The long-term relationship between financial markets and economic conditions is unclear. This paper aims to investigate how movements in the financial markets interact with the broader economy in the long term. Dynamic factor models are implemented to capture unobserved factors—common factor and sector factors. The common factor represents the co-movement between the real economy and the financ...

Since the late 1980s, most developing countries adopt a policy of attracting investments for Private Participation in Infrastructure (PPI) projects. With a perspective of sustainability, this paper offers a first attempt to examine whether the sustainable PPI investments promote financial market development. First, we demonstrate how the PPI policy enlargers the size of financial markets and th...

In this paper we want to discuss macroscopic and microscopic properties of financial markets. By analyzing quantitatively a database consisting of 13 minute per minute recorded financial time series, we identify some macroscopic statistical properties of the corresponding markets, with a special emphasize on temporal correlations. These analysis are performed by using both linear and nonlinear ...

We analyse the impact of news on five financial markets in the Czech Republic, Hungary and Poland using a newly constructed data set in a GARCH framework. Macroeconomic shocks (on GDP, inflation rate, current account and trade balance) are constructed as deviations from expected values. EMU-related political and fiscal news is captured as news dummies. Macroeconomic shocks significantly affect ...

Speech given at Session 1: The Global Capital Market: What’s Next. Michael Patterson spoke on aspects of the global financial markets that are common to Japan and the United States including the converging roles of traditionally distinct kinds of institutions participating in such markets; the impact of that convergence on legal and regulatory structures, particularly in the United States; and ...

Financial time series forecasting is a popular application of machine learning methods. Previous studies report that advanced forecasting methods predict price changes in financial markets with high accuracy and that profit can be made trading on these predictions. However, financial economists point to the informational efficiency of financial markets, which questions price predictability and ...

BACKGROUND AND AIMS To date, few studies have examined the clinical manifestation of disordered gamblers in financial markets. This study examined the differences in the clinical and treatment-related features of gambling disorder between financial markets and horse races. METHODS Subjects who met the DSM-IV criteria for pathological gambling (PG) and who sought treatment were assessed by ret...