Computational techniques for banking and risk management /:
Gespeichert in:
| Weitere Verfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
[Hauppauge], New York :
Nova Publishers,
[2013]
|
| Schriftenreihe: | Studies in financial optimization and risk management.
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | 1 online resource |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 9781626185234 1626185239 |
Internformat
MARC
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| 245 | 0 | 0 | |a Computational techniques for banking and risk management / |c C. Zopounidis and M. Doumpos, editors. |
| 264 | 1 | |a [Hauppauge], New York : |b Nova Publishers, |c [2013] | |
| 300 | |a 1 online resource | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
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| 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 PREFACE ; Chapter 1 A CONTROL SYSTEMS APPROACH FOR CREDIT RISK SIMULATION AND CONTROL OF A LOAN PORTFOLIO ; ABSTRACT ; INTRODUCTION ; STUDY OF THE MODEL BASED ON THE LOAN CLASSIFICATION BY REPAYMENT STATUS ; Model Description ; Model Identification ; System Stability and Steady State Values ; Simulation Results ; STUDY OF THE MODEL BASED ON THE LOAN CLASSIFICATION BY RATING ; Model Description ; Model Identification ; Definition and Solution of the Open Loop Optimal Control Problem ; Open Loop Solution -- Case Study ; CONCLUSION ; REFERENCES. | |
| 505 | 8 | |a Chapter 2 MONEY LAUNDERING (ML) POLICIES IN THE GREEK BANKING SECTOR AND PERSPECTIVES RELATED TO AN EFFECTIVE CONFRONTATION FRAMEWORK ABSTRACT ; 1. INTRODUCTION ; 2. DETERMINATION OF THE PROBLEM OF MONEY LAUNDERING AND THE INTERNATIONAL EXPERIENCE ; 3. METHODOLOGY ; 4. ML FRAMEWORK ; 4.1. Definition of ML ; 4.2. The Implications of ML PHenomenon ; 4.3. ML Stages ; Stage L: The stage of "placement" ; Stage LI: The stage of "layering" ; Stage LII: The stage of "integration" ; 4.4. ML Sources ; 4.5. Off-Shore Companies and ML; 5. AWARENESS AGAINST MLPHENOMENON. | |
| 505 | 8 | |a 6. APPLICATION OF THE POLICIES AGAINST MLIN THE GREEK BANKING SECTOR 6.1. The Greek Regulatory Framework against ML; 6.2. Enrollment of the Greek Regulatory Framework against ML: The Case of "Piraeus Bank" ; 6.3. Investigations on the Spot and Sanctions Enforced from Bank of Greece ; CONCLUSION ; The Erosive Influence of Organized Crime to the Society ; International Economy and ML ; General Conclusion-the Greek Case ; REFERENCES ; Other Relevant References ; Web Resources ; Chapter 3 ON THE NELSON-SIEGEL AND GAMTAUX YIELD CURVE MODELS ; ABSTRACT ; 1. INTRODUCTION ; 2. YIELD CURVES. | |
| 505 | 8 | |a 3. PARSIMONIOUS METHODS 3.1. The Nelson-Siegel Method ; 3.2. The Extended Nelson-Siegel Method ; 3.3. The Gamtaux Method ; 3.4. The Extended Gamtaux Method ; 3.5. Parameter Estimation; 4. RESULTS ; CONCLUSION ; REFERENCES ; Chapter 4 MEAN VARIANCE PORTFOLIO SELECTION SUBJECT TO VALUE-AT-RISK CONSTRAINTS APPLIED TO REAL STOCK MARKET DATA ; ABSTRACT ; 1. INTRODUCTION; 2. THEORETICAL REVIEW OF THE INTERACTION BETWEEN THE VAR AND THE MEAN-VARIANCE MODEL ; 3. COMPUTATIONAL STUDY WITH REAL STOCKMARKET DATA INPUTS ; 3.1. Data and Optimization Tool Description ; 3.2. Results. | |
| 505 | 8 | |a 3.2.1. Efficient Frontier 3.2.2. Sensitivity to Value Change ; 3.2.3. Sensitivity to Alpha Value Change ; 3.2.4. Tangent Portfolio ; CONCLUSION ; REFERENCES ; Chapter 5 EVALUATION OF BANK EFFICIENCY WITH THE DEA APPROACH: A COMPARISON OF EUROPEAN COMMERCIAL BANKS ; ABSTRACT ; 1. INTRODUCTION ; Financial Institutions in the Light of the Financial Crisis ; Evaluating Bank Efficiency ; 2. LITERATURE REVIEW ; Introduction and Background ; The Measuring of Efficiency in Banking Sector -- Empirical Studies ; 3. DATA AND METHODOLOGY ; Data Envelopment Analysis ; Data and Variables. | |
| 650 | 0 | |a Bank management |x Mathematical models. | |
| 650 | 0 | |a Banks and banking |x Mathematical models. | |
| 650 | 0 | |a Financial risk |x Mathematical models. | |
| 650 | 0 | |a Decision making |x Mathematical models. |0 http://id.loc.gov/authorities/subjects/sh85036200 | |
| 650 | 6 | |a Banques |x Gestion |x Modèles mathématiques. | |
| 650 | 6 | |a Risque financier |x Modèles mathématiques. | |
| 650 | 6 | |a Prise de décision |x Modèles mathématiques. | |
| 650 | 7 | |a BUSINESS & ECONOMICS |x Banks & Banking. |2 bisacsh | |
| 650 | 7 | |a Bank management |x Mathematical models |2 fast | |
| 650 | 7 | |a Banks and banking |x Mathematical models |2 fast | |
| 650 | 7 | |a Decision making |x Mathematical models |2 fast | |
| 700 | 1 | |a Zopounidis, Constantin, |e editor. | |
| 700 | 1 | |a Doumpos, Michael, |e editor. | |
| 758 | |i has work: |a Computational techniques for banking and risk management (Text) |1 https://id.oclc.org/worldcat/entity/E39PCGRjFMyBD6wKQT6tVpw8cq |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 0 | 8 | |i Print version: |t Computational techniques for banking and risk management. |d [Hauppauge], New York : Nova Publishers, [2013] |z 9781626185227 |w (DLC) 2013011837 |
| 830 | 0 | |a Studies in financial optimization and risk management. |0 http://id.loc.gov/authorities/names/no2012135642 | |
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| adam_text | |
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| author2_role | edt edt |
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| author_facet | Zopounidis, Constantin Doumpos, Michael |
| building | Verbundindex |
| bvnumber | localFWS |
| callnumber-first | H - Social Science |
| callnumber-label | HG1615 |
| callnumber-raw | HG1615 |
| callnumber-search | HG1615 |
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| contents | PREFACE ; Chapter 1 A CONTROL SYSTEMS APPROACH FOR CREDIT RISK SIMULATION AND CONTROL OF A LOAN PORTFOLIO ; ABSTRACT ; INTRODUCTION ; STUDY OF THE MODEL BASED ON THE LOAN CLASSIFICATION BY REPAYMENT STATUS ; Model Description ; Model Identification ; System Stability and Steady State Values ; Simulation Results ; STUDY OF THE MODEL BASED ON THE LOAN CLASSIFICATION BY RATING ; Model Description ; Model Identification ; Definition and Solution of the Open Loop Optimal Control Problem ; Open Loop Solution -- Case Study ; CONCLUSION ; REFERENCES. Chapter 2 MONEY LAUNDERING (ML) POLICIES IN THE GREEK BANKING SECTOR AND PERSPECTIVES RELATED TO AN EFFECTIVE CONFRONTATION FRAMEWORK ABSTRACT ; 1. INTRODUCTION ; 2. DETERMINATION OF THE PROBLEM OF MONEY LAUNDERING AND THE INTERNATIONAL EXPERIENCE ; 3. METHODOLOGY ; 4. ML FRAMEWORK ; 4.1. Definition of ML ; 4.2. The Implications of ML PHenomenon ; 4.3. ML Stages ; Stage L: The stage of "placement" ; Stage LI: The stage of "layering" ; Stage LII: The stage of "integration" ; 4.4. ML Sources ; 4.5. Off-Shore Companies and ML; 5. AWARENESS AGAINST MLPHENOMENON. 6. APPLICATION OF THE POLICIES AGAINST MLIN THE GREEK BANKING SECTOR 6.1. The Greek Regulatory Framework against ML; 6.2. Enrollment of the Greek Regulatory Framework against ML: The Case of "Piraeus Bank" ; 6.3. Investigations on the Spot and Sanctions Enforced from Bank of Greece ; CONCLUSION ; The Erosive Influence of Organized Crime to the Society ; International Economy and ML ; General Conclusion-the Greek Case ; REFERENCES ; Other Relevant References ; Web Resources ; Chapter 3 ON THE NELSON-SIEGEL AND GAMTAUX YIELD CURVE MODELS ; ABSTRACT ; 1. INTRODUCTION ; 2. YIELD CURVES. 3. PARSIMONIOUS METHODS 3.1. The Nelson-Siegel Method ; 3.2. The Extended Nelson-Siegel Method ; 3.3. The Gamtaux Method ; 3.4. The Extended Gamtaux Method ; 3.5. Parameter Estimation; 4. RESULTS ; CONCLUSION ; REFERENCES ; Chapter 4 MEAN VARIANCE PORTFOLIO SELECTION SUBJECT TO VALUE-AT-RISK CONSTRAINTS APPLIED TO REAL STOCK MARKET DATA ; ABSTRACT ; 1. INTRODUCTION; 2. THEORETICAL REVIEW OF THE INTERACTION BETWEEN THE VAR AND THE MEAN-VARIANCE MODEL ; 3. COMPUTATIONAL STUDY WITH REAL STOCKMARKET DATA INPUTS ; 3.1. Data and Optimization Tool Description ; 3.2. Results. 3.2.1. Efficient Frontier 3.2.2. Sensitivity to Value Change ; 3.2.3. Sensitivity to Alpha Value Change ; 3.2.4. Tangent Portfolio ; CONCLUSION ; REFERENCES ; Chapter 5 EVALUATION OF BANK EFFICIENCY WITH THE DEA APPROACH: A COMPARISON OF EUROPEAN COMMERCIAL BANKS ; ABSTRACT ; 1. INTRODUCTION ; Financial Institutions in the Light of the Financial Crisis ; Evaluating Bank Efficiency ; 2. LITERATURE REVIEW ; Introduction and Background ; The Measuring of Efficiency in Banking Sector -- Empirical Studies ; 3. DATA AND METHODOLOGY ; Data Envelopment Analysis ; Data and Variables. |
| ctrlnum | (OCoLC)855022898 |
| dewey-full | 332.1068/1 |
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| dewey-ones | 332 - Financial economics |
| dewey-raw | 332.1068/1 |
| dewey-search | 332.1068/1 |
| dewey-sort | 3332.1068 11 |
| dewey-tens | 330 - Economics |
| discipline | Wirtschaftswissenschaften |
| format | Electronic eBook |
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| illustrated | Not Illustrated |
| indexdate | 2024-11-27T13:25:28Z |
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| isbn | 9781626185234 1626185239 |
| language | English |
| lccn | 2020677472 |
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| series | Studies in financial optimization and risk management. |
| series2 | Studies in financial optimization and risk management |
| spelling | Computational techniques for banking and risk management / C. Zopounidis and M. Doumpos, editors. [Hauppauge], New York : Nova Publishers, [2013] 1 online resource 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. PREFACE ; Chapter 1 A CONTROL SYSTEMS APPROACH FOR CREDIT RISK SIMULATION AND CONTROL OF A LOAN PORTFOLIO ; ABSTRACT ; INTRODUCTION ; STUDY OF THE MODEL BASED ON THE LOAN CLASSIFICATION BY REPAYMENT STATUS ; Model Description ; Model Identification ; System Stability and Steady State Values ; Simulation Results ; STUDY OF THE MODEL BASED ON THE LOAN CLASSIFICATION BY RATING ; Model Description ; Model Identification ; Definition and Solution of the Open Loop Optimal Control Problem ; Open Loop Solution -- Case Study ; CONCLUSION ; REFERENCES. Chapter 2 MONEY LAUNDERING (ML) POLICIES IN THE GREEK BANKING SECTOR AND PERSPECTIVES RELATED TO AN EFFECTIVE CONFRONTATION FRAMEWORK ABSTRACT ; 1. INTRODUCTION ; 2. DETERMINATION OF THE PROBLEM OF MONEY LAUNDERING AND THE INTERNATIONAL EXPERIENCE ; 3. METHODOLOGY ; 4. ML FRAMEWORK ; 4.1. Definition of ML ; 4.2. The Implications of ML PHenomenon ; 4.3. ML Stages ; Stage L: The stage of "placement" ; Stage LI: The stage of "layering" ; Stage LII: The stage of "integration" ; 4.4. ML Sources ; 4.5. Off-Shore Companies and ML; 5. AWARENESS AGAINST MLPHENOMENON. 6. APPLICATION OF THE POLICIES AGAINST MLIN THE GREEK BANKING SECTOR 6.1. The Greek Regulatory Framework against ML; 6.2. Enrollment of the Greek Regulatory Framework against ML: The Case of "Piraeus Bank" ; 6.3. Investigations on the Spot and Sanctions Enforced from Bank of Greece ; CONCLUSION ; The Erosive Influence of Organized Crime to the Society ; International Economy and ML ; General Conclusion-the Greek Case ; REFERENCES ; Other Relevant References ; Web Resources ; Chapter 3 ON THE NELSON-SIEGEL AND GAMTAUX YIELD CURVE MODELS ; ABSTRACT ; 1. INTRODUCTION ; 2. YIELD CURVES. 3. PARSIMONIOUS METHODS 3.1. The Nelson-Siegel Method ; 3.2. The Extended Nelson-Siegel Method ; 3.3. The Gamtaux Method ; 3.4. The Extended Gamtaux Method ; 3.5. Parameter Estimation; 4. RESULTS ; CONCLUSION ; REFERENCES ; Chapter 4 MEAN VARIANCE PORTFOLIO SELECTION SUBJECT TO VALUE-AT-RISK CONSTRAINTS APPLIED TO REAL STOCK MARKET DATA ; ABSTRACT ; 1. INTRODUCTION; 2. THEORETICAL REVIEW OF THE INTERACTION BETWEEN THE VAR AND THE MEAN-VARIANCE MODEL ; 3. COMPUTATIONAL STUDY WITH REAL STOCKMARKET DATA INPUTS ; 3.1. Data and Optimization Tool Description ; 3.2. Results. 3.2.1. Efficient Frontier 3.2.2. Sensitivity to Value Change ; 3.2.3. Sensitivity to Alpha Value Change ; 3.2.4. Tangent Portfolio ; CONCLUSION ; REFERENCES ; Chapter 5 EVALUATION OF BANK EFFICIENCY WITH THE DEA APPROACH: A COMPARISON OF EUROPEAN COMMERCIAL BANKS ; ABSTRACT ; 1. INTRODUCTION ; Financial Institutions in the Light of the Financial Crisis ; Evaluating Bank Efficiency ; 2. LITERATURE REVIEW ; Introduction and Background ; The Measuring of Efficiency in Banking Sector -- Empirical Studies ; 3. DATA AND METHODOLOGY ; Data Envelopment Analysis ; Data and Variables. Bank management Mathematical models. Banks and banking Mathematical models. Financial risk Mathematical models. Decision making Mathematical models. http://id.loc.gov/authorities/subjects/sh85036200 Banques Gestion Modèles mathématiques. Risque financier Modèles mathématiques. Prise de décision Modèles mathématiques. BUSINESS & ECONOMICS Banks & Banking. bisacsh Bank management Mathematical models fast Banks and banking Mathematical models fast Decision making Mathematical models fast Zopounidis, Constantin, editor. Doumpos, Michael, editor. has work: Computational techniques for banking and risk management (Text) https://id.oclc.org/worldcat/entity/E39PCGRjFMyBD6wKQT6tVpw8cq https://id.oclc.org/worldcat/ontology/hasWork Print version: Computational techniques for banking and risk management. [Hauppauge], New York : Nova Publishers, [2013] 9781626185227 (DLC) 2013011837 Studies in financial optimization and risk management. http://id.loc.gov/authorities/names/no2012135642 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=620134 Volltext |
| spellingShingle | Computational techniques for banking and risk management / Studies in financial optimization and risk management. PREFACE ; Chapter 1 A CONTROL SYSTEMS APPROACH FOR CREDIT RISK SIMULATION AND CONTROL OF A LOAN PORTFOLIO ; ABSTRACT ; INTRODUCTION ; STUDY OF THE MODEL BASED ON THE LOAN CLASSIFICATION BY REPAYMENT STATUS ; Model Description ; Model Identification ; System Stability and Steady State Values ; Simulation Results ; STUDY OF THE MODEL BASED ON THE LOAN CLASSIFICATION BY RATING ; Model Description ; Model Identification ; Definition and Solution of the Open Loop Optimal Control Problem ; Open Loop Solution -- Case Study ; CONCLUSION ; REFERENCES. Chapter 2 MONEY LAUNDERING (ML) POLICIES IN THE GREEK BANKING SECTOR AND PERSPECTIVES RELATED TO AN EFFECTIVE CONFRONTATION FRAMEWORK ABSTRACT ; 1. INTRODUCTION ; 2. DETERMINATION OF THE PROBLEM OF MONEY LAUNDERING AND THE INTERNATIONAL EXPERIENCE ; 3. METHODOLOGY ; 4. ML FRAMEWORK ; 4.1. Definition of ML ; 4.2. The Implications of ML PHenomenon ; 4.3. ML Stages ; Stage L: The stage of "placement" ; Stage LI: The stage of "layering" ; Stage LII: The stage of "integration" ; 4.4. ML Sources ; 4.5. Off-Shore Companies and ML; 5. AWARENESS AGAINST MLPHENOMENON. 6. APPLICATION OF THE POLICIES AGAINST MLIN THE GREEK BANKING SECTOR 6.1. The Greek Regulatory Framework against ML; 6.2. Enrollment of the Greek Regulatory Framework against ML: The Case of "Piraeus Bank" ; 6.3. Investigations on the Spot and Sanctions Enforced from Bank of Greece ; CONCLUSION ; The Erosive Influence of Organized Crime to the Society ; International Economy and ML ; General Conclusion-the Greek Case ; REFERENCES ; Other Relevant References ; Web Resources ; Chapter 3 ON THE NELSON-SIEGEL AND GAMTAUX YIELD CURVE MODELS ; ABSTRACT ; 1. INTRODUCTION ; 2. YIELD CURVES. 3. PARSIMONIOUS METHODS 3.1. The Nelson-Siegel Method ; 3.2. The Extended Nelson-Siegel Method ; 3.3. The Gamtaux Method ; 3.4. The Extended Gamtaux Method ; 3.5. Parameter Estimation; 4. RESULTS ; CONCLUSION ; REFERENCES ; Chapter 4 MEAN VARIANCE PORTFOLIO SELECTION SUBJECT TO VALUE-AT-RISK CONSTRAINTS APPLIED TO REAL STOCK MARKET DATA ; ABSTRACT ; 1. INTRODUCTION; 2. THEORETICAL REVIEW OF THE INTERACTION BETWEEN THE VAR AND THE MEAN-VARIANCE MODEL ; 3. COMPUTATIONAL STUDY WITH REAL STOCKMARKET DATA INPUTS ; 3.1. Data and Optimization Tool Description ; 3.2. Results. 3.2.1. Efficient Frontier 3.2.2. Sensitivity to Value Change ; 3.2.3. Sensitivity to Alpha Value Change ; 3.2.4. Tangent Portfolio ; CONCLUSION ; REFERENCES ; Chapter 5 EVALUATION OF BANK EFFICIENCY WITH THE DEA APPROACH: A COMPARISON OF EUROPEAN COMMERCIAL BANKS ; ABSTRACT ; 1. INTRODUCTION ; Financial Institutions in the Light of the Financial Crisis ; Evaluating Bank Efficiency ; 2. LITERATURE REVIEW ; Introduction and Background ; The Measuring of Efficiency in Banking Sector -- Empirical Studies ; 3. DATA AND METHODOLOGY ; Data Envelopment Analysis ; Data and Variables. Bank management Mathematical models. Banks and banking Mathematical models. Financial risk Mathematical models. Decision making Mathematical models. http://id.loc.gov/authorities/subjects/sh85036200 Banques Gestion Modèles mathématiques. Risque financier Modèles mathématiques. Prise de décision Modèles mathématiques. BUSINESS & ECONOMICS Banks & Banking. bisacsh Bank management Mathematical models fast Banks and banking Mathematical models fast Decision making Mathematical models fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh85036200 |
| title | Computational techniques for banking and risk management / |
| title_auth | Computational techniques for banking and risk management / |
| title_exact_search | Computational techniques for banking and risk management / |
| title_full | Computational techniques for banking and risk management / C. Zopounidis and M. Doumpos, editors. |
| title_fullStr | Computational techniques for banking and risk management / C. Zopounidis and M. Doumpos, editors. |
| title_full_unstemmed | Computational techniques for banking and risk management / C. Zopounidis and M. Doumpos, editors. |
| title_short | Computational techniques for banking and risk management / |
| title_sort | computational techniques for banking and risk management |
| topic | Bank management Mathematical models. Banks and banking Mathematical models. Financial risk Mathematical models. Decision making Mathematical models. http://id.loc.gov/authorities/subjects/sh85036200 Banques Gestion Modèles mathématiques. Risque financier Modèles mathématiques. Prise de décision Modèles mathématiques. BUSINESS & ECONOMICS Banks & Banking. bisacsh Bank management Mathematical models fast Banks and banking Mathematical models fast Decision making Mathematical models fast |
| topic_facet | Bank management Mathematical models. Banks and banking Mathematical models. Financial risk Mathematical models. Decision making Mathematical models. Banques Gestion Modèles mathématiques. Risque financier Modèles mathématiques. Prise de décision Modèles mathématiques. BUSINESS & ECONOMICS Banks & Banking. Bank management Mathematical models Banks and banking Mathematical models Decision making Mathematical models |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=620134 |
| work_keys_str_mv | AT zopounidisconstantin computationaltechniquesforbankingandriskmanagement AT doumposmichael computationaltechniquesforbankingandriskmanagement |