Weiler Dynamics of Cross-Border Flow-Performance Relationships

The Case of European Equity (UCITS) Funds
1. Auflage 2014
ISBN: 978-3-658-08154-6
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 107 Seiten

Reihe: BestMasters

In order to measure the dynamics of flow-performance relationships for a multi-domicile sample, Simon Weiler applies existing flow-performance research methods to a broad set of European equity (UCITS) funds and proves that major findings (performance-chasing behaviour and a convex flow-performance relationship) also hold true in a cross-border market environment.

Simon Weiler works as a research analyst and consultant for an international fund research and information provider.

Autoren/Hrsg.

Weiler, Simon

Inhaltsverzeichnis

1;Table of contents;6
2;List of tables;9
3;List of illustrations;10
4;List of appendices;12
5;Abbreviations;13
6;Abstract;14
7;1. Introduction;15
7.1;1.1. Problem outline and significance;15
7.2;1.2. Review of comparable and related research;17
7.3;1.3. Research questions and hypotheses;20
7.4;1.4. Set up & structure;23
7.5;1.5. Primary sources;26
8;2. Properties of the mutual fund industry;28
8.1;2.1. Properties of mutual funds;28
8.1.1;2.1.1. Purpose and benefits of mutual funds;28
8.1.2;2.1.2. Active versus passive mutual funds;29
8.1.3;2.1.3. Open-ended versus closed-end funds;30
8.1.4;2.1.4. Justification for existence;31
8.2;2.2. Market development and competition;32
8.2.1;2.2.1. Market size and development: Global;32
8.2.2;2.2.2. Market size and development: Europe;34
8.2.3;2.2.3. Competition within the European fund industry;38
8.3;2.3. Economies of scale;42
8.4;2.4. Boutique versus large fund management companies;43
9;3. Outperformance & performance persistence;46
9.1;3.1. How to identify outperformers;46
9.1.1;3.1.1. Asset class classifications;46
9.1.2;3.1.2. Performance evaluation;47
9.2;3.2. Persistence of mutual fund returns;51
9.3;3.3. Life-cycle theory;53
10;4. Investor behavior;56
10.1;4.1. Behavioral finance and the flow-performance relationship;56
10.2;4.2. Incorporating investor irrationalities in quantitative models;58
11;5. Methodology & definitions;59
11.1;5.1. Empirical set up;59
11.1.1;5.1.1. Data source;59
11.1.2;5.1.2. Data horizon and frequency;60
11.1.3;5.1.3. Data focus & sample limitations;61
11.1.4;5.1.4. Required data types;64
11.2;5.2. Data sample;67
11.3;5.3. Quantitative methods;70
11.3.1;5.3.1. General remarks;70
11.3.2;5.3.2. Correlation models;72
11.3.3;5.3.3. Regression models;74
12;6. Time series analysis;78
12.1;6.1. Correlation analysis;78
12.2;6.2. Bivariate linear regression analysis;84
12.3;6.3. Multivariate linear regression analysis;89
13;7. Empiric evidence;93
13.1;7.1. Research question & hypothesis 1;93
13.1.1;7.1.1. Research question & hypothesis 1.1;93
13.1.2;7.1.2. Research question & hypothesis 1.2;94
13.2;7.2. Research question & hypothesis 2;95
13.3;7.3. Research question & hypothesis 3;95
14;Conclusion;97
15;Bibliography;99
16;Appendix A: correlation-test details: flow~percentage growth;104
17;Appendix B: correlation-test details: flow~volatility;105
18;Appendix C: correlation-test details: flow~Sharpe ratio;106
19;Appendix D: geographical database coverage: Lipper for Investment Management;107