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Prognozowanie indeksu WIG za pomocą jądrowych estymatorów funkcji regresji

Author

Listed:
  • Witold Orzeszko

    (Uniwersytet Mikołaja Kopernika, Katedra Zastosowań Informatyki i Matematyki w Ekonomi)

Abstract

Celem pracy jest ocena wybranych jądrowych estymatorów funkcji regresji jako narzędzi prognozowania indeksu WIG. Prognozie poddano dwa szeregi czasowe: logarytmiczne stopy zmian indeksu oraz ich kwadraty. W badaniu zastosowano cztery metody prognozowania: estymator Nadarai-Watsona, lokalną jądrową regresję liniową oraz – dla porównania – model regresji liniowej i metodę naiwną. Jako zmienne objaśniające w modelach regresji zastosowano opóźnione o jeden dzień: indeks S&P 500, kurs USD/PLN, wolumen obrotów spółek wchodzących w skład indeksu WIG, a także zmienną autoregresyjną. Do oceny możliwości predykcyjnych analizowanych metod wykorzystano cztery różne kryteria jakości prognoz. Otrzymane wyniki nie pozwalają na sformułowanie jednoznacznego wniosku o wyższości estymatorów jądrowych nad pozostałymi zastosowanymi metodami prognozowania. Wykazano jednak, że w pewnych sytuacjach metody te mogą być użytecznymi narzędziami prognozowania. Zależy to np. od prognozowanego okresu, zastosowanego predyktora czy przyjętego kryterium jakości prognozy.

Suggested Citation

  • Witold Orzeszko, 2018. "Prognozowanie indeksu WIG za pomocą jądrowych estymatorów funkcji regresji," Bank i Kredyt, Narodowy Bank Polski, vol. 49(3), pages 253-288.
    • Handle: RePEc:nbp:nbpbik:v:49:y:2018:i:3:p:253-288
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    References listed on IDEAS

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    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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