Beginner
Case Study: Analyzing the 2020 Covid Crash Through a Volatility Lens
A beginner-friendly quant case study that re-reads the March 2020 Covid crash using volatility as the measuring instrument instead of price. You will learn what realized and implied volatility actually measure, how NSE computes India VIX, and then apply those tools to the actual 2020 timeline: the calm January, the 38% collapse in Nifty, VIX at 86, two circuit-breaker halts, and the V-shaped recovery. The final chapter shows how to reproduce every chart in Python and turn the lessons into a simple volatility-aware position-sizing rule.
Realized VolatilityImplied VolatilityIndia VIXMarket CrashesVolatility RegimesPython for Markets
MODULES
5
DURATION
~3.5 hrs
TRACK
Quantitative Finance
What You'll Master
What volatility measures, how it is calculated from daily returns, and why it is the quant's preferred lens for a crash
How NSE builds India VIX from the Nifty options chain and what a reading of 12 versus 86 actually implies
The day-by-day volatility story of January to June 2020 on NSE, including the 13 March and 23 March circuit-breaker halts
Why volatility clusters, why returns have fat tails, and why correlations across stocks and assets rushed to one in March 2020
How volatility mean-reverts after a spike and what the vol regime signalled during the V-shaped recovery
How to download Nifty and India VIX data, reproduce the analysis in Python, and build a simple volatility-scaled position-sizing rule
Access Level
LEARNER
Everything included
Full Text Playbooks
Actionable Exercises
Mobile Reading Mode
Lifetime Updates