4 resultados para Chinese stock market

em Universidade Complutense de Madrid


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In the period 1999-2007 Spanish imports from China multiplied by six, making that Asian country the fourth largest supplier to the Spanish economy. In this paper, we analyse whether this massive increase in imports impacted on the labour markets of Spanish provinces to differing degrees, due to differences in their initial productive specialization. Our results show that Spanish provinces with a higher exposure to Chinese imports experienced larger drops in manufacturing employment as a share of the working-age population. However, this reduction was compensated for by increases in non-manufacturing employment.

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The primary purpose of the paper is to analyze the conditional correlations, conditional covariances, and co-volatility spillovers between international crude oil and associated financial markets. The paper investigates co-volatility spillovers (namely, the delayed effect of a returns shock in one physical or financial asset on the subsequent volatility or co-volatility in another physical or financial asset) between the oil and financial markets. The oil industry has four major regions, namely North Sea, USA, Middle East, and South-East Asia. Associated with these regions are two major financial centers, namely UK and USA. For these reasons, the data to be used are the returns on alternative crude oil markets, returns on crude oil derivatives, specifically futures, and stock index returns in UK and USA. The paper will also analyze the Chinese financial markets, where the data are more recent. The empirical analysis will be based on the diagonal BEKK model, from which the conditional covariances will be used for testing co-volatility spillovers, and policy recommendations. Based on these results, dynamic hedging strategies will be suggested to analyze market fluctuations in crude oil prices and associated financial markets.

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Introduction. This thesis is framed in the last 15 years of history of the Spanish equity market (years 2000 to 2014). In this sense and, as an introduction of this work, in the first chapter the main features of the background of the electronic market for shares and the implications that the migration from out-c1y circles to this automatic system is explained. The main changes of this electronic system (Spanish stock exchange interconnection system) are detailed in this part. Also in this first chapter is explained the important European meeting, in December 1999, of eight stock exchanges which foresee, in a first step, to design a single market model for, lately, try to merge, final step that did not take place. After this initial moment in December 1999, in this work the main features of the market model of the main European markets (London, Paris, Germany and Italy) are generally described, given that it is important to consider the European context of the Spanish equity market, specially during these last fifteen years. Along chapter two, the thesis is supported with the theoretic frame explaining here the nature of markets and their important role in the economy, detailing afte1wards the Spanish case from the point of view of its institutional structure and legal framework. Besides, in this chapter, a deep review of initial public offerings (main concepts and calendar steps) is done as well as take-over bids (typology and key-concepts)...

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This paper empirically investigates volatility transmission among stock and foreign exchange markets in seven major world economies during the period July 1988 to January 2015. To this end, we first perform a static and dynamic analysis to measure the total volatility connectedness in the entire period (the system-wide approach) using a framework recently proposed by Diebold and Yilmaz (2014). Second, we make use of a dynamic analysis to evaluate the net directional connectedness for each market. To gain further insights, we examine the time-varying behaviour of net pair-wise directional connectedness during the financial turmoil periods experienced in the sample period Our results suggest that slightly more than half of the total variance of the forecast errors is explained by shocks across markets rather than by idiosyncratic shocks. Furthermore, we find that volatility connectedness varies over time, with a surge during periods of increasing economic and financial instability.