiosyncratic risk which is not rewarded by the market. Moreover, this seems to contradict the assumption of rational investors. This gap between theoretical portfolio models and the actual composition of investors’ portfolios has drawn a lot of attention in financial research. A substantial body of literature confirmed the existence of home bias,^[32] but in spite of a variety of explanation attempts, the underlying rationale remains puzzling. In the elaboration in section 3, stock prices are treated as exogenous. The implications on stock prices are in the focus of section 4.

In addition to home bias, recent evidence suggests a local bias in the national context, meaning that investors tend to overweight local securities compared to distant ones. According to Coval and Moskowitz (1999), the typical portfolio of the mutual fund managers in the U.S. comprises stocks of companies which are located between 160 and 184 kilometers closer to the manager’s office than the average U.S. company is.^[33] In other words, the average manager holds stocks that are around ten percent geographically closer than the average stock in his benchmark portfolio.^[34] This implies a significant geographic preference for local investments. Hong, Kubik and Stein (2005b) confirm these results with their finding that if a fund and a firm are located in the same Census division^[35], the fund increases the weight of the stock in his portfolio by eleven percent of its unconditional mean holdings.^[36] As these studies focus on institutional investors, Zhu (2002) and Ivković and Weisbenner (2005) observe an even stronger local bias for U.S. individual equity holders which can be explained by the higher financial sophistication of institutional investors.^[37] Turning to Europe, a significant preference for local firms in the Finnish market was documented by Grinblatt and Keloharju (2001) who state that the bias of individual investors towards local firms is significantly higher than of institutional investors. It is even shown that differences in financial sophistication within the individual investor class results in different levels of local bias.^[38]

In contrast to home bias, local bias allows researchers to differentiate the geographic effect from the national border effects. As discussed in the next section, institutional barriers among countries may only hamper international diversification but not diversification within a country. Understanding the existence of the unsolved international bias puzzle may also shed light on the local bias. It is perspicuous that both biases are positively correlated because financially sophisticated investors will diversify their portfolios nationally as well as internationally. With an extrapolation, Coval and Moskowitz (1999) show that the preference for geographically proximate investments and the relative scale of the world economy account for one third of the home bias puzzle. This underlines the relevance of geographic distance in the context of asset allocation despite decreasing transaction costs associated with technological advances in communication and transportation.^[39]

In order to grasp the complexity of the home and local bias puzzle, the next section introduces various explanation attempts.^[40]

3.2 Different Explanations to the Bias Puzzle

As so far no extensive research on local bias exists, this section will present different potential rationales for the existence of local bias with the help of the domestic bias literature. The different rationales of domestic bias can be summarized into two categories. The first category, which is considered in section 3.2.1 and 3.2.2, is based on national constraints associated with additional costs which hamper foreign investments. In contrast, the second category suggests that investors do not act completely rational when selecting their investments. Sections 3.2.3 to 3.2.5 introduce several lines of argumentation which question the rationality of investors.

3.2.1 National Barriers to International Investments

Initial attempts to resolve the international home bias puzzle were based on institutional constraints, such as monetary and regulatory constraints of capital markets, which explicitly limit investors’ ability to invest in foreign assets. Monetary boundaries are reflected in high transaction costs for investing abroad. Among others, transaction fees, costs of information acquisition and taxes are subsumed under these costs. Black (1974) develops a model of capital market equilibrium which incorporated barriers in the form of tax payments on foreign investment and demonstrated that optimal portfolios largely consist of domestic securities.^[41] Transaction costs are burdensome and lower the returns of foreign investments substantially.^[42] Regulatory impediments, ranging from capital controls to restricted supervision of the market, could hamper investors’ ability to invest in foreign assets and lead to partially segmented markets. The empirical model of Errunza and Losq (1985), which controls for legal restrictions imposed by governments, could tentatively support this mild segmentation.^[43] The explicit barriers limit investors’ choice and imply that gains from international diversification are to some extent absorbed by these deadweight costs.^[44] In contrast, Cooper and Kaplanis (1994) show that the level of deadweight costs necessary to generate the home bias is only feasible if investors have very high levels of risk tolerance.^[45] Moreover, Tesar and Werner (1995) argue that the observed high level of international trading activity does not go along with the hypothesis of prohibitive transaction costs.^[46] Although the barriers to international investments have fallen dramatically over the past decades, the propensity to invest in domestic stocks remains strong among investors.^[47] This lack of diversification and the magnitude of the evident home bias render this explanation approach almost obsolete.^[48]

All of the above presented barriers are explicit in the sense that they are observable and to a large extent quantifiable. This is not the case for implicit barriers. Even though these impediments are not visible, the negative impact on portfolio choice could be as severe as those of explicit barriers. For instance, political risk is inherent in foreign investments.^[49] While this risk is significantly higher for emerging countries than for developed ones, a global convergence of political risk can be observed.^[50] Moreover, cultural barriers between countries hamper international diversification. For instance, investors may experience difficulties in processing information in a foreign language. As a result, investors prefer to invest in domestic assets and exhibit home bias. It must be noted that these national boundaries are unique to the international setting and cannot account for the observed local bias within a country. Instead, this rather suggests that national constraints only amplify the effects of home bias but do not generate the bias itself.^[51] Other implicit barriers rest upon behavioral grounds and are discussed in more detail in the sections 3.2.3 to 3.2.5.

3.2.2 Hedging of Country-specific Risks

A need for hedging domestic risks may arise for several reasons. In the following three cases, domestic risk is hedged with domestic equity, which creates a domestic bias.

The first source of risk arises from domestic inflation risk. Based on the purchasing power parity^[52], all investors perceive the same real returns and no demand for hedging against inflation risk emerges. Deviations from the purchasing power parity, meaning that inflation rates can differ across countries, cause investors to alter their evaluation of returns and might generate a need to hedge inflation risk.^[53] Such deviation can stem from the violation of the law of one price^[54] or differences in the consumption of goods among investors.^[55] Advanced equilibrium models were developed, most notably those of Stulz (1981a) and Adler and Dumas (1983), which take the impact of the domestic inflation rate on portfolio allocation into consideration. The main result of these models is that investors become more risk-averse which increases the fraction of domestic assets in the portfolios.^[56] Yet, Uppal (1993), who additionally accounts for costs of transferring goods across countries, concludes that optimal portfolios are only biased if the risk aversion of investors is extraordinary low.^[57] Similarly, Cooper and Kaplanis (1994) find that home bias could only be explained with the rationale of inflation hedging if investors have very low levels of risk aversion and stock returns correlate negatively with domestic inflation.^[58] Therefore, domestic equities do not provide a proper hedge against inflation risk. The extent to which equities are concentrated in the home country cannot be entirely attributed to the desire of investors to hedge inflation risk.^[59]

A second explanation of home bias is derived from a hedging desire for non-tradable goods. Most of the wealth of the nation is comprised of goods which are not traded across financial markets, most important human capital. General equilibrium models were developed which incorporate this non-tradable component.^[60] A demand for hedging against these goods with home equities arises, which eventually leads to home biased portfolios. Even if the CAPM is not applicable for these wealth components as it presumes liquidity and tradability, Baxter and Jermann (1997) show theoretically and tested empirically that domestic human capital returns are significantly correlated with domestic stock market returns but not with foreign stock returns.^[61] Consequently, the evidence strongly suggests that investors should shorten their holdings in domestic equities and hold even more foreign stocks in their portfolio in order to hedge the domestic risk associated with non-tradable goods. With this proposition in mind, the home bias puzzle seems not to be solved but is even more striking.^[62]

Turning to the third rationale of hedging against domestic risks, it is argued that the international diversification potential can be mimicked to some extent by investing in domestic multinational companies.^[63] These firms have foreign operations depending on the foreign development and, hence, can provide investors with similar diversification gains as foreign equities. This home-made diversification is not uncontroversial. Rather, the betas of multinational companies with domestic market indices are close to one. This makes sense as large, multinational corporations are often included in domestic stock market indices. As a result, the diversification potential of multinational corporations is hardly better than that of other domestic equities. From the standpoint of portfolio theory, foreign assets with low correlation with the domestic market cannot be substituted by domestic multinational corporations stocks in investors’ portfolios without substantially reducing the diversification benefits.^[64]

Summarizing the presented explanations, none of them could explain the phenomenon of domestic bias sufficiently. In some cases, foreign equities instead of domestic equities would provide a better hedge against country-specific risk implying that the puzzle is even worse than supposed. This supports the proposition that national borders only amplify the effects and, hence, the explanation of domestic bias as well as local bias rests upon behavioral rationales as presented below.

3.2.3 Information Advantages of Local Investors

Recent literature predominately mentions information asymmetries between local and non-local investors as explanation for domestic and local bias. Generally, information asymmetries arise if different investors have different information levels about the same asset. In the context of this thesis, local investors enjoy easier access to relevant information about local firms since they can talk to employees or obtain information from the local media which normally covers local firms in great detail. Moreover, local investors might gain superior information from close personal ties to local executives. Their insider knowledge induces local investors to invest heavily in local assets. In this light, the gradual diffusion of information staggers investors in different investor groups according to their distance to the corporate headquarters. This, however, violates the informational market efficiency.^[65]

The existence of information asymmetries resulting from geographic distance is already acknowledged in different financial contexts as for instance in corporate acquisitions.^[66] Moreover, financial analysts are more accurate in their earnings forecasts of regional firms than distant analysts suggesting that local analysts exploit information advantages.^[67] Further, Hau (2001) demonstrates that information asymmetries across the trader population exist which are based on geographic proximity.^[68]

If most of the corporate activity takes place within the local region, the firms are less visible to non-local investors. Particularly, small and highly levered firms whose goods are primarily produced for the local market are less visible to non-local investors.^[69] For these companies, the information asymmetries between local and distant investors are even stronger. As a result, their information becomes more valuable to local investors. Related, Merton (1987) argues that the information transition process from the company to investors is associated with costs. Thus, the investor chooses to focus on specific stocks rather than following all publicly traded companies in order to minimize costs. In this way, he assumes “receiver set-up costs”^[70] only for the stocks he follows and achieves a better position to receive information from the respective companies. Thereby, the investor will most likely choose stocks with initial low costs. The acquisition of information about foreign investment is most likely associated with additional costs. The lack of knowledge about the foreign market hinders investors to assess the legal framework, accounting practices, and corporate environment and to derive proper investment ideas.^[71] As the information advantage for local investors often go along with lower initial costs of local stocks, the investor will eventually overweight local stocks in his portfolio. This will additionally reduce the estimation risk.^[72] Not only will the investor hold local stocks, but he will also trade them in accordance with the piece of information at his disposal and, hence, earn abnormal returns.^[73]

The impact of information asymmetries can be modeled with noisy rational expectations models, as proposed by Gehrig (1993) as well as Brennan and Cao (1997), showing that investors rationally favor domestic assets. Moreover, this evidence suggests that market anomalies, which are interpreted as market failures with traditional models such as the Capital Asset Pricing Model (CAPM), should rather be regarded as a “manifestation of the misspecification of the underlying theoretical model”^[74].^[75]

Further, information asymmetries can be measured by analyzing the performance of the local stocks. If local stocks earn excess returns in comparison with non-local investments, one can conjecture that locally biased investors exploit information advantages. Ivković and Weisbenner (2005) compare the local investments to the non-local investments of individual investors and confirmed that local stocks outperform non-local ones as investors exploit value-relevant information. Moreover, they concluded that mimicking these local investments can eliminate most of the information disadvantage of non-local investors and, hence, presents a useful investment strategy. The information asymmetries are most prevalent for less visible stocks which underlines that these companies are rarely followed by financial press and analysts. Yet, their results are to some extent striking as the low sophistication of individual investors would normally imply a lower ability to utilize valuable information compared to institutional investors. In contrast to the latter group, individual investors do not have the resources to exploit information professionally. However, the results of Ivković and Weisbenner (2005) question the superior skill of professional investment managers to diligently process and interpret information and suggest a high relevance of the information collection process, particularly the awareness of the availability of local value-relevant information. Accordingly, the information advantage does not differ significantly among the investor groups but depends on the location of the investor.^[76]

Several researchers are skeptical about the information-based rationale of home and local bias. For instance, Grinblatt and Keloharju (2001) as well as Zhu (2002) cannot demonstrate a superior performance of investors’ portfolios with high local bias compared to ones with less local bias. Further evidence against the superior information hypothesis can be derived from literature concerning investor response to earnings announcements. Under the assumption of information asymmetry, one would expect local investors to trade more and consistently with actual earnings. However, before earnings announcements, local investors cannot predict earnings better than distant investors.^[77]

In order to account sufficiently for home bias, information asymmetries require an extremely high reduction of domestic risk which is in many countries unrealistic.^[78] Thus, it is unlikely that information asymmetries can entirely solve the puzzle. This criticism demands the discussion of another behavioral home bias rationale in the next section.

3.2.4 Familiarity

In contrast to information asymmetry, Huberman (2001) explains the local bias through familiarity. By analyzing Regional Bell Operating Companies (RBOC), he showed that RBOC customers tend to hold stocks of their supplier RBOC rather than stocks of other RBOCs and, thus, prefer the familiar.^[79] This behavioral pattern, feeling comfortable with the familiar, is prevalent in most aspects of life. “People root for the home team, and feel comfortable investing their money in a business that is visible to them.”^[80] This implies that non-financial aspects such as language, culture or distance are driving the investor’s choice. Evidence for a language effect, for example, is provided by Grinblatt and Keloharju (2001) who demonstrate that Finnish-speaking investors favor Finnish-speaking firms and Swedish-speaking investors favor Swedish-speaking firms.^[81]

In particular, employees often choose to invest in the stock of their employers. In the U.S., around one third of the retirement savings are invested in company stock. Obviously, many employers offer incentive schemes and pension plans with stock participation for workers. Yet, employees also invest a substantial amount of their discretionary funds in stocks of the company which can be explained with familiarity. Moreover, employees tend to believe that they have a direct influence on the performance of the firm and, hence, can generate high returns.^[82]

People are usually better informed about the familiar rather than the unfamiliar as they might consume their products or be exposed to advertising.^[83] The critical point is that familiarity does not necessarily provide investors with value-relevant information. In essence, familiarity does not require local investors to have an information advantage. The hypothesis is rather based on asymmetric expectations.^[84] This potential information advantage could occur in different forms, ranging from actually possessing superior information to thinking that one will obtain superior information in the future. This actual or imagined information induces investors to spot buy as well as sell opportunities, depending on the content of the information, and trade accordingly. Nonetheless, it seems that local investors tend to have static buy-and-hold portfolios. This cannot be associated with exploiting superior information because local stocks are predominantly bought but rarely sold, which implies a low trading frequency.^[85]

Instead, “it reflects people’s tendency to be optimistic about and charitable toward what they feel affinity with – the comfortable and the familiar.”^[86] It seems intuitive that investors believe to be more competent and more optimistic about home, tantamount to familiar, assets and hold pessimistic expectations about foreign ones which tempt them to hold a familiar biased portfolio.^[87] Among others, Kilka and Weber (2000) support this proposition with their finding that German (U.S.) business students tend to have higher expected returns for German (U.S.) than for U.S. (German) stocks.^[88] Miller (1986) concludes that “for these investors stocks are usually more than just the abstract ‘bundles of returns’ of our economic models. Behind each holding may be a story of family business, family quarrels, legacies received, divorce settlements, and a host of other considerations almost totally irrelevant to our theories of portfolio selection. That we abstract from all these stories in building our models is not because the stories are uninteresting but because they may be too interesting and thereby distract us from the pervasive market forces that should be our principal concern.”^[89]

The familiarity hypothesis is not the only contribution to the domestic and local bias puzzle from behavioral finance. As can be seen subsequently, the asset allocation decision of investors may also be influenced by the trading patterns of other investors.

3.2.5 Social Interaction of Investors and Trading Patterns

This explanation attempt rests upon the general proposition that investors are influenced in their decisions by interactions with others. Such an influence can lead to herd behavior, meaning that investors converge in their behavior, or informational cascades, implying that investors ignore their private information signals and derive their investment decisions from the actions of others.^[90]

Through word-of-mouth communication with other investors, an investor can learn about the capital markets in general or about specific investment opportunities. For instance, he will learn more about the risk and return characteristics, the interaction of investors and the price mechanism on the stock market. Moreover, an investor may enjoy talking about the experiences in the stock market with his peer group who are fellow investors. Hong, Kubik and Stein (2004) analyze the impact of social interaction on stock market participation. According to them, social households, in terms of knowing the neighbors and attending church, have a four percent higher probability of investing in the stock market than less social households.^[91]

Transferring these findings to the local bias phenomenon implies that social interactions between local investors influence the trading patterns. This is reasonable because investors have easier access to information about local corporations. As a result, the participation costs are lower for this kind of assets.^[92] By talking to the peer group, other potential investors may get notice of the events on the stock market or fellow investors will adapt their trading patterns accordingly. Combined with potential information advantages, local investors may prefer to invest their assets locally. Eventually, the trading pattern of the investors will be aligned and result in a comovement in the portfolio holdings. Consequently, a comovement of local stock returns could emerge.^[93] Similarly to Hong, Kubik and Stein (2004), the empirical study of Feng and Seasholes (2004) in the Chinese market observes that groups of investors in the same region tend to buy and sell together and, thus, exhibit correlated trading patterns. Yet, their interpretation differs significantly from that of Hong, Kubik and Stein (2004). They rule out information diffusion theories as they estimate correlated trading behavior on a high frequency which do not allow diffusion. Rather they propose public information releases as the major driver of observed trading patterns.^[94]

This hypothesis of social interaction and correlated trading patterns cannot be unambiguously distinguished from the information-based hypothesis in section 3.2.3. The key difference is pronounced to lie in the channel of information gathering. Whereas information asymmetries arise in the context of information through local media and personal ties, behavioral convergence emerges mainly through word-of-mouth communication with other investors. Yet, these channels cannot be easily separated as both provide investors with value-relevant investment information. In essence, both channels of communication are similar in so far that investors derive their information ideas from sources physically nearby. The basic tenor of both explanation attempts is the gradual diffusion of information across the investor group. Moreover, Fellner and Maciejovsky (2003) argue that familiarity, the relative optimism as well as social interaction between investors might merely be concomitants of a social process, the psychological model of social identity.^[95] This underlines the complexity and interrelations of the different behavioral explanation attempts.^[96]

Summing up the different explanation approaches, the root cause of domestic and local bias cannot be easily determined. A clear cut between them is hardly possible suggesting that each of the approaches is contributing to the puzzle. The next section picks up the discussion about international diversification and home bias from the perspective of German investors.

3.3 Home Bias from a German Perspective

3.3.1 Benefits from International Diversification for German Investors

As the focus of the empirical study lies on the analysis of the German market, this section provides details about the literature on international diversification and home bias related to Germany. The German market offers an adequate framework for the subsequent empirical study since it is one of the major developed stock markets in the world but relatively rarely researched. Further, focusing on this market permits to exclude a potential influence of variations in regulation, currency, taxation or culture. Thus, the homogenous corporate environment within Germany builds a useful ground to isolate the geographical impact of home bias from the national-border effect. This allows eliminating national barriers of international investments as rationale for local bias. It must be noted that the local preference within the country is not proven for the German market yet. Notwithstanding this fact, it is presumable that the findings from Coval and Moskowitz (1999), Pirinsky and Wang (2006) and Grinblatt and Keloharju (2001) are applicable to the German market.

In order to assess the diversification potential, it is crucial to look at the correlation of German stock returns with returns from other countries. According to Szczecki (2002), Germany exhibits a high correlation with nearby countries such as France or the Netherlands, which is supported by the correlation of the DAX with indices from the European area as illustrated in Table 1.^[97] The correlation between German stock returns with returns of distant regions, as the U.S. or Asia, is relatively low. Overall, the correlation coefficients are clearly below one which implies that gains from international diversification exist.^[98]

Table 1: Correlation of the DAX with Major Stock Indices from 1997 to 2005

illustration not visible in this excerpt

Source: FactSet, own calculation

The benefits of international diversification for German investors have a variety of aspects. Tesar and Werner (1995) observe benefits in terms of expected returns for the time period from 1980 to 1990.^[99] Incorporating the currency hedging decision, the analysis of Bugár and Maurer (2002) confirm the potential for return enhancement. Additionally, a performance increase in terms of risk reduction could be shown.^[100] With regard to optimal diversification, their results put a maximum weight of 16.62 percent on domestic assets.^[101] Regardless of the level of risk aversion, the low allocation of German assets in optimal international portfolios is supported by several studies.^[102] An extreme view is represented by Gerke, Mager and Röhrs (2005) who conclude that a German investor could have optimized his portfolio during the time period from 1980 to 2001 by putting no weight on German assets. Based on the Sharpe ratio, all computed international portfolios and the international indices, Morgan Stanley Capital International (MSCI) World Index and MSCI Europe Index, outperformed the German market over the whole time period and no portfolio on the efficient frontier contained German assets.^[103] Szczecki (2002) shows that the overall proportion allocated to German stocks in the world market portfolio is less than ten percent.^[104] Less persuasive evidence for international diversification is contributed by the ex ante study of Maurer and Mertz (2000) who only observe benefits from international diversification strategies in combination with currency hedging as all other portfolio strategies were susceptible to estimation risk. Similarly, the results of Bugár and Maurer (2002) indicate that the benefits from international diversification are not unambiguous as the performance of international diversification strategies was not significantly improved compared to pure national strategies. Nonetheless, the majority of evidence showed that pure German portfolio strategies cannot line up against internationally diversified ones. A German investor could gain benefits from investing in international assets even after taking the estimation risk into account.^[105]

3.3.2 Actual Portfolio Holdings of German Investors

Contrary to the optimal portfolios strategies, German investors mainly disregarded the benefits of international diversification in the past. This can partially be attributed to regulatory constraints. For instance, German insurance companies and pension funds were obliged to match the majority of their domestic currency liabilities with domestic assets implying domestically biased portfolios.^[106] Another example is the old German tax credit method which privileged German shareholdings in comparison to foreign ones as only domestic dividends received a tax credit.^[107] Even if mutual funds, which are mostly exempt from regulation, are more diversified across countries, their portfolios are also strongly biased.^[108] Over all investor groups, 82 percent of the portfolios of German investors consisted of domestic assets in 1996.^[109] Yet, the strong reluctance diminished recently, which is emphasized by the augmenting proportion of foreign assets in German portfolios. From 1990, the fraction of foreign investments in portfolios of domestic institutional investors increased substantially from 20 percent to 70 percent in 2000. A comparable boost is also observable in the portfolios of individual investors.^[110]

With regard to correlation, Kilka (1998) demonstrates that German investors, if investing in foreign stocks, overweight stock from countries with high correlation and underweight securities from countries with low correlation.^[111] This implies that theoretical portfolio optimization models play only a subordinate role for German investors when investing in foreign stocks.

The evidence presented so far shows that, in spite of compelling gains from diversification, German investors choose to hold biased portfolios similar to investors of most other countries. This suggests that local bias is prevalent in Germany, with some initial evidence on domestic bias presented in this section. The subsequent section goes a step further and disentangles a potential impact of local bias on asset pricing.

4 Geographic Component of Asset Pricing

Asset pricing is influenced by a variety of determinants. The question arises whether the geographic location of a firm is one of these factors. Therefore, this section elaborates on the location of corporate headquarters and outlines the role of headquarters in economic theory. Subsequently, an analysis of geographical implications on stock returns tries to shed light on the interrelation of local bias and asset pricing and derive hypotheses for the empirical study.

4.1 Location of Corporate Headquarters

Turning first to the firm-level, this section provides determinants of the selection of the corporate headquarters’ location. The success of new firms during different stages of the life cycle is cited to depend also upon the location of the firm.^[112] Yet, the choice of location is a complex decision, which involves a variety of aspects. For the sake of brevity, only the major drivers of the corporate location decision are presented.

The corporate headquarters are usually close to the core business activities of a corporation. Hence, the headquarters’ location plays a key role in the communication between the firm and its different stakeholder groups ranging from investors over suppliers and service providers to customers.^[113] Further, “the headquarters location is still largely tied to such subjective factors as image, physical accessibility and the ever-intangible factor of quality of life”.^[114] Specifically, the corporate needs of the location are highly dependent on what divisions should be incorporated in the headquarters.^[115]

Executives might prefer to locate their corporation near to the sales market in order to be more responsive to changes in consumer needs. Concerning their production, firms have an interest to have a well-functioning supply chain, which is only partly dependent on geographical constraints. With regard to the region, also the economic conditions are highly relevant. This means that local economic shocks and migration plans of workers and consumers influence the operational activity of the business as well as the local service sector and the labor market.^[116] In this respect, it is also crucial what quality of life the region can provide for the employees. Similarly, the infrastructure and the transportation facilities as well as the legal and regulatory environment play an important role in the decision. With tax deductions, municipalities can convince firms to locate their headquarters within the region hoping to attract further business and to strengthen the corporate dominance of the region itself. For instance, German municipals freely set the trade tax via a collection rate and are further entitled to make exceptions.^[117]

Another crucial consideration involves the proximity to universities and scientists, which enhances knowledge spillovers. For instance, Audretsch and Feldman (1996) test the impact of geographic location on the innovative activity. Specifically, they established a link between geographic concentration of firms in an industry and the existence of knowledge externalities emphasizing the importance of geography and knowledge spillovers. Further, Audretsch and Stephan (1996) underline the key role of local scientists for the knowledge transfer between firms and scientists in the case of biotechnology firms. Recently, the positive impact of geographic proximity and academic research spillovers on firm performance was empirically proven.^[118]

The headquarters’ location is often different from the locations of production facilities. At first glance, this seems to cause heavy costs of intra-firm communication. Nonetheless, executives often prefer a physical separation.^[119] The advantages of this separation can be explained with two fundamental theories: the diversity of local service inputs and the scale of other headquarters nearby. These theories are explained in more detail in the next section.

[...]

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^[1] Cf. Pirinsky/Wang (2006), p. 1991.

^[2] Cf. Markowitz (1952), p. 77.

^[3] See Appendix 2 for the formulas of expected return and variance of the portfolio.

^[4] Cf. Sharpe (1994), p. 50.

^[5] Cf. Bodie/Kane/Marcus (2005), pp. 240-253.

^[6] Cf. Tesar/Werner (1995), p. 475; Hasan/Simaan (2000), p. 344.

^[7] Cf. Hasan/Simaan (2000), pp. 338, 347.

^[8] Cf. Eun/Resnick (1988), pp. 197-198; Eun/Resnick (1994), p. 140; Glassman/Riddick (1994), p. 86; Hasan/Simaan (2000), pp. 358-359.

^[9] Cf. Grubel (1968), pp. 1307-1308.

^[10] E.g. Levy/Sarnat (1970), pp. 668, 673; Lessard (1973), pp. 625-626; Lessard (1974), p. 390; Solnik (1974), pp. 500-501; Grauer/Hakansson (1987), p. 722; De Santis/Gerard (1997), pp. 1908-1909.

^[11] Cf. Lewis (1999), p. 577; Maurer/Mertz (2000), p. 423.

^[12] Cf. Eun/Resnick (1988), p. 211; Glen/Jorion (1993), pp. 1865, 1876.

^[13] Cf. Levy/Lim (1994), pp. 166-168.

^[14] Cf. Lewis (1999), p. 578.

^[15] Cf. Jorion/Schwartz (1986), p. 604; Lewis (1999), pp. 578-579; Szczecki (2002), pp. 102-103; Bodie/Kane/Marcus (2005), p. 372.

^[16] Cf. Jorion/Schwartz (1986), p. 604 classify market imperfections into these two categories.

^[17] Cf. Freund/Larrain/Pagano (1997), pp. 32-33; Dimson/Mussavian (1998), p. 91.

^[18] Cf. Fama (1970), p. 383.

^[19] Cf. Bodie/Kane/Marcus (2005), p. 380.

^[20] Cf. Fama (1970), p. 388.

^[21] Cf. Harris (2003), p. 229.

^[22] Cf. Fama (1970), pp. 409, 415; Fama (1991), pp. 1577, 1607. It must be noted that the event study methodology applied to test semi-strong efficiency is constraint to the adjustment of stock prices to one piece of information. By accumulating the evidence from individual tests, the model is validated. See also Fama (1970), p. 404.

^[23] Cf. Hong/Kubik/Stein (2005b), p. 2821. Section 3.2.3 reverts to this point in more detail.

^[24] Cf. Bodie/Kane/Marcus (2005), p. 381.

^[25] E.g. Barberis/Thaler (2003), pp. 1053-1054.

^[26] For a detailed elaboration on the limits of arbitrage see De Long et al. (1990), pp. 704-705; Shleifer/Vishny (1990), p. 148; Shleifer/Vishny (1997), p. 35.

^[27] Cf. Bodie/Kane/Marcus (2005), pp. 396, 400-401.

^[28] Cf. Anderson/Beracha (2006b), p. 6.

^[29] Cf. Stein (2005), p. 14.

^[30] Cf. Lewis (1999), p. 572; Obstfeld/Rogoff (2000), pp. 341-342.

^[31] Cf. French/Poterba (1991), p. 222.

^[32] E.g. Cooper/Kaplanis (1994), p. 46; Tesar/Werner (1995), p. 468; Lewis (1999), p. 572; Chan/Covrig/Ng (2005), p. 1509.

^[33] Cf. Coval/Moskowitz (1999), pp. 2047, 2056.

^[34] Cf. Coval/Moskowitz (1999), pp. 2047, 2056.

^[35] The U.S. Census Bureau classified the U.S. territory in nine Census divisions. For the register refer to http://www.census.gov/geo/www/us_regdiv.pdf, date retrieved 10.02.2007.

^[36] Cf. Hong/Kubik/Stein (2005b), p. 2812.

^[37] Cf. Zhu (2002), pp. 10-11, 19; Ivković/Weisbenner (2005), p. 276.

^[38] Cf. Grinblatt/Keloharju (2001), p. 1062.

^[39] Cf. Coval/Moskowitz (1999), pp. 2047, 2059; Zhu (2002), p. 13.

^[40] For the rest of this thesis, home bias is referred to domestic bias as well as local bias otherwise it will be explicitly noted.

^[41] Cf. Black (1974), p. 348. Later, Stulz (1981b) refined the model and yielded similar results, cf. Stulz (1981b), pp. 924-925.

^[42] Cf. French/Poterba (1991), p. 224; Kilka (1998), pp. 11-13; Huberman (2001), p. 662.

^[43] Cf. Errunza/Losq (1985), pp. 107, 120-121; see also cf. Eun/Janakiramanan (1986), p. 910.

^[44] Cf. Cooper/Kaplanis (1994), pp. 53-54; Lewis (1999), pp. 582-583.

^[45] Cf. Cooper/Kaplanis (1994), pp. 55, 57.

^[46] Cf. Tesar/Werner (1995), pp. 469, 479. Confirmed by Lewis (1999), p. 590. Warnock (2002) criticized that Tesar/Werner (1995) underestimated the U.S. holdings of foreign equities which generated an artificially high turnover rate. Nonetheless, he confirmed that transactions costs do not help to explain the home bias puzzle, cf. Warnock (2002), pp. 797, 802.

^[47] Cf. Tesar/Werner (1995), p. 479; Coval/Moskowitz (1999), p. 2045; Lewis (1999), pp. 583-584.

^[48] Cf. French/Poterba (1991), p. 222; Kang/Stulz (1997), p. 4.

^[49] Cf. Kang/Stulz (1997), pp. 6-7.

^[50] Cf. Diamonte/Liew/Stevens (1996), pp. 72, 74.

^[51] Cf. Coval/Moskowitz (1999), p. 2046.

^[52] The theorem of purchasing power parity holds that exchange rates are in equilibrium if the purchasing power is equal in two countries.

^[53] Cf. Adler/Dumas (1983), pp. 926, 929-934; see also Cooper/Kaplanis (1994), p. 46; Lewis (1999), pp. 579-580.

^[54] The law of one price states that if markets are efficient, an asset must have one single price no matter how it is created.

^[55] Cf. Kilka (1998), p. 14.

^[56] Cf. Stulz (1981a), p. 398; Adler/Dumas (1983), pp. 944-945; Uppal (1992), pp. 175, 178.

^[57] Cf. Uppal (1993), pp. 543-544; see also Uppal (1992), p. 180.

^[58] Cf. Cooper/Kaplanis (1994), p. 57.

^[59] Cf. Cooper/Kaplanis (1994), p. 52; Baxter/Jermann (1997), p. 170.

^[60] E.g. Eldor/Pines/Schwartz (1988), p. 166; Stockman/Dellas (1989), p. 272.

^[61] Cf. Baxter/Jermann (1997), pp. 171-174.

^[62] Cf. Baxter/Jermann (1997), pp. 178-179; Lewis (1999), pp. 581-582; see also Pesenti/van Wincoop (2002), pp. 39, 41.

^[63] Cf. Errunza/Hogan/Hung (1999), pp. 2076, 2086-2087; Rowland/Tesar (2004), pp. 808, 812.

^[64] Cf. Lewis (1999), p. 582.

^[65] Cf. Coval/Moskowitz (1999), p. 2046.

^[66] Cf. Kedia/Panchapagesan/Uysal (2005), p. 1.

^[67] Cf. Malloy (2005), p. 719; see also Orpurt (2004), p. 1.

^[68] Cf. Hau (2001), pp. 1978, 1980.

^[69] Cf. Coval/Moskowitz (1999), p. 2066.

^[70] Merton (1987), p. 489.

^[71] Cf. Lewis (1999), p. 584; see also Glassman/Riddick (1994), p. 88.

^[72] Cf. Kilka (1998), p. 17; Glassman/Riddick (2001), p. 38.

^[73] Cf. Merton (1987), pp. 488-490; Coval/Moskowitz (1999), pp. 2066-2067, 2070.

^[74] Gehrig (1993), p. 106.

^[75] Cf. Brennan/Cao (1997), pp. 1852-1853.

^[76] Cf. Ivković/Weisbenner (2005), pp. 278, 287, 304-305.

^[77] Cf. Grinblatt/Keloharju (2001), p. 1072; Zhu (2002), pp. 17, 21, 27-28; see also Hong/Kubik/Stein (2005b), p. 2803.

^[78] Cf. Jeske (2001), p. 36.

^[79] Cf. Huberman (2001), p. 671.

^[80] Huberman (2001), p. 659.

^[81] Cf. Grinblatt/Keloharju (2001), pp. 1054, 1062; see also Chan/Covrig/Ng (2005), pp. 1524-1525.

^[82] Cf. Benartzi (2001), pp. 1747, 1761-1762; Huberman (2001), p. 663; Oehler et al. (2005), p. 8.

^[83] The importance of advertising for the communication of information is pioneered by Nelson (1974) who observes that individuals are more likely to be exposed to advertising of local firms than of distant ones, cf. Nelson (1974), pp. 746-747; see also Zhu (2002), pp. 21-22.

^[84] Cf. Kilka/Weber (2000), p. 177; Zhu (2002), p. 16.

^[85] Cf. Huberman (2001), pp. 675-676; Lütje/Menkhoff (2004), pp. 9-10.

^[86] Huberman (2001), p. 676.

^[87] Cf. French/Poterba (1991), pp. 223, 225; Schiereck/Weber (2000), pp. 15-16; Goldberg/von Nitzsch (2001), p. 112; see also Goetzmann/Kumar (2003), pp. 22-23; Lütje/Menkhoff (2004), pp. 7-8 for support of the familiarity hypothesis. From a psychological perspective, this behavioral pattern can be explained with the overconfidence of investors, cf. Kottke (2005), p. 201.

^[88] Cf. Kilka/Weber (2000), pp. 181, 184; see also Shiller/Kon-Ya/Tsutsui (1991), p. 3; Strong/Xu (2003), pp. 309-311.

^[89] Miller (1986), p. S467.

^[90] Cf. Hirshleifer/Hong Teoh (2003), p. 26; see also pp. 27-29 for a detailed taxonomy of social learning and behavioral convergence.

^[91] Cf. Hong/Kubik/Stein (2004), pp. 139-140.

^[92] Cf. Hong/Kubik/Stein (2004), p. 162.

^[93] Cf. Pirinsky/Wang (2006), p. 1993.

^[94] Cf. Feng/Seasholes (2004), pp. 2120-2121, 2131.

^[95] Cf. Fellner/Maciejovsky (2003), p. 6.

^[96] Cf. Hong/Kubik/Stein (2005b), pp. 2802-2804, 2821.

^[97] The correlation coefficients are based on daily stock returns from January 1, 1997 to December 30, 2005. Thereby, the exchange rate is disregard.

^[98] Cf. Lapp (2001), pp. 40, 42; Szczecki (2002), pp. 164-165.

^[99] Cf. Tesar/Werner (1995), pp. 477-478.

^[100] Cf. Bugár/Maurer (2002), p. 180.

^[101] Cf. Bugár/Maurer (2002), p. 193.

^[102] Cf. Lapp (2001), p. 54; Szczecki (2002), pp. 167-168.

^[103] Cf. Gerke/Mager/Röhrs (2005), pp. 92-93, 95.

^[104] Cf. Szczecki (2002), p. 169.

^[105] Cf. Maurer/Mertz (2000), p. 437; Bugár/Maurer (2002), p. 190; see also Szczecki (2002), p. 181.

^[106] Cf. former § 54a parapraph 3 VAG, effective until January 1, 1999.

^[107] Recently, the European Court of Justice ruled that this tax credit violated the free movement of capital within the EU. Cf. Gordon (2007), p. 9.

^[108] Cf. Oehler et al. (2005), pp. 15-16.

^[109] Cf. Tesar/Werner (1995), pp. 484-485; Tesar/Werner (1998), p. 299.

^[110] Cf. Gerke/Mager/Röhrs (2005), pp. 86-87; Oehler et al. (2005), p. 17.

^[111] Cf. Kilka (1998), pp. 32-33.

^[112] Cf. Dodge/Fullerton/Robbins (1994), pp. 129-130.

^[113] Cf. Pirinsky/Wang (2006), p. 1994.

^[114] Barovick/Steele (2001), p. 359.

^[115] See Barovick/Steele (2001), pp. 359-362 for an extensive overview about what specific needs major divisions have regarding the side selection.

^[116] Cf. Davis/Henderson (2004), p. 11.

^[117] Cf. Brown et al. (1993), p. 208.

^[118] Cf. Audretsch/Feldman (1996), pp. 630-631; Audretsch/Stephan (1996), pp. 650-651; Audretsch/Lehmann (2006), p. 78.

^[119] Cf. Davis/Henderson (2004), pp. 2-3.