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S&P BSE Sensex and S&P BSE IT return forecasting using ARIMA
被引:21
作者:
Challa, Madhavi Latha
[1
]
Malepati, Venkataramanaiah
[2
]
Kolusu, Siva Nageswara Rao
[3
]
机构:
[1] CMR Coll Engn & Technol, Dept CSE, Hyderabad, India
[2] SG Govt Degree & PG Coll, Dept Commerce, Piler, Andhra Pradesh, India
[3] Vignan Fdn Sci Technol & Res, Dept Management Studies, Guntur, Andhra Pradesh, India
关键词:
Efficient market hypothesis;
Bombay stock exchange;
ARIMA;
KPSS;
S&
P BSE Sensex;
Forecasting;
P BSE IT;
CHINESE STOCK MARKETS;
VARIANCE-RATIO TESTS;
TIME-SERIES;
LONG MEMORY;
COMBINATION;
HYPOTHESIS;
EFFICIENT;
PREMIUM;
MODELS;
PREDICTABILITY;
D O I:
10.1186/s40854-020-00201-5
中图分类号:
F8 [财政、金融];
学科分类号:
0202 ;
摘要:
This study forecasts the return and volatility dynamics of S&P BSE Sensex and S&P BSE IT indices of the Bombay Stock Exchange. To achieve the objectives, the study uses descriptive statistics; tests including variance ratio, Augmented Dickey-Fuller, Phillips-Perron, and Kwiatkowski Phillips Schmidt and Shin; and Autoregressive Integrated Moving Average (ARIMA). The analysis forecasts daily stock returns for the S&P BSE Sensex and S&P BSE IT time series, using the ARIMA model. The results reveal that the mean returns of both indices are positive but near zero. This is indicative of a regressive tendency in the long-term. The forecasted values of S&P BSE Sensex and S&P BSE IT are almost equal to their actual values, with few deviations. Hence, the ARIMA model is capable of predicting medium- or long-term horizons using historical values of S&P BSE Sensex and S&P BSE IT.
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页数:19
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