Our study examines the investment determinants of worldwide mutual funds from the perspective of economic geography. In particular, we investigate the local preferences of “impatient” mutual funds for specific countries. By analyzing a sample of 22,996 worldwide mutual funds over the period from 2005 to 2009, we demonstrate that impatient mutual funds are favorable to 1) large stock markets, 2) markets with a high level of protection for shareholders, 3) markets with familiar institutional practices, and 4) markets dominated by the presence of “strategic” investors as main shareholders of large listed companies.
Since June 2007, global finance has faced a crisis of great magnitude. The subprime financial crisis, initially regarded as a crisis of the US housing market, soon spread to the international financial system confirming the globalization of equity markets. If the globalization of stock markets and ICT (information and communication technologies) enable investors to invest in all markets, globalization does not prevent them from developing local strategies. Indeed if capital flows theoretically can be invested everywhere (global strategies), the distribution of capital flows in global markets reveals their concentration in some markets (financial centers) [
Generally, to understand several aspects of investor localization strategies, standard portfolio models are used but they present some limits. Indeed, according to these models, assets are purchased on the basis of investor analysis regarding the return and risk of these assets and the covariance of these returns with other financial assets in the investment portfolio [
In particular, we question the preference of mutual funds for some specific markets. Mutual funds are currently dominant in terms of assets managed on global stock markets because they reflect 75% of the financial assets of institutional investors. They are considered to be key actors in global stock markets because of their common expectations regarding standards of disclosure, transparency, and their requirements for shareholder value ( [
Our study focuses on the geographical location of assets managed by worldwide mutual funds and particularly on impatient mutual funds, that is, investors whose portfolio turnover is less than one year. These short-term investors, who are regularly identified by the economic and financial press and accused of favoring volatility in equity markets, often sell their stocks before companies have paid dividends and play on differences in stock prices to extract a short-term profit. In particular, we question the determinants of location of impatient mutual funds by focusing on two main questions: 1) where do impatient mutual funds invest internationally and 2) what are the local specificities of markets that are privileged when these investors internationalize their portfolios?
The article is organized into four sections. Section 2 introduces theoretical aspects of the importance of geography in global finance and reviews the importance of the institutional framework for understanding the investment behavior of mutual funds. Section 3 presents a sample of 22,996 worldwide mutual funds and the practical results of their global behavior on stock markets in 2009 and over the period from 2005 to 2009. Section 4 presents the methodology used to test the preference of impatient mutual funds for certain stock markets. In particular, we demonstrate that impatient mutual funds prefer investing in large stock markets characterized by the same legal tradition and presence of strategic investors in ownership structures.
We question if local specificity of capital markets can play a significant role in explaining the worldwide allocation of mutual fund portfolios. In particular, we make the assumption that the 6 geography (countries) and the institutional framework (legal regimes of countries and shareholder protection) are central elements for understanding the investment behavior of mutual funds. We thus refer to two fields of research to demonstrate the centrality of those two factors: the literature on the geography of finance and law and finance literature.
Our study contributes to a growing and recent literature on the economic importance of geography in understanding global finance ( [
As argued by Clark and Wójcik (2007) [
We refer to recent studies that highlight the importance of geography for understanding the investment behavior of worldwide mutual funds. In their 2001 study, Coval and Moskowitz [
If all these studies have highlighted the importance of geography in understanding mutual fund behavior on stock markets, very few have asked this question in relationship to the portfolio turnover of mutual funds. The oldest study is by Tesar (1995) [
Two recent studies have addressed these issues with two different approaches to the turnover. Dupuy, Lavigne, and Nicet-Chenaf (2010) [
In the vein of these previous works, we question the preference of mutual funds for certain stock markets (in particular, markets with the same legal origins as the investor’s own country).
The recognition that geography matters leads implicitly to the assertion that the institutional framework (laws and their enforcement) is central to understand the behavior of investors2. A large number of academic works have emphasized the importance of legal systems for understanding differences among countries in terms of stock market development, financing of companies, and standards of corporate governance ( [
against managers or controlling shareholders in the corporate decision process3. Common law countries afford the best legal protection to shareholders because they allow investors to vote by mail, never block shares before shareholder meetings, and require only a small share of capital to call an extraordinary shareholder meeting. Although common law countries protect investors better than countries with civil law traditions, German civil law and Scandinavian countries have the best quality of law enforcement, the French civil law system has the worst4. Similar to Shleifer and Vishny (1997), La Porta et al. (2000) and Dahlquist, Pinkowitz, Stulz, and Williamson (2003) [
Our study covers a sample of 22,996 international mutual funds investing in 35 countries6. Mutual funds are the largest category of institutional investors in financial markets, the major actors on international stock markets [
The data indicate that the mutual funds industry is geographically concentrated in two geographic areas (North America and Europe), which accounted for 89.19% of global funds in 2009. Over the period of analysis (2005-2009), which includes the US subprime crisis, there was a decline in the European share of mutual fund managers: whereas 29% of mutual funds came from Europe in 2005, the figure was only 23% in 2009, showing the decline of Europe as the origin of mutual funds. However, there was strong growth in the proportion of funds in two other geographical areas, Asia and Latin America: 2% of mutual funds were of Asian origin in 2005 against 4% in 2009, and 5% of investors were of Latin American origin in 2005 against 24% in 2009. As for the weight of the North American area, it remains very stable over the period and accounts for about 62% of all mutual funds (
At the country level, five countries (United States, United Kingdom, Canada, Germany, and France) account for 82% of the assets of the global mutual funds industry, again attesting to the high concentration of the sector.
If we now examine where mutual funds invest, in relation to their country of origin, it is difficult to observe a geographical diversification of their portfolios. Portfolio
Ranking in 2005 | 2005 | Ranking in 2009 | 2009 | |
---|---|---|---|---|
1 | United States | 61.6% | United States | 61.60% |
2 | United Kingdom | 12.5% | United Kingdom | 10.07% |
3 | Germany | 4.8% | Canada | 3.95% |
4 | Canada | 3.9% | Germany | 3.38% |
5 | Sweden | 2.6% | France | 2.98% |
6 | France | 2.4% | China | 2.55% |
7 | Japan | 1.8% | Japan | 1.99% |
8 | Switzerland | 1.4% | Sweden | 1.52% |
9 | Ireland | 1.0% | Switzerland | 1.50% |
10 | Belgium | 0.7% | Brazil | 1.41% |
11 | Bahamas | 0.7% | Hong Kong | 1.03% |
12 | Italy | 0.7% | Mexico | 0.92% |
13 | Singapore | 0.7% | Singapore | 0.85% |
14 | Netherlands | 0.6% | Netherlands | 0.49% |
15 | Hong Kong | 0.5% | India | 0.48% |
16 | India | 0.5% | Belgium | 0.47% |
17 | Spain | 0.4% | Bahamas | 0.46% |
18 | Denmark | 0.4% | Ireland | 0.46% |
19 | Norway | 0.3% | Australia | 0.41% |
20 | Luxembourg | 0.3% | Denmark | 0.39% |
Total | 100% | Total | 100% |
Source: Thomson one banker ownership, Thomson financial, 2009.
concentration, mimetic behavior, and home bias7 (i.e., high share of the total portfolio invested in domestic assets) are more appropriate strategies for mutual funds. Mutual funds invest as a priority in their own geographic area and especially when they originate from areas with well-developed financial markets (
For instance, North American funds invest 92% of their assets in North America and European funds invest 57% of their assets in Europe. For South American funds, the relative weakness of the capital invested in their domestic area can be explained by the proximity of the North American market.
When we turn to the analysis of where impatient mutual funds invest, we find the same configuration as in
Geographic areas | African MF | Asian MF | European MF | South American MF | North American MF |
---|---|---|---|---|---|
Africa | 25% | 0% | 0% | 0% | 0% |
Asia | 2% | 46% | 2% | 4% | 0% |
Europe | 31% | 18% | 57% | 28% | 7% |
Latin America | 1% | 1% | 5% | 24% | 1% |
North America | 41% | 34% | 36% | 44% | 92% |
Total | 100% | 100% | 100% | 100% | 100 |
Source: Thomson one banker ownership, Thomson financial, 2009.
address the question of home bias (i.e., the tendency of investors to invest heavily in domestic equity). Instead, we investigate what kind of country is selected by mutual funds, and especially by impatient mutual funds, when they decide to invest abroad.
We now test the following two propositions: that 1) geographical and institutional origin of countries influence mutual fund choices of location and 2) some countries have characteristics that make them more attractive to impatient mutual funds (in particular the presence of strategic investors in the ownership structures of companies).
These propositions are first tested with two control variables: the market capitalization of countries and the size of mutual fund assets portfolios.
In our empirical study we question whether some countries attract more impatient investors and why. We then investigate what kind of criteria (geographical and institutional) can explain the presence of impatient mutual funds in some specific markets. In the econometric analysis we consider the US market as a localization reference and we question the investment behaviors of worldwide mutual funds.
The empirical analysis involves two steps. First, we question the degree of relationship among investor portfolio turnover, their choices of location in 35 countries8, and their portfolio size considered as a control variable (portfolio size is labelled EQUITY ASSET). The aim is to question if some markets are preferred by impatient mutual funds and to determine what the characteristics of these markets are. We tested whether the choice of location of investment may be influenced by geographical and institutional variables.
In a baseline model, we analyze the relationship between the portfolio turnover of investors and two variables: 1) the variable EQUITY ASSET and 2) the variable MARKETSIZE, which is the host country’s market capitalization. For the latter variable we postulate a positive relationship between market size and a strong presence of impatient investors. In the vein of the CAP model, the idea is that large markets are more liquid and enable reducing some risks (uncertainty and illiquidity). We control investor preference for these two variables and we step-by-step introduce three independent variables: a) the presence of strategic entities in ownership structures of companies9: with this variable labelled STRATEGIC we postulate a positive relationship between the presence of impatient investors and that of strategic investors as underlined by [
We extract two variables from the Thomson financial database: the amount of financial assets managed by mutual funds (EQUITY ASSET) and their portfolio turnover level (high, moderate, and low)10. To include these qualitative variables in our empirical study, we consolidate the three levels of turnover (high, moderate, and low) into a single type of variable to enable a binary encoding11: HIGH against NOT HIGH. If a mutual fund’s turnover is high the variable takes a value of one and in all other cases (low and moderate turnover) the variable takes a value of zero.
The variable HIGH refers to impatient mutual funds, that is, mutual funds with a high portfolio turnover. Inversely, investors with a low or moderate turnover are called patient investors.
Regarding the methodology and the data analysis, we use a binary probit model to test the probability that a country i rather a country j receive an investment from an impatient mutual fund. The sample consists of j mutual funds indexed by j = 1, ・・・, 22,996 and where index i represents the country (i = 1, ・・・, 35) in which mutual funds invest. Estimations are made for the year 200912.
We thus consider Yi , a dependent ε [1,N]):
Yi = 1 if the condition “have a high turnover” is true for mutual funds j investing in country i
Yi = 0 if the condition “have a turnover different from high” is true for mutual funds j investing in country i
With the probit model regression, we assess the probability of occurrence of the event “have a high turnover” considering two dependent variables (xi: the host country i and x2: equity asset).
We also propose a second binary probit model to test the probability that a country i rather a country j receive an investment from a patient investor. We thus consider Yi, dependent variable, coded (0,1) and associated with these events ε [1,N]):
Yi = 1 if the event “have a low turnover” occurs for mutual funds j investing in country i
Yi = 0 if the event “have a turnover different from low” occurs for mutual funds j investing in country i
We assess the probability of occurrence of the event “have a low turnover” considering the same two dependent variables (xi: the host country i and x2: equity asset). The models are estimated by the maximum likelihood method using the US market as a reference. The results with the dependent variable high are presented in
In
dy/dx is for discrete change of dummy from 0 to 1 The estimation shows that there are two types of investor strategies in relation to the US market: investment is less likely to come from an impatient mutual fund than from a patient mutual fund for the following countries: Australia, Canada, China, Denmark, Greece, Ireland, Japan, Korea, Mexico, Norway, Portugal, South Africa, and Taiwan. Conversely, investment is more likely to come from an impatient mutual fund than from a patient mutual fund for the following countries: Argentina, Austria, Belgium, Brazil, Finland, India, Italy, the Netherlands, Sweden, Thailand, and the United Kingdom.
Globally, we can underline that countries with significant negative elasticities (Australia, Canada, China, Taiwan, Japan, Korea, Mexico and Taiwan,) are countries where impatient mutual funds do not prefer investing and countries with significant positive elasticities (Austria, Belgium, Italy, Finland, and the Netherlands) are countries where they prefer investing. It is not possible to conclude for the specific case of France, Germany, or Switzerland because their elasticities are not significant.
At this stage, if certain countries seem to be privileged destinations for impatient mutual funds, the model does not say why. The study now proposes to deepen our understanding of this preference for certain markets.
Although we can highlight preferences of impatient mutual funds for some specific host
Number of observations = 22,996 | Iterations completed = 5 | ||
---|---|---|---|
Log likelihood function = −13,314.27 | Degrees of freedom = 35 | ||
Chi squared = 1277.76 | Pseudo R-squared = 0.0458 | ||
Prob[ChiSqd > value] = 0.000000 | |||
Variables | Marginal Effects | z | P[Z/>z] |
Equity Asset | 0.00003 | 8.44 | 0.000 |
Argentina | 0.2288 | 2.70 | 0.007 |
Brazil | 0.1717 | 18.25 | 0.000 |
Thailand | 0.0989 | 4.44 | 0.000 |
Italy | 0.0683 | 5.78 | 0.000 |
Austria | 0.0544 | 4.40 | 0.000 |
India | 0.0473 | 3.72 | 0.0000 |
Finland | 0.0462 | 4.43 | 0.000 |
United Kingdom | 0.0424 | 5.38 | 0.000 |
Netherlands | 0.0336 | 3.51 | 0.000 |
Sweden | 0.0237 | 2.15 | 0.031 |
Belgium | 0.0232 | 2.37 | 0.018 |
Japan | −0.0703 | −8.14 | 0.000 |
China | −0.0661 | −6.11 | 0.000 |
Australia | −0.0616 | −6.57 | 0.000 |
Taiwan | −0.0574 | −4.74 | 0.000 |
Ireland | −0.0536 | −6.57 | 0.000 |
Greece | −0.0449 | −3.71 | 0.000 |
Canada | −0.0441 | −6.12 | 0.000 |
Norway | −0.0409 | −3.54 | 0.000 |
South Africa | −0.0408 | −3.24 | 0.001 |
Korea | −0.0353 | −2.70 | 0.007 |
Denmark | −0.0349 | −2.99 | 0.003 |
Portugal | −0.0251 | −2.03 | 0.043 |
Mexico | −0.0222 | −1.71 | 0.087 |
Spain | −0.0129 | −1.31 | 0.192 |
Indonesia | −0.0241 | −1.21 | 0.225 |
France | −0.0163 | −1.51 | 0.131 |
Honk Kong | 0.0147 | 1.25 | 0.212 |
Luxembourg | −0.0087 | −1.10 | 0.272 |
Chile | −0.085 | −0.45 | 0.650 |
Germany | −0.0065 | −0.61 | 0.545 |
Singapore | −0.010 | −0.95 | 0.342 |
Switzerland | 0.0004 | 0.05 | 0.957 |
Russia | −00153 | −1.13 | 0.260 |
In the grayed parts, variables are not significant.
countries, the previous model tells us little about the determinants of this location. We now make the assumption that these location strategies may be determined by four variables that we have constructed in our database: 1) the size of the markets (measured by market capitalization) that we label MARKETSIZE; 2) the percentage of capitalization held by strategic entities labelled STRATEGIC; 3) the difference between the origin of the legal system in the investor domestic market and host countries, labelled LEGAL ORIGIN OF LAW; and 4) shareholder protection measured by the level of anti-director rights, labelled SHAREHOLDER.
By introducing capital market size in our analysis we assume that market capitalization offers the liquidity necessary for the strategies of impatient mutual funds. The size of markets is next considered as a control variable in our baseline model.
To consider the influence of the host country’s size on the choice of location of mutual funds, we construct four qualitative variables: MARKETSIZE intermediate, MARK- ETSIZE large, MARKETSIZE small, and MARKETSIZE all. MARKETSIZE large is used when mutual funds invest only in large markets13, MARKETSIZE small is used when they invest only in small markets and MARKETSIZE intermediate when mutual funds invest only in intermediate markets. MARKETSIZE all is our benchmark and refers to cases in which mutual funds can invest in all kinds of markets (see
Dahlquist et al. (2003 [
To introduce differentiated strategies of mutual funds according to the presence (or not) of strategic entities in the capital of large listed companies, we created three qualitative variables: STRATEGIC all, STRATEGIC strong, and STRATEGIC few. STRA- TEGIC strong is used when mutual funds invest only in markets with a strong presence of strategic investors14; STRATEGIC few designates cases in which mutual funds invest only in markets with few strategic investors; STRATEGIC all is our benchmark and occurs when mutual funds invest in both kinds of market15.
We also include the variable SHAREHOLDER, which is the anti-director index (ranging from 0 to 6). It measures how strongly the legal system favors minority share-
Number of observations = 22,996 Time period 2009 Pseudo R2 = 0.049 LR Chi Squared = 146.04*** Log Likelihood function −14,809.793 | ||
---|---|---|
Independent Variables | Standardized coeff. | Marginal effects (dy/dx) |
Equity Asset | 0.103*** (7.12) | 0.0000157*** (7.14) |
Marketsizesmall | −0.072*** (−6.37) | −0.088*** (−6.13) |
Marketsizeintermediate | −0.057*** (−4.51) | −0.064*** (−4.76) |
Marketsizelarge | 0.053*** (6.11) | 0.045*** (6.25) |
Number of observations = 24,529 Time Period 2005 Pseudo R2 = 0.066 LR Chi Squared = 197.10*** Log Likelihood function −14,784.264 | ||
---|---|---|
Variables | Standardized coeff. | Marginal effects (dy/dx) |
Equity Asset | 1.00*** (7.87) | 0.0000378*** (7.94) |
Marketsizesmall | −1.478** (−6.23) | −0.085*** (−5.93) |
Marketsizeintermediate | −0.722*** (−6.14) | −0.063*** (−4.80) |
Marketsizelarge | 0.796*** (4.48) | 0.045*** (6.32) |
p-value: *p < 0.10; **p < 0.5; ***p < 0.01. Note: values in parentheses are z-statistic. Note: dy/dx is to discrete change of dummy variable from 0 to 1.
p-value: *p < 0.10; **p < 0.5; ***p < 0.01. Note: values in parentheses are z-statistic. Note: dy/dx is to discrete change of dummy variable from 0 to 1.
North America | Australia | South Africa | Europe | Asia | |
---|---|---|---|---|---|
Institutional investors | 60.20% | 56.84% | 52.53% | 44.33% | 39.39% |
Strategic entities | 39.98% | 43.16% | 47.47% | 55.67% | 60.63% |
Source: Thomson one Banker Ownership, Thomson Financial, 2009.
holders against managers or dominant shareholders in the corporate decision-making process. We consider two cases: when 1) mutual funds invest in a country where the index value is between 0 and 2.5 and 2) mutual funds invest in a country where the index value is higher than 2.5. If the share of investments is realized in countries where the index value is low (i.e., weak protection), the variable SHAREHOLDER takes the value zero and one in the other cases. The variable SHAREHOLDER enables us to measure the tendency of mutual funds to prefer countries where the level of shareholder protection is high.
Finally, the variable LEGAL ORIGIN measures the institutional distance between the host country and the domestic countries of investors. We consider two cases: when 1) mutual funds invest in markets where the legal regime is the same as the regime of law of its domestic country and 2) mutual funds invest in markets where the legal regime is different from its country of origin. If the share of investments in countries where the legal origin is the same as the mutual fund country and is superior to 50%, the variable takes the value one and zero in the other cases. With the variable LEGAL ORIGIN, we measure the tendency of mutual funds to prefer investments in countries where the legal regime is the same as the legal origin of their own countries.
With these new variables, we again consider Yi, dependent variable, coded (1,0) and associated with these events ε [1,N]):
Yi = 1 if the event “have a high turnover” occurs for mutual funds j investing in market i
Yi = 0 if the event “have a turnover different from high” occurs for mutual funds j investing in market i
With this probit model we assess the probability of occurrence of the event “have a high turnover” considering five dependent variables (equity assets of mutual funds, market capitalization of host countries, presence of strategic investors, differences regarding legal origin, and level of anti-director rights). We use this second binary probit model to test the probability that an impatient mutual fund j rather than a patient mutual fund will invest in markets categorized by the five variables (see
In the baseline model, each variable (excluding STRATEGIC few) has a significant coefficient. This probit model shows that being an impatient mutual fund rather than a patient mutual fund increases the probability of preferring to invest in markets with a
Number of observations = 22,996 Time period: 2009 | |||
---|---|---|---|
Variables | Standardized coeff. (2) | Standardized coeff. (3) | Standardized coeff. (4) |
Equity Asset | 0.102*** (7.06) | 0.102*** (7.05) | 0.099*** (6.860) |
Marketsizesmall | −0.068*** (−5.87) | −0.066*** (−5.67) | −0.074*** (−6.28) |
Marketsizeintermediate | −0.05*** (−4.24) | −0.050*** (−4.23) | −0.049*** (−4.14) |
Marketsizelarge | 0.062*** (5.10) | 0.062*** (5.08) | 0.057*** (4.67) |
Strategic Investorsstrong | 0.025*** (2.08) | 0.029*** (3.21) | 0.028*** (3.09) |
Strategic Investorsfew | 0.004 (0.36) | 0.004 (0.35) | 0.002 (0.20) |
Shareholder protection | - | −0.031*** (−3.67) | −0.038*** (−4.35) |
Institutional distance | - | - | 0.031*** (3.64) |
Statistics | Pseudo R2 = 0.052 LR c2 = 154.36*** Log Lik. Funct −14805.633 | Pseudo R2 = 0.056 LR c2 = 167.85 Log Lik funct −14798.838 | Pseudo R2 = 0.057 LR c2 = 186.95 Log Lik. funct −14789.342 |
p-value: *p < 0.10; **p < 0.5; ***p < 0.01. Note: values in parentheses are z-statistic. Note: dy/dx is to discrete change of dummy variable from 0 to 1.
strong presence of strategic investors (STRATEGIC strong has a positive significant coefficient). However, impatient investors are indifferent to the weak presence of strategic investors (the coefficient STRATEGIC few is not significant). The model also shows that being an impatient mutual fund 21 rather than a patient mutual fund increases the probability of preferring large stock markets (MARKETSIZE large has a positive significant coefficient), and being an impatient mutual fund rather than a patient mutual fund decreases the probability of preferring small and intermediary stock markets (MACA intermediate and MACA small have significant but negative coefficients). With the variable LEGAL ORIGIN we find that impatient funds prefer markets where they understand the legal system (LEGAL ORIGIN has a positive and significant coefficient). Last, with the variable SHAREHOLDER we highlight that being an impatient mutual fund rather a patient one decreases the probability of preferring a market with weak shareholder protection (the variable SHAREHOLDER has a significant but negative coefficient). We now turn to a ranking of mutual fund investment criteria (see
Marginal effects (
The data of this paper cover the period before the subprime crisis (start 2005) and the year when the effects of the crisis start (beginning of the year 2009). Before the subprime crisis and in early 2009, mutual funds prefer to invest in large stock markets and markets with a high protection of shareholders. The collapse of international lending markets has shown the retraction of investors from international markets to the advantage of domestic markets and less risky markets ( [
Dependent Variables | Marginal effects-dy/dx (2a) | Marginal effects-dy/dx (2b) | Marginal effects-dy/dx (2c) |
---|---|---|---|
Equity Asset | 0.0000156*** (7.07) | 0.0000155*** (7.07) | 0.00001*** (6.87) |
Marketsizesmall | −0.083*** (−5.66) | −0.080*** (−5.47) | −0.090*** (−6.04) |
Marketsizeintermediate | −0.010*** (−4.46) | −0.060*** (−4.46) | −0.059*** (−4.36) |
Marketsizelarge | 0.0493*** (5.23) | 0.0491*** (5.21) | 0.045*** (4.78) |
Strategic Investorsstrong | 0.027*** (2.77) | 0.031*** (3.17) | 0.030*** (3.05) |
Strategic Investorsfew | 0.0040 (0.37) | 0.003 (0.35) | 0.002 (0.20) |
Shareholder protection | - | −0.038*** (−3.78) | −0.038*** (−3.75) |
Institutional distance | - | - | 0.026*** (4.35) |
p-value: *p < 0.10; **p < 0.5; ***p < 0.01. Note: values in parentheses are z-statistic. Note: dy/dx is to discrete change of dummy variable from 0 to 1.
returns, investors have invested more on proximate markets, the most liquid markets (the largest ones) and markets with the highest protection for shareholders. Results obtained in this paper should therefore be robust and even stronger after the subprime crisis.
Our findings contribute to a growing literature on the importance of geography to the study of global finance. We demonstrate that geography and the institutional frameworks of countries are two factors that help understand the way mutual funds, and in particular impatient mutual funds, select the countries in which to invest. More generally this study provides new insights into the mutual fund industry and offers evidence of mutual fund tendency (with a focus on impatient mutual funds) to select stocks in specific countries. First, despite financial globalization, the global mutual fund industry remains very focused on two geographical areas and five countries, all characterized by developed financial markets. Second, mutual funds prefer investing in nearby markets provided mutual funds come from countries where financial markets are developed. Third, some countries attract more impatient mutual funds than others: this is mostly the case in countries whose legal systems are based on the Anglo-Saxon model. Inversely, impatient mutual funds are under-represented in some countries (essentially countries following the European continental model). Finally, impatient mutual funds are comfortable with large stock markets, markets with a high level of protection for shareholders, and markets with an institutional proximity. More surprisingly, impatient mutual funds have a preference for companies with strategic investors (family owners, the state, etc.) as dominant shareholders of large listed companies. In markets with a strong presence of strategic investors, closed ownership structures promote higher volatility in market prices, which attract impatient mutual funds. Our study validates and completes the results of [
Dupuy, C., Lavigne, S. and Nicet-Chenaf, D. (2016) Where Do “Impatient” Mutual Funds Invest? A Special Attraction for Large Proximate Markets and Companies with Strategic Investors. Journal of Mathematical Finance, 6, 502-523. http://dx.doi.org/10.4236/jmf.2016.64040