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.
引用
收藏
页数:19
相关论文
共 50 条
[41]   Predictability and Persistence of the Price Movements of the S&P/Case-Shiller House Price Indices [J].
Schindler, Felix .
JOURNAL OF REAL ESTATE FINANCE AND ECONOMICS, 2013, 46 (01) :44-90
[42]   Volatility Spillover, Hedging and Portfolio Diversification Between Oil Market and S&P Sectoral Indices [J].
Gencyurek, Ahmet Galip ;
Ekinci, Ramazan ;
Agan, Busra .
EGE ACADEMIC REVIEW, 2023, 23 (01) :127-144
[43]   An explorative analysis of sentiment impact on S&P 500 components returns, volatility and downside risk [J].
Figa-Talamanca, Gianna ;
Patacca, Marco .
ANNALS OF OPERATIONS RESEARCH, 2024, 342 (03) :2095-2117
[44]   QARMA-Beta-t-EGARCH versus ARMA-GARCH: an application to S&P 500 [J].
Blazsek, Szabolcs ;
Mendoza, Vicente .
APPLIED ECONOMICS, 2016, 48 (12) :1119-1129
[45]   Sectoral Efficiency and Resilience: A Multifaceted Analysis of S&P Global BMI Indices Under Global Crises [J].
Kojic, Milena ;
Rakic, Slobodan ;
da Silva, Jose Wesley Lima ;
de Araujo, Fernando Henrique Antunes .
MATHEMATICS, 2025, 13 (04)
[46]   Looking into the relationship between implied and realized volatility: a study on S&P CNX Nifty index option [J].
Mishra A.K. ;
Panda S.P. .
Eurasian Economic Review, 2016, 6 (1) :67-96
[47]   Analysis of the predictive ability of time delay neural networks applied to the S&P 500 time series [J].
Sitte, R ;
Sitte, J .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS, 2000, 30 (04) :568-572
[48]   Asymmetry in the jump-size distribution of the S&P 500: Evidence from equity and option markets [J].
Kaeck, Andreas .
JOURNAL OF ECONOMIC DYNAMICS & CONTROL, 2013, 37 (09) :1872-1888
[49]   Model Complexity and Out-of-Sample Performance: Evidence from S&P 500 Index Returns [J].
Kaeck, Andreas ;
Rodrigues, Paulo ;
Seeger, Norman J. .
JOURNAL OF ECONOMIC DYNAMICS & CONTROL, 2018, 90 :1-29
[50]   Female CEO leadership and the likelihood of corporate diversity misconduct: Evidence from S&P 500 firms [J].
Dadanlar, Hazel H. ;
Abebe, Michael A. .
JOURNAL OF BUSINESS RESEARCH, 2020, 118 :398-405