臺灣博碩士論文加值系統

對於現有文獻中討論的預測市場模型，嘗試加入風險與聲譽變數，觀察與分析其成效，並參考文獻中的代理人系統實驗方法，對論文中相關部分進行修正、設計並模擬之預測市場模型。

In this research, we proposed two variables that could be incorporated with prediction
markets: Reputation and Risk. Instead of attracting new players, The reputation system
could stop losing bankrupted player, Player willing to help bankrupted player will gain
reputation, and bankrupted player will lose reputation. Previous works suggest longshot
bias is related to the risk-neutrality of players. Our approach is to experiment dierent
risk distribution. We observe the impact of these variables in an agent-based model
of prediction markets. We use zero-intelligence agents, where human qualities such as
maximizing prot, learning or obeserving are missing. We further discuss the result, and
the impact of risk and reputation.

1 Introduction 1
1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Issues of Prediction Market Systems . . . . . . . . . . . . . . . . . . . . . . 2
1.3 Agents and Prediction Markets . . . . . . . . . . . . . . . . . . . . . . . . 3
1.4 Research Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.5 Thesis Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2 Literature Review 6
2.1 Prediction Markets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.1.1 Evolution of Prediction Markets . . . . . . . . . . . . . . . . . . . . 7
2.1.2 Implementations and Experiments . . . . . . . . . . . . . . . . . . . 8
2.2 Multi-Agent System for Simulating Prediction Markets . . . . . . . . . . . 8
2.2.1 Zero-Intelligence Agents in Prediction Markets . . . . . . . . . . . . 9
2.2.2 Non-ZI Agents versus ZI agents . . . . . . . . . . . . . . . . . . . . 9
3 Methodology 11
3.1 Prediction Market Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . 11
3.1.1 Information Structure . . . . . . . . . . . . . . . . . . . . . . . . . 13
3.1.2 Market Mechanism . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
3.1.3 Trader Behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
3.2 Reputation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
3.3 Risk Parameter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
3.4 Populating Agents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
3.5 Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
3.5.1 Control set . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
3.5.2 Risk only set . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
3.5.3 Reputation only set . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
3.5.4 Reputation and Risk set . . . . . . . . . . . . . . . . . . . . . . . . 21
4 Simulation Results 23
4.1 Performance metrics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
4.2 Experiment results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
4.2.1 Control experiments . . . . . . . . . . . . . . . . . . . . . . . . . . 25
4.2.2 Risk-only experiments . . . . . . . . . . . . . . . . . . . . . . . . . 28
4.2.3 Reputation-only experiments . . . . . . . . . . . . . . . . . . . . . . 30
4.2.4 Risk and Reputation experiments . . . . . . . . . . . . . . . . . . . 32
4.3 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
5 Conclusions 36
5.1 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
5.2 Future Works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
Bibliography 38
Appendix 41
A Figures of experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
A.1 Control experiments . . . . . . . . . . . . . . . . . . . . . . . . . . 41
A.2 Risk-only experiments . . . . . . . . . . . . . . . . . . . . . . . . . 42
A.3 Reputation-only experiments . . . . . . . . . . . . . . . . . . . . . . 43
A.4 Risk and reputation experiments . . . . . . . . . . . . . . . . . . . 44

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