February 2000. The dot-com bust. Nifty fell from 1,750 to 800 in eight months. Arjun visualized the V-shaped recovery that followed. He saw May 2004, when the "NDA shock" crashed the market 17% in a week—only to double in the next three years. He traced the long, painful plateau of 2011-2013, when everyone said India was doomed. The data showed a quiet accumulation phase, like a coiled spring.
The 2008 line looked like a cliff. He zoomed in. October 24, 2008: Nifty crashed 11% in a single day. Arjun remembered that day. He was in college, watching news channels show Lehman Brothers employees walking out with cardboard boxes. His father had almost sold everything in panic. The data whispered: Those who sold at the bottom missed the next 500% rise.
At first, it was just numbers. Then he started graphing it. nse nifty historical data
He kept digging.
One night, he found an anomaly. On May 18, 2009, after the election results, Nifty jumped 17% in one day—the largest single-day gain ever. But the day before, volumes were normal. No one knew. The market’s greatest moves happened when everyone was certain of the opposite. February 2000
Then he saw it: a pattern no news anchor discussed. Every major crash—2000, 2008, 2020—was followed by a recovery that broke the previous all-time high within 18 to 36 months. The drawdowns were terrifying. But the long-term slope was relentless: roughly 14% compounded annually.
Arjun had always dismissed the stock market as sophisticated gambling. But when the pandemic lockdowns emptied the streets of Mumbai in 2020, boredom drove him to open a demat account. He wasn’t a trader; he was a historian by training, now working a lifeless IT job. One night, staring at a chaotic Excel sheet of Nifty 50 closing prices, he had an idea: What if I treat the market like a living archive? Arjun visualized the V-shaped recovery that followed
He downloaded the full historical dataset—every single trading day from its 1995 base value of 1,000 points to the present. 25 years of data. 6,000-odd rows of open, high, low, close.