Measuring Bond Mutual Fund Performance with Portfolio Characteristics

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,

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Measuring Bond Mutual Fund

Performance with Portfolio

Characteristics

Boston College

The Carroll Graduate School of Management

Department of Finance

MEASURING BOND MUTUAL FUND PERFORMANCE WITH

PORTFOLIO CHARACTERISTICS

a dissertation

by

Fabio Moneta

submitted in partial fulfillment of the requirements

for the degree of

Doctor of Philosophy in Finance

© Copyright by Fabio Moneta

2009

ABSTRACT

Employing a novel data set of portfolio weights from 1997 to 2006, the performance of taxable bond mutual funds is studied. The timing ability of fund managers is examined considering different asset allocation choices such as asset class, credit quality allocation, and portfolio maturity decisions. I show that active managers engage in strategies of rotating their portfolios across fixed-income sectors and bond characteristics. Some bond funds exhibit successful timing ability by adopting these strategies. Comparing fund returns plus expenses and transaction costs with the returns of a portfolio that is invested in the previously disclosed holdings, I document that active managers exhibit some ability to select securities that deliver better returns than the securities in the indices. In particular, on average, active managers generate gross returns of 1% per annum over the benchmark portfolio constructed using past holdings.

i TABLE OF CONTENTS

ABSTRACT

TABLE OF CONTENTS

LIST OF TABLES AND FIGURES

ACKNOWLEDGEMENTS AND DEDICATION

1 Introduction 1

2 Related Mutual Fund Literature 9

3 Research Design 15

3.1 The Unconditional Characteristic Timing (CT) Measure…………... 15

3.2 Mutual Fund Return Decomposition………17

3.3 The Conditional Characteristic Timing (CCT) Measure………..19

4 Data 20

4.1 Bond Fund Data………20

4.2 Bond Indices and Instrumental Variables……….24

4.3 Macroeconomic Announcements Data……….26

5 Preliminary Analysis of Portfolio Weights 28 6 Results 31 6.1 CT Results ………31

6.2 Return Decomposition: CT and RG……….38

6.3 Returns-based Measures………...44

6.4 CCT Results………..47

6.5 Performance Persistence and Panel Data Analyses………..48

7 Conclusion 53

Appendix 58 References 66

ii LIST OF TABLES AND FIGURES

Table 1: Morningstar Portfolio Analysis 59

Table 2: Number of Funds and Average Number of Portfolio

Weight Records per Year for Different Allocations 60

Table 3: Statistics of Asset Class Weights: Sector Allocation (1997-2006) 60 Table 4: Statistics of Asset Class Weights:

Credit Quality Allocation (1997-2006) 61

Table 5: Statistics of Asset Class Weights:

Maturity Range Allocation (1997-2006) 62

Table 6: Bond Indices and Matched Asset Classes 64

Table 7: U.S. Macroeconomic Announcements 65

Table I: Statistics of U.S. Taxable Bond Mutual Funds (1997-2006)

and Aggregate Bond Indices 76

Table II: Taxable Bond Mutual Funds Turnover Rate

Compared to Equity Mutual Funds (1997-2006) 77

Table III: Portfolio Allocation Turnover of Bond Funds

and Selected Index Funds for Different Allocations 78

Table IV: Morningstar Category and Style Changes 78

Table V: Characteristic Timing (CT) Measure of Bond Funds

Using Different Allocations and Horizons 79

Table VI: Characteristic Timing (CT) Measure of Bond Funds

by Style Group Using Credit Quality and Maturity Range Allocations 80 Table VII: Mutual Fund Return Decomposition:

Average Style, Characteristic Timing, and Return GAP 82

Table VIII: Regression of return GAP on Monthly Dummies 83

Table IX: Estimates of the Unconditional and Conditional Index Model 84 Table X: Conditional and Unconditional Characteristic

iii

Table XI: Persistence of Characteristic Timing and Return Gap 87

Table XII: Return Gap Measure and Mutual Fund Characteristics 88

Table XIII: Characteristic Timing Measure and Mutual Fund Characteristics 90

Table XIV: Portfolio Returns Based on Past Alpha and Return GAP 91

Figure 1: Recent Trends in Bond Mutual Funds 92

Figure 2: Annual Returns for Selected Fixed-income Indices (1997-2006) 92 Figure 3: Annual Return GAP for an Equally-weighted Portfolio

iv ACKNOWLEDGEMENTS AND DEDICATION

I am very grateful to my advisors Pierluigi Balduzzi and Wayne Ferson for their guidance and support. Wayne imparted a lot of his passion and enthusiasm about research to me. It was a loss when he left Boston College. Pierluigi has been an exceptional chair and he has taught me to be very rigorous and critical with my own work.

I am also grateful to my other committee members David Chapman and Alan Marcus for their support and helpful comments and discussions. A special thanks also goes to Ludwig Chincarini, Ian Cooper, Roger Edelen, Richard Evans, and seminar participants at the Boston College finance seminar, HEC Montréal, Pace University, Erasmus University, Federal Reserve Board, Queen's University, Norwegian School of Management BI, Bocconi University, Swiss Finance Institute (Lugano), 7th Trans-Atlantic Doctoral Conference at London Business School, the 2008 European Finance Association Annual Meeting, the 2008 Financial Management Association Annual Meeting, and the 2008 Southern Finance Association Annual Meeting for their valuable comments and suggestions.

I also wish to thank my friends in the Economics department. Their friendship gave me a lot of strength. Finally, my parents, my five brothers, and four sisters were always a source of inspiration and encouragement. I am grateful for their continuous support.

This dissertation is dedicated to my wife Angela and our baby whom is carrying. Her love and encouragement helped me a lot throughout all the dissertation process.

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