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

Zero-non-zero patterned vector error correction modeling for I(2) cointegrated time series with applications in testing PPP and stock market relationships

Vector error-correction models (VECMs) have become increasingly important in their application to financial markets. Standard full-order VECM models assume non-zero entries in all their coefficient matrices. However, applications of VECM models to financial market data have revealed that zero entries are often a necessary part of efficient modelling. In such cases, the use of full-order VECM models may lead to incorrect inferences. Specifically, if indirect causality or Granger non-causality exists among the variables, the use of over-parameterised full-order VECM models may weaken the power of statistical inference. In this paper, it is argued that the zero–non-zero (ZNZ) patterned VECM is a more straightforward and effective means of testing for both indirect causality and Granger non-causality. For a ZNZ patterned VECM framework for time series of integrated order two, we provide a new algorithm to select cointegrating and loading vectors that can contain zero entries. Two case studies are used to demonstrate the usefulness of the algorithm in tests of purchasing power parity and a three-variable system involving the stock market.

Causality detection on US mutual fund movements using evolutionary subset time-series

In this paper we develop an evolutionary kernel-based time update algorithm to recursively estimate subset discrete lag models (including fullorder models) with a forgetting factor and a constant term, using the exactwindowed case. The algorithm applies to causality detection when the true relationship occurs with a continuous or a random delay. We then demonstrate the use of the proposed evolutionary algorithm to study the monthly mutual fund data, which come from the 'CRSP Survivor-bias free US Mutual Fund Database'. The results show that the NAV is an influential player on the international stage of global bond and stock markets.

Conditional risk, return and contagion in the banking sector in Asia

This paper investigates risk and return in the banking sector in three Asian markets of Taiwan, China and Hong Kong. The study focuses on the risk-return relation in a conditional factor GARCH-M framework that controls for time-series effects. The factor approach is adopted to incorporate intra-industry contagion and an analysis of spillovers between large banks and small banks. Finally, the study provides evidence on these relations before and after the Asian financial crisis of 1997. The results are generally consistent across the markets and with expectations.