Selection of the right proxy market portfolio for CAPM

  • Received May 14, 2021;
    Accepted July 6, 2021;
    Published July 27, 2021
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/imfi.18(3).2021.02
  • Article Info
    Volume 18 2021, Issue #3, pp. 16-26
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This work is licensed under a Creative Commons Attribution 4.0 International License

The purpose of the paper is to select the right market proxy for calculating the expected return, since critically evaluating proxies or selecting the correct proxy market portfolio is essential for portfolio management because the change in the market portfolio proxy affects returns. In this study, monthly data of equity indices are evaluated to find out the better market proxy. The indices taken are BSE 30 (Sensex), Nifty 50, BSE 100, BSE 200, and BSE 500. The macroeconomic variables used in the study are industrial production index (IIP), consumer price index (CPI), money supply (M1), and exchange rate in India. To avoid the influence of COVID-19, the research period was from January 2013 to December 2019 to critically evaluate these proxies in order to find the most appropriate market proxy. This paper reveals a noteworthy relationship between stock market returns and macroeconomic factors, while suggesting that the BSE 500 is a better choice for all equity indices, as the index also shows a significant relationship with all macroeconomic variables. BSE500 is a composite index comprising all sectors with low, mid and large cap securities, therefore it reflects the impact of macroeconomic factors most efficiently, taking it as a market proxy. This study was carried out in the context of India and can be replicated for other countries.

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    • Table 1. Description of variables
    • Table 2. Descriptive statistics of Indian stock indices and macroeconomic variables (natural log form): 2013–2019
    • Table 3. ADF unit root test for variables for 2013–2019
    • Table 4. Cointegration test for stock indices and macroeconomic variables for 2013–2019
    • Table 5. Long-term equations
    • Table 6. Error correction model
    • Conceptualization
      Rashmi Chaudhary, Priti Bakhshi
    • Data curation
      Rashmi Chaudhary
    • Formal Analysis
      Rashmi Chaudhary, Priti Bakhshi
    • Investigation
      Rashmi Chaudhary, Priti Bakhshi
    • Methodology
      Rashmi Chaudhary, Priti Bakhshi
    • Project administration
      Rashmi Chaudhary, Priti Bakhshi
    • Resources
      Rashmi Chaudhary, Priti Bakhshi
    • Software
      Rashmi Chaudhary
    • Supervision
      Rashmi Chaudhary, Priti Bakhshi
    • Validation
      Rashmi Chaudhary, Priti Bakhshi
    • Visualization
      Rashmi Chaudhary, Priti Bakhshi
    • Writing – original draft
      Rashmi Chaudhary, Priti Bakhshi
    • Writing – review & editing
      Rashmi Chaudhary, Priti Bakhshi