臺灣博碩士論文加值系統

風險偏好與預測精確性對生存力的重要性吸引進來許多理論學者的注意。一個極端是認為風險偏好完全不重要，唯一重要是預測精確性。然而此乃基於柏拉圖最適配置之下。透過代理人基模型，我們發現相異的結果，即風險偏好在生存力上扮演重要角色。

The relevance of risk preference and forecasting accuracy to the survival of investors is an issue that has recently attracted a number of recent theoretical studies. At one extreme, it has been shown that risk preference can be entirely irrelevant, and that in the long run what distinguishes the agents who survive from those who vanish is just their forecasting accuracy.
Being in line with the market selection hypothesis, this theoretical result is, however,
established mainly on the basis of Pareto optimal allocation. By using agent-based computational
modeling, this dissertation extends the existing studies to an economy where adaptive
behaviors are autonomous and complex heterogeneous, and where the economy is notorious
for its likely persistent deviation from Pareto optimality. Specifically, a computational multiasset
artificial stock market corresponding to Blume and Easley (1992) and Sandroni (2000)
is constructed and studied. Through simulation, we present results that contradict the market
selection hypothesis. Risk preference plays a key role in survivability. And agents who
have superior forecasting accuracy may be driven out just because of their risk preference.
Nevertheless, when all the agents are with the same preference, the wealth share is positively
correlated to forecasting accuracy, and the market selection hypothesis is sustained, at least
in a weak sense.

1 Introduction and Motivation................................ 5
2 The Model .................................................11
2.1 The Blume-Easley-Sandroni Model . . . . . . . .......... 11
2.2 The Agent-Based Multi-Asset Artificial Stock Market . . .13
2.2.1 Agent’s Cognition . . . . . . . . . ............ . .. 14
2.2.2 Autonomous Agents . . . . . . . . . ........ . . . . . 18
2.2.3 CAPM Believers . . . . . . . .. . .... . . . . . . . . 19
2.2.4 Summary of the Market . . . . . ..... . . . . . . . . 20
3 Experimental Designs ......................................21
3.1 Market and Participants . . . . . . . . . .... . . . . . 21
3.2 Parameters related to Autonomous Agents . .... . . . . . 23
4 Experimental Results ......................................26
4.1 Experiment 1 . . . . . . . . . . . . . . . . . . ... . 27
4.1.1 Wealth Share Dynamics . . . . . . . . . . . . . ... . 27
4.1.2 Forecasting Accuracy . . . . . . . . . . . . . ... . . 28
4.2 Experiment 2 . . . . . . . . . . . . . . . . . . ... . 29
4.3 Summary . . . . . . . . . . . . . . . . . . . . .. . . . 32
5 Further Analysis and Discussion ..................... .....34
5.1 The Investment Decisions . . . . . . . . . . . .........34
5.1.1 Saving Rates . . . . . . . . . . . . . . . . . . . ...34
5.1.2 Portfolio Performance . . . . . . . . . . . . . . . . 37
5.2 The Further Exploration in the Empirical Range of RRA coefficients.................................................39
5.2.1 Empirical RRA Coefficients and Control Parameters . .. 40
5.2.2 Wealth Share Dynamics . . . . . . . . . . . . . . . . 42
5.2.3 Saving Rates . . . . . . . . . . . . . . . . .. . . . 42
5.2.4 Portfolio Performance . . . . . . . . . . . . . . . . 45
6 Concluding Remarks ........................................47
7 Future Research........................................... 49
Appendix ....................................................51
A ...........................................................51
A.1 Evolution at the Low Level: Investment Strategies .. . . 51
A.2 Evolution at the High Level: Beliefs . . . . . . . . . . 55
A.3 The Behavior of CAPM Believers . . . . . . . . . .. . . 61
Bibliography.................................................63

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