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Predictability of the Swiss Stock Market with Respect to Style / by Patrick Scheurle
Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: SpringerLink BücherPublisher: Wiesbaden : Gabler Verlag / GWV Fachverlage GmbH, Wiesbaden, 2010Description: Online-Ressource (XXIII, 165p. 10 illus, digital)ISBN:- 9783834987297
- 657.8333
- 658.152
- 336 23
- 332.64209494
- 346.494 346.49409
- HG1-9999 HG4501-6051 HG1501-HG3550
- HJ9-9940
- HG5652
Contents:
Summary: Literature Review -- Return Predictability and the Real Economy -- Study Design and Data -- Empirical Part I - Testing for Predictability -- Forecasting Models -- Empirical Part II - Investment Strategies -- ConclusionSummary: There is evidence of fairly strong serial correlation in small caps and a lead-lag relationship between large caps and small caps. Moreover, the discussion of a risk premium for cyclical risks which are captured by small caps and value stocks make style portfolios particularly interesting for research. Patrick Scheurle investigates refined market segments such as small value stocks or large growth stocks with respect to return predictability. The empirical research reveals significant positive first-order serial correlation in the returns of large value stocks, large neutral stocks, small neutral stocks, and small growth stocks. The evidence found supports the view that time-varying risk premia for cyclical risks might induce return predictabilityPPN: PPN: 1650024355Package identifier: Produktsigel: ZDB-2-SBE
Preface; Overview of Contents; Contents; Executive Summary; Executive Summary (German); List of Figures; List of Tables; Notations and Abbreviations; 1. Introduction; 1.1. Motivation; 1.2. Research Idea; 1.3. Outline; 2. Literature Review; 2.1. Structure of Literature Review; 2.2. Factor-Mimicking Portfolios and Macroeconomics; 2.3. Literature on Return Predictability; 2.3.1. Macroeconomic Variables; 2.3.2. Valuation Ratios; 2.3.3. Accounting Data; 2.3.4. Calendar Anomalies; 2.3.5. Serial Correlation and Momentum; 3. Return Predictability and the Real Economy; 3.1. Efficient Market Hypothesis
3.2. Random Walk3.3. Predictability and Cyclical Risks; 3.3.1. Does the Efficient Market Hypothesis Hold?; 3.3.2. Time-Varying Risk Premia; 3.3.3. Investors and Return Predictability; 3.4. Style Investing; 3.4.1. Approaches for the Allocation of Funds; 3.4.2. Reasons for Emerging and Vanishing Styles; 3.4.3. Reasons for Following Style Investing; 3.4.4. Risks and Reward of Style-Based Investment Strategies; 4. Study Design and Data; 4.1. Research Methodology; 4.2. Data; 4.3. Construction of Fama-French Portfolios; 4.4. Descriptive Statistics; 5. Empirical Part I - Testing for Predictability
5.1. Hypothesis I5.2. Autocorrelation Coefficients and Variance Ratios; 5.3. Results; 5.3.1. Autocorrelation Coefficients; 5.3.2. Variance Ratios; 5.4. Summary of Empirical Part I; 6. Forecasting Models; 6.1. Implied and Estimated Cross-Autocorrelation; 6.2. Basic Forecasting Models; 6.3. Robustness and Possible Refinements; 7. Empirical Part II - Investment Strategies; 7.1. Hypothesis II; 7.2. Overview; 7.3. Calibration Windows and Investment Process; 7.4. Performance Measurement; 7.5. Style Rotation Strategies - 4 Style Portfolios; 7.5.1. Fixed Predictor Portfolios
7.5.2. Changing Predictor Portfolios7.6. Style Rotation Strategies - 6 Style Portfolios; 7.6.1. Fixed Predictor Portfolios; 7.6.2. Changing Predictor Portfolios; 7.7. Summary of Empirical Part II; 8. Conclusion; 8.1. Summary of Findings; 8.2. Implications for Practice; 8.3. Research Outlook; Appendix; A1. Variance Ratios (q=4); A2. Style Rotation Strategies (1a to 3b) vs. SMALL; A3. Style Rotation Strategies (4a to 6b) vs. SMALL; A4. Style Rotation Strategies (1a_6 to 3b_6) vs. SH; A5. Style Rotation Strategies (4a_6 to 6b_6) vs. SH; References
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