Quant Finance Bootcamp 2026 (New Cohort)

What Will You Learn?

• Foundational Knowledge: Gain a solid understanding of derivative markets, including forwards, futures, and options, and the roles of different traders such as hedgers, arbitrageurs, and speculators.
• Future Markets: Learn the intricacies of futures contracts, margin account operations, and the distinctions between forward and futures contracts through practical examples and case studies.
• Options Mechanics: Master the types of options, trading positions, payoff diagrams, and the key differences between European and American options.
• Option Trading Strategies: Build a strong foundation in option strategy design by studying single-leg and multi-leg positions, profit and loss dynamics, Greeks exposure, risk management, and real-world trading applications.
• Stochastic Processes: Delve into continuous and discrete stochastic processes, Brownian Motion, Geometric Brownian Motion, Poisson processes, and the application of Ito's Lemma in quantitative finance.
• Option Pricing: Explore the binomial tree method for pricing options, understand risk-neutral valuation, and develop intuition behind modern derivative pricing frameworks.
• Black-Scholes Model: Understand the assumptions, derivation, application, and interpretation of the Black-Scholes-Merton model for European option pricing.
• Risk Management with Greeks: Learn how to calculate and utilize Delta, Gamma, Theta, Vega, and Rho for hedging, portfolio management, and options risk control.
• Monte Carlo Simulation: Learn how Monte Carlo methods are used to model uncertainty and generate thousands of potential market scenarios for pricing, risk management, and portfolio analysis. Explore random number generation, asset price path simulation, variance reduction techniques such as antithetic variates and control variates etc.,
• Exotic Options: Explore the pricing and risk characteristics of exotic derivatives such as Asian, Binary, Barrier, Lookback, and Chooser options. Learn how Monte Carlo simulation techniques are used to generate asset price paths and estimate option values under uncertainty. Develop practical skills in modeling, pricing, and analyzing complex derivative products.
• Stochastic Volatility Modeling: Study stochastic volatility models such as Heston, focusing on model intuition, calibration techniques, simulation methods, and practical implementation.
• Stochastic Interest Rate Modeling: Study interest rate models such as Vasicek and CIR, focusing on calibration, simulation, term structure dynamics, and fixed income applications.
• Value at Risk (VaR): Analyze portfolio risk using Value at Risk and Expected Shortfall, with model validation through backtesting and stress testing. Build VaR models through Variance-Covariance, Historical Simulation, and Monte Carlo methodologies and backtest the model using regulatory and statistical approach.
• Copula Modeling: Learn how copulas are used to model dependence structures between financial assets beyond traditional correlation measures. Explore Gaussian and Student-t copulas, tail dependence, copula calibration, simulation techniques, and applications in portfolio risk management and derivative pricing.
• Equity Portfolio Analytics: Learn how portfolio managers evaluate investment performance using metrics such as alpha, beta, Sharpe ratio, information ratio, and drawdowns. Explore portfolio construction, diversification, factor exposures, and risk-adjusted return analysis using real market data.