Analyzing Indian Stock Markets through Correlations: Comparative Insights

DOI

10.2991/978-94-6239-685-2_13How to use a DOI?

Keywords

Indian equity systems; inter-market relationships; diversification insights; risk assessment; network modeling

Abstract

Traditional methods for analyzing emerging markets like India often fall short in capturing the full picture of systemic risk because they rely on single-metric, linear correlation models. To address this gap, this study introduces a multi-metric comparative framework built on concepts from Financial Engineering and Data Science to examine how ten major sectors of the Indian stock market move together over time. The approach integrates four different correlation measures—Pearson, Spearman, Kendall’s Tau, and time-lagged cross-correlation—to capture not just linear connections but also monotonic and time-dependent relationships. These correlations are then combined with Minimum Spanning Trees (MSTs) and clustering algorithms to map out the network of sector relationships and track how it evolves with market conditions. The results show a significant average divergence (AvgDiff ≈ 0.40) among the different correlation methods, highlighting that relying on a single measure can give an incomplete view of market dynamics. The analysis effectively grouped the market into distinct clusters: the Automobile sector emerged as a tightly connected network (Pearson ρ ≈ 0.96), whereas the pharmaceutical sector appeared more dispersed, indicating greater potential for diversification. Furthermore, the time-lagged analysis revealed lead-lag effects, such as a 75-day delay between specific stock movements. Overall, this study provides a comprehensive and data-driven framework for assessing systemic risk and optimizing portfolios in volatile emerging markets like India, offering deeper insights into how different sectors interact and influence each other over time.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

TY  - CONF
AU  - Ashish Shrivastav
AU  - Stuti Patel
AU  - Vihaan Kapopara
AU  - Archita Chandwani
AU  - Mann Ahalpara
AU  - Ashlesha Bhise
PY  - 2026
DA  - 2026/05/26
TI  - Analyzing Indian Stock Markets through Correlations: Comparative Insights
BT  - Proceedings of the International Conference on Infrastructure Development and Sustainability (ICIDS 2025)
PB  - Atlantis Press
SP  - 206
EP  - 239
SN  - 3005-155X
UR  - https://doi.org/10.2991/978-94-6239-685-2_13
DO  - 10.2991/978-94-6239-685-2_13
ID  - Shrivastav2026
ER  -