Adaptive Information Systems And Modelling in Economics And Management Science: Taudes, Alfred : 9783211206843: Book: Business & Economics: eCampus.com

List of Contributors

(2)

Introduction General scientific concept: aims of SFB 010

(6)

I Modeling Consumer Behavior

(50)

Basic Concepts and a Discrete-Time Model

(22)

1 Purpose and Modules of the Artificial Consumer Market as a Simulation Environment

(2)

2 The ACM Macro Structure

(2)

3 Set Theory, Brand Choice, (Dis)satisfaction and Adaptive Preferences

(2)

4 The ACM Micro Structure: Tracing the Individual Consumer

(5)

5 A Formal Description of the Discrete-Time Model

(1)

6 Attitude Formation

(3)

7 Dynamics of Perceptions

(2)

8 Measuring the State of a Consumer

(3)

9 Choice of a Produce 4i

10 Word-of-mouth communication

(2)

A Continuous-Time ACM Model and Experiment

(12)

1 Description of the Continuous Artificial Consumer Market (CACM)

(5)

1.1 Dynamics of the Perceptions

(3)

1.2 Ideal-Point Model

(1)

2 Application and Results

(2)

Experimental Market Scenario and Model Calibration

(2)

2.7 Maximizing Profits under Alternative Advertising Impact Functions

(5)

Capturing Unobserved Consumer Heterogeneity Using the Bayesian Heterogeneity Model

(14)

1 Introduction

(1)

2 The General Heterogeneity Model

(6)

2.1 Bayesian Estimation of the Heterogeneity Model under Heterogeneous Variances

(4)

2.2 Bayesian Model Comparison through Model Likelihoods

(1)

3 An Illustrative Application from Conjoint Analysis

(4)

3.1 The Data

(1)

3.2 The Design Matrix

(1)

3.3 Model Selection

(1)

3.4 Model Identification for the Selected Model

(2)

4 Summary and Outlook

(4)

II Modeling Financial Markets

(42)

Non-linear Volatility Modeling in Classical and Bayesian Frameworks with Applications to Risk Management

(26)

1 Introduction

(2)

2 Description of Models

(2)

3 Data Sets

(1)

4 Maximum Likelihood Framework

(8)

4.1 Estimation of Models

(1)

4.2 Out-of-Sample Loss Function Performance

(4)

4.3 VaR Application

(3)

5 Bayesian Approach

(8)

5.1 Basic Concepts and Notations

(1)

5.2 Priors

(1)

5.3 MCMC Posterior Simulation

(1)

5.4 Bayesian Comparison Results

(3)

6 Discussion and Conclusions

(6)

Expectation Formation and Learning in Adaptive Capital Market Models

(14)

1 Introduction

(2)

2 A Basic Capital Market Model

101

(2)

3 Learning and Stability for the Homogeneous Agent Model

103

(3)

3.1 Sample Autocorrelation Learning

103

(2)

3.2 Learning by Exponential Smoothing

105

(1)

4 Consistent Expectations Equilibria

106

(2)

5 Adaptive Belief Systems

108

(2)

6 Conclusions and Discussion

110

(3)

III Agent-Based Simulation Models

113

(106)

The Artificial Economy: A Generic Simulation Environment for Heterogeneous Agents

115

(12)

1 Introduction

115

(1)

2 The Simulation Manager

116

(3)

2.1 A Typical Simulation Cycle

116

(1)

2.2 Using XML for Simulation Settings

117

(2)

3 Agent Specification

119

(3)

3.1 Wrapping Agents

119

(1)

3.2 flow Agents Are Controlled during Simulations

120

(1)

3.3 Using XML for Defining Agent Interfaces

121

(1)

4 Communication Structures

122

(1)

5 Dynamic Settings

123

(1)

6 Control Issues

123

(1)

7 Summary

124

(3)

Disruptive Technologies: the Threat and its Defense

127

(18)

1 Introduction

127

(2)

2 Model

129

(3)

3 Simulation Setup and Experimental Design

132

(3)

4 Results

135

(3)

5 Defending Disruption

138

(3)

5.1 Model Extensions

139

(1)

5.2 Experiments and Results

140

(1)

6 Conclusions

141

(4)

Agent-Based Simulation of Power Markets

145

(14)

1 Introduction

145

(1)

2 Market agent

146

(1)

3 The Aggregated Demand�The Consumer

147

(2)

4 Modeling of the Producers

149

(3)

5 Simulation of the Austrian Electricity Market

152

(3)

6 Conclusion and Outlook

155

(4)

A Simulation Model of Coupled Consumer and Financial Markets

159

(36)

1 Introduction

159

(2)

2 Overview of Results

161

(3)

2.1 Integration and Stochasticity

161

(1)

2.2 Bounded Rationality and Information Usage

162

(1)

2.3 Validation

162

(1)

2.4 Fundamental Value and Stock Price Inflation

163

(1)

2.5 Managerial Compensation

163

(1)

3 The Integrated Markets Model

164

(3)

3.1 The Consumer Market

164

(2)

3.2 The Financial Market

166

(1)

4 Model Validation

167

(11)

4.1 Model Parameters

168

(1)

4.2 The Metropolis Algorithm

169

(1)

4.3 Markov Chain Model Exploration

170

(3)

4.4 Ideal Parameters

173

(3)

4.5 Discussion

176

(2)

5 Share Price Inflation and Product Hype

178

(4)

5.1 Hypist Traders

178

(1)

5.2 Simulation Results

179

(2)

5.3 Discussion

181

(1)

6 Managerial Compensation

182

(7)

6.1 Compensation in the Integrated Markets Model

183

(1)

6.2 Risk Aversion

183

(1)

6.3 Simulation Results

184

(4)

6.4 Discussion

188

(1)

7 Conclusions

189

(6)

Product Diversification in an Artificial Strategy Environment

195

(24)

1 Introduction

195

(1)

2 Diversification Strategies

196

(4)

3 The Artificial Strategy Environment

200

(5)

3.1 Internal Factors

200

(2)

3.2 External Factors

202

(3)

3.3 Cash Flow and Investment

205

(1)

4 Simulation Experiments and Results

205

(5)

5 Conclusions and Further Research

210

(9)

IV Statistical Modeling and Software Development

219

Parameter Estimation and Forecasting under Asymmetric Loss

221

(12)

1 Introduction

221

(1)

2 Concept

222

(2)

3 Location estimator

224

(4)

4 Linear Regression

228

(5)

Identification of multivariate state-space systems

233

(10)

1 Introduction

233

(1)

2 ARX, ARMAX and State-Space Systems

233

(2)

3 Parameterizations of State-Space Systems

235

(4)

3.1 Data Driven Local Coordinates (DDLC)

238

(1)

3.2 Separable Least Squares Data Driven Local Coordinates

239

(1)

3.3 Orthogonal Data Driven Local Coordinates (orthoDDLC)

239

(1)

4 Future Research Topics

239

(4)

Factor Models for Multivariate Time Series

243

(10)

1 Introduction

243

(1)

2 The Basic Framework

243

(2)

3 Quasi-Static Principal Components Analysis (Quasi-Static PCA)

245

(1)

4 Dynamic PCA

246

(1)

5 Quasi-static Frisch Model

246

(2)

6 Dynamic Frisch Model

248

(1)

7 Reduced Rank Regression Model

248

(5)

Detecting Longitudinal Heterogeneity in Generalized Linear Models

253

(8)

1 Introduction

253

(1)

2 Generalized Fluctuation Tests in the Generalized Linear Model

254

(3)

2.1 Empirical Fluctuation Processes

254

(2)

2.2 Test Statistics

256

(1)

2.3 Visualization

256

(1)

3 The Boston Homicides Data

257

(1)

4 Summary

258

(3)

Ensemble Methods for Cluster Analysis

261

(8)

1 Introduction

261

(1)

2 Aggregation Based on Prototypes

262

(2)

3 Aggregation Based on Memberships

264

(2)

4 Summary and Outlook

266

(3)

Open and Extensible Software for Data Analysis in Management Science

269

1 Introduction

269

(1)

2 R: An Environment for Statistical Computing

270

(2)

2.1 The language S

270

(1)

2.2 Features of R

270

(1)

2.3 R Package Management

271

(1)

3 R and Management Science

272

(2)

3.1 Market Segmentation, GLIMMIX and FlexMix

272

(1)

3.2 Graphical Models

273

(1)

4 Conclusions

274


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