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000724493 019__ $$a908087528
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000724493 050_4 $$aHF5681.F84
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000724493 1001_ $$aWeiler, Simon,$$eauthor.
000724493 24510 $$aDynamics of cross-border flow-performance relationships$$h[electronic resource] :$$bthe case of European equity (UCITS) funds /$$cSimon Weiler.
000724493 264_1 $$aWiesbaden :$$bSpringer Gabler,$$c[2014]
000724493 264_4 $$c©2015
000724493 300__ $$a1 online resource (xvii, 94 pages) :$$bcolor illustrations.
000724493 336__ $$atext$$btxt$$2rdacontent
000724493 337__ $$acomputer$$bc$$2rdamedia
000724493 338__ $$aonline resource$$bcr$$2rdacarrier
000724493 4901_ $$aBestMasters
000724493 5050_ $$aTable of contents; List of tables; List of illustrations; List of appendices; Abbreviations; Abstract; 1. Introduction; 1.1. Problem outline and significance; 1.2. Review of comparable and related research; 1.3. Research questions and hypotheses; 1.4. Set up & structure; 1.5. Primary sources; 2. Properties of the mutual fund industry; 2.1. Properties of mutual funds; 2.1.1. Purpose and benefits of mutual funds; 2.1.2. Active versus passive mutual funds; 2.1.3. Open-ended versus closed-end funds; 2.1.4. Justification for existence; 2.2. Market development and competition
000724493 5058_ $$a2.2.1. Market size and development: Global2.2.2. Market size and development: Europe; 2.2.3. Competition within the European fund industry; 2.3. Economies of scale; 2.4. Boutique versus large fund management companies; 3. Outperformance & performance persistence; 3.1. How to identify outperformers; 3.1.1. Asset class classifications; 3.1.2. Performance evaluation; 3.2. Persistence of mutual fund returns; 3.3. Life-cycle theory; 4. Investor behavior; 4.1. Behavioral finance and the flow-performance relationship; 4.2. Incorporating investor irrationalities in quantitative models
000724493 5058_ $$a5. Methodology & definitions5.1. Empirical set up; 5.1.1. Data source; 5.1.2. Data horizon and frequency; 5.1.3. Data focus & sample limitations; 5.1.4. Required data types; 5.2. Data sample; 5.3. Quantitative methods; 5.3.1. General remarks; 5.3.2. Correlation models; 5.3.3. Regression models; 6. Time series analysis; 6.1. Correlation analysis; 6.2. Bivariate linear regression analysis; 6.3. Multivariate linear regression analysis; 7. Empiric evidence; 7.1. Research question & hypothesis 1; 7.1.1. Research question & hypothesis 1.1; 7.1.2. Research question & hypothesis 1.2
000724493 5058_ $$a7.2. Research question & hypothesis 27.3. Research question & hypothesis 3; Conclusion; Bibliography; Appendix A: correlation-test details: flow~percentage growth; Appendix B: correlation-test details: flow~volatility; Appendix C: correlation-test details: flow~Sharpe ratio; Appendix D: geographical database coverage: Lipper for Investment Management
000724493 506__ $$aAccess limited to authorized users.
000724493 520__ $$aIn 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.
000724493 650_0 $$aFund accounting$$zEuropean Union countries.
000724493 650_0 $$aFinance$$zEuropean Union countries.
000724493 77608 $$iPrint version:$$aWeiler, Simon$$tDynamics of Cross-Border Flow-Performance Relationships : The Case of European Equity (UCITS) Funds$$dWiesbaden : Springer Fachmedien Wiesbaden,c2014$$z9783658081539
000724493 830_0 $$aBestMasters.
000724493 852__ $$bebk
000724493 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-658-08154-6$$zOnline Access$$91397441.1
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000724493 980__ $$aEBOOK
000724493 980__ $$aBIB
000724493 982__ $$aEbook
000724493 983__ $$aOnline
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