I'm an IPM student at IIM Bodh Gaya building around quantitative finance, financial modelling, markets, and data.
I enjoy taking ideas that usually live inside research papers, spreadsheets, or trading terminals and turning them into systems people can actually interact with.
Most of my projects start with a question.
How should an option be priced?
What happens when the yield curve moves?
What is actually driving a stock?
How does a macroeconomic event transmit through markets?
What does a real transaction model look like?
I like going underneath the interface, understanding the mathematics and assumptions, building the engine, and then making the result explorable.
Understand the model. Build the machinery. Make the result explorable.
Corporate finance & M&A transaction analysis
An India-focused transaction modelling platform connecting company analysis, valuation, deal structure, financing, synergies, pro forma statements, and EPS accretion in one connected model.
- Driver-based forecasting and DCF valuation
- WACC/CAPM and trading comparables
- Sources & Uses, debt financing, purchase price allocation
- Synergy modelling and three-statement pro forma analysis
- EPS accretion / dilution and credit metrics
- Scenario analysis, sensitivities, and deal-specific solvers
- Calculation lineage and model diagnostics
Stack: Python · FastAPI · Next.js · TypeScript · PostgreSQL · Supabase
Equity valuation & financial modelling workbench
A financial modelling platform connecting data ingestion, normalization, forecasting, valuation, accounting QA, and Excel model generation.
- Driver-based 5-year three-statement forecasts
- Base, Bull, and Bear scenarios
- CAPM-based WACC and FCFF DCF
- Reverse DCF and valuation sensitivities
- Public comps and football-field valuation
- PE exit returns and IRR waterfall
- Automated accounting and model QA
- Dynamic 30-tab Excel model exporter
Stack: Python · FastAPI · Pydantic · OpenPyXL · SQLite · Next.js · React · TypeScript
Option pricing, volatility, and risk
What started as a Monte Carlo vs Black-Scholes comparison grew into a broader options research platform.
- Black-Scholes-Merton pricing and Greeks
- Five Monte Carlo estimators
- Implied volatility solving
- P&L attribution and multi-leg strategies
- Scenario stress testing
- Heston calibration and stochastic volatility
- SVI volatility surface fitting
- Delta-hedging and model comparisons
Stack: Python · FastAPI · NumPy · SciPy · Next.js · TypeScript · Tailwind · Recharts
Fixed-income analytics for Indian Government Securities
An interactive fixed-income platform for fitting the yield curve, measuring risk, and studying portfolio behaviour under curve scenarios.
- Nelson-Siegel-Svensson yield-curve fitting
- Zero-coupon bootstrapping
- Parallel shifts, steepeners, flatteners, twists, and butterflies
- Duration and convexity
- DV01 and Key Rate Duration
- Portfolio scenario P&L
Stack: Python · FastAPI · SciPy · Next.js · TypeScript · Supabase
Event-driven macro analysis for Indian markets
A research platform for studying market behaviour around major Indian macroeconomic events.
RBI MPC · CPI · IIP · NIFTY 50 · USD/INR · India VIX · 10Y G-Sec
Combines event windows, surprise analysis, market reactions, and interactive visualisation.
Stack: Python · FastAPI · Next.js · Supabase · Recharts
Pharmaceutical market attractiveness across India
A statistical framework covering all 785 Indian districts, combining demographic, health, economic, and geospatial data to evaluate pharmaceutical market attractiveness.
Produces district-level Overall, Chronic, and Acute indices with current-state and future-trajectory views.
Stack: Python · Pandas · SciPy · Next.js · D3.js · Tailwind CSS
What's really driving your returns?
Rolling factor regressions across the NIFTY 500.
Market · Value · Momentum · Size · Volatility
The heavy analysis is pre-computed through GitHub Actions and served through a FastAPI backend for interactive exploration.
Stack: Python · Pandas · Statsmodels · Scikit-learn · FastAPI · Next.js · Supabase
From weekday gap probabilities to an options strategy
A research and backtesting tool studying weekday-to-weekday NIFTY 50 gaps and turning those probabilities into systematic CE/PE trade rules.
- Weekday-pair gap probability analysis
- Wilson confidence intervals and sample guards
- Black-Scholes option pricing
- GTT-style premium exit ladder
- In-sample vs out-of-sample diagnostics
- Interactive trade and equity-curve dashboard
Stack: Python · FastAPI · Black-Scholes · yfinance · Chart.js
Detecting changing relationships across markets
Tracks rolling relationships across:
NIFTY 50 · USD/INR · Gold · Brent Crude · 10Y G-Sec Yield · FII Net Flows
Uses rolling correlations and anomaly detection to surface periods where historically stable relationships begin behaving differently.
Stack: Python · FastAPI · Next.js · D3.js
Your timetable, on your home screen.
A Flutter Android scheduling app built around a simple idea: your next class should be visible without opening the app.
- Excel / CSV timetable import
- Three home-screen widget sizes
- Live "Up Next" countdown
- Unified classes and tasks timeline
- SQLite persistence
- Native Kotlin Android integration
- Material 3 interface
Stack: Flutter · Dart · Kotlin · SQLite · Riverpod · Android
I write technical notes alongside the software.
The current series follows a progression through the foundations of mathematical finance:
Options → Brownian Motion → Geometric Brownian Motion → Itô Calculus → Black-Scholes → Risk-Neutral Pricing
What Exactly Is an Option?
The mechanics of calls, puts, payoffs, intrinsic value, and time value.
The Language of Fluctuation
Brownian motion and the mathematical language of continuous uncertainty.
The Geometry of Fluctuation
Geometric Brownian Motion and multiplicative asset-price dynamics.
The Extra Term
Quadratic variation and the emergence of Itô's Lemma.
The Frontier of Certainty
Dynamic replication, delta hedging, the Black-Scholes PDE, and its transformation.
The Measure of Arbitrage
Girsanov's theorem, risk-neutral pricing, martingale measures, and market completeness.
NumPy · Pandas · SciPy · Statsmodels · Scikit-learn · FastAPI · Supabase · Recharts · D3.js
Quantitative finance, volatility modelling, fixed income, market microstructure, financial modelling infrastructure, mathematical finance, and AI systems that are actually useful.