Financial Forecasting Model in Developed and Developing Economies
Tripti Tripathi1, Umesh Holani2
1Dr. Tripti Tripathi, Post Doctorate Fellow UGC, School of Commerce and Management, Jiwaji University, Gwalior (M.P), India.
2Prof. Umesh Holani, Ex-Dean and Chairman, School of Studies Commerce and Management, Jiwaji University, Gwalior (M.P), India.
Manuscript received on 25 November 2019 | Revised Manuscript received on 06 December 2019 | Manuscript Published on 16 December 2019 | PP: 291-296 | Volume-8 Issue-3S3 November 2019 | Retrieval Number: C10671183S319/2019©BEIESP | DOI: 10.35940/ijrte.C1067.1183S319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The study focused on the volatility forecasting in developed and developing share market. The objective of the study was to evaluate the ability of six different statistical and econometric volatility forecasting models in the context of India, Brazil, Japan and US stock market from November 1994 till February 2005 on the basis of four evaluation error measures statistics which are mean absolute error (MAE), root mean square error (RMSE), Theil’s U (TU) and MAPE. The monthly data of stock market index of India, Brazil, Japan and US were collected from January 1992 till April 2005 and also monthly data of stock market index, discount rate, consumer price index (CPI), industrial production and foreign exchange reserves of India, Brazil, Japan and US respectively were collected. Then further analysis was done using four forecasting models which were moving average, exponential weighted moving average, multiple regression, GARCH. The study found out that GARCH and MAE forecasting models are superior in developed market as well as developing market like India.
Keywords: Stock Market, Developed And Developing Economies, Mean Absolute Error, Root Mean Square Error, Theil’s U, MAPE, Moving Average, Exponential Weighted Moving Average, Multiple Regression, GARCH.
Scope of the Article: Social Sciences