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60 Seiten, Note: 7.5
2 Literature Review
2.1 Development of the mutual fund literature and international fund performance
2.2 Past performance
2.3 Liquidity issues
2.4 Small cap segment
2.5 Activist investors
2.6 Low cost alternatives to mutual funds
3 Industry Review
3.1 Discretionary mandates
4 Data and Methodology
4.3 Data quality
5.1 Fama-French Model
5.2 Carhart Model
5.3 Liquidity Model
5.4 Discussion of the results
5.5 Fees added back
6.1 Implications for academia
6.2 Implications for retail investors
6.3 Wrap up
The following study examines the performance of mutual funds investing in small cap companies in the period from 1990 until 2013. Therefore, funds investing in small companies in Germany are tested on their ability to deliver risk-adjusted abnormal returns. The returns are risk-adjusted according to Fama French (1996) three-factor model, Carhart four-factor model and the liquidity adjusted five-factor model of Pastor and Stambaugh (2003). A separate examination of the internet crisis 2000 until 2003 and the financial crisis period 2008 until 2013 is done, to assess the ability of fund managers in isolation to examine their results in situations when their skills are most needed. On average, I conclude that fund managers, investing in the small capitalization segment in Germany, are not able to outperform the market even before fees.
First and foremost I want to thank Iman Honarvar Gheysary for his unlimited help and availabil- ity in times of pressure. He was, in his role of a supervisor, thrown into the project and within minimum time involved. Thanks for the quick feedback on all my drafts and the various phone calls. Thank you for your great help, without you this thesis would not have happened.
Second, I want to thank Dr. Roger Otten for the idea, approval of the idea and lead supervision of my topic. Furthermore, thank you for the support in the early stage of this thesis regardless of the circumstances.
Third, and a special thanks to Mr. Jeroen Derwall who answered e-mails and took over the role as a intermediate supervisor without being forced by any rules and regulations of Maastricht University. His contribution was especially significant in the determination of the European factors and the Dataset. He was the person on whom my hopes relied in foggy times.
Thank you to all of you!
To all people who have to be well soon!
1 Volume chart DAX vs. SDAX
2 Worldwide AUM categorized for regions
3 Absolute $ value AUM
4 Relative distribution AUM in the US
5 Percentage growth AUM in the US
6 Distribution of European AUM at the end of
7 Country shares in the European Market
8 Growth of European investment fund industry until
9 Market share of discretionary mandates and fund assets
10 Nominal value NASDAQ 1996-
11 LIBOR-OIS three-month spread 2007-
12 QQ plot for the full period (1991-2013)
13 Full period histogram and descriptive statistic
14 QQ plot for the internet crisis period (2000-
15 Internet bubble histogram and descriptive statistics
16 QQ plot for the financial crisis period (2008 - 2013)
17 Financial crisis histogram and descriptive statistics
1 Summary of sample statistic
2 Correlation and Descriptive Statistics 1991 - 2013..
3 Correlation and Descriptive Statistics 2000 - 2003..
4 Correlation and Descriptive Statistics from 2008 - 2013
5 R2 and adjusted R2 statistics (multiperiod)
6 Fama-French model for the full period 1991 - 2013.
7 Fama-French model for the internet crisis 2000 -
8 Summary of Fama-French 3-factor model 2008 - 2012
9 Carhart four-factor model for the full period 1991 -
10 Carhart model for the internet crisis period 2000 - 2003.
11 Carhart model for the financial crisis period 2008 - 2012
12 Liquidity five-factor model for the full period 1991 - 2013
13 Liquidity model for the internet crisis period 2000 - 2003
14 Liquidity model for the financial crisis period 2008 - 2012
15 Results overview for all models and periods before and after fees
If the efficient market hypothesis (EMH) holds, then passive investors should not be able to earn (abnormal returns). Therefore, many event studies try to gain insights about the performance of mutual fund managers and their performance persistence. For the US there is no evidence of persistent outperformance by fund managers as documented by Sharpe (1966), Jensen (1968), Gruber (1996) and Malkiel (1995). Daniel, Grinblatt, Titman, & Wermers (1997) use a character- istics based approach to benchmarking and find the opposite. In particular, they find that some managers in the period 1974 until 1994 in the US achieve abnormal returns due to the optimal timing of the change of their investment style (Daniel, Grinblatt, Titman, & Wermers, 1997). Their finding of no significant outperformance also holds true for the Swedish market (Dahlquist, Engström,& Söderlind, 2000). Moreover, plenty of research is available for the US mutual fund market, while the research coverage for the European market is mediocre (Otten and Thevissen, 2011). Gruber (1996) finds that the average US mutual fund underperforms a passive index fund by 65 basis points (bps). However, Otten and Bams (2002) find that due to the small size of the European market, compared to the US, the German, Italian, Dutch, French and UK funds are able to outperform the market on a before fee basis. They collect return data from 1991 until 1998 for 506 European funds and test a conditional and unconditional four-factor Carhart model to determine alpha. The result could be grounded in a smaller market importance than in the US, according to them. As the sector as a whole grows larger, it becomes harder to beat the market (Otten and Bams, 2002). Funds in Europe seem to be able to find and incorporate information to offset their expense and provide diversification and transaction cost benefits to the ultimate fund investors (Otten and Bams, 2002).
In particular, small funds due to the relative small size of the market are able to do so. In a composition of interviews, published in 2011 in the Frankfurter Allgmeine Zeitung, fund managers from Lupus Alpha and Templeton describe the German market for mutual funds, investing in small- and midcaps, as very small and rarely covered by major analysts (von Gaertringen, 2011). Especially, in times of crisis investors and investment banks focus their research on the larger blue chip stocks. Therefore, markets for smaller companies become inefficient and illiquid (Ennis and Sebastian, 2002). As a result, with thorough research and expertise it should be possible to add value to clients, according to von Gaertringen (2011).
Therefore, the interest of this thesis is to study if mutual fund managers, specializing in small stock investments, are able to outperform their German country benchmark by means of an ordinary least squared (OLS) regression analysis. Moreover, the current state and the development of the mutual fund market in the small cap area in Europe over the past years are portrayed. Additionally, I would like to find out how fund managers performed during the internet crisis in 2001 and during the most recent financial crisis starting in 2008 with the collapse of Lehman Brothers. Finally, the results are discussed and sorted into existing economic reasoning.
Since there is limited research available for the last decade about the performance of mutual funds investing in small companies my results add to the academic community as well as to the professional world. In academia, I follow on Otten and Bams (2002) and Otten and Thevissen (2011) call for further research to conduct follow up research in the small cap area to document, if a development has taken place in the European mutual fund market, in particular in Germany, with focus on small companies over the past couple of years, or if the small cap market remains a niche market for mutual fund vendors. Banks and money management companies can use results to base decisions on, such as developing new products or refocusing business in the small cap area. It is particularly interesting from the point of view that the financial industry changes rapidly because of recent developments initiated by the financial crisis. Moreover, the isolation of the crisis periods gives insight into the effectiveness of mutual fund managers as a group in extreme situations. These results are interesting for retail investors that ultimately invest in those vehicles.
The thesis exhibits the following structure. First, a literature review is done to survey the existing mutual fund literature and to better understand the discussion of the results in the after- math. Next, a top down approach to the description of the German mutual fund market is taken, starting with the two most important markets - the US and Europe. Third, the data collection method, methodology of the study and research set up is described. Following, the results are presented and discussed, starting with the whole period and continuing with the separation of the crisis period. Finally, a conclusion is drawn with implications for academia, practitioners and investors.
The concept of market efficiency says that markets fully reflect all available information (Malkiel and Fama, 1970). As a result nobody should be able to earn an excess return and fund managers should not earn a positive alpha either. If the strong form EMH holds, then market participants cannot earn a return on the basis of public and private information. Since it is generally assumed that professional mutual fund managers abide to the law, they will not trade on private information. Even if fund managers would be willing to breach the law, due to numerous regulations and compliance directives professional money managers are most of the times not able to exploit insider opportunities. Of course a simple regression analysis cannot reveal the source of the alpha. The semi-strong form EMH does not hold from the point of view of money managers either, otherwise they would not do what they do. Namely, trying to identify undervalued companies and incorporating information more efficient and effective in their view on the markets. The results of the regression analysis (Section 5) show if active management can add value. Of course, money managers provide other benefits such as economies of scale in trading and the pooling of assets to better achieve diversification. However, nowadays low cost vehicles called ETFs can achieve this, too.
Finally, market participants practicing technical analysis reject the weak form EMH. Therefore, I assume that fund managers also rely on technical signals to generate abnormal returns. However, the assumptions underlying the EMH of homogenous expectations by all market participants, no transaction cost and the incorporation of all currently available information are very ambiguous anyway. This ambiguity is, among some empirical evidence of persistent outperformance by some money managers (Grinblatt and Titman, 1992; Brown and Goetzmann, 1995), the reason why academics and practicing money managers challenge the concept of market efficiency (Carhart, 1997). Fama and French (2007) proclaim that maybe investors do not choose the optimal portfolio but have other motivations such as tax reasons or consumption preferences. Chevallier and Elli- son (1999) find a causal relationship between managers that attended higher-SAT undergraduate schools and the persistent delivery of risk-adjusted excess returns. A study of mutual funds with managers from higher SAT universities in the US and higher GMAT requirements in Europe might reveal that money managers are not able to outperform as a group on average but some individuals are able to outperform consistently.
Basu (1977) provides evidence on the informational content of P/E ratios and the possibility to persistently outperform by buying low P/E stocks (value stocks). Of course market inefficien- cies are smaller today than several years ago because of the advancement of technology or the systematically computerized exploitation of arbitrage opportunities and inefficiencies. Reinganum (1981) finds that the P/E effect disappears once a size factor is added to the CAPM model. The evaporation of the P/E effect implies a rejection of smaller companies with little earnings in their early phase by investors. It results either from the fact that the company is unknown, has less media coverage than their larger peers and as a result investors are not aware of its existence or investors refrain because of the opacity about the future inherent in small companies in their early phase. As a result they are underprized and meticulous investors can earn an abnormal return. Similarly, mutual fund managers have a fiduciary duty to their clients. Therefore, they have to act within their mandate and guidelines specified in the policies with the clients. Transparency is an important factor in this context, therefore fund managers in their role as a fiduciary are often not authorised to invest in intransparent and opaque companies.
Due to different time periods, methodology and samples, several streams of literature exist, most deny the persistence of performance and the ability of outperformance, while some find partial evidence. The following paragraphs elaborate on these different research efforts.
Numerous studies proof that mutual funds, actively managed investment vehicles, are not able to outperform the market. Fama and French (2008) find that in the US, managers of equity funds produce an alpha of close to zero on a before fee basis adjusted for the common risk factors. Gruber (1996) finds that the average mutual fund underperforms by 65 bps per year. Carhart (1997) draws the link between trade frequency and performance and finds more active trading leads to lower performance. It confirms Sharpe (1966) who finds the expense ratio to be a better predictor of future performance than is past performance. In particular, Sharpe (1966) bargains that good performance is associated with low expense ratios. Though, Engström (2004) finds a positive relationship of mutual fund trading activity and performance in Sweden. Nevertheless, the empirics imply that on average, the typical investor is better off by investing in the market portfolio, than in the portfolio of a mutual fund. Dahlquist et al. (2000) show that actively managed funds in Sweden perform better than passively managed funds. Therefore, the ultimate investor in the fund makes a negative-sum game after deducting management fees as concluded by Fama and French (2008) and Jensen (1968). Things have not turned around the last 50 years. Sharpe (1966) and Jensen (1968) document no significant outperformance in the 1970s when the first evaluations of mutual fund performance appeared, neither do the authors today except for some rare cases.
Mutual funds from the UK were able to persistently outperform the market as a group before fees after adjusting for the Fama French and Carhart risk factors (Otten and Bams, 2002). In contrast to German, Dutch, French, Italian and UK funds outperform the market on a before-fee basis, though not significant. As said earlier, differing opinions exist for different time periods and samples.
D. Blake and Timmermann (1998) find that UK mutual funds underperform by 1.8% per year on a risk-adjusted basis in the aggregate. Since the UK has the largest and most developed mutual fund market in Europe it can either be that the high number of fund vendors makes it difficult to generate alpha, due to high market efficiency, or that the mutual fund industry just provides the value added service such as diversification. In the latter case, clients do not pay the manager to generate higher returns than the market, but to allocate the money in a way to achieve diversified portfolios because they cannot do it themselves for the same cost or do not have the technical resources and knowledge. However, one can attribute the underperformance to a high density of mutual funds in the UK since the authors find persistence in performance of the best and worst performing quartile (D. Blake and Timmermann, 1998). This confirms the earlier results of Grinblatt and Titman (1992). They find persistence in mutual fund performance over the period from 1974 till 1984 in the US. The differences are not explained by inefficiencies related to firm size, dividend yield, CAPM or others (Grinblatt and Titman, 1992). In general, empirical evidence for persistence in mutual fund performance is more pronounced than evidence against it (Carhart, 1997).
These results are in line with the fact that bond mutual fund regressions of risk-adjusted performance against fees have a slope of minus one, implying that a percentage points in fees lowers the return available to investors one-by-one (C. R. Blake, Elton, and Gruber, 1993). However, the early studies were mainly based on the Capital Asset Pricing Model, which assumes efficient markets. Fama and French (1996) argue that other style factors than solely the market factor influence an assets return. The introduction of a three-factor model removes the ability of some other variables to also predict performance that is apparently not explained by the CAPM model (Fama and French, 1996). Therefore, the three-factor model is a suitable tool to attribute the return of a security to different sources of risk as elaborated on in the methodology part. A model with only one market factor and information about future GDP growth is not sufficient to replicate the results of the Fama-French Model (Vassalou, 2000). As a result, it can be concluded that the HML and SMB factors help to explain equity returns (Vassalou, 2000). However, the three-factor model is not able to explain the momentum of short-term returns as described by Jegadeesh and Titman (2001). The solution to this problem is the extended four-factor Carhart model (Carhart, 1997). Following this new statistical model, researchers started to confirm or disprove the earlier mutual fund performance studies.
Most of the above-cited studies were conducted in the US. Otten and Bams (2002) conducted research for the European market and find significant alphas for France, Italy and the Netherlands before fees and for the UK even before and after fees. The finding might be the result of lower market efficiency due to size and is in stark contrast with the above-cited studies.
A short interlude on international stock market efficiency should clarify some issues. Chan, Gup, and Pan (1997) test 18 world markets in the period from 1960 until 1997 for market efficiency by means of cointegration tests. Among others, the US and Canada as a group and Germany, UK, France and Italy as a group are tested. In isolated tests for individual countries they find a unit root and conclude that markets are individually efficient. The authors claim two markets to be cointegrated if one can find arbitrage opportunities. In the long run, for the stock markets to be collectively efficient, their stock prices cannot be cointegrated (Chan et al., 1997). They find no cointegration for the North American group, but for the European one. The finding implies lower stock market efficiency for the group of four European countries and supports my earlier argumentation. Wu (2002) cites the fact that abnormal performance by certain managers, as a group is possible as a counterargument for efficient markets. Therefore, market efficiency is lower in Europe than in the US.
However, to revisit the economic reason why academics do not find abnormal returns: Managers have to be paid. Managers extract rents, in the form of fees and expense for their work, therefore most studies do not find abnormal net returns but gross returns (Grinblatt and Titman, 1989). Ippolito (1989) showed that managers are at least able to earn their fees and loads. Hence, funds are able to efficiently incorporate the benefits of their information and trading activities. Starting from this point of view, managers in the small cap segment should be able to utilize their expertise and find undervalued stocks as described in the next paragraph. For this reason, I am going to investigate managers’ performance before and after fees similar as Otten and Bams (2002).
Elton, Gruber, and Blake (1995) find evidence for the predictive capability of past performance of funds returns in the short run in a survivorship free sample. However, using risk-adjusted returns the results hold in the long run, too (Elton et al., 1995). They also identify the problem of measuring persistent outperformance in a group of funds where characteristics change over time, such as transition from small cap to growth fund. The momentum anomaly first found by Jegadeesh and Titman (1993) outlines that investing in last years good performers yields superior results in subsequent years. However, among others Carhart (1997) documents the effect only for the short term in the time period from 1963 until 1992. In the same vein, Rouwenhorst (1998) confirms the short-term momentum effect in 12 European countries. They load negative on size and market factors and the continuation of short-term returns is more pronounced for smaller companies. In contrast Gruber (1996) discovers that past performance reveals independent information about future performance to a certain extent, while expense do not necessarily. In fact expenses of the top performing funds rise more slowly than for the bottom performing funds (Gruber, 1996). Jegadeesh and Titman (1993) explain the momentum anomaly by a slow reaction to new information. Nevertheless, since 1993 the pace of the information incorporated in models increased exponentially. Therefore, I expect to find similar results as Carhart (1997) due to a behavioural bias of investors.
In addition to the 3-factor and 4-factor model another factor has to be taken into consideration, namely liquidity. A more liquid asset has to carry a lower spread than a less liquid asset relatively speaking. Therefore, assets with less liquid markets have to carry a higher expected return similar to corporate bond markets. De Jong and Driessen (2012) study liquidity premia for corporate bonds and find a spread differential for longer maturities of 0.45% and 1% for investment grade and non-investment grade bonds respectively. Longer maturities normally trade at lower volume such as the off-the-run treasury issue (De Jong and Driessen, 2012). Also, larger players such as mutual funds can influence the price considerably with a large trade volume, which results in unfavourable execution for them. Since the volume and the liquidity are much lower in the small capitalization market compared to the large capitalization market, I test a fifth model with a pricing factor for liquidity included.
To support my argumentation about the huge volume difference, I retrieved the trading volume for the DAX and the SDAX from Datastream. It serves as a proxy for the large and small market, respectively, since 2003. Figure 1 compares the volume side by side. Trading volume is defined as the average number of shares traded and not monetary volume. Therefore, it is a good measure for my purpose because of the differences in share prices between the large and small cap index, and for securities within the respective indices. A higher number of shares traded, implies besides the higher average price of a DAX share relative to a SDAX share, that more trades have taken place. And liquidity, in its most essential sense, is the ability to find counterparties in the market. With a high volume it is easier than in a low volume market. The average volume of traded shares for the DAX is 2,664,394 while the average volume for the SDAX is 53,519. This makes huge difference liquidity wise.
As a group, mutual funds in the small cap area are able to persistently outperform the market due to their market niche in Europe (Otten and Bams, 2002). In my eyes, these results imply that fund managers are less likely to outperform the market the more market participants are in the market. Therefore, with caution one could proclaim that fund managers in less liquid and therefore less efficient equity markets are more likely to outperform. Banz (1981) finds that small firms had significantly larger risk-adjusted abnormal returns in the period 1936 until 1977. This finding supports my argumentation. However, he was not able to pinpoint the source of return. One possibility is the partial correlation with size, while the size factor captures some of these effects (Banz, 1981). Therefore, in case managers are able to outperform the market on a risk adjusted- basis based on the model, it might be just a compensation for some risk that has not been captured yet by existing and proven models. Another explanation can be the non-existence of possibilities to execute market transactions in a totally efficient manner. The underlying assumption of efficient
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Figure 1: The upper, grey line shows the volume of the DAX index on the left vertical axis, while the lower, black line displays the SDAX volume on the right vertical axis. The time period ranges from 2003 until 2014. The average number of traded shares per month over the period is 2,664,394 and 53,517 for the DAX and SDAX respectively.
markets could have been violated in the past. However, nowadays we are moving closer to 100% market efficiency due to better technical innovations.
Since Otten and Bams (2002) research, twelve years have passed; new technology has arrived, which creates more efficient markets due to better execution, information distribution and wider reach of market participants. What is more, the recent financial crisis changed the way, how banks and smart money managers act and decide. They have to act more careful, move in tighter boundaries and their results and actions are scrutinized by the media, the public, and politics shortly: by the whole society. Academics, practitioners and investors are interested in the fact if professional money managers are able to outperform a market benchmark and as a result are able to add value to their clients, based on prevailing models.
In 2011, Otten and Thevissen (2011) make a follow up on the earlier study conducted by Otten and Bams (2002) to confirm the hypothesis that a larger and more developed market for mutual funds investing in small- and mid-cap companies, leads to less alpha generation ability by managers. Otten and Thevissen (2011) examine 16,055 European equity funds over the 1992 until 2006 period. The large sample size arises because they sample the whole mutual fund market in Europe including all styles and sizes. They are literally sampling the whole mutual fund market in Europe. Nevertheless, this finding confirms the earlier findings of D. Blake and Timmermann (1998), that on average managers in the UK, the most liquid and developed market in Europe, underperform. Likewise, the result confirms the conclusion of Malkiel and Fama (1970) because they document ample evidence in favour of the efficient markets model, higher liquidity and volume reduce transaction cost. Often, higher volume implies more coverage and a higher number of market participants. Therefore, the results of Otten and Thevissen (2011) support the earlier work of Fama and other authors in the area of efficient markets.
Nevertheless, it seems that UK funds are able to outperform in the more exotic areas of the market, such as small cap, activist investing and ethical investing. Often those funds are highly exposed to small cap stocks (Bauer, Koedijk, and Otten, 2005). As shown by Bauer et al. (2005) mutual funds in the UK, adapting a style of ethical investing are able to outperform the market in contrast to their US and German peers. The UK funds, investing in an ethical manner, are the only funds out of this specific sample that outperform after a conditional model is applied. In the unconditional model the outperformance is not significant, though. The performance of activist investors, which are characterized by deep involvement into the management of a company, is discussed in a next sub-chapter.
A new class of funds, activist investment funds, are on the rise. These funds invest in companies and try to increase the value of their portfolio companies by private or public intervention. Thereby, they take a more fundamental, long-term approach in contrast to the mutual fund managers that try to practice strategic and tactical asset allocation because of yearly evaluations and the market discipline of a job loss. Becht, Franks, Mayer, and Rossi (2010) analyse the performance of the Hermes UK Focus Fund (HUKFF). They find abnormal performance of 4.9% net of fees against the FTSE all-share index for the period 1998 until 2004 (Becht et al., 2010). It is remarkably though that this performance was achieved with the internet bubble included. Thereby, they document a free rider problem. Since the HUKFF does not hold 100% of the outstanding shares other investors earn some of the benefits achieved by the expense of the HUKFF. Therefore, mutual fund managers might be able to boost their performance by closely watching the companies the HUKFF invests in and allocate some of their resources to these shares. Nevertheless, this is only possible if the evaluation period of mutual fund managers is prolonged in duration.
Nowadays, ETFs serve the customers’ need in a better way. Though, one should note that compared to an actively managed mutual fund, underperformance of the index is guaranteed with an ETF due to the tracking error and a small fee associated. Most ETFs track an index one-to-one. Meaning, they replicate the index and make a convenient, easy to understand low cost vehicle available to the retail investor community. Thereby, investors can gain risk exposure to the index without taking, i.e. the margin risk of futures. However, the transaction- and operational cost leads to guaranteed underperformance of the ETF (Gastineau, 2004). An outperformance could be possible if ETF manager would have more flexibility in their mandates because market timing in the index replication could lead to the recoupment of the fees (Gastineau, 2004). The first listing of an ETF in Europe was in 2000 by Deutsche Börse and LSE. By 2005 AUM had grown at an annual rate of 40% to 45 billion with 160 ETFs listed (Deville, 2008).
illustration not visible in this excerpt
Figure 2: Worldwide AUM categorized for regions (Shub et al., 2013). All parts of the world experience a positive trend in their annual AUM growth.
The following section develops a comprehensive view on the mutual fund industry as of 2013. I take a top-down approach by first providing a quick overview of the worldwide asset management industry, followed by a catch up with the US market and finally in more detail the European and in particular the German market.
According to BCG the global amount of assets under management (later referred to as: AUM) surpassed their pre-crisis level for the first time at the end of 2012 (Shub et al., 2013). Worldwide AUM increased to $62.4 trillion at the end of 2012, compared to $57.2 trillion in 2007. A strong trend and need for professional money management is visible. Figure 2 graphically illustrates the worldwide development of AUM. In particular, despite or because of the financial crisis investors are more concerned about the right management of their fortune to preserve it but also to increase their wealth. Still, there is no definite answer yet but opinions. It is not totally clear if the demand grows because the topic of money management becomes more prevalent in the news and investors become more aware of the need for professional management or if they try to exploit the opportunities given after a major crisis.
As Otten and Bams (2002) state, the US mutual fund industry had a total of $5.2 trillion in AUM at the end of 1998. In comparison, there were $14.7 trillion AUM for the US and $26.8
illustration not visible in this excerpt
Figure 3: Time series of absolute $ value of total AUM in the US industry until 2012.
trillion for the whole world at the end of 2013, an increase of 82.3% (ICI, 2013). Figure 3 gives a graphical representation in a time series to track the development. Figure 3, 4 and 5 show that the US industry and in particular the mutual fund industry is growing nearly every year. However, one can see clearly a new arising species, namely ETFs, increasing its market share significantly starting in 1996 with $1 billion AUM. Figure 4 illustrates the development of the ETF market in terms of AUM over the period 1995 until 2012. I assume that by now the US results are much closer to the European market environment because the markets became more similar in the last ten years. The average growth rate of AUM since 1996 for ETFs is 61.39% with only one negative year in 2000.
The statistic about mutual funds by the ICI is limited by only including funds reporting to the ICI statistical information. Therefore, a self-selection bias could be present. Moreover, funds of funds are excluded.
In Europe, despite the global inflows into the worldwide mutual fund industry, 30% of the managers experienced a net asset outflow of at least 5% in 2013 (Shub et al., 2013). In total, 29% of AUM was allocated to equity investments (EFAMA, 2013). The European market had
illustration not visible in this excerpt
Figure 4: Time series of relative distribution of AUM in the US industry among different products until 2012.
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Figure 5: Time series of percentage growth of total assets under management and mutual fund assets in the US industry until 2012. The growth of the mutual fund industry drives the industry growth pattern.
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