Thesis (M.M. (Finance & Investment)--University of the Witwatersrand, Faculty of Commerce, Law and Management, Wits Business School, 2017 / The world has and is still witnessing a tremendous growth in various categories of mutual funds. Active fund managers continue to grow globally with many asking for exorbitant fees for their research and investment services. Equally, passive funds in the form of Exchange Traded Funds (ETF's) and index trackers have also continued to grow. This massive growth does not preclude funds domiciled in South Africa. Passive investments have grown by about 51 percent a year in the last 10 years in South Africa. As at 2016, there are over 3000 mutual funds domiciled in South Africa. Amidst these growing funds is the ongoing debate relating to the question of which fund management style yields the best outcome. The global debate relating to passive versus active fund management has raged for decades with no clear winner. The extant literature provides mixed evidence on the competitive advantage to either investment strategies. Surprisingly, the evidence for South Africa remains scanty, with a handful of authors addressing the issue. This study therefore, sets out to examine the comparative performance of all equity-only active mutual and passive funds domiciled in South Africa. In addition, it analyses the performance persistence of active and passive funds in different business cycles. A major contribution of this study is that it examines, for the first time, the applicability of the Fama-French five factor model on South African mutual funds. It also employs a battery of econometric methods to address the issue at hand. Relying on data from 2003 to 2016, the study presents evidence that both active and passively managed mutual funds do not earn abnormal returns but rather underperform the benchmark. However, the active portfolio performs relatively better than the passive portfolio, although both underperform the market. The study also documents evidence of time-varying performance; both active and passive funds record their worst underperformance during periods of financial crisis. The study also shows that passive portfolios tend to track the market performance more than active portfolios and that both fund categories tend to be sensitive to global market movements, suggesting that global factors matter for the riskiness of these funds. Finally, it is shown that in terms of driving factors, both active and passive fund managers generally give more preference to small cap returns than large cap returns. In addition, they are more growth oriented, as indicated by the negative coefficients for the HML factor. / MT2017

Thesis advisor: Thomas Chemmanur / My dissertation is comprised of three chapters. In this first chapter, I study the effect of social connections on mutual fund investors' information production and accuracy of their signals. While connected investors have access to information in their social network (information diffusion effect), social connections also reduce their incentives to acquire costly information, since they can free ride on connected peers ("free riding on friends" effect). I find this negative "free riding on friends" effect of social connections dominates information diffusion effect in the mutual fund industry, using fund managers' connections built upon their prior career experiences. First, I find that connected funds are more likely to hold the same stocks and to trade in the same direction, relative to unconnected funds. Second, I find that funds with lower network centrality earn higher alphas, even after controlling for other fund and manager characteristics. A one-standard-deviation increase in eigenvector centrality predicts a decrease of 29-37 basis points in annualized fund alphas. Third, when I define a stock-level variable PMC (Peripheral minus Central) as the difference in average portfolio weights between peripheral funds and central funds, I find that stocks with higher PMC have significantly higher abnormal stock returns. A one-standard-deviation increase in PMC predicts an increase of 1.48%-1.52% in the next quarter risk-adjusted returns (annualized). Finally, I find that PMC predicts firms' future earnings surprises. In the second chapter, co-authored with Thomas Chemmanur, Yingzhen Li, and Jie Xie, we propose a "noisy signaling" hypotheses of open market share repurchase (OMSR) programs, where the equity market equilibrium that prevails after OMSR program announcements is a partial pooling rather than a fully separating equilibrium. We argue that two complementary mechanisms, namely, actual share repurchases by firms and information production by institutions, serve to reduce the residual equity market information asymmetry facing firms subsequent to OMSR program announcements. We test the implications of this noisy signaling hypothesis using transaction-level data on trading by institutions and by a subsample of identified hedge funds, and find strong support for the above hypothesis. In the third chapter, co-authored with Thomas Chemmanur, and Jiekun Huang, we analyze how the geographical locations of institutions affect their investments in IPOs and various characteristics of the IPOs that they invest in. We argue that institutions geographically close to each other may free-ride on each other's information when evaluating IPOs, resulting in IPOs dominated by geographically clustered institutions reflecting less accurate information signals compared to those dominated by geographically dispersed institutions. We find that the equity holdings of institutions in IPOs are influenced more by the investments made by neighboring institutions. We show that an increase in the geographical dispersion of the institutions investing in an IPO is associated with higher IPO price revisions, higher firm valuations at offering and secondary market, larger IPO initial returns, greater long-run post-IPO stock returns lower information asymmetry facing an IPO firm in the equity market. Finally, the predictive power of institutional trading post-IPO for subsequent long-run stock returns and earnings surprises for the first fiscal-year end after the IPO is greater for geographically isolated institutions compared to those that are geographically clustered. / Thesis (PhD) — Boston College, 2017. / Submitted to: Boston College. Carroll School of Management. / Discipline: Finance.

Made available in DSpace on 2015-12-03T18:33:14Z (GMT). No. of bitstreams: 1 Ronaldo_Sueo_Hirota.pdf: 2239401 bytes, checksum: 481be2cb72a80eeb4e9057d7463e34cf (MD5) Previous issue date: 2015-03-23 / This study aims to analyze the influence of performance measure in the rankings of multimarket funds in Brazil. The specific objectives sought to understand the concepts and application of the parameters in the evaluation of investment funds performance, present the similarities and differences of performance measures of investment funds, verify the performance of mutual funds in the period of 6 years and applying the Spearman correlation coefficient to describe and measure the relationship between the rankings produced by different levels of performance. The main contribution of this work is to identify if the indicators create different rankings for the individual or corporate investor can decide how to evaluate these funds. It attempted to separate 385 multimarket investment funds which are not exclusive with returns that represent a normal distribution (309 funds) and non-normal distribution (76 funds), in the period of January 2008 to December 2013 to analyze the correlation of rankings between the indexes. The relevance of correlation between the performance measures is if these indexes impact directly in the rankings of multimarket investment funds. Existing high rank correlations, it s clear that it s up to the investor to decide which index to use evaluating the multimarket funds. In the period analyzed, there was a high correlation between the rates of Modigliani, Sharpe and Sortino. The Treynor index was the only one where it was found a low correlation with the others / O presente trabalho tem como principal objetivo analisar a influ??ncia dos ??ndices de desempenho nos rankings dos fundos multimercado no Brasil. Como objetivos espec??ficos, buscou-se compreender os conceitos e aplica????o dos ??ndices na avalia????o de desempenho de fundos de investimento, apresentar as semelhan??as e diferen??as dos ??ndices de desempenho de fundos de investimento, verificar o desempenho dos fundos de investimento no per??odo de 6 anos e aplicar o ??ndice de correla????o de Spearman para descrever e mensurar a rela????o entre os rankings produzidos por diferentes ??ndices de desempenho. A principal contribui????o desse trabalho ?? identificar se os indicadores de desempenho produzem rankings diferentes para que o investidor individual ou corporativo possa decidir como avaliar esses fundos. Buscou-se separar 385 fundos de investimento multimercado n??o exclusivos com retornos mensais que representam uma distribui????o normal (309 fundos) e distribui????o n??o normal (76 fundos), do per??odo de Janeiro de 2008 a Dezembro de 2013 para analisar a correla????o dos rankings entre os ??ndices. A relev??ncia da correla????o entre os ??ndices ?? analisar se a escolha dessas medidas impactam diretamente nos rankings dos fundos multimercado. Existindo alta correla????o, ?? poss??vel afirmar que fica a crit??rio do investidor qual ??ndice utilizar para a avalia????o de fundos. No per??odo analisado, houve alta correla????o entre os ??ndices de Modigliani, Sharpe e Sortino. O ??ndice de Treynor foi o ??nico em que foi constatada baixa correla????o com os demais.

My dissertation consists of two essays on mutual funds. The first essay examines the role of extreme positive returns on future fund flows using maximum style-adjusted daily returns (hereafter MAX) over the previous month. My results suggest that there is a positive and significant relation between MAX and future fund flows. The results are robust to controls for fund performance, fund size, age, turnover, fund fees, volatility, and skewness of fund returns. Of particular interest, this relation exits only in retail funds. Moreover, MAX is persistent from one month to the next, but MAX-based investment strategies are associated with lower risk-adjusted returns than investors could have achieved in otherwise similar funds. Overall, my analysis suggests that mutual fund investors are attracted to maximum style-adjusted daily returns, which is in line with the theoretical argument that investors exhibit a preference for lottery-like payoffs. These investors are successful in achieving a lottery-like return profile, but this strategy is costly in terms of expected returns The second essay studies the effect of recent and long-term mutual fund performance on future fund flows. I document that investors' response to recent performance depends on average long-term performance. In particular, a recent loser fund experiences outflows only if its longer-term performance is also poor. Similarly, recent good performance leads to more inflows only if the fund has also good long-run performance. In contrast, investors ignore recent performance if it provides a signal that conflicts with the longer-term signal. This implies that good fund managers with a longer-term focus will find it easier to attract future inflows than managers with a short-term horizon.

Chu, Ho. / "December 2009." / Thesis (M.Phil.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (p. 99-111). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.iv / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Overview of Mutual Fund Investment --- p.1 / Chapter 1.2 --- Research Motivation --- p.4 / Chapter 1.3 --- List of Contributions --- p.9 / Chapter 1.4 --- Thesis Structure --- p.12 / Chapter 2 --- Literature Review --- p.14 / Chapter 2.1 --- Traditional Measurement Approaches --- p.14 / Chapter 2.1.1 --- Jensen's Alpha --- p.16 / Chapter 2.1.2 --- Treynor Index --- p.19 / Chapter 2.1.3 --- Sharpe Ratio --- p.21 / Chapter 2.1.4 --- Other Measures --- p.23 / Chapter 2.1.4.1 --- M2 Measure --- p.23 / Chapter 2.1.4.2 --- Multifactor Models --- p.25 / Chapter 2.1.4.3 --- Morningstar's RAR --- p.27 / Chapter 2.1.5 --- Shortcomings of Traditional Measures --- p.30 / Chapter 2.2 --- Data Envelopment Analysis --- p.33 / Chapter 2.2.1 --- Brief Introduction --- p.33 / Chapter 2.2.2 --- Research Review on Fund Performance Mea-surement --- p.37 / Chapter 2.2.3 --- Limitations of Basic DEA Models --- p.42 / Chapter 3 --- DEA Methodology and Formulation --- p.47 / Chapter 3.1 --- CCR and BCC Model --- p.48 / Chapter 3.2 --- Problem of Slacks and DEA efficiency --- p.52 / Chapter 3.3 --- Slacks-based Measure --- p.55 / Chapter 3.4 --- Variables with Negative Values --- p.57 / Chapter 3.5 --- Range Directional Measure --- p.59 / Chapter 3.6 --- Modified Slacks-Based Measure --- p.62 / Chapter 4 --- Empirical Study and Discussions --- p.65 / Chapter 4.1 --- Data Source and Tools for Measurement --- p.65 / Chapter 4.2 --- Model Variables Defined --- p.67 / Chapter 4.3 --- Comparison of MSBM Performance Measure to Other Measures --- p.73 / Chapter 4.4 --- Comparison of Hong Kong MPFs with Different Categories --- p.78 / Chapter 5 --- Conclusions and Future Work --- p.90 / Bibliography --- p.99

The first chapter studies mutual funds. I model intraquarter trading and use a genetic algorithm to estimate the trade pattern that is most consistent with the fund's daily reported returns. I validate the model empirically on a sample of institutional trades from Ancerno and I confirm that the method more accurately predicts daily holdings when compared to existing naive assumptions. Further, my method is substantially more accurate in classifying a fund's tendency to supply liquidity, and this increased precision has important implications for identifying superior performing funds. Specifically, a long-short strategy based on the model's liquidity provision measures earns significant abnormal returns, while a similar strategy that relies on quarterly holdings does not exhibit any outperformance. The second chapter studies investment research. We find evidence that crowdsourced investment research facilitates informed trading by retail investors and improves firm liquidity. Specifically, retail order imbalances are strongly correlated with the sentiment of Seeking Alpha articles, and the ability of retail order imbalances to predict returns is roughly twice as large on research article days. In addition, firms with exogenous reductions in Seeking Alpha coverage experience increases in bid-ask spreads and price impact, with the effect being stronger for firms with high retail ownership. Our findings suggest that technological innovations have helped democratize access to investment research with important implications for firm liquidity.

<p>Syftet med uppsatsen är att ta reda på vilka faktorer som ligger till grund för bankers riskklassificering av fonder. För att få svar på frågan sökte vi kontakt med de fyra storbankerna, varav tre kunde ställa upp på intervju (Handelsbanken, Nordea och Swedbank). Dessa banker intervjuades via telefon då detta var den bästa metoden enligt vår synvinkel. För att få mer klarhet i ämnet har svaren från intervjupersonerna kompletterats med publicerat material på respektive banks hemsida.</p><p>Det som framkom efter insamlingen av allt material från bankerna var att samtliga banker använder sig av skalor för att presentera risk på fonder. Skalformatet samt färgsättning varierar dock mellan bankerna. Faktorer som avgör i vilken riskklass en fond hamnar i är fondens investeringsinriktning, t.ex. om det är en aktiefond eller en räntefond. Aktiefonder har generellt högre risk än räntefonder och har därmed en högre standardavvikelse. Standardavvikelsen är den faktor som mest ligger till grund för fonders riskklassificering vilket samtliga banker betonade. Det är ett riskmått som innebär att ju högre standardavvikelsen är desto högre är risken. Standardavvikelsen grundar sig på historisk avkastningsdata som varierar mellan bankerna, men det vanliga är att standardavvikelsen grundas på 1, 3 eller 5 år bakåt i tiden. Det som avgör är hur lång tid fonden har funnits. Utöver standardavvikelsen så finns det andra parametrar som bankerna använder sig av vid riskklassificering. Handelsbanken använder sig exempelvis av value at riskmetoder och stresstester. Även Nordea använder sig av value at riskmetoder i vissa fall. I Swedbanks fall kan metoden inte vara särskilt central då metoden inte har nämnts. De övriga faktorer som påverkar i vilken riskklass en specifik fond hamnar är olika risker, där marknadsrisken är den risk som påverkar mest enligt respondenterna. Andra risker påverkar också i olika grad, men den största tonvikten ligger på marknadsrisken. De olika måtten som exempelvis sharpekvot, informationskvot och aktiv risk, ligger inte till grund för fonders riskklassificering.</p><p> </p>

Thesis (Ph. D.)--University of Texas at Austin, 2006. / Vita. Includes bibliographical references.

Syftet med uppsatsen är att ta reda på vilka faktorer som ligger till grund för bankers riskklassificering av fonder. För att få svar på frågan sökte vi kontakt med de fyra storbankerna, varav tre kunde ställa upp på intervju (Handelsbanken, Nordea och Swedbank). Dessa banker intervjuades via telefon då detta var den bästa metoden enligt vår synvinkel. För att få mer klarhet i ämnet har svaren från intervjupersonerna kompletterats med publicerat material på respektive banks hemsida. Det som framkom efter insamlingen av allt material från bankerna var att samtliga banker använder sig av skalor för att presentera risk på fonder. Skalformatet samt färgsättning varierar dock mellan bankerna. Faktorer som avgör i vilken riskklass en fond hamnar i är fondens investeringsinriktning, t.ex. om det är en aktiefond eller en räntefond. Aktiefonder har generellt högre risk än räntefonder och har därmed en högre standardavvikelse. Standardavvikelsen är den faktor som mest ligger till grund för fonders riskklassificering vilket samtliga banker betonade. Det är ett riskmått som innebär att ju högre standardavvikelsen är desto högre är risken. Standardavvikelsen grundar sig på historisk avkastningsdata som varierar mellan bankerna, men det vanliga är att standardavvikelsen grundas på 1, 3 eller 5 år bakåt i tiden. Det som avgör är hur lång tid fonden har funnits. Utöver standardavvikelsen så finns det andra parametrar som bankerna använder sig av vid riskklassificering. Handelsbanken använder sig exempelvis av value at riskmetoder och stresstester. Även Nordea använder sig av value at riskmetoder i vissa fall. I Swedbanks fall kan metoden inte vara särskilt central då metoden inte har nämnts. De övriga faktorer som påverkar i vilken riskklass en specifik fond hamnar är olika risker, där marknadsrisken är den risk som påverkar mest enligt respondenterna. Andra risker påverkar också i olika grad, men den största tonvikten ligger på marknadsrisken. De olika måtten som exempelvis sharpekvot, informationskvot och aktiv risk, ligger inte till grund för fonders riskklassificering.

Based on previous evidence that there are information heterogeneities in capital markets, three essays including empirical frameworks for examining the information processes that impact portfolio investments and corporate investments was proposed. The first essay considers information channels among mutual fund managers (fund-fund networks), and between holding companies and fund managers (fund-company networks). Results show that (1) fund-fund (fund-company) information networks help in generating positive risk-adjusted returns from holdings in absence of fund-company (fund-fund) networks; (2) fund-company networks create information advantage only when the networks are relatively exclusive. Superior networks seem to pick stocks which outperform beyond the quarter. The second essay examines mutual fund managers tendency to deviate from the strategies of their peers. Results indicate a significantly negative relationship between the managers deviating tendency and fund performance, suggesting that the average fund manager is more likely to make erroneous decisions when they deviate from their peers. The third essay investigates the determinants of target choices in corporate acquisitions. Results reveal the influence of various factors, including information asymmetries, which may drive this behavior, including economic opportunities, anti-takeover regimes, competitive responses to other managers, and acquirers size and book-to-market ratios.