A comparative study of static and iterative models of ARIMA and SVR to predict stock indices prices in developed and emerging economies
Mohit Beniwal and Archana Singh, Nand Kumar
| Year of publication: |
2023
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|---|---|
| Authors: | Beniwal, Mohit ; Archana Singh ; Kumar, Nand |
| Published in: |
International journal of applied management science : IJAMS. - Genève [u.a.] : Inderscience Enterprises, ISSN 1755-8921, ZDB-ID 2471980-8. - Vol. 15.2023, 4, p. 352-371
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| Subject: | ARIMA | auto-regressive integrated moving average | efficient market hypothesis | emerging economies | EMH | predicting stock prices | random walk hypothesis | RWH | support vector regression | SVR | time series analysis | Schwellenländer | Emerging economies | Zeitreihenanalyse | Time series analysis | Börsenkurs | Share price | Prognoseverfahren | Forecasting model | Effizienzmarkthypothese | Efficient market hypothesis | ARMA-Modell | ARMA model | Aktienindex | Stock index | Random Walk | Random walk | Theorie | Theory |
Online Resource
| Type of publication: | Article |
|---|---|
| Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
| Language: | English |
| Other identifiers: | 10.1504/IJAMS.2023.134452 [DOI] |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10014391724