I. Moosa

Exchange Rate Forecasting: Techniques and Applications (eBook, PDF)

• Format: PDF

Produktbeschreibung

Forecasting exchange rates is a variable that preoccupies economists, businesses and governments, being more critical to more people than any other variable. In Exchange Rate Forecasting the author sets out to provide a concise survey of the techniques of forecasting - bringing together the various forecasting methods and applying them to the exchange rate in a highly accessible and readable manner. Highly practical in approach, the book provides an understanding of the techniques of forecasting with an emphasis on its applications and use in business decision-making, such as hedging, speculation, investment, financing and capital budgeting. In addition, the author also considers recent developments in the field, notably neural networks and chaos, again, with easy-to-understand explanations of these "rocket science" areas. The practical approach to forecasting is also reflected in the number of examples that pepper the text, whilst descriptions of some of the software packages that are used in practice to generate forecasts are also provided.

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Produktdetails

• Verlag: Springer-Verlag GmbH
• Seitenzahl: 424
• Erscheinungstermin: 5. Februar 2016
• Englisch
• ISBN-13: 9780230379008
• Artikelnr.: 45964972

Autorenporträt

IMAD MOOSA is currently Professor in Economics and Finance at La Trobe University, Australia, prior to which he lectured at the University of Sheffield, UK. Before entering academia, he worked as a professional economist and investment banker for over ten years.

Inhaltsangabe

Expectations and Forecasting: An Overview Exchange Rate Forecasting as an Input in the Decision-Making Process Univariate Time Series Techniques Multivariate Time Series Models Market-Based Forecasting: The Spot and Forward Exchange Rates Judgmental and Composite Forecasting Technical Analysis Trading Rules Recent Developments: Neural Networks and Chaos Measuring Forecasting Accuracy Selection, Implementation and Monitoring of Forecasts Case Studies Concluding Remarks References