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姓名 何坤炫(Kun-hsuan Ho)  查詢紙本館藏   畢業系所 財務金融學系
論文名稱 外匯市場私有訊息之程度對於匯率變動之影響
(Information Asymmetry in the Foreign Exchange Market: Effect on Exchange Rate Changes)
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摘要(中) 傳統文獻以總體經濟變數嘗試尋找影響匯率變動的因素,但由於此資本市場分析法的失效,近期文獻結合市場微結構 (market microstructure) 的理論,試圖找出影響匯率變動的重要因素,如Evans and Lyons (2002) 使用買賣單流量 (order flow) 解釋馬克/美元匯率的變動,發現迴歸模型的解釋能力高達60%,因此他們主張買賣單流量中隱含了資訊交易的內涵,而且資訊交易 (informed trade) 確實會影響匯率變動。繼Evans and Lyons (2002) 後,Breedon and Vitale (2010) 認為買賣單流量對於匯率變動的影響應分為資訊交易和資產組合平衡 (portfolio balance) 效果,實證結果推翻資訊交易會影響匯率變動的說法。針對這些不一致的實證結果,本論文利用EBS (Electronic Broking Services) 外匯交易系統的歐元-美元和美元-日元交易資料,並計算Easley, Kiefer, O'Hara, and Paperman (1996) 所提出的PIN ( probability of informed trade ) 及Duarte and Young ( 1996 ) 所提出的AdjPIN (adjusted PIN), 以捕捉資訊交易的現象,並證實資訊交易為影響匯率變動的重要因素。我們進一步以匯率變動率為應變數,PIN、AdjPIN、價差、買賣單流量和PSOS 為自變數,並進行OLS迴歸分析,實證結果指出AdjPIN、買賣單流量與匯率報酬的關係相當明顯,故我們認為資訊交易為影響匯率變動的重要因素之一,且買賣單流量依然為捕捉資訊交易現象的良好代理變數。值得一提的是,PIN在外匯市場中較無法捕捉資訊交易的現象。
摘要(英) So far,traditional literature were trying to find the relationship between macroeconomic variables and exchange rate, but it didn’t work anymore. Recent literature wanted to via the view of market microstructure to find the factor that affect exchange rate, such as Evans and Lyons (2002), they explained the changes in the mark / dollar exchange rate by order flow, R2 is 60%, so they thought the order flow implied the information about information based trading. After Evans and Lyons (2002), Breedon and Vitale (2010) divided the order flow into information based trading and portfolio balanced effect, the empirical results show that only portfolio balanced effect can affect exchange rate. For these inconsistent empirical results, this paper uses the two exchange rate:Euro-Dollar and Dollar-Yen which , and calculate the PIN (probability, of informed trade) and AdjPIN (adjusted PIN), to capture the phenomenon of information based trading. We select PIN, Adjpin, PSOS, Spread and order flow as our independent variables in OLS. Our empirical results show that order flow and AdjPIN are better proxy variable for information based trading but not for PIN.
關鍵字(中) ★ 買賣單流量
★ AdjPIN
★ PIN
★ 外匯市場
★ 資訊不對稱
關鍵字(英) ★ AdjPIN
★ PIN
★ order flow
★ foreign exchange market
★ information asymmetric
論文目次 第一章、 緒論....................................... ... .............................................................1
第一節、 研究背景及動機...................................................................................1
第二節、 研究目的................................................................................................4
第三節、 研究架構................................................................................................4
第二章、 文獻探討...........................................................................................................5
第一節、 匯率報酬受買賣單流量的影響..........................................................5
第二節、 匯率報酬受流動性的影響...................................................................8
第三節、 PIN...........................................................................................................9
第四節、 AdjPIN...................................................................................................12
第五節、 改善PIN估計方式..............................................................................14
第三章、 PIN、AdjPIN的概念與估計方法...............................................................16
第一節、 資訊交易機率(PIN)的計算方法....................................................16
第二節、 調整後資訊交易機率(AdjPIN)的計算方法.................................17
第三節、 求取最佳系數的方法..........................................................................19
第四章、 資料形式..........................................................................................................20
第一節、 介紹電子仲介服務系統(EBS)與EBS資料型式.......................20
第二節、 資料取樣...............................................................................................21
第五章、 估計結果與迴歸分析.....................................................................................23
第一節、 估計結果、迴歸相關變數與迴歸結構.............................................23
第二節、 日內交易活動.......................................................................................25
第三節、 迴歸分析:歐元/美元.........................................................................26
第四節、 迴歸分析:美元/日元.........................................................................27
第五節、 估計心得與估計過程中所遭遇的困難.............................................28
第六章、 結論與建議......................................................................................................30
第一節、 研究結論...............................................................................................30
第二節、 研究限制與建議..................................................................................30
參考文獻............................................. ............................................. .................................31
參考文獻 Aktas, Nihat, Eric de Bodt, Fany Declerck, Herve’ Van Oppens, 2007. PIN anomaly around M&A announcements. Journal of Financial Markets 10, 169-191.
Amihud, Yakov, 2002. Illiquidity and stock returns: Cross-section and time-series effects. Journal of Financial Markets 5, 31-56.
Bacchetta, Philippe, Eric Van Wincoop, 2006. Can information heterogeneity explain the exchange rate determination puzzle? American Economic Review 96, 552-576.
Berger, David, Alain Chaboud, Sergey Chernenko, Edward Howorka, Raj Krishnasami Iyer, David Liu, Jonathan Wright, 2008. Order flow and exchange rate dynamics in electronic brokerage system data. Journal of International Economics 75, 93-109.
Bhattacharya, Utpal, Hazem Daouk, Brian Jorgenson, Carl-Heinrich Kehr, 2000. When an event is not an event: The curious case of an emerging market. Journal of Financial Economics 55, 69-101.
Bjonnes, Geir, Carol Osler, Dagfinn Rime, 2011. Sources of information advantage in the foreign exchange market. Norges Bank Working Paper.
Breedon, Francis, Paolo Vitale, 2010. An empirical study of portfolio-balance and information effects of order flow on exchange rates. Journal of International Money and Finance 29, 504-524.
Brown, Stephen, Stephen A. Hillegeist, 2007. How disclosure quality affects the level of information asymmetry. Review of Accounting Studies 12, 443-477.
Brown, Stephen, Stephen A. Hillegeist, Kin Lo, 2004. Conference calls and information asymmetry. Journal of Accounting and Economics 37, 343-366.
Brown, Stephen, Stephen A. Hillegeist, Kin Lo, 2004. Conference calls and information asymmetry. Journal of Accounting and Economics 37, 343-366.
Byun, Hae-Young, Lee-Seok Hwang, Woo-Jong Lee, 2011. How does ownership concentration exacerbate information asymmetry among equity investors? Pacific-Basin Finance Journal 19, 511-534.
Chen, Shikuan, Chih-Chung Chien , Ming-Jen Chang, 2011. Order flow, bid–ask spread and trading density in foreign exchange markets. Journal of Banking & Finance 36, 597-612.
Chen, Tsung-Kang, Yi-Ping Liao, 2011. Incomplete accounting information and corporate bond yield spreads: Segment disclosure quality perspective. American Accounting Association Annual Meeting. Denver: American Accounting Association.
Chordia, Tarun a, Richard Roll, Avanidhar Subrahmanyam, 2008. Liquidity and market efficiency. Journal of Financial Economics 87, 249-268.
Duarte, Jefferson, Lance Young, 2009.Why is PIN priced? Journal of Financial Economics 91, 119-138.
Duarte, Jefferson, Lance Young, 2009. Whyis PIN priced? Journal of Financial Economics 91,119-138.
Easley, David, Maureen O’’Hara, 2004. Information and the cost of capital. Journal of Finance 59, 1553-1583.
Easley, David, Maureen O’’Hara, Joseph Paperman, 1998. Financial analysts and information-based trade. Journal of Financial Markets 1,175-201.
Easley, David, Nicholas Kiefer, Maureen O’’Hara, 1997. One day in the life of a very common stock. The review of financial studies 10, 805-835.
Easley, David, Nicholas Kiefer, Maureen O’’Hara, Joseph Paperman, 1996. Liquidity, information and infrequently traded stocks. Journal of Finance 51, 1405-1436.
Easley, David, Robert Engle, Maureen O’Hara, Liuren Wu, 2008. Time-varying arrival rates of informed and uninformed trades. Journal of Financial Econometrics 6, 171-207.
Easley, David, Soeren Hvidkjaer, Maureen O’’Hara, 2002. Is Information risk a determinant of asset returns? Journal of Finance 57, 2185-2221.
Easley, David, Soeren Hvidkjaer, Maureen O’’Hara, 2010. Factoring information into return. Journal of Financial and Quantitative Analysis 45, 293-309.
Ertimur, Yonca, 2007. Discussion of “How disclosure quality affects the level of information asymmetry.” Review of Accounting Studies 12, 479-485.
Evans, Martin, Richard Lyons, 2002. Order flow and exchange rate dynamics. Journal of Political Economy 110, 170-180.
Ito, Takatoshi, Yuko Hashimoto, 2006. Intraday seasonality in activities of the foreign exchange markets: Evidence from the electronic broking system. Journal of the Japanese and International Economies 20, 637-664.
Kubota, Keiichi, Takashi Ebihara, Hitoshi Takehara, Eri Yokota, 2012. Market liquidity, private information, and the cost of capital: microstructure studies on family firms in Japan. Working Paper.
Lin, Hsiou-Wei William, Wen-Chyan Ke, 2011. A computing bias in estimating the probability of informed trading. Journal of Financial Markets 14, 625-640.
Lu, Chia-Wu, Tsung-Kang Chen, Hsien-Hsing Liao, 2010. Information asymmetry and corporate bond yield spreads. Journal of Banking & Finance 34, 2265-2279.
O’Hara, Maureen, 2003. Presidential address: Liquidity and price discovery. Journal of Finance 63, 1335-1354.
Osler, Carol, 2008. Foreign exchange microstructure: A Survey of the empirical literature. Working Paper, Brandeis University.
Payne, Richard , 2003. Informed trade in spot foreign exchange markets: An empirical investigation. Journal of International Economics 61, 307-329.
Rime, Dagfinn, 2003. New electronic trading systems in foreign exchange markets. Norges Bank and Stockholm Institute for Financial Research.
Rime, Dagfinn, Lucio Sarno, Elvira Sojli, 2007. Exchange-rate forecasting, order flow, and macro information. Norges Bank Working Paper.
Sager, Michael, Mark P. Taylor, 2008. Commercially available order flow data and exchange rate movements: Caveat emptor. Journal of Money Credit Bank 40, 583-625.
Stoll, Hans, 1989. Inferring the components of the bid-ask spread: theory and empirical tests. Journal of Finance 44, 115-134.
Tang, Bin, Yafeng Qin, Min Bai, 2010. A re-examination of informed trading and firm size in the Thailand capital market, International Review of Business Research Papers 6, 106-122.
Vega, Clara, 2005. Stock price reaction to public and private information. Journal of Financial Economics 82, 103-133.
Yan, Yuxing , Shaojun Zhang, 2012. An Improved estimation method and empirical properties of the probability of informed trading. Journal of Banking & Finance 36, 454-467.
指導教授 高櫻芬 審核日期 2012-6-22
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