دانلود مقاله ISI انگلیسی شماره 15721
عنوان فارسی مقاله

سطح مقطع عملکرد صندوق سرمایه گذاری مشترک در بازارهای سهام اروپا

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
15721 2013 28 صفحه PDF سفارش دهید محاسبه نشده
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عنوان انگلیسی
The cross section of conditional mutual fund performance in European stock markets
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Journal of Financial Economics, Volume 108, Issue 3, June 2013, Pages 699–726

کلمات کلیدی
بازارهای سهام در اروپا - عملکرد صندوق سرمایه گذاری مشترک - فرصت های سرمایه گذاری متغیر با زمان -
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پیش نمایش مقاله سطح مقطع عملکرد صندوق سرمایه گذاری مشترک در بازارهای سهام اروپا

چکیده انگلیسی

This paper implements strategies that use macroeconomic variables to select European equity mutual funds, including Pan-European, country, and sector funds. We find that several macro-variables are useful in locating funds with future outperformance and that country-specific mutual funds provide the best opportunities for fund rotation strategies using macroeconomic information. Specifically, our baseline long-only strategies that exploit time-varying predictability provide four-factor alphas of 12–13% per year over the 1993–2008 period. Our study provides new evidence on the skills of local versus Pan-European asset managers, as well as how macroeconomic information can be used to locate and time these local fund manager skills.

مقدمه انگلیسی

A vast literature focuses on the predictability of U.S. and international stock returns using macroeconomic variables, such as the short government interest rate or the yield spread between defaultable and government bonds. For instance, Ferson and Harvey (1993) find that returns on international stock indexes are predictable using macroeconomic indicators as conditioning variables. More strikingly, Ferson and Harvey (1999) find that broad economic variables explain the cross-sectional variation in U.S. individual stock returns better than the Fama and French (1993) empirical factors. Avramov and Chordia (2006) extend this literature by showing that substantial alphas are derived from choosing individual stocks based on macroeconomic conditioning variables. These papers, as well as numerous others in the academic literature, indicate that substantial gains in portfolio choice can be obtained from the use of macroeconomic information. Other literature examines whether asset managers or sell-side analysts are better able to collect private information on equities of corporations in their geographic area. For instance, Coval and Moskowitz (1999) find that fund managers are better able to select stocks of firms headquartered nearby, and Cohen, Frazzini, and Malloy (2008) find that fund managers with past educational ties to corporate managers overweight and outperform in the stocks of those corporations. This literature suggests that geographic proximity or social networks, or both, can aid the transfer of private information. Further, Sonney (2009) finds that European sell-side analysts with a country specialization outperform analysts with an industry specialization, suggesting that an understanding of local product markets is crucial to analyzing stock valuation. Together, these two seemingly unrelated bodies of research suggest that professional asset managers could be better able to choose local stocks under certain macroeconomic conditions. For instance, during the recent financial crisis, active UK asset managers could be expected to be valuable because of their ties to London financial institutions, in the face of large asymmetric information on the value of banking stocks. During the technology collapse, investors could prefer active Scandinavian managers with a specialized knowledge of local telecommunication companies, who could help to sort out which firms might recover most quickly. In essence, macroeconomic information can help to indicate when local skills are most needed in a particular market. Hence, a rotation among asset managers with local expertise as macroeconomic conditions evolve could outperform strategies involving either local expertise or macro-indicators alone to choose active managers. This paper brings these issues to a unique data set that contains the monthly returns of European-domiciled equity mutual fund managers over a 20-year period. Specifically, we ask whether an investor can outperform when she has access to country-specific managers across several developed European markets and is allowed to rotate the portfolio allocation among the countries (and managers) as macroeconomic conditions in Europe evolve. If such a strategy does result in outperformance, we wish to know which country's local equity managers exhibit the best skills during a particular phase of the European business cycle. To address these points, we explore whether, under some macroeconomic conditions, a multi-country fund (i.e., a Pan-European fund) should be chosen due to its ability to time various countries and sectors (perhaps itself using macroeconomic information) or to provide lower-cost diversification. Conversely, we ask whether a country or regional fund should sometimes be chosen due to its greater knowledge of industries or stocks in its local geographic area. Our study has significant real-world economic implications. European funds grew from a little over $3 trillion during 2000 to nearly $9 trillion during 2007. By the end of 2007, the European industry amounted to nearly three-quarters of the size of the U.S. mutual fund industry, which, over the same period, grew from $7 trillion to $12 trillion. Further, there were more than 35 thousand European-domiciled mutual funds by the end of 2010 (Investment Company Institute, 2011), almost five times the number of U.S.-domiciled funds, indicating that the European market is highly fragmented. Clearly, European investors have a confusing array of decisions to make in choosing their stock portfolio managers, including country allocations, sector allocations, and Pan-European versus individual country funds. Despite the economic significance and fragmentation of the European mutual fund industry, European-domiciled funds remain very much an under-researched area. Some studies have been conducted at the individual country level, e.g., for funds that invest in the UK, Germany, Italy, or France, or some combination of these countries. One such widely known study is Otten and Bams (2002). However, no comprehensive study has simultaneously examined the performance of stock funds that invest across Europe (Pan-European funds), funds that invest in specific countries or regions (e.g., Germany or Scandinavia), and funds that invest in specific sectors (e.g., telecommunications) over a long time period that includes the integration of European financial markets of the past 20 years. This gap is an important omission, because investors in any European country find it increasingly easy and inexpensive to invest in mutual funds incorporated in other countries as a result of this market integration and the adoption (by many developed European countries) of the common euro currency. We focus on the dynamics of active management skills and how an investor might optimally choose active funds during varying business conditions. Building on studies such as Avramov and Wermers (2006) and Moskowitz (2000), we allow for the possibility of time-varying mutual fund alphas and betas among active managers in Europe. Following Christopherson, Ferson and Glassman (1998) and Ferson and Schadt (1996), we model such time variation using a publicly available set of conditioning state variables. Thus, another of the objectives of our study is to explore which, if any, macroeconomic state variables are helpful in identifying funds with superior future skills in selecting European equities. We first construct Pan-European size, book-to-market, and momentum risk factors for stocks. Then, we report on the average performance of European mutual funds over our time period using these benchmarks. Our findings are similar to those of many studies of U.S. mutual funds (e.g., Carhart, 1997 and Wermers, 2000). Specifically, the median one-factor and four-factor alphas are −0.90% per year and −0.32% per year, respectively. This finding indicates that our benchmarks successfully control for common variation in European equity mutual fund returns. We next move to our main contribution, which is to determine whether a European investor can actively select Pan-European, regional, country, and sector funds with persistent performance, relative to our European risk factors, and, if so, to identify how macroeconomic information helps to improve the selection of these funds. Given the modest costs of trading most open-ended mutual funds, such a strategy would be attractive to a large population of investors in European funds if it is successful. By including funds whose investment objectives focus on a particular region or sector, as well as funds that invest in the entire European region, we allow our strategies to generate abnormal returns by timing countries or sectors (through their selection of funds) or by identifying funds with superior security selection within each of these investment objective categories. Thus, we can determine whether country or sector funds, during certain phases of the business cycle, outperform funds that invest more broadly across countries and sectors in Europe.1 Following recent work in the mutual fund literature (e.g., Pastor and Stambaugh, 2002a and Pastor and Stambaugh, 2002b), we study European mutual fund choice through the lenses of four different types of Bayesian investors. These four types have differing prior views of the ability of mutual funds to generate abnormal returns (alpha) and whether alphas and risk loadings (betas) of funds are predictably time-varying from the point of view of an investor using public information variables. The investment performance of these four types is compared with the performance of a dogmatic investor who does not believe that funds can generate alpha, relative to the capital asset pricing model (CAPM). Our main empirical findings are as follows. We find that a range of financial and macroeconomic variables prove helpful in selecting funds that are capable of generating future alphas. In particular, we find evidence that a number of investment strategies (that use macroeconomic variables to predict fund returns) generate out-of-sample alphas from 7% to 9% per year (after fund-level trading costs and fees), when measured with a single-factor model, and from 12% to 13% per year with a four-factor model that controls for fund exposures to size, book-to-market, and momentum.2 Moreover, the results are robust in separate out-of-sample portfolio selection tests conducted over the periods 1993–2000 and 2001–2008.3 For the investor types believing that active managers can generate alphas, we find that the ability to identify superior performing funds is further improved, albeit slightly, by augmenting the four-factor model with country indices, even if these indices represent nonpriced factors, consistent with Pastor and Stambaugh (2002b). To illustrate, our baseline analysis finds CAPM alpha enhancements of up to 5% per year from using macroeconomic state variables to choose funds, relative to active manager choice using an unconditional CAPM. Further improvements of up to 1% per year are attained from the tighter predictive distribution for fund alphas obtained using the Pastor and Stambaugh (2002b) specification, which, in turn, leads to improved portfolio selection. These baseline results assume a standard set of macroeconomic state variables previously used to analyze U.S. mutual fund return predictability by Avramov and Wermers (2006)—the dividend yield, default spread, short-term interest rate, and term spread. We find that these variables prove valuable in selecting funds with superior performance in Europe, which indicates their ability to locate skilled managers. Interestingly, we find that some additional variables, such as growth in industrial production, inflation, and a proxy for stock market volatility, are also useful in identifying funds with superior future alphas. The predictive success of these additional macro-variables is consistent with their documented power in predicting market returns over historical periods prior to much of our time series by Fama and Schwert (1981) (inflation), Pesaran and Timmermann (1995) (industrial production), and Welch and Goyal (2008) (volatility).4 To better understand the sources of outperformance, we undertake an attribution analysis that decomposes investor returns into that from the selection of Pan-European funds, the selection of country funds, the selection of sector funds, and the timing of country weights implied by the selection of country funds. This analysis shows that the superior returns associated with the macroeconomic-driven strategies arise from the last three sources of performance, not from choosing Pan-European funds. These Pan-European funds, while providing lower-cost diversification, do not exhibit exploitable alphas, either time-varying or unconditional.5 In addition, we implement a version of our strategies that allows investment in individual European stocks, instead of funds. Here, we find that the investment strategies that use macroeconomic variables to predict investment alphas significantly outperform when they have access to funds (either with or without access to stocks) relative to when they have access only to stocks. Thus, macroeconomic variables help us to locate fund managers with skills, but they do not indicate that these fund managers are merely using the macrovariables themselves to time their stock purchases. Because we adopt a Bayesian approach in our paper, the choice of investor priors is an issue. We find that investors do best when they allow the data to largely determine the parameters that they use in their portfolio analysis, that is, when we designate diffuse priors. While a large part of the performance against a CAPM benchmark comes from a fixed (constant) alpha component, modeling time-varying alphas substantially helps to improve performance from country fund selection and from timing country weights. In addition to identifying funds with superior alphas, our model proves capable in identifying funds with inferior performance, that is, funds least likely to hold outperforming stocks. To summarize, our study provides the first evidence of local stock-picking skills of country-focused mutual funds. Further, we show that these skills are time-varying and are best captured through the use of macroeconomic variables. To return to the issue of industry versus country in Europe, we find evidence that much more effort is spent on managing and offering country-focused funds, although sector-focused funds are gaining in popularity in Europe. As such, it appears that the industry versus country debate is not yet resolved in the asset management world. And, to answer our earlier question, country funds continue to be important in capturing time-varying alpha, even with the reduced frictions of investing across Europe during the latter part of our sample period. Our paper proceeds as follows. Section 2 reviews our data and describes the economic state variables and risk factors used in the study. Section 3 reviews the investor types considered in our study and provides details on the methodology. Section 4 presents the main empirical results, Section 5 conducts an attribution analysis, and Section 6 provides robustness results. Finally, Section 7 concludes. Details on data sources, variable construction, and additional robustness results are provided in an online Appendix.

نتیجه گیری انگلیسی

Despite their significant growth in recent years, the performance of European equity mutual funds is a largely unexplored area of research. This paper shows that macroeconomic state variables can be used to identify a significant alpha component among a large sample of Pan-European, European country, and sector funds. State variables such as the default yield spread, the term spread, the dividend yield, and the short risk-free rate as well as macroeconomic variables tracking growth in industrial production are useful in identifying superior performance among funds. Most of the alpha that these state variables help identify using ex ante information comes from their ability to generate returns from country and sector fund selection, as well as from timing country weights. Thus, time-varying strategies appear to be successful, partly because they better identify country- and sector-specific managers with superior skills at a particular point in the business cycle. This finding suggests that there exists managers with superior country- and sector-specific skills, but that these skills can vary with the state of the economy. We also find that timing passive country funds does not work. The positive contribution from timing country weights achieved by the time-varying strategies, therefore, indicates that using macroeconomic variables helps to identify the countries with the best active managers at a given time rather than from timing country indexes. Again, this finding is interesting in light of the industry concentration of some countries.

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