| Description |
1 online resource |
| Series |
International series in operations research & management science ; volume 257 |
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International series in operations research & management science ; v. 257.
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| Contents |
Preface; Contents; Part I Risk Modeling; 1 Directional Returns for Gold and Silver: A Cluster Analysis Approach; 1.1 Introduction and Literature Review; 1.2 Data Collection and Preparation; 1.3 Methodology: Two-Step Cluster Analysis; 1.4 Gold with Clusters; 1.4.1 Training Set Variable Importance; 1.4.2 Validation Set Results for the Gold Models; 1.5 Silver with Clusters; 1.5.1 Training Set Variable Importance; 1.5.2 Validation Set Results for the Silver Models; 1.6 Summary and Conclusions; References; 2 Impact of Credit Risk and Business Cycles on Momentum Returns; 2.1 Introduction |
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2.2 Literature Review2.2.1 The Persistence of Momentum Returns in Different Dimensions; 2.2.2 Momentum Returns and Credit Ratings; 2.2.3 Momentum Returns and Risk Factors; 2.3 Data; 2.3.1 Methods; 2.4 Empirical Findings; 2.4.1 Can the Fama-French Three Factors Explain Momentum Returns in Credit-Rated Stocks?; 2.4.2 Can Market States Explain the Momentum Returns in Credit-Rated Stocks?; 2.4.3 Can Macroeconomic Factors Explain the Momentum Returns in Credit-Rated Stocks?; 2.5 Conclusions; Appendix: S & P Credit Rating; References |
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3 Drivers of LBO Operating Performance: An Empirical Investigation in Asia3.1 Introduction; 3.2 Literature Review; 3.2.1 Tax Benefit; 3.2.2 Free Cash-Flow; 3.2.3 Ownership Structure; 3.2.4 Macroeconomic Factors; 3.3 Institutional Background of Emerging Economies: The Case of Asia; 3.3.1 Academic Background; 3.3.2 Institutional Background; 3.4 Data Sources and Descriptive Statistics; 3.4.1 Sample Description; 3.4.2 Benchmark Comparison; 3.4.3 Descriptive Statistics; 3.4.4 Analysis and Discussion; 3.5 Results; 3.5.1 OLS Model; 3.5.2 Introduction of LBO Dummy Variable |
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3.5.3 Introduction of Geographical Area Dummy Variables3.5.4 Geographical Areas and Governance (Table 3.8); 3.5.5 Efficiency and Profitability Impacts (Table 3.9); 3.6 Conclusion; References; 4 Time Varying Correlation: A Key Indicator in Finance; 4.1 Introduction; 4.2 Recent Literature; 4.3 The Correlation Measure; 4.3.1 Data Simulation; 4.3.2 Comparing the Correlation Estimators; 4.4 Measuring Correlation; 4.4.1 Stationarity of the Series; 4.4.2 Structural Breaks; 4.4.3 Correlations Between Commodities and Financial Markets; 4.4.4 Correlations Between Energy Commodities |
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4.5 Concluding RemarksReferences; 5 Measuring Model Risk in the European Energy Exchange; 5.1 Introduction and Background; 5.2 The Relative Measure of Model Risk; 5.3 Data and Preliminary Analysis; 5.4 Model Setting and Estimation; 5.4.1 The GARCH Methodology; 5.4.2 Dynamic Model Risk Quantification; 5.5 Empirical Results; 5.6 Conclusions and Future Research; References; Part II Pricing and Valuation; 6 Wine Futures: Pricing and Allocation as Levers Against Quality Uncertainty; 6.1 Introduction; 6.1.1 Winemaking Process and the Tasting Reviews; 6.2 Literature Review |
| Summary |
This handbook includes contributions related to optimization, pricing and valuation problems, risk modeling and decision making problems arising in global financial and commodity markets from the perspective of Operations Research and Management Science. The book is structured in three parts, emphasizing common methodological approaches arising in the areas of interest: - Part I: Optimization techniques - Part II: Pricing and Valuation - Part III: Risk Modeling <The book presents to a wide community of Academics and Practitioners a selection of theoretical and applied contributions on topics that have recently attracted increasing interest in commodity and financial markets. Within a structure based on the three parts, it presents recent state-of-the-art and original works related to: - The adoption of multi-criteria and dynamic optimization approaches in financial and insurance markets in presence of market stress and growing systemic risk; - Decision paradigms, based on behavioral finance or factor-based, or more classical stochastic optimization techniques, applied to portfolio selection problems including new asset classes such as alternative investments; - Risk measurement methodologies, including model risk assessment, recently applied to energy spot and future markets and new risk measures recently proposed to evaluate risk-reward trade-offs in global financial and commodity markets; and derivatives portfolio hedging and pricing methods recently put forward in the financial community in the aftermath of the global financial crisis |
| Bibliography |
Includes bibliographical references |
| Notes |
Online resource; title from PDF title page (EBSCO, viewed October 16, 2017) |
| Subject |
Commodity exchanges -- Handbooks, manuals, etc
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Commodity futures -- Handbooks, manuals, etc
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Financial futures -- Handbooks, manuals, etc
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Risk management -- Handbooks, manuals, etc
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Macroeconomics.
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Operational research.
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BUSINESS & ECONOMICS -- Finance.
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Commodity exchanges
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Commodity futures
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Financial futures
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Risk management
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| Genre/Form |
Electronic books
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handbooks.
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Handbooks and manuals
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Handbooks and manuals.
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Guides et manuels.
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| Form |
Electronic book
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| Author |
Consigli, Giorgio, editor.
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Stefani, Silvana, editor.
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Zambruno, Giovanni, editor.
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| ISBN |
9783319613208 |
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3319613200 |
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