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

Admati, A. R., (1985), “A Noisy Rational Expectations Equilibrium for Multi-Asset Securities Markets,” Econometrica 53, 629-657.
Allen, F. and Morris, S., (2001), “Finance Applications of Game Theory,” in Advances in Business Applications of Game Theory, ed. by Chatterjee, K. and Samuelson, W., Boston, MA: Kluwer Academic Press.
Allen, F., Morris, S., and Shin, H. S., (2006), “Beauty Contests and Iterated Expectations,” Review of Financial Studies 19, 161-177.
Angeletos, G.-M., Hellwig, C. and Pavan, A., (2006), “Signaling in a Global Game: Coordination and Policy Traps,” Journal of Political economy 114, 452-484.
Angeletos, G.-M., Hellwig, C. and Pavan, A., (2007a), “Defense Policies against Currency Attacks: On the Possibility in a Global Game with Multiple Equiliria,” forthcoming in Journal of International Economics.
Angeletos, G.-M., Hellwig, C. and Pavan, A., (2007b), “Dynamic Global Games of Regime Change: Learning, Multiplicity and Timing of Attacks,” Econometrica 75, 711-756.
Angeletos, G.-M., Lorenzoni, G. and Pavan, A., (2007), “Wall Street and Silicon Valley: A Delicate Interaction,” MIT and Northwest University: Working Paper.
Angeletos, G.-M. and Pavan, A., (2004), “Transparency of Information and Coordination in Economies with Investment Complementaries,” American Economics Reviews 94, 91-98.
Angeletos, G.-M. and Pavan, A., (2007), “Efficient Use of Information and Social Value of Information,” Econometrica 75, 1103-1142.
Angeletos, G-M and Werning, I., (2006), “Crises and Prices: Information Aggregation, Multiplicity and Volatility,” American Economics Reviews 96, 1720-1728.
Arellano, J. P., (1982), “Macroeconomic Stability and the Optimal Degree of Capital Mobility,” Journal of Development Economics 10, 377-393.
Atkeson, A., (2000), “Discussion on Morris and Shin,” NBER Macroeconomics Annual 2000.
Baker, M., Stein, J. and Wurgler, J., (2003), “When Does the Market Matter? Stock Prices and the Investment of Equity-Dependent Firms,” Quarterly Journal of Economics 118, 969-1006.
Barlevy, G. and Veronesi, P., (2003), “Rational Panics and Stock Crashes,” Journal of Economic Theory 110, 234-263.
Battaglini, M. and Benabou, R., (2003), “Trust, Coordination, and the Industrial Organization of Political Activism,” Journal of the European Economic Association 1, 851-870.
Blume, L., Easley, D. and O’Hara, M., (1994), “Market Statistics and Technical Analysis: The Role of Volume,” Journal of Finance 49, 153-181.
Carlsson, H. and van Damme, E. E., (1993), “Global Payoff Uncertainty and Risk Dominance,” Econometrica 61, 989-1018.
Chamley, C., (2003), “Dynamic Speculative Attacks,” American Economic Review 93, 603-621.
Chen, Q., Goldstein, I. and Jiang, W., (2007), “Price Informativeness and Investment Sensitivity to Stock Price,” Review of Financial Studies 20, 619-650.
Cornand, C. and Heinemann, F., (2007),“Optimal Degree of Public Information Dissemination,” forthcoming in Economic Journal.
Corsetti, G., Dasgupta, A., Morris, S. and Shin, S. H., (2004), “Does One Soros Make a Difference? A Theory of Currency Crises with Large and Small Traders,” Review of Economic Studies 71, 87-113.
Danielsson, J. and Saltoglu, B., (2003), “Anatomy of a market crash: A Market Microstructure Analysis of the Turkish Overnight Liquidity Crises,” London School of Economics: Working paper.
Dasgupta, A., (2007), “Coordination and Delay in Global Game,” Journal of Economic Theory 134, 195-225.
Delbecque, B., (1989), “Exchange-Rate Dynamics in a Model with Imperfect Capital Mobility and Asset Substitutability,” European Economic Review 33, 1161-73.
Diamond, D. and Dybvig, P., (1983), “Bank Runs, Deposit Insurance, and Liquidity,” Journal of Political Economics, 91, 401-419.
Edmond, C., (2005), “Information Manipulation, Coordination and Regime Change,” Working paper: NYU Stern School of Business.
Edward, S., (2000), “How Effective are Capital Controls?” Journal of Economic Perspectives 13, 65-84.
Eichengreen, B. J. and Leblang, D., (2002), “Capital Account Liberalization and Growth: Was Mr. Mahathir Right?” NBER: Working paper Series no. 9427.
Evans, M. D. D. and Lyons, R. K., (2002), “Order Flow and Exchange Rate Dynamics,” Journal of Political Economy 19, 170-180.
Gennotte, G. and Leland, H., (1990), “Market Liquidity, Hedging, and Crashes,” American Economic Review 80, 999-1021.
Glosten, L. and Milgrom, P., (1985), “Bid, Ask, and Transaction Prices in a Specialist Market with Heterogeneously Informed Traders,” Journal of Financial Economics 13, 71-100.
Goldstein, I. and Guembel, A., (2008), “Manipulation and the Allocational Role of Prices,” Review of Economic Studies 75, 133-164.
Goldstein, I., Ozdenoren, E. and Yuan, K., (2008), “Learning and Complementarities: Implications for Speculative Attacks,” Pennsylvania and Michigan University: Working Paper.
Goldstein, I. and Pauzner, A., (2005), “Demand-Deposit Contracts and the Probability of Bank Runs,” Journal of Finance 50, 1293-1327.
Grossman, S. J. and Stiglitz, E. S., (1976), “The Existence of Futures Markets, Noisy Rational Expectations and Informational Externalities,” Review of Economic Studies 44, 431-449.
Guimaraes, B. and Morris, S., (2007), “Risk and Wealth in a Model of Self-Fulfilling Currency Attacks,” Journal of Monetary Economics 54, 2205-2230.
Harris, J. and Schultz, P., (1997), “The Importance of Firm Quotes and Rapid Executions: Evidence from the January 1994 SOES Rule Change,” Journal of Financial Economics 45, 135-166.
Heidhues, P. and Melissas, N., (2006), “Equilibria in a dynamic global game: the role of cohort effects, Economic Theory 28, 531-557.
Hellwig, C., (2002), “Public Information, Private Information and the Multiplicity of Equililbria in Coordination Games,” Journal of Economic Theory 107, 191-222.
Hellwig, C., Mukherji, A. and Tsyvinski, A., (2006), “Self-Fulfilling Currency Crises: the Role of Interest Rates,” American Economic Review 96, 1769-1777.
Hellwig, M., (1980), “The Aggregation of Information in Competitive Markets,” Journal of Economic Theory, 22, 477-498.
Hirshleifer, D., Subrahmanyam, A. and Titman, S., (1994), “Security Analysis and Trading Patterns when Some Investors Receive Information before Others,” Journal of Finance 49, 1665-1698.
Hirshleifer, D., Subrahmanyam, A. and Titman, S., (2006), “Feedback and the Success of Irrational Investors,” Journal of Financial Economics 81, 311-338.
Ito, T., Lyons, R. K. and Melvin, M. T., (1998), “Is there Private Information in the Foreign Exchange Market? The Tokyo Experiment,” Journal of Finance 53, 1111-1130.
Khanna, N. and Sonti, R., (2004), “Value Creating Stock Manipulation: Feedback Effect of Stock Prices on Firm Value,” Journal of Financial Market 7, 237-270.
Kyle, A., (1985), “Continuous Auctions and Insider Trading,” Econometrica 53, 1315-1336.
LeRoy, S. F. and Porter, R. D., (1981), “The Present-Value Relation: Tests Based on Implied Variance Bounds,” Econometrica 49, 555-574.
Lewellen, J. and Shanken, J., (2002), “Learning, Asset-Pricing Tests, and Market Efficiency,” Journal of Finance 57, 1113-1145.
Luo, Y., (2005), “Do Insiders Learn from Outsiders? Evidence from Mergers and Acquisitions,” Journal of Finance 60, 1951-1972.
Lyons, R. K., (2001), The Microstructure Approach to Exchange Rates, MIT Press: Cambridge, MA.
Madhavan, A., Porter, D., and Weaver D., (2001), “Should Securities markets be Transparent?”, Banque du Canada.
Milgrom, P. and Stokey, N., (1982), “Information, Trade and Common Knowledge,” Journal of Economic Theory 26, 17-27.
Mishkin, F. S., (2007), The Economics of Money, Banking, and Financial Markets, Cambridge: Cambridge University Press, 475-476.
Morris, S. and Shin, H. S., (1998), “Unique Equilibrium in a Model of Self-fulfilling Currency Attacks,” American Economic Review 88, 587-597.
Morris, S. and Shin, H. S., (2000), “Rethinking Multiple Equilibria in Macroeconomic Modelling,” NBER Macroeconomics Annual.
Morris, S. and Shin, H. S., (2002), “Social Value of Public Information,” American Economic Review 92, 1521-1534.
Morris, S. and Shin, H. S., (2003), “Global Games- Theory and Applications,” in Dewatripont, M., Hansen, L. and Turnovsky, S., eds., Advances in Economics and Econometrics (8th World Congress of the Econometric Society), Cambridge: Cambridge University Press.
Morris, S. and Shin, H. S., (2004), “Liquidity Black Holes,” Review of Finance 8, 1-18.
Morris, S. and Shin, H. S., (2006), “Endogenous Public Signals and Coordination,” Princeton University: Working Paper.
Morris, S. and Shin, H. S., (2007), “Optimal Communication,” Journal of the European Economic Association 5, 594-602.
Obstfeld, M., (1996), “Model of Currency Crises with Self-fulfilling Features,” European Economic Review 40, 1037-1047.
Obstfeld, M. and Taylor, A. M, (2004), Global Capital Markets: Integration, Crises, and Growth, Cambridge: Cambridge University Press, 285-286.
Odean, T., (1998), “Volume, Volatility, Price, and Profit When All Traders Are Above Average”, Journal of Finance 53, 1887-1934.
O’Hara, M., (1995), Market Microstructure Theory, Basil Blackwell, Cambridge, MA.
Ozdenoren, E. and Yuan, K., (2008), “Feedback Effects and Asset Prices,” Journal of Finance 63, 1939-1975.
Phylaktis, K. and Wood, G. E., (1984), “An analytical and Taxonomic Framework for the Study of Exchange Controls,” in: Black, J. and Dorrance, G. S. eds., Problems of International Finance, 149-166, London: Macmillan.
Rindi, B., (2004), “Informed traders as Liquidity: Transparency, Liquidity and Price Formation,” SSRN Working Paper.
Roll, R., (1984), “Orange Juice and Weather,” American Economic Review 74, 861- 880.
Shiller, R. J., (1981), “Do Stock Prices Move too Much to be Justified by Subsequent Changes in Dividends?” American Economic Review 71, 421-436.
Subrahmanyam, A. and Titman, S., (1999), “The Going-Public Decision and the Development of Financial Markets,” Journal of Finance 54, 1045-1082.
Subrahmanyam, A. and Titman, S., (2001), “Feedback from Stock Prices to Cash Flows,” Journal of Finance 56, 2389-2413.
Tarashev, N. A, (2007), “Currency Crises and the Informational Role of Interest Rates,” Journal of the European Economic Association 5, 1-36.
Timmermann, A., (1993), “How Learningin Financial Markets Generates Excess Volatility and Predictability in Stock Prices,” Quarterly Journal of Economiss 108,, 1135-1145.
Timmermann, A., (1996), “Excess Volatility and Predictability of Stock Prices in Autoregressive Dividend Models with Learning,” Review of Economic Studies 63, 523-557.
Topkis, D. M., (1979), “Equilibrium points in Nonzero-sum N-person sub Modular Games,” SIAM Journal on Control and Optimization 17, 773-787.
Ui, T., (2004), “Bayesian Potential and Information Structures: Team Decision Problems Resisited,” Working Paper.
Walsh, C. E., (2005), “Transparency, Flexibility, and Inflation Targeting,” University of California: Working paper.
Wolfers, J. and Zitzewitz, E., (2004), “Prediction Markets,” Journal of Economic Perspectives 18, 107-126.
Woodford, M., (2005), “Central Bank Communication and Policy Effectiveness,” NBER Working paper NO. 11898.
Yuan, K., (2005), “Asymmetric Price Movements and Borrowing Constraints: A Rational Expectations Equilibrium Model of Crises, Contagion, and Confusion,” Journal of Finance 60, 379-411.