S&P BSE Sensex and S&P BSE IT return forecasting using ARIMA

Authors: Madhavi Latha Challa, Venkataramanaiah Malepati, Siva Nageswara Rao Kolusu

Source: Financial Innovation, Vol 6, Iss 1, Pp 1-19 (2020)

Subject Terms: Efficient market hypothesis, Bombay stock exchange, ARIMA, KPSS, S&P BSE Sensex, Forecasting, Public finance, K4430-4675, Finance, HG1-9999

File Description: electronic resource

Relation: http://link.springer.com/article/10.1186/s40854-020-00201-5; https://doaj.org/toc/2199-4730

Access URL: https://doaj.org/article/dc86d45283e94728ab31a99d4b58dd8c

Forecasting risk using auto regressive integrated moving average approach: an evidence from S&P BSE Sensex

Authors: Madhavi Latha Challa, Venkataramanaiah Malepati, Siva Nageswara Rao Kolusu

Source: Financial Innovation, Vol 4, Iss 1, Pp 1-17 (2018)

Subject Terms: Akaike Information Criteria (AIC), Bombay Stock Exchange (BSE), Auto Regressive Integrated Moving Average (ARIMA), Beta, Time series, Public finance, K4430-4675, Finance, HG1-9999

File Description: electronic resource

Relation: http://link.springer.com/article/10.1186/s40854-018-0107-z; https://doaj.org/toc/2199-4730

Access URL: https://doaj.org/article/f9463ba1f6b24c9da41427f40ae5f73e

STOCK MARKET VOLATILITY MODELING AND FORECASTING WITH A SPECIAL REFERENCE TO BSE SENSEX.

Authors: Venkataramanaiah Malepati, Madhavi Latha Challa, Siva Nageswara Rao Kolusu

Source: Research in Finance; 2019, Vol. 35, p105-118, 14p

Subject Terms: STOCK exchanges, MARKET volatility, MARKETING models, TIME series analysis, TIME measurements

Company/Entity: BSE Ltd.