TAILIEUCHUNG - Real Estate Modelling and Forecasting Hardcover_10

Tham khảo tài liệu 'real estate modelling and forecasting hardcover_10', tài chính - ngân hàng, đầu tư chứng khoán phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | Time series models 267 The acf can now be obtained by dividing the covariances by the variance so that _ Y0 _ 1 To 1 Yo _ Y1 T1 Yo __Y T Yo 00 1 1 - 0 a 1 - 0 0 1 - 0Ỉ ị a ỵ 1 - 0 0 01 T3 03 The autocorrelation at lag s is given by Ts 01 which means that corr y yt-s 01. Note that use of the Yule-Walker equations would have given the same answer. 9__ Forecast evaluation Learning outcomes In this chapter you will learn how to compute forecast evaluation tests distinguish between and evaluate in-sample and out-of-sample forecasts undertake comparisons of forecasts from alternative models assess the gains from combining forecasts run rolling forecast exercises and calculate sign and direction predictions. In previous chapters we focused on diagnostic tests that the real estate analyst can compute to choose between alternative models. Once a model or competing models have been selected we really want to know how accurately these models forecast. Forecast adequacy tests complement the diagnostic checking that we performed in earlier chapters and can be used as additional criteria to choose between two or more models that have satisfactory diagnostics. In addition of course assessing a model s forecast performance is also of interest in itself. Determining the forecasting accuracy of a model is an important test of its adequacy. Some econometricians would go as far as to suggest that the statistical adequacy of a model in terms of whether it violates the CLRM assumptions or whether it contains insignificant parameters is largely irrelevant if the model produces accurate forecasts. This chapter presents commonly used forecast evaluation tests. The literature on forecast accuracy is large and expanding. In this chapter we draw upon conventional forecast adequacy tests the application of which generates useful information concerning the forecasting ability of different models. 268 Forecast evaluation 269 At the outset we .

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