Article’s

Abstract – This study provides a comprehensive, long-horizon empirical evaluation of the 50-day/200-day simple moving-average (SMA) crossover — popularly known as the “Golden Cross” and “Death Cross” — on the Nifty 50, India’s benchmark equity index, using 3,077 daily observations from January 2010 to June 2022. Beyond documenting the timing of eleven Golden Cross and eleven Death Cross events, this paper constructs and backtests a full systematic trading strategy built on the crossover rule, benchmarks it against a passive buy-and-hold approach, decomposes performance by market regime and sub-period, tests sensitivity to four alternative moving-average pairings, quantifies transaction-cost drag, and examines volatility dynamics surrounding signal events. The mechanical crossover strategy is found to underperform buy-and-hold substantially on a raw-return basis (4.01% vs. 9.90% CAGR) while achieving materially lower realised volatility (12.54% vs. 22.52% annualised) — a trade-off that nets out to a lower risk-adjusted (Sharpe) ratio for the trend-following approach in this sample. We place these findings in the context of efficient-markets and technical analysis literature, explain the rationale for why the signal always has a time lag and thus cannot be considered a true leading indicator, and describe the implications of the findings both in practice and in the context of academic research using a developed-market signal and data applied to an emerging market that experiences greater price volatility. Key Words: technical analysis, moving average crossover, Golden Cross, Death Cross, Nifty 50, trend following, emerging markets, market efficiency, backtesting.