Computational optimization in economics and finance research compendium /:
Gespeichert in:
| Weitere Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Hauppauge, N.Y. :
Nova Science Publisher's,
©2013.
|
| Schriftenreihe: | Studies in financial optimization and risk management.
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | 1 online resource (viii, 218 pages) : illustrations |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 9781620819302 1620819309 |
Internformat
MARC
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| 245 | 0 | 0 | |a Computational optimization in economics and finance research compendium / |c editor, Constantin Zopounidis. |
| 264 | 1 | |a Hauppauge, N.Y. : |b Nova Science Publisher's, |c ©2013. | |
| 300 | |a 1 online resource (viii, 218 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 1 | |a Studies in financial optimization and risk management | |
| 504 | |a Includes bibliographical references and index. | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a COMPUTATIONAL OPTIMIZATION IN ECONOMICS AND FINANCE RESEARCH COMPENDIUM; COMPUTATIONAL OPTIMIZATION IN ECONOMICS AND FINANCE RESEARCH COMPENDIUM; CONTENTS; PREFACE; Chapter 1 A NOTE ON THE DIACHRONIC BEHAVIOUR OF THE OECD FORECASTS FOR GREECE; ABSTRACT; 1. INTRODUCTION; 2. DATA AND FORECASTS MEASURES; 3. EMPIRICAL RESULTS; CONCLUSION; APPENDIX A; Notes; REFERENCES; Chapter 2 A STUDY ON THE LONG-RUN BENEFITS OF DIVERSIFICATION IN THE STOCK MARKETS OF GREECE, THE UK AND THE US; ABSTRACT; I. INTRODUCTION; II. DATA; III. UNIT ROOT TESTS; IV. COINTEGRATION TESTS; Engle -- Granger Method | |
| 505 | 8 | |a Johansen MethodCONCLUSION; REFERENCES; Chapter 3 APPLICATION OF FEED-FORWARD NEURAL NETWORKS SMOOTHING TRANSITION AUTOREGRESSIVE MODELS IN STOCK RETURNS FORECASTING; ABSTRACT; 1. INTRODUCTION; 2. LITERATURE REVIEW; 3. METHODOLOGY; 3.1. STAR Models Specification and Estimation; 3.2. STAR Models Estimation Using Neural Networks Modeling; 3.3. Bootstrapping Regression; 4. DATA; 5. EMPIRICAL RESULTS; 6. RECOMMENDATIONS; CONCLUSION; APPENDIX A: DEFINITION OF DEPENDENT VARIABLES IN THE NONLINEAR PART OF STAR NEURAL NETWORKS; REFERENCES | |
| 505 | 8 | |a Chapter 4 SURVEYING STOCK MARKET FORECASTING TECHNIQUES -- PART I: CONVENTIONAL METHODSABSTRACT; 1. INTRODUCTI; 2. SURVEYED STOCK MARKETS; 3. INPUT VARIABLES; 4. MODELING TECHNIQUES; Data Preprocessing; Data Frequency and Size; Conventional Models; 5. BENCHMARK MODELS AND COMPARISONS; 6. PERFORMANCE EVALUATION; CONCLUSION; APPENDIX; REFERENCES; Chapter 5 A NOTE ON WHY THE GENERALIZED METHOD OF MOMENTS (GMM) ESTIMATOR IS GETTING MORE POPULAR IN BANKING STUDIES; ABSTRACT; 1. INTRODUCTION; 2. REASONS FOR GMM'S POPULARITY; 3. FORMULATIONS; CONCLUSION; ACKNOWLEDGMENTS; REFERENCES | |
| 505 | 8 | |a Chapter 6 ASSESSING THE MACROECONOMIC COMPETITIVENESS OF EUROPEAN COUNTRIES USING MULTICRITERIA ANALYSISABSTRACT; 1. INTRODUCTION; 2. LITERATURE REVIEW; 3. SAMPLE AND METHODOLOGY; 3.1. Sample and Variables; 4. RESULTS; 4.1. Scenario Design; CONCLUSION; REFERENCES; Chapter 7 A TOPOLOGICAL NETWORK ANALYSIS OF GREEK FIRMS; ABSTRACT; 1. INTRODUCTION AND MOTIVATION; 2. BASIC NETWORK TERMS AND METRICS; 3. FORMATION OF THE NETWORK; 4. NETWORK ANALYSIS FOR CONSTRUCTION FIRM NETWORKS; 5. COMPARISON WITH OTHER NETWORKS; CONCLUSION AND FURTHER RESEARCH; REFERENCES | |
| 505 | 8 | |a Chapter 8 AN EXECUTIVE PERSPECTIVE TO CATEGORY MANAGEMENT: THE CASE OF THE GREEK GROCERY RETAILERSABSTRACT; 1. INTRODUCTION; 2. LITERATURE REVIEW; 2.1. Development of Greek Grocery Retailing; 2.2. Category Management; 3. METHODOLOGY; 4. RESEARCH QUESTIONS; 5. CASES AND FINDINGS; 6.1. Definition of Category Management; 6.2. Motivation for Category Management; 6.3. Implementation of Category Management: ACNielsen Structure; 6.4. Implementation Difficulties; 6.5. Supplier Relations; 6.6. Outcomes; 6.7. Future of Category Management Initiatives; CONCLUSION; REFERENCES | |
| 650 | 0 | |a Business forecasting. | |
| 650 | 0 | |a Economic forecasting. |0 http://id.loc.gov/authorities/subjects/sh85040814 | |
| 650 | 0 | |a Mathematical optimization. |0 http://id.loc.gov/authorities/subjects/sh85082127 | |
| 650 | 6 | |a Prévision commerciale. | |
| 650 | 6 | |a Prévision économique. | |
| 650 | 6 | |a Optimisation mathématique. | |
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| 650 | 7 | |a BUSINESS & ECONOMICS |x Reference. |2 bisacsh | |
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| 700 | 1 | |a Zopounidis, Constantin. | |
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| 830 | 0 | |a Studies in financial optimization and risk management. | |
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| adam_text | |
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| building | Verbundindex |
| bvnumber | localFWS |
| callnumber-first | H - Social Science |
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| callnumber-raw | HD30.27 .C66 2013 |
| callnumber-search | HD30.27 .C66 2013 |
| callnumber-sort | HD 230.27 C66 42013 |
| callnumber-subject | HD - Industries, Land Use, Labor |
| collection | ZDB-4-EBU |
| contents | COMPUTATIONAL OPTIMIZATION IN ECONOMICS AND FINANCE RESEARCH COMPENDIUM; COMPUTATIONAL OPTIMIZATION IN ECONOMICS AND FINANCE RESEARCH COMPENDIUM; CONTENTS; PREFACE; Chapter 1 A NOTE ON THE DIACHRONIC BEHAVIOUR OF THE OECD FORECASTS FOR GREECE; ABSTRACT; 1. INTRODUCTION; 2. DATA AND FORECASTS MEASURES; 3. EMPIRICAL RESULTS; CONCLUSION; APPENDIX A; Notes; REFERENCES; Chapter 2 A STUDY ON THE LONG-RUN BENEFITS OF DIVERSIFICATION IN THE STOCK MARKETS OF GREECE, THE UK AND THE US; ABSTRACT; I. INTRODUCTION; II. DATA; III. UNIT ROOT TESTS; IV. COINTEGRATION TESTS; Engle -- Granger Method Johansen MethodCONCLUSION; REFERENCES; Chapter 3 APPLICATION OF FEED-FORWARD NEURAL NETWORKS SMOOTHING TRANSITION AUTOREGRESSIVE MODELS IN STOCK RETURNS FORECASTING; ABSTRACT; 1. INTRODUCTION; 2. LITERATURE REVIEW; 3. METHODOLOGY; 3.1. STAR Models Specification and Estimation; 3.2. STAR Models Estimation Using Neural Networks Modeling; 3.3. Bootstrapping Regression; 4. DATA; 5. EMPIRICAL RESULTS; 6. RECOMMENDATIONS; CONCLUSION; APPENDIX A: DEFINITION OF DEPENDENT VARIABLES IN THE NONLINEAR PART OF STAR NEURAL NETWORKS; REFERENCES Chapter 4 SURVEYING STOCK MARKET FORECASTING TECHNIQUES -- PART I: CONVENTIONAL METHODSABSTRACT; 1. INTRODUCTI; 2. SURVEYED STOCK MARKETS; 3. INPUT VARIABLES; 4. MODELING TECHNIQUES; Data Preprocessing; Data Frequency and Size; Conventional Models; 5. BENCHMARK MODELS AND COMPARISONS; 6. PERFORMANCE EVALUATION; CONCLUSION; APPENDIX; REFERENCES; Chapter 5 A NOTE ON WHY THE GENERALIZED METHOD OF MOMENTS (GMM) ESTIMATOR IS GETTING MORE POPULAR IN BANKING STUDIES; ABSTRACT; 1. INTRODUCTION; 2. REASONS FOR GMM'S POPULARITY; 3. FORMULATIONS; CONCLUSION; ACKNOWLEDGMENTS; REFERENCES Chapter 6 ASSESSING THE MACROECONOMIC COMPETITIVENESS OF EUROPEAN COUNTRIES USING MULTICRITERIA ANALYSISABSTRACT; 1. INTRODUCTION; 2. LITERATURE REVIEW; 3. SAMPLE AND METHODOLOGY; 3.1. Sample and Variables; 4. RESULTS; 4.1. Scenario Design; CONCLUSION; REFERENCES; Chapter 7 A TOPOLOGICAL NETWORK ANALYSIS OF GREEK FIRMS; ABSTRACT; 1. INTRODUCTION AND MOTIVATION; 2. BASIC NETWORK TERMS AND METRICS; 3. FORMATION OF THE NETWORK; 4. NETWORK ANALYSIS FOR CONSTRUCTION FIRM NETWORKS; 5. COMPARISON WITH OTHER NETWORKS; CONCLUSION AND FURTHER RESEARCH; REFERENCES Chapter 8 AN EXECUTIVE PERSPECTIVE TO CATEGORY MANAGEMENT: THE CASE OF THE GREEK GROCERY RETAILERSABSTRACT; 1. INTRODUCTION; 2. LITERATURE REVIEW; 2.1. Development of Greek Grocery Retailing; 2.2. Category Management; 3. METHODOLOGY; 4. RESEARCH QUESTIONS; 5. CASES AND FINDINGS; 6.1. Definition of Category Management; 6.2. Motivation for Category Management; 6.3. Implementation of Category Management: ACNielsen Structure; 6.4. Implementation Difficulties; 6.5. Supplier Relations; 6.6. Outcomes; 6.7. Future of Category Management Initiatives; CONCLUSION; REFERENCES |
| ctrlnum | (OCoLC)965198105 |
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| dewey-ones | 330 - Economics |
| dewey-raw | 330.01/5196 |
| dewey-search | 330.01/5196 |
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| discipline | Wirtschaftswissenschaften |
| format | Electronic eBook |
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| id | ZDB-4-EBU-ocn965198105 |
| illustrated | Illustrated |
| indexdate | 2024-11-26T14:49:25Z |
| institution | BVB |
| isbn | 9781620819302 1620819309 |
| language | English |
| oclc_num | 965198105 |
| open_access_boolean | |
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| owner_facet | MAIN DE-863 DE-BY-FWS |
| physical | 1 online resource (viii, 218 pages) : illustrations |
| psigel | ZDB-4-EBU |
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| publisher | Nova Science Publisher's, |
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| series | Studies in financial optimization and risk management. |
| series2 | Studies in financial optimization and risk management |
| spelling | Computational optimization in economics and finance research compendium / editor, Constantin Zopounidis. Hauppauge, N.Y. : Nova Science Publisher's, ©2013. 1 online resource (viii, 218 pages) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier Studies in financial optimization and risk management Includes bibliographical references and index. Print version record. COMPUTATIONAL OPTIMIZATION IN ECONOMICS AND FINANCE RESEARCH COMPENDIUM; COMPUTATIONAL OPTIMIZATION IN ECONOMICS AND FINANCE RESEARCH COMPENDIUM; CONTENTS; PREFACE; Chapter 1 A NOTE ON THE DIACHRONIC BEHAVIOUR OF THE OECD FORECASTS FOR GREECE; ABSTRACT; 1. INTRODUCTION; 2. DATA AND FORECASTS MEASURES; 3. EMPIRICAL RESULTS; CONCLUSION; APPENDIX A; Notes; REFERENCES; Chapter 2 A STUDY ON THE LONG-RUN BENEFITS OF DIVERSIFICATION IN THE STOCK MARKETS OF GREECE, THE UK AND THE US; ABSTRACT; I. INTRODUCTION; II. DATA; III. UNIT ROOT TESTS; IV. COINTEGRATION TESTS; Engle -- Granger Method Johansen MethodCONCLUSION; REFERENCES; Chapter 3 APPLICATION OF FEED-FORWARD NEURAL NETWORKS SMOOTHING TRANSITION AUTOREGRESSIVE MODELS IN STOCK RETURNS FORECASTING; ABSTRACT; 1. INTRODUCTION; 2. LITERATURE REVIEW; 3. METHODOLOGY; 3.1. STAR Models Specification and Estimation; 3.2. STAR Models Estimation Using Neural Networks Modeling; 3.3. Bootstrapping Regression; 4. DATA; 5. EMPIRICAL RESULTS; 6. RECOMMENDATIONS; CONCLUSION; APPENDIX A: DEFINITION OF DEPENDENT VARIABLES IN THE NONLINEAR PART OF STAR NEURAL NETWORKS; REFERENCES Chapter 4 SURVEYING STOCK MARKET FORECASTING TECHNIQUES -- PART I: CONVENTIONAL METHODSABSTRACT; 1. INTRODUCTI; 2. SURVEYED STOCK MARKETS; 3. INPUT VARIABLES; 4. MODELING TECHNIQUES; Data Preprocessing; Data Frequency and Size; Conventional Models; 5. BENCHMARK MODELS AND COMPARISONS; 6. PERFORMANCE EVALUATION; CONCLUSION; APPENDIX; REFERENCES; Chapter 5 A NOTE ON WHY THE GENERALIZED METHOD OF MOMENTS (GMM) ESTIMATOR IS GETTING MORE POPULAR IN BANKING STUDIES; ABSTRACT; 1. INTRODUCTION; 2. REASONS FOR GMM'S POPULARITY; 3. FORMULATIONS; CONCLUSION; ACKNOWLEDGMENTS; REFERENCES Chapter 6 ASSESSING THE MACROECONOMIC COMPETITIVENESS OF EUROPEAN COUNTRIES USING MULTICRITERIA ANALYSISABSTRACT; 1. INTRODUCTION; 2. LITERATURE REVIEW; 3. SAMPLE AND METHODOLOGY; 3.1. Sample and Variables; 4. RESULTS; 4.1. Scenario Design; CONCLUSION; REFERENCES; Chapter 7 A TOPOLOGICAL NETWORK ANALYSIS OF GREEK FIRMS; ABSTRACT; 1. INTRODUCTION AND MOTIVATION; 2. BASIC NETWORK TERMS AND METRICS; 3. FORMATION OF THE NETWORK; 4. NETWORK ANALYSIS FOR CONSTRUCTION FIRM NETWORKS; 5. COMPARISON WITH OTHER NETWORKS; CONCLUSION AND FURTHER RESEARCH; REFERENCES Chapter 8 AN EXECUTIVE PERSPECTIVE TO CATEGORY MANAGEMENT: THE CASE OF THE GREEK GROCERY RETAILERSABSTRACT; 1. INTRODUCTION; 2. LITERATURE REVIEW; 2.1. Development of Greek Grocery Retailing; 2.2. Category Management; 3. METHODOLOGY; 4. RESEARCH QUESTIONS; 5. CASES AND FINDINGS; 6.1. Definition of Category Management; 6.2. Motivation for Category Management; 6.3. Implementation of Category Management: ACNielsen Structure; 6.4. Implementation Difficulties; 6.5. Supplier Relations; 6.6. Outcomes; 6.7. Future of Category Management Initiatives; CONCLUSION; REFERENCES Business forecasting. Economic forecasting. http://id.loc.gov/authorities/subjects/sh85040814 Mathematical optimization. http://id.loc.gov/authorities/subjects/sh85082127 Prévision commerciale. Prévision économique. Optimisation mathématique. BUSINESS & ECONOMICS Economics General. bisacsh BUSINESS & ECONOMICS Reference. bisacsh Business forecasting fast Economic forecasting fast Mathematical optimization fast Zopounidis, Constantin. has work: Computational optimization in economics and finance research compendium (Text) https://id.oclc.org/worldcat/entity/E39PCGwKBcJgkgWMDmbHDxqhHC https://id.oclc.org/worldcat/ontology/hasWork Print version: Computational optimization in economics and finance research compendium. Hauppauge, N.Y. : Nova Science Publisher's, ©2013 9781620819289 (DLC) 2012017854 (OCoLC)792887859 Studies in financial optimization and risk management. FWS01 ZDB-4-EBU FWS_PDA_EBU https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1430458 Volltext |
| spellingShingle | Computational optimization in economics and finance research compendium / Studies in financial optimization and risk management. COMPUTATIONAL OPTIMIZATION IN ECONOMICS AND FINANCE RESEARCH COMPENDIUM; COMPUTATIONAL OPTIMIZATION IN ECONOMICS AND FINANCE RESEARCH COMPENDIUM; CONTENTS; PREFACE; Chapter 1 A NOTE ON THE DIACHRONIC BEHAVIOUR OF THE OECD FORECASTS FOR GREECE; ABSTRACT; 1. INTRODUCTION; 2. DATA AND FORECASTS MEASURES; 3. EMPIRICAL RESULTS; CONCLUSION; APPENDIX A; Notes; REFERENCES; Chapter 2 A STUDY ON THE LONG-RUN BENEFITS OF DIVERSIFICATION IN THE STOCK MARKETS OF GREECE, THE UK AND THE US; ABSTRACT; I. INTRODUCTION; II. DATA; III. UNIT ROOT TESTS; IV. COINTEGRATION TESTS; Engle -- Granger Method Johansen MethodCONCLUSION; REFERENCES; Chapter 3 APPLICATION OF FEED-FORWARD NEURAL NETWORKS SMOOTHING TRANSITION AUTOREGRESSIVE MODELS IN STOCK RETURNS FORECASTING; ABSTRACT; 1. INTRODUCTION; 2. LITERATURE REVIEW; 3. METHODOLOGY; 3.1. STAR Models Specification and Estimation; 3.2. STAR Models Estimation Using Neural Networks Modeling; 3.3. Bootstrapping Regression; 4. DATA; 5. EMPIRICAL RESULTS; 6. RECOMMENDATIONS; CONCLUSION; APPENDIX A: DEFINITION OF DEPENDENT VARIABLES IN THE NONLINEAR PART OF STAR NEURAL NETWORKS; REFERENCES Chapter 4 SURVEYING STOCK MARKET FORECASTING TECHNIQUES -- PART I: CONVENTIONAL METHODSABSTRACT; 1. INTRODUCTI; 2. SURVEYED STOCK MARKETS; 3. INPUT VARIABLES; 4. MODELING TECHNIQUES; Data Preprocessing; Data Frequency and Size; Conventional Models; 5. BENCHMARK MODELS AND COMPARISONS; 6. PERFORMANCE EVALUATION; CONCLUSION; APPENDIX; REFERENCES; Chapter 5 A NOTE ON WHY THE GENERALIZED METHOD OF MOMENTS (GMM) ESTIMATOR IS GETTING MORE POPULAR IN BANKING STUDIES; ABSTRACT; 1. INTRODUCTION; 2. REASONS FOR GMM'S POPULARITY; 3. FORMULATIONS; CONCLUSION; ACKNOWLEDGMENTS; REFERENCES Chapter 6 ASSESSING THE MACROECONOMIC COMPETITIVENESS OF EUROPEAN COUNTRIES USING MULTICRITERIA ANALYSISABSTRACT; 1. INTRODUCTION; 2. LITERATURE REVIEW; 3. SAMPLE AND METHODOLOGY; 3.1. Sample and Variables; 4. RESULTS; 4.1. Scenario Design; CONCLUSION; REFERENCES; Chapter 7 A TOPOLOGICAL NETWORK ANALYSIS OF GREEK FIRMS; ABSTRACT; 1. INTRODUCTION AND MOTIVATION; 2. BASIC NETWORK TERMS AND METRICS; 3. FORMATION OF THE NETWORK; 4. NETWORK ANALYSIS FOR CONSTRUCTION FIRM NETWORKS; 5. COMPARISON WITH OTHER NETWORKS; CONCLUSION AND FURTHER RESEARCH; REFERENCES Chapter 8 AN EXECUTIVE PERSPECTIVE TO CATEGORY MANAGEMENT: THE CASE OF THE GREEK GROCERY RETAILERSABSTRACT; 1. INTRODUCTION; 2. LITERATURE REVIEW; 2.1. Development of Greek Grocery Retailing; 2.2. Category Management; 3. METHODOLOGY; 4. RESEARCH QUESTIONS; 5. CASES AND FINDINGS; 6.1. Definition of Category Management; 6.2. Motivation for Category Management; 6.3. Implementation of Category Management: ACNielsen Structure; 6.4. Implementation Difficulties; 6.5. Supplier Relations; 6.6. Outcomes; 6.7. Future of Category Management Initiatives; CONCLUSION; REFERENCES Business forecasting. Economic forecasting. http://id.loc.gov/authorities/subjects/sh85040814 Mathematical optimization. http://id.loc.gov/authorities/subjects/sh85082127 Prévision commerciale. Prévision économique. Optimisation mathématique. BUSINESS & ECONOMICS Economics General. bisacsh BUSINESS & ECONOMICS Reference. bisacsh Business forecasting fast Economic forecasting fast Mathematical optimization fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh85040814 http://id.loc.gov/authorities/subjects/sh85082127 |
| title | Computational optimization in economics and finance research compendium / |
| title_auth | Computational optimization in economics and finance research compendium / |
| title_exact_search | Computational optimization in economics and finance research compendium / |
| title_full | Computational optimization in economics and finance research compendium / editor, Constantin Zopounidis. |
| title_fullStr | Computational optimization in economics and finance research compendium / editor, Constantin Zopounidis. |
| title_full_unstemmed | Computational optimization in economics and finance research compendium / editor, Constantin Zopounidis. |
| title_short | Computational optimization in economics and finance research compendium / |
| title_sort | computational optimization in economics and finance research compendium |
| topic | Business forecasting. Economic forecasting. http://id.loc.gov/authorities/subjects/sh85040814 Mathematical optimization. http://id.loc.gov/authorities/subjects/sh85082127 Prévision commerciale. Prévision économique. Optimisation mathématique. BUSINESS & ECONOMICS Economics General. bisacsh BUSINESS & ECONOMICS Reference. bisacsh Business forecasting fast Economic forecasting fast Mathematical optimization fast |
| topic_facet | Business forecasting. Economic forecasting. Mathematical optimization. Prévision commerciale. Prévision économique. Optimisation mathématique. BUSINESS & ECONOMICS Economics General. BUSINESS & ECONOMICS Reference. Business forecasting Economic forecasting Mathematical optimization |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1430458 |
| work_keys_str_mv | AT zopounidisconstantin computationaloptimizationineconomicsandfinanceresearchcompendium |