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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 陳思寬(Shi-Kuan Chen) | |
dc.contributor.author | Chih-Chung Chien | en |
dc.contributor.author | 簡智崇 | zh_TW |
dc.date.accessioned | 2021-06-17T00:47:36Z | - |
dc.date.available | 2015-01-17 | |
dc.date.copyright | 2012-01-17 | |
dc.date.issued | 2012 | |
dc.date.submitted | 2011-12-22 | |
dc.identifier.citation | References in Chapter 2
Amihud, Y., 2002. Illiquidity and stock returns: Cross-section and time-series effects. Journal of Financial Markets 5, 31-56. Bacchetta, P., van Wincoop, E., 2006. Can information heterogeneity explain the exchange rate determination puzzle? American Economic Review 96, 552-576. Barker, W., 2007. The global foreign exchange market: Growth and transformation. Bank of Canada Review, Autumn, 3-12. Cerrato, M., Sarantis N., Saunders, A., 2011. An investigation of customer order flow in the foreign exchange market. Journal of Banking and Finance 35, 1892-1906. Chan, K., Fong, W.M., 2000. Trade size, order imbalance, and the volatility-volume relation. Journal of Financial Economics 57, 247-273. Chordia, T., Roll, R., Subrahmanyam, A., 2008. Liquidity and market efficiency. Journal of Financial Economics 87, 249-268. Easley, D., Kiefer, N.M., O’Hara, M., Paperman, J.B., 1996. Liquidity, information, and infrequently traded stocks. Journal of Finance 51, 1405-1436. Evans, M.D.D., Lyons, R.K., 2002. Order flow and exchange rate dynamics. Journal of Political Economy 110, 170-180. Evans, M.D.D., Lyons, R.K., 2008. How is macro news transmitted to exchange rates? Journal of Financial Economics 88, 26-50. Evans, M.D.D., 2011. The microstructure of currency markets. In: Caprio, G. (Eds.), The Encyclopedia of Financial Globalization, Elsevier: Amsterdam. Glosten, L., Milgrom, P., 1985. Bid, ask and transaction prices in a specialist market with heterogeneously informed traders. Journal of Financial Economics 14, 71-100. Glosten, L., 1987. Components of the bid-ask spread and the statistical properties of transaction prices. Journal of Finance 42, 1293-1307. Grossman, S.J., Miller, M.H., 1988. Liquidity and market structure. Journal of Finance 43, 617-637. Gwilym, O., Meng, L., 2010. Size clustering in the FTSE 100 index futures market. Journal of Futures Markets 30, 432-443. Hasbrouck, J., 1993. Assessing the quality of a security market: A new approach to transaction cost measurement. Review of Financial Studies 6, 191-212. Hasbrouck, J., Seppi D., 2001. Common factors in prices, order flows, and liquidity. Journal of Financial Economics 59, 383-411. Huang, R.D., Stoll, H.R., 1997. The components of the bid-ask spread: A general approach. Review of Financial Studies 10, 995-1034. Lin, J.C., Sanger, G., Booth, G.G., 1995. Trade size and components of the bid-ask spread. Review of Financial Studies 8, 1153-1183. Lyons, R.K., 2006. The Microstructure Approach to Exchange Rates. MIT Press, Cambridge. Kaul A., Sapp, S., 2009. Trading activity, dealer concentration and foreign exchange market quality. Journal of Banking and Finance 33, 2122-2131. Moulton, P.C., 2005. You can’t always get what you want: Trade-size clustering and quantity choice in liquidity. Journal of Financial Economics 78, 89-119. O’Hara, M., 2003. Presidential address: Liquidity and price discovery. Journal of Finance 63, 1335-1354. Osler, C., 2009. Foreign exchange microstructure: A survey of the empirical literature. In: Meyers, R.A. (Eds.), Encyclopedia of Complexity and System Science, Springer: New York. Pastor, L., Stambaugh, R.F., 2003. Liquidity risk and expected stock returns. Journal of Political Economy 111, 642-685. Roll, R., 1984. A simple implicit measure of the effective bid-ask spread in an efficient market. Journal of Finance 39, 1127-1139. Sager, M., Taylor, M., 2008. Commercially available order flow data and exchange rate movements: Caveat emptor. Journal of Money, Credit and Banking 40, 583-625. Stoll, H.R., 1989. Inferring the components of the bid-ask spread: Theory and empirical tests. Journal of Finance 44, 115-134. References in Chapter 3 Alexander, G. and Peterson, M., 2007. An analysis of trade size clustering and its relationship to stealth trading. Journal of Financial Economics 84, 435-471. Andrews, D.W.K., 1991. Heteroskedasticity and autocorrelation consistent covariance matrix estimation. Econometrica 59, 817-858. Bessembinder, H., Panayides, M. and Venkataraman, K., 2009. Hidden liquidity: An analysis of order exposure strategies in electronic stock markets. Journal of Financial Economics 94, 361-383. Barker, W., 2007. The global foreign exchange market: Growth and transformation. Bank of Canada Review 7, 4-13. Cerrato, M., Sarantis, N. and Saunders, A., 2011. An investigation of customer order flow in the foreign exchange market. Journal of Banking and Finance 35, 1892-1906. Chakravarty, S., 2001. Stealth trading: Which traders’ trades move stock prices? Journal of Financial Economics 61, 589-607. Chakravarty, S. and Sarkar, A., 2002. A model of broker’s trading, with application to order flow internalization. Review of Financial Economics 11, 19-36. Chan, K.S., 1993. Consistency and limiting distribution of the least squares estimates of a threshold autoregressive model. The Annals of Statistics 21, 520-533. Easley, D. and O’Hara, M., 2010. Liquidity and valuation in an uncertain world. Journal of Financial Economics 97, 1-11. Evans, M.D.D. and Lyons, R.K., 2002. Order flow and exchange rate dynamics. Journal of Political Economy 110, 170-180. Evans, M.D.D. and Lyons, R.K., 2008. How is macro news transmitted to exchange rates? Journal of Financial Economics 88, 26-50. Grossman, S.J. and Miller, M.H., 1988. Liquidity and market structure. Journal of Finance 43, 617-637. Grossman, S.J., Miller, M.H., Cone, K., Fischel, D. and Ross, D., 1997. Clustering and competition in asset markets. Journal of Law and Economics 40, 23-60. Grundy, B. and McNichols, M., 1989. Trade and revelation of information through prices and direct disclosure. Review of Financial Studies 2, 495-526. Gwilym, O., Clare, A. and Thomas, S., 1998. Extreme price clustering in the London equity index futures and options markets. Journal of Banking and Finance 22, 1193-1206. Gwilym, O. and Alibo, E., 2003. Decreased price clustering in FTSE 100 futures contracts following a transfer from floor to electronic trading. Journal of Futures Markets 23, 647-659. Gwilym, O. and Meng, L., 2010. Size clustering in the FTSE 100 index futures market. Journal of Futures Markets 30, 432-443. Harris, L., 1991. Stock price clustering and discreteness. Review of Financial Studies 4, 389-415. Harris, L., 1996. Does a minimum price variation encourage order exposure? Unpublished working paper, University of Southern California, Los Angeles. Hasbrouck, J., 1995. One security, many markets: Determining the contributions to price discovery. Journal of Finance 50, 1175-1199. Hodrick, L.S. and Moulton, P.C., 2005. Liquidity. Unpublished working paper, Columbia University. Kim, O. and Verrecchia, R., 1991. Market reactions to anticipated announcements. Journal of Financial Economics 30, 273-310. Lee, J. and Strazicich, M.C., 2003. Minimum Lagrange multiplier unit root test with two structural breaks. Review of Economics and Statistics 85, 1082-1089. Lee, J. and Strazicich, M.C., 2004. Minimum LM unit root test with one structural break. Manuscript, Department of Economics, Appalachian State University. Lyons, R.K., 2001. A review of transactions data sets. The Microstructure Approach to Exchange Rates. MIT Press. Mola, S. and Loughran, T., 2004. Discounting and clustering in seasoned equity offering prices. Journal of Financial and Quantitative Analysis 39, 1-23. Moinas, S., 2006. Hidden limit orders and liquidity in limit order markets. Unpublished working paper, Toulouse Business School, Toulouse, France. Moulton, P.C., 2005. You can't always get what you want: Trade-size clustering and quantity choice in liquidity. Journal of Financial Economics 78, 89-119. Osler, C., 2009. Foreign exchange microstructure: A survey of the empirical literature. In: Meyers, R.A. (Eds.), Encyclopedia of Complexity and System Science, Springer: New York. Perron, P., 1989. The great crash, the oil price shock, and the unit root hypothesis. Econometrica 57, 1361-1401. Perron, P., 2006. Dealing with structural breaks. Handbook of Econometrics (1): Econometric Theory. Sager, M. and Taylor, M., 2008. Commercially available order flow data and exchange rate movements: Caveat empto. Journal of Money, Credit and Banking 40, 583-625. Schmidt, P. and Phillips, B., 1992. LM tests for a unit root in the presence of deterministic trends. Oxford Bulletin of Economics and Statistics 54, 257-280. Sopranzetti, B.J. and Datar, V., 2002. Price clustering in foreign exchange spot markets. Journal of Financial Markets 5, 411-417. Yeoman, J.C., 2001. The optimal spread and offering price for underwritten securities. Journal of Financial Economics 62, 169-198. References in Chapter 4 Andrews, D. W. K., 1991. Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation. Econometrica 59 (3), 817-858. Backus, D., Foresi, S., Telmer, C. I., 2001. Affine Term Structure Models and the Forward Premium Anomaly. Journal of Finance 56 (1), 279-304. Backus, D., Kehoe P. J., Kydland, F. E., 1992. International Real Business Cycles. Journal of Political Economy 100 (4), 745-775. Backus, D., Smith, G., 1993. Consumption and Real Exchange Rates in Dynamic Economies with Non-traded Goods. Journal of International Economics 35 (3)-(4), 297-316. Bansal, R., 1997. An Exploration of the Forward Premium Anomaly in Currency Markets. Review of Financial Studies 10, 369-403. Bekaert, G., 1996. The Time-Variation of Risk and Return in Foreign Exchange Markets: A General Equilibrium Perspective. Review of Financial Studies 9 (2), 427-470. Burnside, C., Eichenbaum, M., Rebelo, S., 2008. Can Peso Problems Explain the Returns to the Carry Trade? NBER Working Paper No. 14054. Campbell, J. Y., 2003. Consumption-Based Asset Pricing. Handbook of the Economics of Finance, Edited by G. M. Constantinides, M. Harris and R. Stulz. Campbell, J. Y., Yogo, M., 2006. Efficient Tests of Stock Return Predict¬ability. Journal of Financial Economics 81 (1), 27-60. Campbell, J. Y., Yogo, M., 2005. Implementing the Econometric Methods in Efficient Tests of Stock Return Predictability. Unpublished Working Paper, University of Pennsylvania. Clarida, R., Davis, J., Pedersen, N., 2009. Currency Carry Trade Regimes: Beyond the Fama Regression. Journal of International Money and Finance 28 (8), 1375-1389. Cochrane, J. H., 2005. Asset Pricing. Revised Edition, Princeton University Press, Princeton, New Jersey. DeSantis, R. A., Fornari, F., 2008. Dose Business Cycle Risk Account for Systematic Returns from Currency Positioning? The International Perspective. European Central Bank. Engle, C., 1996. The Forward Discount Anomaly and the Risk Premium: A Survey of Recent Evidence. Journal of Empirical Finance 3 (2), 123-192. Fama, E. E., MacBeth, J. D., 1973. Risk Return and Equilibrium: Empirical Tests. Journal of Financial Political Economy 81 (3), 607-636. Fama, E. E., 1984. Forward and Spot Exchange Rates. Journal of Monetary Economics 14 (3), 319-338. Hollifield, B., Yaron, A., 2003. The Exchange Risk Premium: Real and Nominal Factors. Unpublished Working Paper, University of Pennsylvania. Lustig, H., Verdelhan, A., 2007. The Cross Section of Foreign Currency Risk Premia and Consumption Growth Risk. American Economics Review 97 (1), 89-117. Lustig, H., Roussanov, N., Verdelhan, A., 2008. Common Risk Factors in Currenncy Markets. NBER Working Paper No. 14082. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/66632 | - |
dc.description.abstract | 本論文研究的目的是利用市場微結構以及總體經濟理論來探討匯率的決定因子。本論文以三篇子研究來驗證(1)委託單流量以及流動性因子之整合模型在每日匯率變動中所扮演的角色,(2)跨國的消費成長差異在拋補的利率平價模型中是否能解釋每週匯率的變動。
第二章,我們著重在為何委託單流量模型應該加入流動性因子的原因。我們建立一個整合的模型去討論不同交易密度之外匯市場中,委託單流量以及實現的買賣價差如何影響匯率的變動。最後以一般化的動差模型來驗證該實證結果的穩固性以及一致性。我們的實證結果顯示委託單流量以及買賣價差在決定每日匯率變動上同時扮演重要的角色。有鑑於此,我們主張除了某些交易密度很高的貨幣外,委託單流量模型最好能考慮這些流動性因子在外匯市場微結構的影響性。 第三章,我們討論委託單流量在不同的訊息異質性與流動性下,對三種主要貨幣傳送訊息的能力。我們根據價格叢集性與交易量叢集性將樣本觀察值分成3×3的實驗設計矩陣來分析委託單流量傳送訊息的能力。該研究特別之處是我們分別以價格叢集性與交易量叢集性測度來代表不完美外匯市場的訊息異質性與流動性。我們發現市場參與者偏好在高訊息異質性以及與流動性時進行交易,這可能是因為市場參與者想要對其他交易者隱藏交易訊息並且為了避免交易的不確定性而對流動性有較高的需求。 第四章,我們探討當外匯市場出現未解的遠期溢酬現象時,拋補的利率平價模型對遠期匯率變動的估計會出現不合理的結果。此時,跨國間的消費成長差異是否具有改善利率平價模型估計偏誤的功能?實證結果指出我們的模型能夠降低利率平價模型對外匯遠期溢酬估計偏誤的情況。 | zh_TW |
dc.description.abstract | The purpose of this dissertation is to investigate the determinant of the foreign exchange rate according to the microstructure and macroeconomic theory. In particular, this dissertation proposes three essays in order to (1) investigate what roles of the order flow and liquidity factors play on the dynamics in the daily foreign exchange rates by estimating the unified model, (2) examine whether the consumption growth differential across the countries with the covered interest rate parity model can explain the change in the weekly foreign exchange rates.
In Chapter 2, we aim to demonstrate why liquidity factors should be involved in the daily order flow model. We develop a unified model to show explicitly how the order flow and realized bid-ask spread affect the foreign exchange rate when trading density is different. Toward this end, robust estimation of the generalized method of moments is proposed. The proposed model is designed to reexamine the consistent estimates of our unified model with the order flow and the bid-ask spread. Empirically, our results provide consistent evidence that both order flow and liquidity factors play important roles in the determinant of the daily foreign exchange rate. Our findings suggest that the order flow model is better at incorporating these microstructure effects except for some currencies with a very high level of trading density. In Chapter 3, we discuss the ability of the information transmission of the order flow for major three currency pairs with the distinct heterogeneous information and liquidity. Our proposed model is designed to analyze the explanatory power of the order flow by using the price clustering and trade-size clustering measures to divide the total observations into the 3 by 3 matrix. In particular, heterogeneous information and liquidity are estimated by introducing measures under the setting of the price clustering and trade-size clustering in the imperfect foreign exchange rate markets. We find that traders prefer to trade when foreign exchange market is in the high heterogeneous information and the high liquidity. This result can be explained by the hidden information to reveal less information to other traders and the demand of liquidity to avoid the execution uncertainty. In Chapter 4, we investigate whether the consumption growth differential is involve in the covered interest rate parity when there is an invalid estimate of the interest rate differential caused by the forward premium puzzle. Empirically, we show that our proposed model is able to reduce the estimating bias caused by the forward premium puzzle. | en |
dc.description.provenance | Made available in DSpace on 2021-06-17T00:47:36Z (GMT). No. of bitstreams: 1 ntu-101-D92724015-1.pdf: 877556 bytes, checksum: 24d162f56d6b988ee01084362699ca42 (MD5) Previous issue date: 2012 | en |
dc.description.tableofcontents | 中文摘要 I
Abstract III Contents V 1. Introduction 1 2. Order flow, bid-ask spread and trading density in foreign exchange markets 5 2.1. Introduction 5 2.2. Methodology 10 2.2.1. Total price change in efficient markets 10 2.2.2. Price changes due to the bid-ask spread 11 2.2.3. Serial covariance of price change due to the spread 14 2.3. Data description and empirical procedures 16 2.3.1. The extended order flow model 21 2.3.2. Volatility of the foreign exchange rate 22 2.4. Empirical results of liquidity and order flow effect 24 2.5. Conclusions 29 Appendix 2.A. Derivation of serial covariance of transaction price changes 30 Appendix 2.B. Details of the daily interest rate 30 Appendix 2.C. Robustness checks of the GMM model 31 References 33 Table 2.1 Summary statistics of daily currency returns, order flows, and the changes in bid-ask spreads 35 Table 2.2 Estimates of daily model for high trading density currencies 36 Table 2.3 Estimates of daily model for low trading density currencies 37 Table 2.4 GMM estimates of daily high trading density currencies 38 Table 2.5 GMM estimates of daily low trading density currencies 39 Table 2.A Derivation of serial covariance of transaction price changes 41 Table 2.B List of interest rates corresponding to each currency 41 Table 2.C.1 Tests for GMM estimates of daily high trading density currencies 42 Table 2.C.2 Tests for GMM estimates of daily low trading density currencies 43 Figure 2.1 Time series of the non-adverse selection components 40 3. Re-examining the order flow and exchange rate dynamics–using the clustering in trade-size and price 44 3.1. Introduction 44 3.2. Data description of heterogeneous information and liquidity 51 3.3. Empirical results of asymmetric effects on the order flow 58 3.4. Conclusion 71 Appendix 3.A. Asymmetry of the heterogeneous information and the liquidity forthe lagged order flow model 73 Appendix 3.B. Comparison of the order flow coefficients 74 Appendix 3.C. LM Unit Root Tests with One or Two Structural Breaks 75 References 77 Table 3.1 Frequency and independence of price and quantity clustering 80 Table 3.2 Summary statistics of daily currency-pair returns and order flows 81 Table 3.3 Asymmetry of the heterogeneous information and the liquidity for the order flow on the foreign exchange rate return 82 Table 3.4 Three factor model 83 Table 3.5 Asymmetric threshold model of the order flow 84 Table 3.6 Presence of structural breaks for the foreign exchange rate returns 85 Table 3.7 Comparison of the order flow models 86 Table 3.A Asymmetry of the heterogeneous information and the liquidity for the lagged order flow model 87 Table 3.B Comparison of the order flow coefficients 88 4. Does consumption growth differential affect the currency excess return? 89 4.1. Introduction 89 4.2. A consumption-based CIP model for currency excess returns 95 4.3. Data description and empirical results 98 4.3.1 Data 99 4.3.2 Building currency portfolios to consumption growth differential 100 4.3.3 Currency return predictability and robustness check 106 4.4. Conclusion 111 Appendix 4.A. Pricing kernels across country for the foreign exchange rate 113 Appendix 4.B. Approximation for currency excess returns 114 Appendix 4.C. Data source and description 115 Appendix 4.D. Description of Bonferroni Q test 116 References 118 Table 4.1 Risk prices of consumption growth differential, interest rate differential and forward premium factors 120 Table 4.2 Properties of weekly excess return, interest rate differential and the consumption growth risk factor 121 Table 4.3 Predictive regression of the weekly currency excess return on the lagged interest rate differential and lagged consumption growth risk factor for those portfolios with the corresponding maturity 122 Table 4.4 Predictive regression of the weekly change in the exchange rate on the lagged forward premium and lagged consumption growth risk factor for those portfolios with the corresponding maturity 123 5. Conclusion 124 | |
dc.language.iso | en | |
dc.title | 匯率決定因子之研究 | zh_TW |
dc.title | Essays on the Determinants of Foreign Exchange Rates | en |
dc.type | Thesis | |
dc.date.schoolyear | 100-1 | |
dc.description.degree | 博士 | |
dc.contributor.coadvisor | 張銘仁(Ming-Jen Chang) | |
dc.contributor.oralexamcommittee | 林修葳,張元晨,萬哲鈺 | |
dc.subject.keyword | 市場微結構,委託單流量,流動性,買賣價差,交易密度,訊息異質性,消費成長差異, | zh_TW |
dc.subject.keyword | Microstructure,Order flow,Liquidity,Bid-ask spread,Trading density,Heterogeneous information,Consumption growth differential, | en |
dc.relation.page | 125 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2011-12-23 | |
dc.contributor.author-college | 管理學院 | zh_TW |
dc.contributor.author-dept | 國際企業學研究所 | zh_TW |
顯示於系所單位: | 國際企業學系 |
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