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Sai Prakash

8757511504 · imsaichauhan@gmail.com · in/imsaichauhan · imsaichauhan
Education
Madras School of Economics Chennai
Master of Arts in Applied Quantitative Finance 2023 – 2025
Central University of Tamil Nadu Thiruvarur
Bachelor of Arts in Economics 2020 – 2023
Experience
MicroSave Consulting (MSC), Research Intern Dec 2025 – Mar 2026
  • Constructed climate-adjusted credit risk scenarios for an MFI loan portfolio by engineering district-level physical hazard indicators from 200+ OCR-digitised government reports and web-scraped media sources; stress-tested expected loan losses under drought, flood, and cyclone scenarios, quantifying portfolio-at-risk exposure by geography
  • Engineered a composite district risk scoring model integrating multi-source hazard, exposure, vulnerability, and adaptive capacity data for 50+ districts; applied weighted aggregation methodology to rank and shortlist districts for UNDP field deployment
  • Analysed climate finance expenditure data across two states, identifying scheme-level allocation gaps and quantifying adaptation financing shortfalls against national targets
Projects
Credit Scoring and PD Estimation|Python, scorecardpy, XGBoost, scikit-learn
  • Developed WoE-based logistic scorecard on 307K retail loan applications with IV-driven feature selection; achieved Gini 45.2% (XGBoost benchmark: 45.9%), within the 40–60% industry range for retail PD models
  • Corrected balanced-weight miscalibration (MAE: 0.354 to 0.0018) via Platt scaling; threshold analysis at PD 0.10 yields 55.9% default capture rate at 73.8% portfolio approval rate
Volatility Modelling and Conditional VaR|Python, ARIMA-GARCH, arch, yfinance
  • Fitted ARIMA(1,0,0)-GARCH(1,1) on 5 years of Coromandel International daily returns; confirmed ARCH effects via Engle's LM test (p < 0.001); estimated persistence 0.915, volatility shock half-life ~8 trading days
  • Derived conditional 1-day VaR from time-varying GARCH volatility; backtested 250 days using Basel traffic light framework; peak 99% VaR 8.08% vs mean 4.16%, with elevated volatility windows aligning with Cyclone Asani (2022) and monsoon deficit (2023)
Options Pricing and Volatility Analysis|Python, Black-Scholes, Binomial Tree
  • Built Black-Scholes pricer, analytical Greeks, and CRR binomial tree from first principles; tree converges to BS price within 0.004 at N=500, confirming theoretical equivalence
  • Extracted IV from live NSE Nifty 50 options chain (141 strikes) using Brent's method; smile shows ATM IV 18.5% vs OTM put IV 43.0%, skew spread 8.55 pp
Coursework
IIT Madras | BS in Data Science and Applications Online (2024 – Present)
Madras School of Economics | Selected Coursework
Financial Derivatives Fixed Income Securities Risk Analysis and Management
Financial Mathematics Econometric Methods Stochastic Calculus & Quant. Finance
Corporate Finance Mathematical Methods Applied Macro & Fin. Econometrics
Certifications and Skills
Certifications
Climate Data · Public Policy · Python 101 · R for Data Science · Advanced SQL
Skills
Programming Python (pandas, NumPy, scikit-learn, statsmodels, arch, scipy) · R (tidyverse, forecast)
SQL (window functions, CTEs) · Stata · LaTeX
Tools Power BI · MS Excel · QGIS · Git

Sai Prakash

8757511504 · imsaichauhan@gmail.com · in/imsaichauhan · imsaichauhan
Education
Madras School of Economics Chennai
Master of Arts in Applied Quantitative Finance 2023 – 2025
Central University of Tamil Nadu Thiruvarur
Bachelor of Arts in Economics 2020 – 2023
Experience
MicroSave Consulting (MSC), Research Intern Dec 2025 – Mar 2026
  • Designed a multi-criteria district prioritisation framework for a UNDP climate adaptation finance study; scored 50+ districts across hazard, exposure, vulnerability, and adaptive capacity indicators; produced QGIS spatial outputs incorporated into UNDP field site selection
  • Mapped climate finance flows across Jharkhand and Odisha; benchmarked state adaptation plans against NDC and UNFCCC frameworks; quantified financing shortfalls to inform resource allocation
  • Quantified MSC's Scope 3 GHG emissions baseline across all GHG Protocol categories; modelled reduction pathways and delivered findings as input to the firm's net zero strategy
Projects
Climate Physical Risk Quantification|Python, NGFS Scenarios, TCFD Framework
  • Built a TCFD-aligned physical risk model for a 10-stock Indian equity portfolio; mapped 30 company-district asset locations to district-level hazard scores across flood, drought, cyclone, and heat stress perils using ThinkHazard (GFDRR/World Bank)
  • Quantified portfolio Climate VaR under NGFS Orderly Transition (1.5°C) and Current Policies (4°C) scenarios at 5.97% and 8.96% annual expected loss; 2.99 pp incremental exposure under the adverse pathway; agriculture inputs identified as highest-risk sector
Regional Climate Cooperation Analysis|Python, RICE-2013 IAM, Pyomo, IPOPT
  • Simulated US–EU–China–India cooperation using RICE-2013 IAM; cooperative scenario reduced global emissions to 13.61 GtCO₂ vs 17.09 GtCO₂ under Nash equilibrium by 2085, limiting warming to 2.96°C vs 3.23°C
  • Quantified uneven welfare distribution under cooperation — developed economies bear higher abatement costs; emerging economies gain more from avoided damages; modelled technology transfer and climate finance as equity mechanisms
Volatility Modelling and Conditional VaR|Python, ARIMA-GARCH, arch, yfinance
  • Fitted ARIMA(1,0,0)-GARCH(1,1) on 5 years of Coromandel International daily returns (NSE agrochemical); confirmed ARCH effects (p < 0.001); persistence 0.915, volatility shock half-life ~8 trading days
  • Derived conditional 1-day VaR; backtested 250 days under Basel traffic light framework; peak 99% VaR 8.08% vs mean 4.16%; elevated volatility windows align with Cyclone Asani (2022) and monsoon deficit (2023)
Coursework
IIT Madras | BS in Data Science and Applications Online (2024 – Present)
Madras School of Economics | Selected Coursework
Financial Economics Econometric Methods Economics of Global Climate Change
Financial Mathematics Mathematical Methods Applied Macro & Fin. Econometrics
Financial Derivatives Fixed Income Securities Risk Analysis and Management
Certifications and Skills
Certifications
Climate Data · Public Policy · Python 101 · R for Data Science · Advanced SQL
Skills
Programming Python (pandas, NumPy, statsmodels, geopandas, arch) · R (tidyverse, forecast, ggplot2)
SQL (window functions, CTEs) · Stata · LaTeX
Tools QGIS · Power BI · MS Excel · Git