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dc.contributor.authorBhattacharya, Prasad Sen_NZ
dc.contributor.authorSingh, Harminderen_NZ
dc.date.available2011-04-07T03:18:54Z
dc.date.copyright2007-03-23en_NZ
dc.identifier.citationBhattacharya, P. S., & Singh, H. (2007, March 23). An explanation of unbiased expectations and efficient market hypothesis using Markov switching framework. University of Otago Department of Finance Seminar Series. Presented at the University of Otago, Finance department, Seminar.en
dc.identifier.urihttp://hdl.handle.net/10523/1510
dc.description.abstractThis paper uses Indian stock futures data to explore unbiased expectations and efficient market hypothesis. Having experienced voluminous transactions within a short time span after its establishment, the Indian stock futures market provides an unparalleled case for exploring these issues involving expectation and efficiency. Besides analyzing market efficiency between cash and futures prices using cointegration and error correction frameworks, the efficiency hypothesis is also investigated after explicitly modeling the underlying state of the market (expansion or contraction) through the first-order Markov switching set-up. The results based on Markov switching analysis show that relatively longer time horizon is more effective in eliminating arbitrage opportunities than the short run.en_NZ
dc.format.mimetypeapplication/pdf
dc.relation.ispartofUniversity of Otago Department of Finance Seminar Seriesen_NZ
dc.relation.urihttp://www.business.otago.ac.nz/finc/research/seminars.htmlen_NZ
dc.subjectEfficient market hypothesisen_NZ
dc.subjectFutures marketen_NZ
dc.subjectCointegrationen_NZ
dc.subjectError correction, Markov switching.en_NZ
dc.subject.lcshHF Commerceen_NZ
dc.subject.lcshHF5601 Accountingen_NZ
dc.subject.lcshHG Financeen_NZ
dc.titleAn explanation of unbiased expectations and efficient market hypothesis using Markov switching frameworken_NZ
dc.typeConference or Workshop Item (Seminar, Speech or Other Presentation)en_NZ
dc.description.versionUnpublisheden_NZ
otago.bitstream.pages39en_NZ
otago.date.accession2007-04-12en_NZ
otago.schoolFinanceen_NZ
otago.openaccessOpen
otago.place.publicationDunedin, New Zealanden_NZ
dc.identifier.eprints600en_NZ
dc.description.refereedNon Peer Revieweden_NZ
otago.school.eprintsFinance & Quantitative Analysisen_NZ
dc.description.referencesFama, E. (1970). “Efficient capital markets: a review of theory and empirical work.” Journal of Finance, 25, 383- - 417. Fuller, W.A. (1995). Introduction to Statistical Time Series. 2nd edition. New York: Wiley. Hansen, L.P. and R.J. Hodrick. (1980). “Forward exchange rates as optimal predictors of future spot rates: an economic analysis.” Journal of Political Economy, 88, 829- - 853. Haigh, M.S. (2000). “Cointegration, Unbiased expectations, and forecasting in the BIFFEX freight futures market.” The Journal of Futures Market, 20, 545- - 571. Higgs, J.G., Rambaldi, A and B. Davidson, B. (1999). “Is the Australian wool futures market efficient as a predictor of spot prices?” The Journal of Futures Market, 19, 565- - 582. Hokkio, C. and M. Rush. (1989). “Market efficiency and cointegration: an application to Sterling and Deutschmark exchange rates,” Journal of International Money and Finance, 8, 74- - 88. Ivanovic, I., and Howley, P. (2004). “Examining the Forward Pricing function of the Australian Equity Index Futures Contract,” Accounting and Finance, 44, 57-73. Kavussanos, M.G., and Nomikos N.K. (1999). “The forward pricing function of the Shipping freight futures market,” The Journal of Futures Market, 19, 353- -376. Kenourgios, D.F. (2005). “Testing Efficiency and the Unbiasedness hypothesis of the Emerging Greek Futures Market,” European Review of Economics and Finance, 4, 3- - 20. Kenourgios. D., and Samitas, A. (2004). “Testing efficiency of the Copper Futures Market: New Evidence from London Metal Exchange,” Global Business and Economics Review, 261- - 271. Johansen, S. (1998). “Statistical Analysis of Cointegration Vectors,” Journal of Economic Dynamic and Contrology, 12, 231-254. Johansen, S. (1991). “Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models,” Econometrica, 59, 1551- -1580. Johansen, S. and K. Juselius. (1990). “The Full Information Maximum Likelihood Procedure for Inference on Cointegration with Application to the Demand for Money,” Oxford Bulletin of Economics and Statistics, 52, 169- - 210. Perron, P. (1997). “Further Evidence from Breaking Trend Functions in macroeconomic variables,” Journal of Econometrics, 80, 355- - 385. Pizzi, M.A., Economopoulos, A.J. and H.M. O’Neill. (1988). “An Examination of the Relationship between Stock Index Cash and Futures Markets: A Cointegration Approach,” The Journal of futures Markets, 18, 297- - 305. Tsay, R. S. (1986). Nonlinearity tests for Time Series. Biometrika, 73, 461- - 466. Tsay, R.S. (2001). Analysis of Financial Time Series. New York: John Wiley. Vipul. (2005). “Futures and Options Expiration-Day Effects: The Indian Evidence,” The Journal of Futures Markets, 25, No. 11, 1045- - 1065.en_NZ
otago.event.dates23 March 2007en_NZ
otago.event.placeCommerce 5.37, University of Otago, Dunedin, Otagoen_NZ
otago.event.typeotheren_NZ
otago.event.titleUniversity of Otago, Finance department, Seminaren_NZ
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