The price elasticity of the Euro to movements in foreign reserves through European Central Bank intevention

The Euro has been used as the largest weighting element in a basket of currencies for forex arrangements adopted by several Central European countries outside the European Union (EU). The paper uses a new time-series approach to examine the relationship between the Euro exchange rate and the level of foreign reserves. It employs Zero-no-zero (ZNZ) patterned vector error-correction (VECM) modelling to investigate Granger causal relations among foreign reserves, the European Monetary Union money supply and the Euro exchange rate. The findings confirm that foreign reserves may influence movements in the Euro's exchange rate. Further, ZNZ patterned VECM modelling with exogenous variables is used to estimate the amount of foreign reserves currently required in order to again achieve a targetted Euro exchange rate

System for foreign exchange trading using genetic algorithms and reinforcement learning

Foreign exchange trading has emerged recently as a significant activity in many countries. As with most forms of trading, the activity is influenced by many random parameters so that the creation of a system that effectively emulates the trading process will be very helpful. A major issue for traders in the deregulated Foreign Exchange Market is when to sell and when to buy a particular currency in order to maximize profit. This paper presents novel trading strategies based on the machine learning methods of genetic algorithms and reinforcement learning.

Hegemony, Institutionalism and US Foreign Policy: theory and practice in comparative historical perspective

This paper explores the theoretical and policy implications of contemporary American hegemony. A key argument is that the development of US hegemony generally, and the distinctive turn in US foreign policy that has occurred in the wake of 11 September in particular, can best be understood by placing recent events in a comparative and historical framework. The immediate post-World War II order laid the foundations of a highly institutionalised multilateral system that provided key benefits for a number of countries while simultaneously constraining and enhancing US power. An historical reading of US hegemony suggests that its recent unilateralism is undermining the foundations of its power and influence.

Diplomatic divergence in the antipodes: Globalisation, foreign policy and state identity in Australia and New Zealand

This article compares the constitutive relationship between foreign policy and globalisation in Australia and New Zealand. Drawing upon insights from constructivist international relations theory we argue that foreign policy instantiates a state's social identity, its self-understanding of its role and moral purpose by projecting a distinctive image onto the global stage. We explore the differences and the similarities between Australia and New Zealand by examining how each country views international order, global trade, global governance and human rights and international security. Although both countries appear to be transforming themselves into more 'globalised' states, there are significant differences in the way each seeks to balance the competing strategic and normative demands. This diplomatic divergence, we argue, stems from different conceptions of state identity.

A machine learning approach to intraday trading on foreign exchange markets

Foreign Exchange trading has emerged in recent times as a significant activity in many countries. As with most forms of trading, the activity is influenced by many random parameters so that the creation of a system that effectively emulates the trading process will be very helpful. In this paper we try to create such a system using Machine learning approach to emulate trader behaviour on the Foreign Exchange market and to find the most profitable trading strategy.

An implementation of genetic algorithms as a basis for a trading system on the foreign exchange market

Foreign exchange trading has emerged in recent times as a significant activity in many countries. As with most forms of trading, the activity is influenced by many random parameters so that the creation of a system that effectively emulates the trading process is very helpful. In this paper, we try to create such a system with a genetic algorithm engine to emulate trader behaviour on the foreign exchange market and to find the most profitable trading strategy.