By the end of this case study, students should be able to:
▪ Understand how the introduction of Nifty Futures has affected spot market efficiency and volatility in India.
▪ Evaluate the strategic rationale and implications of cross-listing Nifty Futures on the Singapore Exchange (SGX).
▪ Apply econometric techniques, such as impulse response functions and lead-lag analysis, to analyze relationships between SGX and NSE Nifty Futures.
▪ Interpret volatility and causality results to make data-driven recommendations for trading and market positioning.
▪ Assess the role of futures markets in price discovery and their impact on overall market quality.
This case explores the strategic and operational challenges faced by Ravi Mehta, a financial analyst at a hedge fund, following the disassociation of the National Stock Exchange (NSE) from Singapore Exchange (SGX) in 2018. The disassociation altered the trading landscape for Nifty Futures, leading Ravi to reassess his reliance on SGX for market insights. The case examines the implications of this move on market dynamics, particularly on price discovery and liquidity, using econometric tools such as vector autoregressive (VAR) models, Granger causality and GARCH analysis. Students are encouraged to engage in data-driven analysis and consider strategic trade-offs in financial decision-making.
This case is suitable for graduate, Postgraduate and executive education program participants, particularly in courses on financial markets, derivatives trading, financial econometrics and data-driven decision-making in finance – such as financial analytics.
Teaching notes are available for educators only.
CSS 1: Accounting and Finance.
