Econometrics of Risk / / edited by Van-Nam Huynh, Vladik Kreinovich, Songsak Sriboonchitta, Komsan Suriya

• Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015
• Edizione: 1st ed. 2015.
• Descrizione fisica: 1 online resource (X, 498 p. 94 illus., 19 illus. in color.)
• Disciplina: 332
• Soggetto topico: Computational intelligence; Economics, Mathematical ; Econometrics; Quality control; Reliability; Industrial safety; Computational Intelligence; Quantitative Finance; Quality Control, Reliability, Safety and Risk
• Persona (resp. second.): HuynhVan-Nam; KreinovichVladik; SriboonchittaSongsak; SuriyaKomsan
• Note generali: Bibliographic Level Mode of Issuance: Monograph
• Nota di contenuto: Intro -- Preface -- Contents -- Part IFundamental Theory -- Challenges for Panel Financial Analysis -- 1 Introduction -- 2 Estimation of Panel Standard Errors -- 3 Multiple Equations Modeling -- 4 To Pool or Not to Pool -- 5 Aggregation and Predictions -- 6 Cross-Sectional Dependence -- 7 Multi-dimensional Statistics -- 8 Concluding Remarks -- References -- Noncausal Autoregressive Model in Application to Bitcoin/USD Exchange Rates -- 1 Introduction -- 2 The Bitcoin/USD Exchange Rate -- 2.1 Bitcoin Currency -- 2.2 Bitcoin Transactions -- 2.3 The Data -- 3 The Model -- 3.1 The Noncausal and Mixed Autoregressive Process -- 3.2 The Bubble Effect -- 3.3 Estimation and Inference -- 3.4 Forecasting -- 4 Application -- 4.1 ACF Analysis -- 4.2 Global and Local Trends -- 4.3 The Causal and Noncausal Components -- 4.4 Prediction -- 5 Conclusion -- References -- An Overview of the Black-Scholes-Merton Model After the 2008 Credit Crisis -- 1 Introduction -- 2 Credit Value Adjustment (CVA) and Debit Value Adjustment (DVA) -- 3 The Risk-Free Rate: The Proxies LIBOR Versus OIS -- 4 Collateral and Funding Costs -- 5 The FVA Debate -- 6 The BSM Model -- 6.1 The BSM Model Which Includes Collateral and Funding Costs -- 6.2 The BSM Model Which Includes CVA, DVA and FCA -- 7 Conclusion -- References -- What if We Only Have Approximate Stochastic Dominance? -- 1 Stochastic Dominance: Reminder and Formulation of the Problem -- 2 How to Make Decisions Under Approximate Stochastic Dominance: Analysis of the Problem -- 3 How to Make Decisions Under Approximate Stochastic Dominance: Main Result -- References -- From Mean and Median Income to the Most Adequate Way of Taking Inequality into Account -- 1 Mean Income, Median Income, What Next? -- 2 Analysis of the Problem and the Resulting Measure. ; 3 First Example of Using the New Measure of ``Average'' Income: Case of Low Inequality -- 4 Second Example of Using the New Measure of ``Average'' Income: Case of a Heavy-Tailed Distribution -- 5 Auxiliary Result: The New Measure of ``Average'' Income May Explain the Power-Law Character of Income Distribution -- References -- Belief Aggregation in Financial Markets and the Nature of Price Fluctuations -- 1 Introduction -- 2 Belief Aggregation -- 3 The Portfolio -- 4 The Nature of Price Fluctuations -- References -- The Dynamics of Hedge Fund Performance -- 1 Introduction -- 2 Fund Performance Dynamics -- 2.1 Performance and Ranking -- 2.2 Stochastic Migration and Migration Correlation -- 3 Application to Hedge Funds -- 3.1 Data -- 3.2 Summary Statistics of Returns -- 3.3 The Ratings -- 3.4 Time Homogeneous Transition Matrices -- 3.5 Time Heterogeneous Transition Matrices -- 3.6 Stochastic Transition -- 3.7 Duration Analysis -- 4 Conclusion -- References -- The Joint Belief Function and Shapley Value for the Joint Cooperative Game -- 1 Introduction -- 2 The Characterization of the Joint Belief Function of Discrete Random Set Vector -- 3 The Joint Cooperative Game -- 4 The Bivariate Shapley Value -- 4.1 The Bivariate Shapley Value Through the Cores of the Belief Function H -- 4.2 The Bivariate Shapley Value Through the Joint Game -- References -- Distortion Risk Measures Under Skew Normal Settings -- 1 Introduction -- 2 Distortion Risk Measures -- 3 A New Distortion Function Based on the Wang Transform -- 4 The Capital Asset Pricing Model -- 5 The Model for the Behavior of Stock Prices -- 6 Simulation Results -- 7 Conclusion -- References -- Towards Generalizing Bayesian Statistics: A Random Fuzzy Set Approach -- 1 Introduction -- 2 Coarsening Schemes for Experts' Knowledge -- 3 Random Sets -- 3.1 Finite Random Sets -- 3.2 Random Closed Sets. ; 3.3 Random Fuzzy Closed Sets -- 4 Concluding Remarks -- References -- Local Kendall's Tau -- 1 Introduction and Preliminaries -- 2 Uni-conditional Local Kendall's Tau -- 3 Bi-conditional Local Kendall's Tau -- 4 Pointwise Kendall's Tau -- References -- Estimation and Prediction Using Belief Functions: Application to Stochastic Frontier Analysis -- 1 Introduction -- 2 Inference and Prediction Using Belief Functions -- 2.1 Inference -- 2.2 Prediction -- 3 Application to Stochastic Frontier Analysis -- 3.1 Model and Inference -- 3.2 Simulation Experiments -- 4 Conclusions -- References -- The Classifier Chain Generalized Maximum Entropy Model for Multi-label Choice Problems -- 1 Introduction -- 2 The Single-Label GME Model -- 3 The Multi-label CC-GME Model -- 3.1 The CC Model -- 3.2 The CC-GME Model -- 3.3 Result Analysis -- 4 Monte-Carlo Experiment -- 4.1 Simulation -- 4.2 Results -- 5 Occupational Hazards Empirical Example -- 5.1 Data Description -- 5.2 Results -- 6 Concluding Remarks -- References -- Part IIApplications -- Asymmetric Volatility of Local Gold Prices in Malaysia -- 1 Introduction -- 2 Literature Review -- 3 Volatility Model -- 3.1 TGARCH Model -- 3.2 EGARCH Model -- 4 Empirical Analysis -- 4.1 Data -- 4.2 Descriptive Statistics -- 4.3 Econometrics Analysis -- 5 Conclusion -- References -- Quantile Regression Under Asymmetric Laplace Distribution in Capital Asset Pricing Model -- 1 Introduction -- 2 Quantile Regression Model -- 3 Validating Linear Quantile Models -- 4 An Application to the Stock Market -- 4.1 Capital Asset Pricing Model:CAPM -- 4.2 Beta estimation -- 4.3 Empirical Results -- 4.4 Measures the volatility of stock -- 5 Conclusions and Extension -- References -- Evaluation of Portfolio Returns in Fama-French Model Using Quantile Regression Under Asymmetric Laplace Distribution -- 1 Introduction. ; 2 Quantile Regression and Fama-French Model -- 2.1 Quantile Regression with an Asymmetric Laplace Distribution -- 2.2 Fama-French Three-Factor Model -- 3 Simulated Data for ALD -- 4 Application to Portfolio Evaluation -- 4.1 Model and Parameters Estimation -- 4.2 Experimental Results -- 4.3 In Sample prediction -- 5 Conclusions -- References -- Analysis of Branching Ratio of Telecommunication Stocks in Thailand Using Hawkes Process -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Hawkes Process -- 3.2 Parameter Estimation of Hawkes Process -- 3.3 Compensator of Hawkes Process -- 3.4 Goodness of fit -- 4 Empirical Results -- 5 Conclusion and Further Study -- References -- Forecasting Risk and Returns: CAPM Model with Belief Functions -- 1 Introduction -- 2 Maximum Likelihood Estimation of Capital Asset Pricing Model -- 3 Statistical Inference and Prediction Using Belief Functions -- 3.1 Belief Functions -- 3.2 Likelihood-based Belief Functions -- 3.3 Incorporating the Belief Functions -- 4 An Application to Stock Market -- 4.1 Data -- 5 Conclusions -- References -- Correlation Evaluation with Fuzzy Data and its Application in the Management Science -- 1 Introduction -- 2 Fuzzy Theory and Fuzzy Data -- 2.1 Continuous Fuzzy Data -- 2.2 Collecting Continuous Fuzzy Data -- 3 Fuzzy Correlation -- 4 Empirical Studies -- 5 Conclusions -- References -- Empirical Evidence Linking Futures Price Movements of Biofuel Crops and Conventional Energy Fuel -- 1 Introduction -- 2 Copula Based ARMAX-GARCH Models -- 2.1 ARMAX-GARCH Model -- 2.2 Copulas -- 2.3 Time-Varying Copulas -- 3 Vine Copulas -- 4 The Data and Empirical Results -- 4.1 The Data -- 4.2 The Results of ARMAX-GARCH Model -- 4.3 Results for the Static and Time-Varying C-Vine Copula -- 5 Forecasting of the ES and Optimal Portfolio -- 6 Conclusions -- References. ; Optimal Portfolio Selection Using Maximum Entropy Estimation Accounting for the Firm Specific Characteristics -- 1 Introduction -- 2 Literature Review -- 2.1 The Problem of Portfolio Selection Weights -- 2.2 The Firm Characteristics Influence on Optimal Weights -- 3 Methodology -- 3.1 Introduction to Maximum Entropy Method -- 3.2 The Maximum Entropy Method to Portfolio Selection Accounting for Firm Characteristics -- 3.3 Discussion of Advantage and Disadvantage -- 4 Empirical Application -- 4.1 Data Description -- 4.2 The Results of Out-of-Sample Forecasts -- 5 Conclusion -- References -- Risk, Return and International Portfolio Analysis: Entropy and Linear Belief Functions -- 1 Introduction -- 2 Methodology -- 2.1 Portfolio Selection Methods -- 2.2 Linear Belief Function -- 3 An Application to International Portfolio Evaluation -- 4 Conclusions -- References -- Forecasting Inbound Tourism Demand to China Using Time Series Models and Belief Functions -- 1 Introduction -- 2 Methodology -- 2.1 Time Series Models -- 2.2 Likelihood-Based Belief Function -- 3 Estimation and Comparison of Time-Series Models -- 3.1 Data Description -- 3.2 Empirical Results -- 4 Forecast Using the Belief Function Approach -- 5 Conclusions -- References -- Forecasting Tourist Arrivals to Thailand Using Belief Functions -- 1 Introduction -- 2 Definitions, Literature Reviews and Methodology -- 2.1 Basics of Belief Functions -- 2.2 Likelihood-Based Belief Function -- 2.3 Forecasting Using Belief Functions -- 2.4 Review of the Seasonal ARIMA Model -- 3 Application to Tourist Arrivals to Thailand -- 3.1 Data -- 3.2 SARIMA Models -- 3.3 Approach with Belief Functions -- 3.4 Forecasting Using Belief Functions -- 4 Discussion -- 4.1 Combining Historical Data with Expert Opinions -- 5 Concluding Remarks -- References. ; Copula Based Polychotomous Choice Selectivity Model: Application to Occupational Choice and Wage Determination of Older Workers.
• Sommario/riassunto: This edited book contains several state-of-the-art papers devoted to econometrics of risk. Some papers provide theoretical analysis of the corresponding mathematical, statistical, computational, and economical models. Other papers describe applications of the novel risk-related econometric techniques to real-life economic situations. The book presents new methods developed just recently, in particular, methods using non-Gaussian heavy-tailed distributions, methods using non-Gaussian copulas to properly take into account dependence between different quantities, methods taking into account imprecise ("fuzzy") expert knowledge, and many other innovative techniques. This versatile volume helps practitioners to learn how to apply new techniques of econometrics of risk, and researchers to further improve the existing models and to come up with new ideas on how to best take into account economic risks.
• Titolo autorizzato: Econometrics of risk
• ISBN: 3-319-13449-3
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910299700003321
• Lo trovi qui: Univ. Federico II
• Serie: Studies in Computational Intelligence, . 1860-949X ; ; 583