Please use this identifier to cite or link to this item: https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/1375
Full metadata record
DC FieldValueLanguage
dc.contributor.authorDash, Mihir-
dc.date.accessioned2023-09-27T07:26:13Z-
dc.date.available2023-09-27T07:26:13Z-
dc.date.issued2020-04-27-
dc.identifier.urihttps://dx.doi.org/10.2139/ssrn.3567369-
dc.identifier.urihttp://gnanaganga.inflibnet.ac.in:8080/jspui/handle/123456789/1375-
dc.description.abstractThis study combines three distinct empirical models of stock returns into a single model: the autoregressive model, which suggests that stock returns are determined by its own past values, the (generalised) autoregressive conditional heteroscedasticity model, which suggests that stock returns volatility is determined by its past values and by returns shocks, and the day-of-the-week effect, which suggests that stock returns are higher on particular days of the week (usually Fridays). All three models represent departures from the Random Walk Hypothesis (RWH), in the sense of proposing a certain degree of predictability in stock returns. The study examines the extent to which the AR-GARCH model with day-of-the-week dummy variables for twenty major stocks from the Indian banking sector. The stock price data was collected from the National Stock Exchange (NSE). The study period selected was Apr. 1, 2018 to Mar. 31, 2019, a period of one year.en_US
dc.language.isoenen_US
dc.publisherSSRNen_US
dc.subjectRandom Walk Hypothesisen_US
dc.subjectAR-GARCH modelen_US
dc.subjectDay-of-the-week effecten_US
dc.subjectNSEen_US
dc.titleTesting the Day-of-the-Week Effect in the Indian Stock Market using the AR-GARCH Modelen_US
dc.typeArticleen_US
Appears in Collections:Journal Articles

Files in This Item:
File Description SizeFormat 
SSRN-id3567369.pdf
  Restricted Access
566.25 kBAdobe PDFView/Open Request a copy


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.