Stock Market s Reaction to Macroeconomic Variables Evidence from Indian Stock Market

dc.contributor.guideRakesh Kumar
dc.coverage.spatial
dc.creator.researcherAyushman
dc.date.accessioned2024-08-13T12:06:10Z
dc.date.available2024-08-13T12:06:10Z
dc.date.awarded2023
dc.date.completed2023
dc.date.registered2020
dc.description.abstractThe present study has established the relationship between different macroeconomic variables and the Indian stock market with special reference to BSE Sensex and NSE Nifty 50. The twelve macroeconomic variables have been taken into study. The research work is divided into three parts, first part of research empirically investigated the impact of macroeconomics variables on the performance of the Indian stock market, with special reference to BSE Sensex and NSE Nifty 50; in the second part prediction of BSE Sensex and NSE Nifty 50 has been done with the use of econometrics tool and soft computing; and lastly investigated how investors evaluated the effects of macroeconomic variables while investing in the stock market. newlineThe results of the study reveal that macroeconomic variables: BR, CO, CPI-AL, FDI, FXR, GDP, GP, IIP, and FII have a positive correlation with the BSE Sensex and NSE Nifty 50. The Granger Causality test indicates that CO, FXR and CPI-IW do granger cause BSE Sensex Index and it also indicates that CO and FXR do granger Cause NSE Nifty 50 Index. The OLS Regression technique has been used in order to predict the impact of selected macroeconomic variables on BSE Sensex and NSE Nifty 50 index and both the model of BSE Sensex and BSE Nifty 50 Index has passed all assumptions of OLS regression technique. newlineThe Multilayer Perceptron Neural Network, K-Nearest Neighbor model and Support Vector Regression model has been used as a soft computing technique to predict the BSE Sensex and NSE Nifty 50 and the model has been trained on the training dataset with different parameters. After comparing accuracy of different models which have been applied on testing dataset, it can be conclude that K-Nearest Neighbor Algorithm is the best fit model since it has the highest accuracy for both BSE Sensex and NSE Nifty 50 model. So, we can say that while considering macroeconomics factors this model can be used to predict the stock market indices of India. newlineThe examination of the perceptions of the stock market investors revealed that investors consider macroeconomic factors while taking investment decision for the stock market. Mostly investors get to know about the macroeconomic variables from newspapers/business magazines, Handbook and their from friends, family, and colleagues. newline newline
dc.description.note
dc.format.accompanyingmaterialNone
dc.format.dimensions
dc.format.extent
dc.identifier.urihttp://hdl.handle.net/10603/582614
dc.languageEnglish
dc.publisher.institutionDepartment of Accountancy and Law
dc.publisher.placeAgra
dc.publisher.universityDayalbagh Educational Institute
dc.relation
dc.rightsuniversity
dc.source.universityUniversity
dc.subject.keywordBusiness
dc.subject.keywordEconomics and Business
dc.subject.keywordSocial Sciences
dc.titleStock Market s Reaction to Macroeconomic Variables Evidence from Indian Stock Market
dc.title.alternative
dc.type.degreePh.D.

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