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研究生:洪銘駿
研究生(外文):Ming-Chun Hung
論文名稱:全域賽局與學習在透明度、貨幣危機以及回饋效果上的應用
論文名稱(外文):Application of Global Game with Learning: Transparency, Currency Crisis and Feedback Effect
指導教授:徐守德徐守德引用關係
指導教授(外文):David S. Shyu
學位類別:博士
校院名稱:國立中山大學
系所名稱:財務管理學系研究所
學門:商業及管理學門
學類:財務金融學類
論文種類:學術論文
論文出版年:2008
畢業學年度:97
語文別:英文
論文頁數:110
中文關鍵詞:學習全域賽局透明度管制回饋效果
外文關鍵詞:FeedbackLearningGlobal GameTransparencyRegulation
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在金融市場中的人們必定會學習(learning)有關標的變數,並因此發現一些參數的型式,因為人們的學習過程可能取決於他們的計算技巧以及信念(belief),所以不同人的學習計劃可能是不一樣的。本論文在描述當進行行動或交易決策時,人們會如何從其他人的行動中學習,或觀察相關資訊。如果先天觀念(prior)或既有信號(signal)依循一個常態分配,則標準高斯更新法則能應用、並說明人們的學習過程。依此,本論文將以學習與全域賽局(global game)理論為研究架構,分析三個主題;這三個主題分別涵蓋不同類型的金融市場以及交易者結構,得到不同的均衡條件、豐富的政策意義、有趣的市場績效結果以及有益消弭多元(multiplicity)現象的結論。

首先,討論金融市場透明化會如何影響均衡條件,尤其是多元均衡現象。本論文的第一部份將利用市場結清條件、以雜訊理性預期均衡結構為基礎、並使用帶有學習的全域賽局技巧,去呈現人們如何透過學習決定均衡條件,並討論透明化金融市場是否有減低多元均衡之成效。結果發現:在其他條件不變下,不論非資訊交易者私有信號精確度是什麼,在外生股利的例子下,透明化金融市場不能阻止多元均衡現象的消逝。其次,當股利報酬為內生時,單一均衡條件會部份決定於非資訊交易者私有信號的精確度,而非完全決定於市場透明度政策。

另外,政治家以及一些學者常常建議新興市場國家利用資本移動的管制來避免金融不安定性的產生以及減少多元均衡的發生。再者,在高度敏感的金融市場中,管理當局的資訊釋放通常被視為是一種快速反應市場變化以及消除市場不理性預期的方法。本論文的第二部份係利用直接資本移動管制以及資訊釋放來影響人們的信號,用以研究並比較資本不完全移動下的均衡條件變化。本論文發現:在其他條件不變下,雖然這兩個政策都可以減低資本移動,但是直接資本移動管制更可能鼓勵人們在樂觀信號下進行投機攻擊,因此更容易產生多元均衡現象。從一個政策展望中可以發現,當信號是樂觀時,積極地資訊釋放比起消極的資訊釋放、或無任何資本移動管制更容易維持單一均衡現象。

最後,過去許多資產價格以及金融危機文獻多著重在人們不同的學習方向或目標上。然而,學習可能會產生內生的回饋性以及內生的協調誘因,進而影響市場績效的問題卻罕有人討論。因此本論文的第三個主題聚焦在整合資訊的學習以及市場變化的觀察,以研究回饋效果或協調誘因對市場績效的影響。結果,回饋效果可能導因於人們之間的協調誘因,並且協調誘因愈強烈、回饋效果愈高。其次,當金融市場流動性變高時、或當一些衝擊變大時,人們之間的協調誘因會因此下降;資產價格的超額波動性會隨著金融市場中回饋效果或協調誘因的增加而減少。
Agents in financial markets must learn about underlying variables and hence find some patterns of parameter. Learning schemes across agents may be different since agents’ learning procedure depends on their computational technique and their beliefs. This dissertation outlines how agents learn from the actions of others or observe relative information when making trading decisions. If prior or signal follow a normal distribution, the law of standard Gaussian updating can be applied to represent the process of learning by agents. Accordingly, this dissertation use learning and global game technique to solve for the condition of equilibrium, to discuss the problem of eliminating multiplicity and to analyze three topics as follow.

First, how transparency in financial market influences equilibrium condition, ad hoc multiplicity, is rarely to explore. The first part of this dissertation focuses on the market-clearing condition, based on a noisy rational expectations equilibrium and using the global game technique with learning to proposes a policy effect and the variant of equilibrium in financial market. The after which conclusions can be drawn if transparent policy in financial market is implemented. First, all else equal, regardless of the precision of private signals of uninformed traders, financial market transparency cannot prevent from the vanishing of multiplicity under exogenous dividend return. Next, when dividend return is endogenous, the unique equilibrium condition is partly determined by the precision of private signals from uninformed traders rather than perfectly by a policy of market transparency.

Second, politicians and some scholars have advocated that emerging market countries avoid financial instability and reduce multiplicity by restricting capital mobility. Moreover, in the highly sensitized financial markets, information released by the authority is often seen so as to reply rapidly market variety and to correct and remove irrational expectations. The secondary direction of this dissertation employs direct capital mobility controls and informational releases to discuss and compare the variant of equilibrium. A notable finding is that, although direct capital mobility controls and informational releases may successfully reduce capital outflows, direct restrictions on capital mobility are more likely to encourage speculative attack under optimistic signals and are thus more likely to cause multiple equilibriums, ceteris paribus. From a policy perspective, under a signal is optimistic, maintaining uniqueness is more likely when information release is aggressive than when information release is passive or unrestricted on capital mobility, ceteris paribus.

Finally, recent studies about price or crises focus on the different directions or targets of learning. However, the problems that learning may generate endogenous feedback and endogenous coordination incentive and affect market performance are rarely discussed. Hence, the third topic of this dissertation will spotlight learning about aggregating information and observation of market and explain the effect of either coordination incentive or feedback on excess volatility. As a result, feedback effects may result from coordination incentives among agents and more coordination incentives among agents increases the feedback effect. Next, when financial markets are highly liquid or when financial shocks are severe, coordination incentives among agents decline. Excess asset price volatility decreases with either feedback effects or coordination incentives.
Abstract i
Chapter 1 Introduction 1
Chapter 2 Learning and Global game 5
2.1 Learning 5
2.2 Global Game 9
Chapter 3 Endogenous Public Signals, Noisy Dividend and Transparency 13
3.1 Introduce 13
3.2 Benchmark Model and Learning in Risky Asset Market 19
3.3 Endogenous Public Signals and Noisy Dividend 25
3.4 Conclusion 38
Chapter 4 Variety of Equilibrium under Two Different Signal Policies 40
4.1 Introduce 40
4.2 Benchmark Model and Learning in Currency Market 44
4.3 Direct Capital Mobility Restrictions and Informational Releases 50
4.4 Conclusion 63
Chapter 5 Endogenous Coordination Incentive and Feedback Effect 65
5.1 Introduce 65
5.2 Benchmark Model and Learning in a Financial Market 70
5.3 Equilibrium Solution and Endogenous Coordination Incentive 75
5.4 Feedback Effect and Excess Volatility 78
5.5 Conclusion 82
Chapter 6 Conclusion 84
Reference 87
Appendix 91
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