Decoding the Nifty50 Puzzle with ANN: FIIs, DIIs and Market Magic

In the context of a dynamic and highly competitive financial market, understanding the behaviour of various categories of investors becomes a key factor in developing effective investment strategies and forecasting market trends. This study examines the phenomenon of Nifty50 — a group of the 50 most liquid and significant stocks in the Indian stock market, which play an important role in forming the overall index. The purpose of the study is to determine the influence of foreign institutional investors (FIIs) and domestic institutional investors (DIIs) on the dynamics of Nifty50.The authors apply classical research methods: correlation analysis, a statistical model for analysing and forecasting the volatility of time series (GARCH), and artificial neural networks (ANN).The study is based on daily data on investments from the two specified groups of investors and the values of the Nifty50 index of the National Stock Exchange. The study period from 31.12.2019 to 30.11.2023 is divided into two sub-periods: before COVID‑19 and after. In periods of economic shocks, such as the COVID‑19 pandemic, the behaviour of these two types of investors becomes particularly contrasting. The results of the study showed that FIIs and DIIs are opposite to each other: when FIIs invest, DIIs are net sellers, and when FIIs sell, DIIs are net investors. In the context of the pandemic, FIIs often increased their investments in Indian assets, while DIIs, on the contrary, reduced their positions. However, in the post-pandemic period, the situation changed: DIIs began to play a more significant role in the dynamics of Nifty50, while the influence of FIIs decreased. Thus, the analysis of the interaction between FIIs and DIIs allows us to conclude the complex and multifaceted nature of the influence of institutional investors on the Indian stock market. Their strategies and behaviour have a significant impact on market indices and volatility, which requires careful monitoring and analysis for effective management of investment risks and making informed decisions in unstable conditions.