Foreign exchange market

About: Foreign exchange market is a research topic. Over the lifetime, 6661 publications have been published within this topic receiving 153384 citations. The topic is also known as: forex & FX.

Labor markets and adjustment in open Asian economies : the Republic of Korea and Malaysia

Abstract: This article deals with the adjustment following external shocks in two open Asian economies: the Republic of Korea and Malaysia. There were important differences in the economic structure of the two countries as well as significant differences in the way external events produced crises that interrupted their dynamic economic growth. Detailed analyses of economic cycles in the two decades preceding 1987-88 show that the behavior of factor markets, particularly the markets for labor and foreign exchange, helped Korea to adjust quickly to the shocks but in Malaysia actually caused the crisis to deepen. For economies heavily dependent on exports, the unit cost of labor in dollars is of central importance as an index of the competitiveness of exports and hence of their ability to mount a sustained recovery after a difficult period. Accordingly, the heart of the analysis is the determination of the unit cost of labor and the factors affecting its change throughout the cycles. Concentration on this critical variable helps to spotlight the crucial differences in the factor markets of the two economies.

Asymmetric information, price discovery and macroeconomic announcements in FX market: do top trading banks know more?

Abstract: This study investigates information asymmetry in the foreign exchange market by testing the hypothesis that top trading banks possess superior information on the macroeconomy because they process greater order flow, which, according to the micro-structure literature, helps them aggregate the dispersed information and feel the general movements of the economy. Examining the information share of the banks in the Reuters EFX system using indicative GBP–$US data over 5 years, we find that the top 10 banks, out of 100 quoting banks in the market, have a monthly average share of over 70% of total market information, and around 80% during some US macroannouncements. These results suggest the possibility of private information over public news in the foreign exchange market. Copyright © 2009 John Wiley & Sons, Ltd.

An integrated eigenvector-DEA-TOPSIS methodology for portfolio risk evaluation in the FOREX spot market

Abstract: The foreign exchange market (FOREX) is the largest financial market in the world, with a volume of over $2 trillion daily Decision making about buying and selling the existing products in this market depends on several effective factors which cause the high risk in it and make it a sensitive job So in this paper a new method which is extracted from the multiple decision making methods named eigenvector-DEA-TOPSIS methodology is presented to evaluate the risk of the number of related portfolios to this market The eigenvector technique is used to determine the weights of criteria and some linguistic terms are applied for assessing portfolio risks under each criterion, then in order to determine the value of linguistic terms we use the data envelopment analysis (DEA) method Finally we use TOPSIS method for aggregating portfolio risks under different criteria into an overall risk score for each portfolio and ranking the portfolios according to their risks The integrated eigenvector-DEA-TOPSIS methodology is applicable to any number of decision alternatives and is illustrated with a numerical example

Tail dependence structure of the foreign exchange market: A network view

Abstract: Tail dependence of financial entities describes when the price of one financial asset has an extreme fluctuation (e.g., price sharply rises or falls), the degree of its effect on the price fluctuation of another asset. Under the background of the global financial crisis, tail dependence structure of financial entities plays an important role in financial risk management, portfolio selection, and asset pricing. In this paper, we propose a concept of tail dependence networks to investigate the tail dependence structure of the foreign exchange (FX) market. Lower- and upper-tail dependence networks for 42 major currencies in the FX market from 2005 to 2012 are constructed by combing the symmetrized Joe-Clayton copula model and two filtered graph algorithms, i.e., the minimum spanning tree (MST) and the planar maximally filtered graph (PMFG). We also construct the tail dependence hierarchical trees (HTs) associated with the MSTs to analyze the currency clusters. We find that (1) the two series of lower- and upper-tail dependence coefficients present different statistical properties; (2) the upper-tail dependence networks are tighter than the lower-tail dependence networks; and (3) different currency clusters, cliques and communities are respectively found in the two tail dependence networks. The key empirical results indicate that market participants should consider the different topological features at different market situations (e.g., a booming market or a recession market) to make decisions on the investing or hedging strategies. Overall, our obtained results based on the tail dependence networks are new insights in financial management and supply a novel analytical tool for market participants.