Research · Ananya Panayappan

A quantitative framework for portfolio resilience

Indian markets during COVID-19 and demonetization

How should a portfolio be evaluated when a major shock changes the relationships between its assets? This project developed a Resilience Index combining volatility, Value at Risk, and correlation metrics.

The framework was applied to the 2016 demonetization and 2020 COVID-19 disruptions in Indian markets, with comparisons against portfolios optimized using the Sharpe ratio.

Research outcomeAccepted for publication in IJHSRTop 5% evaluation · Pioneer Academics

Methods and outcome

The analysis brings together three views of risk: the size of fluctuations, exposure to losses, and the extent to which assets move together. It uses historical disruption periods to examine whether those measures offer a useful account of portfolio stability.

The paper has been accepted for publication in the International Journal of High School Research. The Pioneer program evaluated it in its top 5%, at undergraduate honors-thesis level. Supporting portfolio and market-analysis notebooks are available in the repository.

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Indian market volatility & risk transmission

Investigating the drivers of India VIX and the transmission of risk into Indian financial markets. The project combines market variables recorded each day with macroeconomic indicators published monthly or quarterly.

Research approach

A central challenge is aligning information recorded at different frequencies. The framework accounts for publication lags, so a model is not given information that would have been unavailable at the time it is predicting.

The work examines both short-term volatility dynamics and longer-term macro-financial influences, including spillovers from global markets. This is independent research under faculty mentorship.

Beyond Geometric Brownian Motion

Modeling fat tails and volatility in financial markets

My Extended Essay investigates where the assumptions of Geometric Brownian Motion break down, particularly around extreme returns and volatility clustering.

Models under comparison

The Merton Jump Diffusion model introduces discrete price shocks. The Heston model allows volatility itself to vary stochastically. Comparing these frameworks with GBM provides a way to examine which market behaviors each model can capture.

The project builds on my earlier work with Indian indices and develops the mathematical argument behind the models, alongside their practical limitations.

GBM in the Indian stock market

An evaluation of Geometric Brownian Motion across eight Indian indices, including NIFTY 50, NIFTY 500, and NIFTY Realty. The work compares short-term model behavior across broad-market and sector-specific indices.

The analysis identified stronger alignment in broad-market and realty indices, alongside breakdowns in Auto and IT during disruptive conditions. Those limitations led into the Extended Essay’s investigation of alternative models.

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