Financial forecasting for business and economics / Eduard J. Bomhoff.Material type: TextPublication details: London : The Dryden Press, c1994. ISBN: 003099005X; 0121128903Subject(s): Economics -- Statistical methods | Economic forecasting -- Methodology | Economic forecastingDDC classification: 330.0112
|Item type||Home library||Call number||Status||Date due||Barcode||Item holds|
|Two Week Loan||de Havilland Learning Resources Centre Main Shelves||338.544 BOM (Browse shelf(Opens below))||Available||4403384984|
|Two Week Loan||de Havilland Learning Resources Centre Main Shelves||338.544 BOM (Browse shelf(Opens below))||Available||4403384993|
Enhanced descriptions from Syndetics:
Bibliography: p212-216. - Includes index.
Ch. 1. Introduction -- Ch. 2. Analysis of a Single Time Series -- Ch. 3. Analysis of Multivariate Time Series -- Ch. 4. Introducing the Multivariate Kalman Filter -- Ch. 5. Forecasting Economic Growth -- Ch. 6. Forecasting with the Term Structure of Interest Rates -- Ch. 7. Forecasting Returns on the Stock Market Index -- Ch. 8. Forecasting Exchange Rates -- Ch. 9. Four Econometric Fashions and the Kalman Filter Alternative.
Until recently a formidable gap separated practical business economists, who forecast economic growth and exchange and interest rate fluctuations, from academic researchers Academic journals focused on statistical techniques which were inappropriate for practical business forecasting. Economic theory, especially in the field of business cycle research became more and more abstract and harder to apply. These twin developments drove many practitioners to technical analysis. Fortunately, the gap is being bridged. New scholarly research offers much more scope for useful forecasts of exchange rates and stock market indices. Advances in statistics, especially in the estimation of Kalman filters, allows for better treatment of non-stationary variables. Financial Forecasting for Business and Economics summarizes the important new thinking on financial market forecasting and on the statistical modelling of non-stationary series in a clear and readable manner. The first four chapters deal with forecasting economic and financial indicators. In addition there are separate chapters on the forecasting of economic growth, stock market indices, exchange rates and on the relationship between short and long term interest rates. The emphasis throughout is on real-life examples using data from a wide variety of countries and sources. Readers who have a basic familiarity with statistical analysis will use this book to learn through practical examples which pitfalls to avoid in economic and financial forecasting and how to construct a sensible forecasting model.