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AISC: MODELING DEPENDENCE IN ECONOMETRICS

Economics

Business & Economics

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B2B GT

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B2B & B2C

In economics, many quantities are related to each other. Such economic relations are often much more complex than relations in science and engineering, where some quantities are independence and the relation between others can be well approximated by linear
functions. As a result of this complexity, when we apply traditional statistical techniques - developed for science and engineering - to process economic data, the inadequate treatment of dependence leads to misleading models and erroneous predictions. Some economists even blamed such inadequate treatment of dependence for the 2008 financial crisis.To make economic models more adequate, we need more accurate techniques for describing dependence. Such techniques are currently being developed. This book contains description of state-of-the-art techniques for modeling dependence and economic applications of
these techniques. Most of these research developments are centered around the notion of a copula - a general way of describing dependence in probability theory and statistics. To be even more adequate, many papers go beyond traditional copula techniques and
take into account, e.g., the dynamical (changing) character of the dependence in economics.

Modeling Dependence in Econometrics

POST SECONDARY FOUR YEAR

COLFR

COLSO

COLJR

COLSR

Duration

Duration Unit Of Measure

Transaction Type

Front Cover.
Other Frontmatter.
Editorial Board.
Title Page.
Copyright Page.
Preface.
Contents.
1: Keynote Paper.
2: Multi-level Conditional VaR Estimation in Dynamic Models.
3: Fundamental Theory.
4: The Effects of Management and Provision Accounts on Hedge Fund Returns &#x2013; Part I: The High Water Mark Scheme.
5: The Effects of Management and Provision Accounts on Hedge Fund Returns &#x2013; Part II: The Loss Carry Forward Scheme.
6: How to Detect Linear Dependence on the Copula Level?.
7: An Innovative Financial Time Series Model: The Geometric Process Model.
8: Residual Based Cusum Test for Parameter Change in AR-GARCH Models.
9: Dependence and Association Concepts through Copulas.
10: Pairs Trading via Three-Regime Threshold Autoregressive GARCH Models.
11: Testing Dependencies in Term Structure of Interest Rates.
12: Joint Distributions of Random Sets and Their Relation to Copulas.
13: Vine Copulas As a Way to Describe and Analyze Multi-Variate Dependence in Econometrics: Computational Motivation and Comparison with Bayesian Networks and Fuzzy Approaches.
14: Applications.
15: Extreme Value Copula Analysis of Dependences between Exchange Rates and Exports of Thailand.
16: Analysis of Volatility of and Dependence between Exchange Rate and Inflation Rate in Lao People&#x0027;s Democratic Republic Using Copula-Based GARCH Approach.
17: Modeling Dependence of Accident-Related Outcomes Using Pair Copula Constructions for Discrete Datas.
18: Dependence Analysis of Exchange Rate and International Trade of Thailand: Application of Vine Copulas.
19: A Vine Copula Approach for Analyzing Financial Risk and Co-movement of the Indonesian, Philippine and Thailand Stock Markets.
20: Studying Volatility and Dependency of Chinese Outbound Tourism Demand in Singapore, Malaysia, and Thailand: A Vine Copula Approach.
21: Vine Copula-Cross Entropy Evaluation of Dependence Structure and Financial Risk in Agricultural Commodity Index Returns.
22: A Study on Whether Economic Development and Urbanization of Areas Are Associated with Prevalence of Obesity in Chinese Adults: Findings from 2009 China Health and Nutrition Surveys.
23: Statistical Analysis of Political Cycles in Australian Stock Market Returns.
24: Dependence Structure between Crude Oil, Soybeans, and Palm Oil in ASEAN Region: Energy and Food Security Context.
25: Copula Based GARCH Dependence Model of Chinese and Korean Tourist Arrivals to Thailand: Implications for Risk Management.
26: Analyzing Relationship between Tourist Arrivals from China and India to Thailand Using Copula Based GARCH and Seasonal Pattern.
27: Modeling Dependency in Tourist Arrivals to Thailand from China, Korea, and Japan Using Vine Copulas.
28: Relationship between Exchange Rates, Palm Oil Prices, and Crude Oil Prices: A Vine Copula Based GARCH Approach.
29: An Analysis of Interdependencies among Energy, Biofuel, and Agricultural Markets Using Vine Copula Model.
30: An Analysis of Volatility and Dependence between Rubber Spot and Futures Prices Using Copula-Extreme Value Theory.
31: Effect of Markets Temperature on Stock-Price: Monte Carlo Simulation on Spin Model.
32: An Analysis of Relationship between Gold Price and U.S. Dollar Index by Using Bivariate Extreme Value Copulas.
33: An Integration of Eco-Health One-Health Transdisciplinary Approach and Bayesian Belief Network.
34: Factors Affecting Hospital Stay Involving Drunk Driving and Non-Drunk Driving in Phuket, Thailand.
35: How Macroeconomic Factors and International Prices Affect Agriculture Prices Volatility?-Evidence from GARCH-X Model.
36: Co-movement of Prices of Energy and Agricultural Commodities in Biofuel Era: A Period-GARCH Copula Approach.
37: Wage Determination and Compensating Wage Differentials in the Informal Sector.
38: Optimal Combination of Energy Sources for Electricity Generation in Thailand with Lessons from Japan Using Maximum Entropy.
39: Valuation of Interest Rate Derivatives under CSA Discounting.
40: Systemic Knowledge Synthesis for Product Recommendation.
Author Index.

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Modeling Dependence in Econometrics