000 | 02431nam a22002655i 4500 | ||
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001 | 137456 | ||
003 | ISI Library, Kolkata | ||
005 | 20170310134205.0 | ||
008 | 151203s2016 nju 000 0 eng | ||
020 | _a9780691140131 | ||
040 | _aISI Library | ||
082 | 0 | 4 |
_a330.0112 _223 _bEl46 |
100 | 1 |
_aElliott, Graham, _eauthor |
|
245 | 1 | 0 |
_aEconomic forecasting / _cGraham Elliott and Allan Timmermann. |
260 |
_aPrinceton : _bPrinceton University Press, _c©2016. |
||
300 |
_axiv, 552 pages : _billustrations ; _c27 cm. |
||
504 | _aIncludes bibliographical references and index. | ||
505 | 0 | _a1. Introduction -- 2. Loss functions -- 3. The parametric forecasting problem -- 4. Classical estimation of forecasting models -- 5. Bayesian forecasting methods -- 6. Model selection -- 7. Univariate linear prediction models -- 8. Univariate nonlinear prediction models -- 9. Vector autoregressions -- 10. Forecasting in a data-rich environment -- 11. Nonparametric forecasting methods -- 12. Binary forecasts -- 13. Volatility and density forecasting -- 14. Forecast combinations -- 15. Desirable properties of forecasts -- 16. Evaluation of individual forecasts -- 17. Evaluation and comparison of multiple forecasts -- 18. Evaluating density forecasts -- 19. Forecasting under model instability -- 20. Trending variables and forecasting -- 21. Forecasting nonstandard data. | |
520 | _aThis text approaches forecasting problems from the perspective of decision theory and estimation, and demonstrates the profound implications of this approach for how we understand variable selection, estimation, and combination methods for forecasting models, and how we evaluate the resulting forecasts. Both Bayesian and non-Bayesian methods are covered in depth, as are a range of cutting-edge techniques for producing point, interval, and density forecasts. The book features detailed presentations and empirical examples of a range of forecasting methods and shows how to generate forecasts in the presence of large-dimensional sets of predictor variables. The authors pay special attention to how estimation error, model uncertainty, and model instability affect forecasting performance. | ||
650 | 0 | _aEconomic forecasting. | |
650 | 0 |
_aEconomic forecasting _xEconometric models. |
|
650 | 0 |
_aFinance _xEconometric models. |
|
700 | 1 |
_aTimmermann, Allan, _eauthor |
|
942 |
_2ddc _cBK |
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999 |
_c421426 _d421426 |