OJS  Vol.4 No.1 , February 2014
Exchange Rate Market Sentiment Analysis of Major Global Currencies
Abstract: The paper deals with the analysis of market sentiments in exchange rates which are of great interest to trading individuals and institutional investors. For example, an institutional investor or a trading individual makes better investments and minimizes losses when equipped with an understanding of market sentiments in weekly or monthly exchange returns. In the approach suggested here, a typical market sentiment is defined on the basis of the certain function of the mean and the standard error of the logarithm of the ratio of successive daily exchange rates. Based on this surmise, the market sentiments are classified into various states, whereby states are defined according to the perceptions of the market player. A multinomial probability model is built to capture the uncertainties in market sentiments. Two asymptotically distribution-free tests, namely the chi-square and the likelihood ratio test of goodness of fit for the hypothesis of the symmetry in market sentiments are suggested. Two different measures of market sentiments are proposed. The approach advocated here will be of interest to researchers, exchange rate traders and financial analysts. As an application of the proposed line of approach, we analyze weekly market sentiments that govern exchange rates of the major global currencies—EUR, GBP, SDR, YEN, ZAR, USD, data from 2001-2012. Some interesting conclusions are revealed based on the data analysis.
Cite this paper: K. Rao and A. Ramachandran, "Exchange Rate Market Sentiment Analysis of Major Global Currencies," Open Journal of Statistics, Vol. 4 No. 1, 2014, pp. 49-69. doi: 10.4236/ojs.2014.41006.

[1]   J. C. Hull, “Options, Futures, and Other Derivatives,” 5th Edition, Englewood Cliffs, Prentice Hall, 2003.

[2]   R. F. Engel, “Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation,” Econometrica, Vol. 50, No. 4, 1982, pp. 987-1008.

[3]   T. A. Bollerslev, “A Conditional Heteroscedastic Time Series Model for Speculative Prices and Rates of Return,” Review of Economics and Statistics, Vol. 69, No. 3, 1987, pp. 542-547.

[4]   D. Blake, “Financial Market Analysis,” 2nd Edition, John Wiley & Sons Ltd., Chichester, 2005.

[5]   N. Sheldon, “Option Volatility & Pricing: Advanced Trading Strategies and Techniques,” McGraw Hill Professional, New York, 1994.

[6]   K. Chung and O. Jorda, “Fluctuations in Exchange Rates and the Carry Trade,” Working Paper No. 405, Institute for Monetary and Economic Research, The Bank of Korea, Seoul, 2009.

[7]   A. Markiewicz, “Model Uncertainty and Exchange Rate Volatility,” International Economic Review, Vol. 53, No. 3, 2012, pp. 815-844.

[8]   C. F. Baum and N. Ozkan, “Nonlinear Effects of Exchange Rate Volatility on the Volume of Bilateral Exports,” Journal of Applied Econometrics, Vol. 19, No. 1, 2004, pp. 1-23.

[9]   T. G. Andersen, T. Bollerslev, F. Diebold and P. Labys, “The Distribution of Realized Exchange Rate Volatility,” Journal of the American Statistical Association, Vol. 96, No. 453, 2000, pp. 42-55.

[10]   C. Christiansen, “Intertemporal Risk-Return Trade-Off in Foreign Exchange Rates,” Journal of International Financial Markets, Institutions & Money, Vol. 21, No. 4, 2011, pp. 535-549.

[11]   O. de Bandt, “Measuring Long-Run Exchange Rate Pass-Through-Recent Developments in International Money and Finance,” Economics, Vol. 2, 2008, pp. 1-36.

[12]   J. J. Lim and C. S. Yue, “Political Risk and the Exchange Rate: An Exploration with a Regime Switching Model, Edited Volumes—Information Technology in Asia: New Development Paradigms,” Institute of Southeast Asian Studies, Singapore City, 2002.

[13]   I. Nouri, “Exchange Rate Forecasting: A Combination Approach,” American Journal of Scientific Research, No. 22, 2011, pp. 110-118.

[14]   R. Ramasamy and M. H. M. Helmi, “Impact of Weiner Process on Exchange Rate Forecasting,” Global Journal of Management and Business Research, Vol. 10, No. 3, 2010, pp. 69-78.

[15]   S. M. Ross, “An Elementary Introduction to Mathematical Finance: Options and Other Topics,” Cambridge University Press, Cambridge, 2003.

[16]   E. L. Grant and R. S. Leavenworth, “Statistical Quality Control,” McGraw-Hill, New York, 2005.

[17]   A. Stuart and K. Ord, “Kendall’s Advanced Theory of Statistics, Volume1: Distribution Theory,” 6th Edition, Holder Arnold, London, 1994.

[18]   A. Stuart, K. Ord and S. Arnold, “Kendall’s Advanced Theory of Statistics, Volume 2 A: Classical Inference & the Linear Model,” 6th Edition, Holder Arnold, London, 1999.