Prediction markets as forecasting tool in decision processes:
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| Main Author: | |
|---|---|
| Format: | Thesis Book |
| Language: | English |
| Published: |
Berlin
Pro Business
2009
|
| Edition: | 1. Aufl. |
| Series: | Schriftenreihe des Instituts für Unternehmungsplanung
47 |
| Subjects: | |
| Online Access: | Inhaltstext Inhaltsverzeichnis |
| Physical Description: | VIII, 219 S. 210 mm x 148 mm, 323 gr. |
| ISBN: | 9783868053180 |
Staff View
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Titel: Prediction markets as forecasting tool in decision processes
Autor: Seemann, Thomas
Jahr: 2009
Table of Contents
List of Figures.v
List of Tables.vii
1 Introduction and Objective.1
1.1 The Role of Forecasting.1
1.2 The Phenomenon—Prediction Markets a New Forecasting Instrument.2
1.3 Contributions.6
1.4 Structure of this Work.7
2 Forecasting Methods in Decision Making.10
2.1 Background on Decision Making.10
2.2 Introduction to Forecasting Methods.12
2.3 Cognition Biases in Individual Judgments.14
2.4 Introduction to Judgmental Forecasting Methods in Groups.17
2.4.1 Statistical Groups/Surveys.17
2.4.2 Group Deliberation.21
2.4.3 Prediction Markets.26
3 Theoretical Foundation of Prediction Markets.28
3.1 Wisdom of Crowds.28
3.2 Market Efficiency Theory.31
3.3 Advantages of the Prediction Market Methodology.34
3.4 Prerequisites for the Application of Prediction Markets.37
3.5 Limitations of Prediction Markets.40
3.5.1 Mispricing in Markets.40
3.5.2 Limited Liquidity.41
3.5.3 Manipulations.42
3.5.4 Summary.44
4 Design Elements of Prediction Markets.45
4.1 Prediction Object.45
4.2 Securities.46
4.3 Incentive System.47
4.3.1 Motivation.47
4.3.2 Economic Incentives.49
4.3.2.1 Economic Incentives in Play-money Markets.49
4.3.2.2 Economic Incentives in Real-Money Markets.51
4.3.3 Social Rewards.52
4.3.4 Summary.53
4.4 Participation.54
4.5 Start Configuration.56
4.5.1 Introducing New Securities.56
4.5.2 Initial Portfolio.56
4.6 Exchange Design.57
4.6.1 Auction Method.57
4.6.1.1 Double Auction.57
4.6.1.2 Pari-Mutuel Auction.59
4.6.1.3 Combinatorial Market.59
4.6.1.4 Dynamic Pari-Mutuel Auction.60
4.6.2 Short Selling.60
4.6.3 Other Exchange Parameters.61
4.7 Summary.62
5 Applications of Prediction Markets.63
5.1 General and Public Markets.63
5.1.1 Election Stock Markets.63
5.1.2 Regulated Futures Markets.65
5.1.3 Betting Markets.66
5.1.4 Play-Money Markets.68
5.1.5 Political-Analysis Markets.69
5.2 Business-Related Markets.70
5.2.1 Product Sales Forecast.70
5.2.1.1 External Prediction.70
5.2.1.2 Internal Prediction.71
5.2.2 Product Design and Feature Selection.72
5.2.3 Regulatory Changes and Approvals.72
5.2.4 Project Execution Predictions.73
5.2.5 Morale Markets.74
5.3 Summary. .76
6 Framework for the Adoption of Prediction Market Applications.77
7 Prediction Market Accuracy.80
7.1 Existing Studies on Prediction Accuracy of Prediction Markets.83
7.1.1 Election Stock Markets.83
7.1.2 Other General and Public Markets. .86
7.1.3 Business-Related Markets.87
7.1.4 Sports-Related Markets.89
7.1.5 Summary.91
7.2 Research Design and Hypotheses.92
7.3 Data Sets.94
7.3.1 Tradesports Data Set.94
7.3.2 Knuddels Data Set.95
7.3.3 Summary of Derived Probability Predictions.96
7.4 Results of the Empirical Analysis.98
7.4.1 Characteristics of the Data Sets.98
7.4.2 Prediction Accuracy.101
7.4.2.1 Performance Metrics.101
7.4.2.2 Discrimination Test for Performance Metrics.104
7.4.2.3 Randomization Test of Performance Metrics.106
7.4.3 Summary of Results.107
7.5 Interpretation and Implication.108
7.6 Further Research.109
8 Cost of Prediction Markets.111
8.1 Cost of Establishment.Ill
8.2 Cost of Adaptation.113
8.3 Agency Cost.113
8.4 Cost of Operations.115
8.5 Summary.115
9 Acceptance and Trust in Prediction Markets.117
9.1 Hypotheses.118
9.1.1 Engagement and Success.119
9.1.2 Understanding of Prediction Market Mechanisms.120
9.1.3 Perception of Market Efficiency.121
9.2 Development and Specification of a Measurement Model.122
9.2.1 Defining Measurements for the Individual Constructs.127
9.2.1.1 Acceptance and Trust in Prediction Markets.127
9.2.1.2 Engagement and Success.128
9.2.1.3 Understanding of Prediction Market Mechanisms.129
9.2.1.4 Perception of Market Efficiency.130
9.2.2 Initial Specification of the Measurement Model.131
9.2.3 Pretest.133
9.3 PrediXion—An Experimental Market.135
9.3.1 Market Design and Interface.135
9.3.2 Process of the Experiments.139
9.4 Data Set from PrediXion Market Experiments.140
9.5 Assessment and Finalization of Measurement Model.145
9.5.1 Criteria of the First Generation.147
9.5.1.1 Introduction of the Criteria.147
9.5.1.2 Evaluation of First-Generation Criteria.151
9.5.2 Criteria of the Second Generation.156
9.5.2.1 Introduction of the Criteria.156
9.5.2.2 Evaluation of Second-Generation Criteria.160
9.5.3 Summary of Assessment and Final Structural Equation Model.163
9.6 Results of the Empirical Analysis of Structural Equation Model.165
9.7 Interpretation and Implication.168
9.8 Further Research.171
10 Evaluation of Prediction Markets.173
10.1 When to Consider Prediction Markets?.173
10.1.1 Collecting Asymmetrically Distributed Information.173
10.1.2 Aggregating Assessments.174
10.2 When Not to Consider Prediction Markets?.177
10.2.1 Risk in Building Cohesiveness.177
10.2.2 Risk in Organizational Hurdles.178
11 Conclusion.180
11.1 Results.180
11.2 Implications.182
11.2.1 Move Beyond "Experts".183
11.2.2 Focus on the Forecasting and Decision Making Processes.184
11.2.3 Experiment with Collective-Intelligence Methods.187
Appendix A: Design of PrediXion Experimental Market.190
Appendix B: IT Structure and Implementation of PrediXion.192
Appendix C: Navigation Structure of PrediXion User Interface.193
Appendix D: Research Questionnaire.194
Appendix E: Layout of the Original Questionnaire in German.198
References. .201
List of Figures
Figure 1: Cumulative Number of Companies that Have Implemented an Internal
Prediction Market.5
Figure 2: Overview Structure of the Work.9
Figure 3: Disciplines Feeding into Decision Analysis.10
Figure 4: Decision Making Process.11
Figure 5: Forecasting Methods: Methodology Tree.13
Figure 6: Cards of Asch's 1955 Cascade Experiment.24
Figure 7: Collective Intelligence.29
Figure 8: Design Elements of Prediction Markets.45
Figure 9: Types of Incentives.48
Figure 10: Order Book and Bid-Ask Spread in a Double-Auction Market.58
Figure 11: Overview Applications of Prediction Markets.63
Figure 12: Factors Influencing the Method Application.79
Figure 13: Primary and Secondary Factors of Information Efficiency.80
Figure 14: Linear Regression: Tradesports vs. Knuddels Match-win Probability.99
Figure 15: Linear Regression: Tradesports vs. Knuddels Probability of Goals.99
Figure 16: Predicted Win-Probability (Quarter Finals Onward).100
Figure 17: Determining ProbWin and ProbLose.102
Figure 18: Density Function of Difference in Average Logarithmic Score
(ALSxradespons-ALSKnuddeis) Match-win Prediction.105
Figure 19: Cost Elements of a Prediction Instrument.Ill
Figure 20: Constructs of the Structural Equation Model.123
Figure 21: Representation of a Formative Construct Specification.125
Figure 22: Representation of a Reflective Construct Specification.126
Figure 23: Initial Structural Equation Model.133
Figure 24: Homepage of PrediXion.136
Figure 25: View of Traded Securities in PrediXion.137
Figure 26: Overview of Portfolio Positions in PrediXion.138
Figure 27: Survey Page of PrediXion.139
Figure 28: Participation by Experimental Market.143
Figure 29: Response Rate by Market.144
Figure 30: Overview of the Evaluation, Modification, and Analysis Process.146
Figure 31: Set of Indicators for an Explorative Factor Analysis.148
Figure 32: Illustration of Factors in the EFA.148
Figure 33: Modified Measurement Model.156
Figure 34: Set of Indicators with Predefined Relationships for a Confirmatory Factor
Analysis.157
Figure 35: Overview of Criteria of the Second Generation.160
Figure 36: Model Structure of the Confirmatory Factor Analysis.161
Figure 37: Path Diagram of the Final Structural Equation Model.165
Figure 38: Explanatory Model for the Acceptance/Trust in Prediction Markets.167
Figure 39: Prediction Markets as Tool to Aggregate Assessments.176
Figure 40: "The Expert Squeez"—The Declining Role of the "Expert" in Decision
Making.184
List of Tables
Table 1: Overview of Further Exchange Parameters.61
Table 2: Overview of Election Stock Markets.64
Table 3: Overview of Regulated Futures Markets.66
Table 4: Overview of Betting Markets.67
Table 5: Overview of Play-Money Markets.68
Table 6: Example of Predicted Match-win Probabilities.96
Table 7: Example of Predicted Goal Probabilities.97
Table 8: Performance Metrics Match-win Predictions.103
Table 9: Performance Metrics Goal Predictions.103
Table 10: Confident Level of Metric Discrimination Test (Match-win Predictions). 105
Table 11: Confident Level of Metric Discrimination Test (Goal Predictions).106
Table 12: Match-win Predictions: Confidence Levels of Performance Metric
Differences (Randomization Test n=10.000).107
Table 13: Goal Predictions: Confidence Levels of Performance Metric Differences
(Randomization Test n= 10.000).107
Table 14: Measurement Concept for Construct Trust and Acceptance.128
Table 15: Measurement Concept for Construct Engagement.129
Table 16: Measurement Concept for Construct Understanding of Prediction Market 130
Table 17: Measurement Concept for Construct Market Perception.131
Table 18: Hit Matrix of Pretest.134
Table 19: Overview of Experimental Markets Executed.142
Table 20: Distribution of Survey Responses by Number of Transactions.144
Table 21: Excerpt of the Survey Data Set.145
Table 22: Overview of Criteria of the First Generation.151
Table 23: Rotated Factor Matrix—Exogenous Measurement Concept.152
Table 24: Criteria of the First Generation—Exogenous Measurement Concept.154
Table 25: Factor Matrix—Endogenous Measurement Concept.154
Table 26: Criteria of the First Generation—Endogenous Measurement Concept.155
Table 27: Partial Criteria of the Second Generation—Exogenous Measurement
Concept.162
Table 28: Global Criteria of the Second Generation—Exogenous Measurement
Concept.163
Table 29: Partial Criteria of the Second Generation—Endogenous Measurement
Concept.163
Table 30: Global Criteria of the Second Generation—Endogenous Measurement
Concept.163
Table 31: Goodness of the Fit—Structural Equation Model.166
Table 32: Classification of Correlation Coefficients.168 |
| any_adam_object | 1 |
| author | Seemann, Thomas |
| author_GND | (DE-588)138021953 |
| author_facet | Seemann, Thomas |
| author_role | aut |
| author_sort | Seemann, Thomas |
| author_variant | t s ts |
| building | Verbundindex |
| bvnumber | BV035493000 |
| classification_rvk | QP 325 QP 611 |
| ctrlnum | (OCoLC)552978110 (DE-599)DNB993592570 |
| dewey-full | 338.520112 |
| dewey-hundreds | 300 - Social sciences |
| dewey-ones | 338 - Production |
| dewey-raw | 338.520112 |
| dewey-search | 338.520112 |
| dewey-sort | 3338.520112 |
| dewey-tens | 330 - Economics |
| discipline | Wirtschaftswissenschaften |
| edition | 1. Aufl. |
| format | Thesis Book |
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| genre | (DE-588)4113937-9 Hochschulschrift gnd-content |
| genre_facet | Hochschulschrift |
| id | DE-604.BV035493000 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-20T10:10:46Z |
| institution | BVB |
| isbn | 9783868053180 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-017549361 |
| oclc_num | 552978110 |
| open_access_boolean | |
| owner | DE-N2 DE-29 DE-945 DE-188 DE-473 DE-BY-UBG |
| owner_facet | DE-N2 DE-29 DE-945 DE-188 DE-473 DE-BY-UBG |
| physical | VIII, 219 S. 210 mm x 148 mm, 323 gr. |
| publishDate | 2009 |
| publishDateSearch | 2009 |
| publishDateSort | 2009 |
| publisher | Pro Business |
| record_format | marc |
| series | Schriftenreihe des Instituts für Unternehmungsplanung |
| series2 | Schriftenreihe des Instituts für Unternehmungsplanung |
| spelling | Seemann, Thomas Verfasser (DE-588)138021953 aut Prediction markets as forecasting tool in decision processes von Thomas Seemann 1. Aufl. Berlin Pro Business 2009 VIII, 219 S. 210 mm x 148 mm, 323 gr. txt rdacontent n rdamedia nc rdacarrier Schriftenreihe des Instituts für Unternehmungsplanung 47 Zugl.: Erlangen-Nürnberg, Univ., Diss., 2008 Börsenspiel stw Deutschland stw Entscheidungsfindung - Marktmechanismus - Prognoseverfahren Prognoseverfahren stw Schätzung stw Theorie stw Vertrauen stw Wahrnehmung stw Abstimmung (DE-588)4166306-8 gnd rswk-swf Testmarkt (DE-588)4184833-0 gnd rswk-swf Konsens (DE-588)4010504-0 gnd rswk-swf Prognosequalität (DE-588)4115643-2 gnd rswk-swf Marktanalyse (DE-588)4037624-2 gnd rswk-swf Marktmechanismus (DE-588)4139127-5 gnd rswk-swf Entscheidungsfindung (DE-588)4113446-1 gnd rswk-swf Prognoseverfahren (DE-588)4358095-6 gnd rswk-swf Vertrauen (DE-588)4063290-8 gnd rswk-swf (DE-588)4113937-9 Hochschulschrift gnd-content Entscheidungsfindung (DE-588)4113446-1 s Marktmechanismus (DE-588)4139127-5 s Prognoseverfahren (DE-588)4358095-6 s Marktanalyse (DE-588)4037624-2 s DE-604 Testmarkt (DE-588)4184833-0 s Abstimmung (DE-588)4166306-8 s Prognosequalität (DE-588)4115643-2 s Konsens (DE-588)4010504-0 s Vertrauen (DE-588)4063290-8 s DE-188 Schriftenreihe des Instituts für Unternehmungsplanung 47 (DE-604)BV023545392 47 text/html http://deposit.dnb.de/cgi-bin/dokserv?id=3276912&prov=M&dok_var=1&dok_ext=htm Inhaltstext HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017549361&sequence=000004&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Seemann, Thomas Prediction markets as forecasting tool in decision processes Schriftenreihe des Instituts für Unternehmungsplanung Börsenspiel stw Deutschland stw Entscheidungsfindung - Marktmechanismus - Prognoseverfahren Prognoseverfahren stw Schätzung stw Theorie stw Vertrauen stw Wahrnehmung stw Abstimmung (DE-588)4166306-8 gnd Testmarkt (DE-588)4184833-0 gnd Konsens (DE-588)4010504-0 gnd Prognosequalität (DE-588)4115643-2 gnd Marktanalyse (DE-588)4037624-2 gnd Marktmechanismus (DE-588)4139127-5 gnd Entscheidungsfindung (DE-588)4113446-1 gnd Prognoseverfahren (DE-588)4358095-6 gnd Vertrauen (DE-588)4063290-8 gnd |
| subject_GND | (DE-588)4166306-8 (DE-588)4184833-0 (DE-588)4010504-0 (DE-588)4115643-2 (DE-588)4037624-2 (DE-588)4139127-5 (DE-588)4113446-1 (DE-588)4358095-6 (DE-588)4063290-8 (DE-588)4113937-9 |
| title | Prediction markets as forecasting tool in decision processes |
| title_auth | Prediction markets as forecasting tool in decision processes |
| title_exact_search | Prediction markets as forecasting tool in decision processes |
| title_full | Prediction markets as forecasting tool in decision processes von Thomas Seemann |
| title_fullStr | Prediction markets as forecasting tool in decision processes von Thomas Seemann |
| title_full_unstemmed | Prediction markets as forecasting tool in decision processes von Thomas Seemann |
| title_short | Prediction markets as forecasting tool in decision processes |
| title_sort | prediction markets as forecasting tool in decision processes |
| topic | Börsenspiel stw Deutschland stw Entscheidungsfindung - Marktmechanismus - Prognoseverfahren Prognoseverfahren stw Schätzung stw Theorie stw Vertrauen stw Wahrnehmung stw Abstimmung (DE-588)4166306-8 gnd Testmarkt (DE-588)4184833-0 gnd Konsens (DE-588)4010504-0 gnd Prognosequalität (DE-588)4115643-2 gnd Marktanalyse (DE-588)4037624-2 gnd Marktmechanismus (DE-588)4139127-5 gnd Entscheidungsfindung (DE-588)4113446-1 gnd Prognoseverfahren (DE-588)4358095-6 gnd Vertrauen (DE-588)4063290-8 gnd |
| topic_facet | Börsenspiel Deutschland Entscheidungsfindung - Marktmechanismus - Prognoseverfahren Prognoseverfahren Schätzung Theorie Vertrauen Wahrnehmung Abstimmung Testmarkt Konsens Prognosequalität Marktanalyse Marktmechanismus Entscheidungsfindung Hochschulschrift |
| url | http://deposit.dnb.de/cgi-bin/dokserv?id=3276912&prov=M&dok_var=1&dok_ext=htm http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017549361&sequence=000004&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV023545392 |
| work_keys_str_mv | AT seemannthomas predictionmarketsasforecastingtoolindecisionprocesses |