Mehul Mehta

Model Implementation: Developed and implemented various stochastic interest rate models, including Vasicek, Cox-Ingersoll-Ross (CIR), and Hull-White models, to capture the dynamics of interest rates.

Bond Pricing Framework: Created a bond pricing framework using the developed stochastic models, accurately pricing fixed income securities and incorporating interest rate movements.

Calibration and Estimation: Calibrated the stochastic models to historical interest rate data using… Show more

Model Implementation: Developed and implemented various stochastic interest rate models, including Vasicek, Cox-Ingersoll-Ross (CIR), and Hull-White models, to capture the dynamics of interest rates.

Bond Pricing Framework: Created a bond pricing framework using the developed stochastic models, accurately pricing fixed income securities and incorporating interest rate movements.

Calibration and Estimation: Calibrated the stochastic models to historical interest rate data using maximum likelihood estimation (MLE) and other statistical techniques, ensuring accurate representation of market conditions.

Sensitivity and Scenario Analysis: Conducted sensitivity analysis and scenario testing to evaluate the impact of different interest rate scenarios on bond prices, providing insights into the risk and return characteristics of fixed income portfolios. Show less

Monte Carlo Simulation: Developed a Monte Carlo simulation framework to price Auto Callable Barrier Reverse Convertible (ACBRC) options, accurately modeling the complex path-dependent features and payoff structures.

Variance Reduction Techniques: Implemented advanced variance reduction techniques, including Antithetic Variates and Control Variates, to enhance the efficiency and accuracy of the Monte Carlo simulations.

Path Dependency Modeling: Accurately captured the path… Show more

Monte Carlo Simulation: Developed a Monte Carlo simulation framework to price Auto Callable Barrier Reverse Convertible (ACBRC) options, accurately modeling the complex path-dependent features and payoff structures.

Variance Reduction Techniques: Implemented advanced variance reduction techniques, including Antithetic Variates and Control Variates, to enhance the efficiency and accuracy of the Monte Carlo simulations.

Path Dependency Modeling: Accurately captured the path dependency of the ACBRC options by simulating numerous price paths and incorporating the auto-call and barrier features.

Sensitivity Analysis: Performed sensitivity analysis to evaluate the impact of key parameters (e.g., volatility, interest rates, barrier levels) on the option price, ensuring a robust and comprehensive pricing model. Show less

VaR Model Development: Developed a Value at Risk (VaR) model using Historical Simulation, Variance-Covariance method, and Monte Carlo Simulation to estimate potential losses in the portfolio.

CVaR Model Implementation: Implemented Conditional Value at Risk (CVaR) model to assess the tail risk, providing a more comprehensive measure of potential extreme losses beyond the VaR threshold.

Model Backtesting: Conducted rigorous backtesting of the VaR model using historical data to… Show more

VaR Model Development: Developed a Value at Risk (VaR) model using Historical Simulation, Variance-Covariance method, and Monte Carlo Simulation to estimate potential losses in the portfolio.

CVaR Model Implementation: Implemented Conditional Value at Risk (CVaR) model to assess the tail risk, providing a more comprehensive measure of potential extreme losses beyond the VaR threshold.

Model Backtesting: Conducted rigorous backtesting of the VaR model using historical data to evaluate its predictive accuracy, ensuring compliance with regulatory standards and identifying areas for improvement.

Sensitivity and Stress Testing: Performed sensitivity analysis and stress testing to understand the impact of market shocks on VaR and CVaR, enhancing the robustness and reliability of the risk assessment models. Show less

Binomial Tree Model Implementation: Developed a Binomial Tree model to price American options, incorporating early exercise features through backward induction and optimal stopping rules.

Trinomial Tree Model Implementation: Extended the analysis by constructing a Trinomial Tree model, enhancing accuracy and stability in option pricing by incorporating an additional middle state.

Greeks Calculation: Implemented the calculation of option Greeks (Delta, Gamma, Theta, Vega) within… Show more

Binomial Tree Model Implementation: Developed a Binomial Tree model to price American options, incorporating early exercise features through backward induction and optimal stopping rules.

Trinomial Tree Model Implementation: Extended the analysis by constructing a Trinomial Tree model, enhancing accuracy and stability in option pricing by incorporating an additional middle state.

Greeks Calculation: Implemented the calculation of option Greeks (Delta, Gamma, Theta, Vega) within both the Binomial and Trinomial Tree frameworks to analyze sensitivity and risk measures.

Comparison and Sensitivity Analysis: Conducted a comparative analysis between the Binomial and Trinomial models, highlighting differences in convergence, computational efficiency, and pricing accuracy, and performed sensitivity analysis on key parameters (e.g., volatility, interest rates) to ensure model robustness. Show less

Model Development and Implementation: Developed and implemented various stochastic volatility models (e.g., Heston, SABR) and time series models (e.g., ARCH, GARCH) to capture and forecast volatility dynamics.

Volatility Data Analysis: Analyzed historical volatility data to identify patterns and trends, preparing the data for model calibration and validation.

Model Calibration and Validation: Calibrated the stochastic volatility and time series models using historical volatility… Show more

Model Development and Implementation: Developed and implemented various stochastic volatility models (e.g., Heston, SABR) and time series models (e.g., ARCH, GARCH) to capture and forecast volatility dynamics.

Volatility Data Analysis: Analyzed historical volatility data to identify patterns and trends, preparing the data for model calibration and validation.

Model Calibration and Validation: Calibrated the stochastic volatility and time series models using historical volatility data, ensuring they accurately reflect market conditions, and validated their performance through backtesting and out-of-sample testing.

Comparative Analysis and Insights: Conducted a comprehensive comparative analysis of the stochastic volatility and time series models, evaluating their predictive power, computational complexity, and robustness, providing actionable insights for optimal model selection in volatility modeling applications. Show less

Implemented the Black-Scholes Model to derive closed-form solutions for European call and put options, compute Greeks, and derive implied volatility.

Developed a Binomial Tree Model using a recombining tree structure for option valuation through backward induction, accommodating variable interest rates and volatility.

Applied the Heston Model to account for stochastic volatility, solving the associated PDE and using the characteristic function for more realistic market… Show more

Implemented the Black-Scholes Model to derive closed-form solutions for European call and put options, compute Greeks, and derive implied volatility.

Developed a Binomial Tree Model using a recombining tree structure for option valuation through backward induction, accommodating variable interest rates and volatility.

Applied the Heston Model to account for stochastic volatility, solving the associated PDE and using the characteristic function for more realistic market representation.

Utilized Monte Carlo Simulation to estimate option prices by simulating numerous price paths for underlying assets, incorporating randomness and flexibility in assumptions. Show less