الصفحة 1
الصفحة 1
Money, Banking, and Financial Markets : A Modern Introduction to Macroeconomics
Introduction to money, banking, and financial markets, with a special emphasis on the importance of confidence and trust in the macroeconomic system. It also presents the theory of endogenous money creation, in contrast to the standard money multiplier and fractional reserve explanation found in other textbooks. The U.S. economy and financial institutions are used to explain the theoretical and practical framework, with international examples weaved in throughout the text. It covers key topics including monetary policy, fiscal policy, accounting principles, credit creation, central banks, and government treasuries. Additionally, the book considers the international economy, including exchange rates, the Eurozone, Chinese monetary policy, and reserve currencies. Taking a broad look at the financial system, it also looks at banking regulation, cryptocurrencies, real estate, and the oil and gold commodity markets. Students are supported with chapter objectives, key terms, and problems.
Monetary Policy and Macroeconomic Stabilization in Latin America
Latin America is a very important region of the globe, which has been buffeted by successive waves of economic instability within the last decades. These waves have caused several episodes of hyperinflation or near hyperinflation, and several currency and financial crises, which, in certain moments, have even spilled over and affected other emerging markets. This has resulted in huge costs in terms of lost potential growth, and, as is inevitable, the markets most affected by this have been the least capable of defending themselves. In a region plagued by still considerable rates of social exclusion, with some of the highest rates of income concentration in the whole globe, the human costs of these crises have been very substantial. Starting in the early 1990s, the slow implementation of reforms, plus the resumption of more sustained growth—to a substantial degree linked to the increase in commodity prices, especially since the early 2000s—seems to have resulted in a more stable situation. Initially, in early reformers like Chile, later in the larger economies of the region, like Brazil and Mexico, a consensus— embraced by both sides of the political spectrum—towards integration in global markets, both in their trade and financial components, floating exchange rates, independent monetary authorities, and sustainable fiscal policies has emerged.
International trade theory : Capital, knowledge, economic structure, money, and prices over time
The development of international trade theory has created a wide array of different theories, concepts and results. Economic students are trained to understand international interactions by severally incompatible theories one by one in the same course. In order to overcome incoherence among multiple theories, we need a general theoretical framework which enables us to account for the phenomena explained by the current theories in a unified manner to draw together all of the disparate branches of trade theory into a single organized system of knowledge. This book provides a powerful – but easy to operate - engine of analysis that sheds light not only on trade theory per se, but on many other dimensions that interact with trade, including inequality, saving propensities, education, research policy, and knowledge. The book starts with the traditional static trade theories. Then, it develops dynamic models with capital and knowledge under perfect competition and/or monopolistic competition.
Foreign Exchange Rate Forecasting using Artificial Neural Networks
In this monograph, the authors try to apply artificial neural networks (ANNs) to exchange rates forecasting. Selection of the ANN approach for - change rates forecasting is because of ANNs’ unique features and powerful pattern recognition capability. Unlike most of the traditional model-based forecasting techniques, ANNs are a class of data-driven, self-adaptive, and nonlinear methods that do not require specific assumptions on the und- lying data generating process. These features are particularly appealing for practical forecasting situations where data are abundant or easily available, even though the theoretical model or the underlying relationship is - known. Furthermore, ANNs have been successfully applied to a wide range of forecasting problems in almost all areas of business, industry and engineering.
