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Comprehensive and Comparative Analysis of HDI, WPI, CPI and CCI on Stock Market Returns

Authors

Arpita Subray Bhat

RV Institute of Management,Bengaluru, Bengaluru, Karnataka, India (IN)

Dr. Sumera Aluru

RV Institute of Management,Bengaluru, Bengaluru, Karnataka, India (IN)

Article Information

DOI: 10.51583/IJLTEMAS.2026.150500167

Subject Category: Finance

Volume/Issue: 15/5 | Page No: 2089-2101

Publication Timeline

Submitted: 2026-06-11

Published: 2026-06-11

Abstract

The stock market returns reflects the performance of the economy and the expectations from the market. In developing markets like India, stock market performance is not only dependent on the performance of the firms but also on the economic and social indicators. This paper aims to analyse the compounded and relative effects of the Human Development Index (HDI), Consumer Price Index (CPI), Wholesale Price Index (WPI), and Consumer Confidence Index (CCI) on stock market returns in India between the years 2015 and 2025. The analysis is based on 128 monthly observations of each Bombay Stock Exchange (BSE) and the National Stock Exchange (NSE) with the help of descriptive statistics, Correlation, Augmented Dickey-Fuller (ADF) unit root tests, multiple regression (OLS), and Autoregressive Distributed Lag (ARDL) models.


 


The correlation between BSE and NSE is nearly 1 (r = 0.999), confirming that the indices move in near-perfect tandem. There is an exceedingly high correlation (r = 0.9999) between CPI and HDI, confirming near-perfect multi-collinearity. Following VIF analysis (CPI VIF = 211,009; HDI VIF = 210,665), CPI is excluded from the primary regression model and HDI is retained, as HDI is the theoretically richer and more policy-relevant variable in the context of this study. The revised model (BSE/NSE ~ CCI + WPI + HDI) resolves the extreme multi-collinearity while maintaining R² = 0.9769 (BSE) and R² = 0.9705 (NSE). All three retained predictors are significant at p < 0.001. CCI is negatively correlated with BSE (–0.652) and NSE (–0.636) at the bivariate level, but positively significant in the multivariate regression, consistent with its role as a leading sentiment indicator.


Monthly HDI data was sourced from the UNDP Human Development Data Centre (hdr.undp.org). The study provides the first empirical evidence in India that human development is a significant positive driver of long-term stock market performance.


Keywords: Human Development Index (HDI), Consumer Confidence Index (CCI), Consumer Price Index, (CPI), Wholesale Price Index (WPI), Stock Market Returns, BSE, NSE, ARDL, Time-Series Analysis, India.

Keywords

Comprehensive, Comparative, Stock Market

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References

1. Baker, M., & Wurgler, J. (2006). Investor sentiment and the cross-section of stock returns. The Journal of Finance, 61(4), 1645-1680. [Google Scholar] [Crossref]

2. BSE India. (2025). Historical index data: BSE Sensex. Bombay Stock Exchange. https://www.bseindia.com [Google Scholar] [Crossref]

3. Chen, N. F., Roll, R., & Ross, S. A. (1986). Economic forces and the stock market. Journal of Business, 59(3), 383-403. [Google Scholar] [Crossref]

4. Fama, E. F. (1981). Stock returns, real activity, inflation, and money. The American Economic Review, 71(4), 545-565. [Google Scholar] [Crossref]

5. Jansen, W. J., & Nahuis, N. J. (2003). The stock market and consumer confidence: European evidence. Economics Letters, 79(1), 89-98. [Google Scholar] [Crossref]

6. Kaur, M. (2009). Causal relationship between macroeconomic variables and stock market returns in India. Finance India, 23(4). [Google Scholar] [Crossref]

7. Ludvigson, S. C. (2004). Consumer confidence and consumer spending. Journal of Economic Perspectives, 18(2), 29-50. [Google Scholar] [Crossref]

8. Modigliani, F., & Cohn, R. A. (1979). Inflation, rational valuation, and the market. Financial Analysts Journal, 35(2), 24-44. Acemoglu, D., & Johnson, S. (2007). Disease and development: The effect of life expectancy on economic growth. Journal of Political Economy, 115(6), 925-985. [Google Scholar] [Crossref]

9. Naik, P. K., & Padhi, P. (2012). The impact of macroeconomic fundamentals on stock prices revisited: Evidence from Indian data. Eurasian Journal of Business and Economics, 5(10), 25-44. [Google Scholar] [Crossref]

10. NSE India. (2025). Historical index data: Nifty 50. National Stock Exchange of India. https://www.nseindia.com [Google Scholar] [Crossref]

11. Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289-326. [Google Scholar] [Crossref]

12. Reserve Bank of India. (2025). Consumer confidence survey: Quarterly reports 2015-2025. RBI Publications. [Google Scholar] [Crossref]

13. Sahu, T. N., & Dhiman, D. K. (2011). Correlation and causality between stock market and macro economic variables in India: An empirical study. International Proceedings of Economics Development and Research, 3(1), 281-290. [Google Scholar] [Crossref]

14. Sharma, G. D., & Mahendru, M. (2010). Impact of macro-economic variables on stock prices in India. Global Journal of Management and Business Research, 10(7), 19-26. [Google Scholar] [Crossref]

15. Singh, T. (2010). Macroeconomic factors and stock market performance in India. Indian Journal of Finance. [Google Scholar] [Crossref]

16. Tripathy, N. (2011). Causal relationship between macro-economic indicators and stock market in India. Asian Journal of Finance & Accounting, 3(1), 208-226. [Google Scholar] [Crossref]

17. UNDP. (2024). Human Development Report 2023/24: Breaking the gridlock. United Nations Development Progra [Google Scholar] [Crossref]

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