A Study on the Factors Affecting the Auto Indices of the Indian Stock Markets – An ARDL Cointegration Approach

The aim of this study is to analyze the relationship between selected macroeconomic variables and auto indices of the two major Indian stock markets (viz. Bombay Stock Exchange and National Stock Exchange) using monthly data during the time period, January 2017 to August 2019. Unit root test is perf...

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التفاصيل البيبلوغرافية
المؤلف الرئيسي: Alexander, Rhoda (author)
منشور في: 2020
الموضوعات:
الوصول للمادة أونلاين:https://bspace.buid.ac.ae/handle/1234/1611
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author Alexander, Rhoda
author_facet Alexander, Rhoda
author_role author
dc.creator.none.fl_str_mv Alexander, Rhoda
dc.date.none.fl_str_mv 2020-06-16T10:02:57Z
2020-06-16T10:02:57Z
2020-05
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv 20183003
https://bspace.buid.ac.ae/handle/1234/1611
dc.language.none.fl_str_mv en
dc.publisher.none.fl_str_mv The British University in Dubai (BUiD)
dc.subject.none.fl_str_mv auto indices
macroeconomic factors
Indian stock markets
National Stock Exchange (NSE)
Bombay Stock Exchange (BSE)
unit root tests
bounds test
Auto Regressive Distributed Lag(ARDL) Cointegration
dc.title.none.fl_str_mv A Study on the Factors Affecting the Auto Indices of the Indian Stock Markets – An ARDL Cointegration Approach
dc.type.none.fl_str_mv Dissertation
description The aim of this study is to analyze the relationship between selected macroeconomic variables and auto indices of the two major Indian stock markets (viz. Bombay Stock Exchange and National Stock Exchange) using monthly data during the time period, January 2017 to August 2019. Unit root test is performed to confirm the order of integration of the data. Bounds test reveals that there is a co-integrating relationship between the dependent and explanatory variables under both models of the study. Hence, autoregressive distributed lag (ARDL) model is employed to examine the co-integrating relationship between them. The results show that, exchange rate is a strong and statistically significant predictor of both S&P BSE auto index and Nifty auto index in the long run. The findings also reveal that, crude price, index of industrial production and repo rates are statistically significant determinants of Nifty auto index in the long run. In addition, first lag of crude price was seen to be a potential indicator of both the indices in the short-run. However, it was quite interesting to note the difference in the direction of relationship of crude price with the indices. The study provides some important policy implications.
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network_name_str The British University in Dubai repository
oai_identifier_str oai:bspace.buid.ac.ae:1234/1611
publishDate 2020
publisher.none.fl_str_mv The British University in Dubai (BUiD)
repository.mail.fl_str_mv
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spelling A Study on the Factors Affecting the Auto Indices of the Indian Stock Markets – An ARDL Cointegration ApproachAlexander, Rhodaauto indicesmacroeconomic factorsIndian stock marketsNational Stock Exchange (NSE)Bombay Stock Exchange (BSE)unit root testsbounds testAuto Regressive Distributed Lag(ARDL) CointegrationThe aim of this study is to analyze the relationship between selected macroeconomic variables and auto indices of the two major Indian stock markets (viz. Bombay Stock Exchange and National Stock Exchange) using monthly data during the time period, January 2017 to August 2019. Unit root test is performed to confirm the order of integration of the data. Bounds test reveals that there is a co-integrating relationship between the dependent and explanatory variables under both models of the study. Hence, autoregressive distributed lag (ARDL) model is employed to examine the co-integrating relationship between them. The results show that, exchange rate is a strong and statistically significant predictor of both S&P BSE auto index and Nifty auto index in the long run. The findings also reveal that, crude price, index of industrial production and repo rates are statistically significant determinants of Nifty auto index in the long run. In addition, first lag of crude price was seen to be a potential indicator of both the indices in the short-run. However, it was quite interesting to note the difference in the direction of relationship of crude price with the indices. The study provides some important policy implications.The British University in Dubai (BUiD)2020-06-16T10:02:57Z2020-06-16T10:02:57Z2020-05Dissertationapplication/pdf20183003https://bspace.buid.ac.ae/handle/1234/1611enoai:bspace.buid.ac.ae:1234/16112021-09-14T12:55:27Z
spellingShingle A Study on the Factors Affecting the Auto Indices of the Indian Stock Markets – An ARDL Cointegration Approach
Alexander, Rhoda
auto indices
macroeconomic factors
Indian stock markets
National Stock Exchange (NSE)
Bombay Stock Exchange (BSE)
unit root tests
bounds test
Auto Regressive Distributed Lag(ARDL) Cointegration
title A Study on the Factors Affecting the Auto Indices of the Indian Stock Markets – An ARDL Cointegration Approach
title_full A Study on the Factors Affecting the Auto Indices of the Indian Stock Markets – An ARDL Cointegration Approach
title_fullStr A Study on the Factors Affecting the Auto Indices of the Indian Stock Markets – An ARDL Cointegration Approach
title_full_unstemmed A Study on the Factors Affecting the Auto Indices of the Indian Stock Markets – An ARDL Cointegration Approach
title_short A Study on the Factors Affecting the Auto Indices of the Indian Stock Markets – An ARDL Cointegration Approach
title_sort A Study on the Factors Affecting the Auto Indices of the Indian Stock Markets – An ARDL Cointegration Approach
topic auto indices
macroeconomic factors
Indian stock markets
National Stock Exchange (NSE)
Bombay Stock Exchange (BSE)
unit root tests
bounds test
Auto Regressive Distributed Lag(ARDL) Cointegration
url https://bspace.buid.ac.ae/handle/1234/1611