IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2207.06963.html
   My bibliography  Save this paper

Effect of Demonetisation of on Indian High Denomination Currencies on Indian Stock Market and its Relationship with Foreign Exchange Rate

Author

Listed:
  • N. Suresh
  • N. R. Bharathi

Abstract

This study examines the impact of the foreign exchange rate, i.e., US Dollar to Indian Rupee (USD/INR) on the Indian Stock Market Index (Nifty 50) during the demonetization of high denomination Indian currencies. A daily rate of return of Foreign exchange rate (USD/INR) and the Indian Stock Market Index (Nifty 50) were considered for the study. The Dummy variable was used to measure the effect of demonetization during Nov/Dec 2016. The period of study was restricted to 243 days from 1st April 2016 to 31st March 2017. The study reveals that there was an upward trend observed in the Indian Stock Market and the Indian currency was strengthened with the decrease in the Foreign exchange rate (USD/INR).

Suggested Citation

  • N. Suresh & N. R. Bharathi, 2022. "Effect of Demonetisation of on Indian High Denomination Currencies on Indian Stock Market and its Relationship with Foreign Exchange Rate," Papers 2207.06963, arXiv.org.
  • Handle: RePEc:arx:papers:2207.06963
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2207.06963
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bucevska Vesna, 2013. "An Empirical Evaluation of GARCH Models in Value-at-Risk Estimation: Evidence from the Macedonian Stock Exchange," Business Systems Research, Sciendo, vol. 4(1), pages 49-64, March.
    2. Marwa A. Elsherif, 2016. "Exchange Rate Volatility and Central Bank Actions in Egypt: Generalized Autoregressive Conditional Heteroscedasticity Analysis," International Journal of Economics and Financial Issues, Econjournals, vol. 6(3), pages 1209-1216.
    3. Sasikanta Tripathy & Abdul Rahman, 2013. "Forecasting Daily Stock Volatility Using GARCH Model: A Comparison Between BSE and SSE," The IUP Journal of Applied Finance, IUP Publications, vol. 19(4), pages 71-83, October.
    4. Uma Murthy & Paul Anthony & Rubana Vighnesvaran, 2016. "Factors Affecting Kuala Lumpur Composite Index (KLCI) Stock Market Return in Malaysia," International Journal of Business and Management, Canadian Center of Science and Education, vol. 12(1), pages 122-122, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tamal Datta Chaudhuri & Indranil Ghosh, 2016. "Artificial Neural Network and Time Series Modeling Based Approach to Forecasting the Exchange Rate in a Multivariate Framework," Papers 1607.02093, arXiv.org.
    2. Šimpach Ondřej & Langhamrová Jitka, 2013. "Forecasting Future Salaries in the Czech Republic Using Stochastic Modelling," Business Systems Research, Sciendo, vol. 4(2), pages 4-16, December.
    3. Kolte, Ashutosh & Roy, Jewel Kumar & Vasa, László, 2023. "The impact of unpredictable resource prices and equity volatility in advanced and emerging economies: An econometric and machine learning approach," Resources Policy, Elsevier, vol. 80(C).
    4. Biswajit Patra & Puja Padhi, 2015. "Backtesting of Value at Risk Methodology: Analysis of Banking Shares in India," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 9(3), pages 254-277, August.
    5. Sikhosana, Ayanda & Aye, Goodness C., 2018. "Asymmetric volatility transmission between the real exchange rate and stock returns in South Africa," Economic Analysis and Policy, Elsevier, vol. 60(C), pages 1-8.
    6. Joseph Osaro Denwi & Nenubari John Ikue & Joseph Jite Onodjaefe & Mtomabari Simeon, 2022. "Trade Liberalization Policy and Economic Growth in Africa: A Threshold Analysis," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 11(7), pages 178-188, October.
    7. Yee-Fan Tan & Lee-Yeng Ong & Meng-Chew Leow & Yee-Xian Goh, 2021. "Exploring Time-Series Forecasting Models for Dynamic Pricing in Digital Signage Advertising," Future Internet, MDPI, vol. 13(10), pages 1-24, September.
    8. Jordan Ngu Chuan Yong & Sayyed Mahdi Ziaei & Kenneth R. Szulczyk, 2021. "The Impact of Covid-19 Pandemic on Stock Market Return Volatility: Evidence from Malaysia and Singapore," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 11(3), pages 191-204, March.
    9. Riko Hendrawan, 2023. "Comparison of Black-Scholes and Garch Option Models on The Kompas100 Index With a Long Straddle Strategy During 2008-2021 ," GATR Journals jfbr208, Global Academy of Training and Research (GATR) Enterprise.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2207.06963. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.