This page contains a sample of some coding that I did for various research projects, advanced statistics and econometrics courses, and courses that I have taught personally.

• On-Line Portfolio Optimization.  [Python Functions] [Console Output]

{Description:  I wrote this library of Python Functions (e.g., using numpy and scipy) as part of a practicum for ECON 647:  Optimal Portfolio Choice.}

• Efficient Computation of Risk Parity (or Risk-Budgeted) Portfolios.  [Python Code]

{Description:  I composed this scientific Python program as part of a computational project on Risk Parity and Risk Budgeting for ECON 647:   Optimal Portfolio Choice.}

• Practical Calculation of Cover's (1991) Universal Portfolio.  [Python Program]

{Description:  I produced this elegant Python program for the sake of a quantitative research project on Cover's (1991) Universal Portfolio selection algorithm for my coursework in ECON 647:  Optimal Portfolio Choice.}

• Bayesian Model Averaging (BMA). [R Script] [LaTeX Output] [Permission Required]

{Description:  I wrote this R script for Chapter 2 of my Ph.D. Thesis.}

• Hurst Exponent and Half-Life Mean Reversion. [R Script] [LaTeX Output] [Permission Required]

{Description:  This R script was done for part of my research project in ECON 793: Financial & Time-Series Econometrics.}

• Variance Stabilization in Beta Regression. [R Script] [LaTeX Output]

{Description:  I wrote this R code as part of a research project for STAT 644: Generalized Linear Models.}

• Complex Portfolio Optimization. [R Script] [LaTeX Output]

{Description:  I wrote this R code as part of the class material for FINA 6339: Quantitative Portfolio Management at Northeastern University.}

• Complex Portfolio Optimization (Simulated Portfolios). [R Script] [LaTeX Output]

{Description:  I wrote this R code as part of the class material for FINA 6339: Quantitative Portfolio Management at Northeastern University.}

• Stock and Crypto Market Risk Assessment:  Bootstrap and Filtered Historical Simulation. [MATLAB® Script] [MATLAB® Output] [Permission Required]

{Description:  This is an updated version of the MATLAB® code that I used for my research project in ECON 743: Financial Economics II.}

• Distribution of Log Returns & Spectral Analysis of Cryptos. [MATLAB® Script] [MATLAB® Output] [Permission Required]

{Description:  This MATLAB® script was written to solve some research problems that I encountered in Chapter 3 of my Ph.D. Thesis.}

• BMA & Stochastic Volatility:  Data Visualization. [MATLAB® Script] [MATLAB® Output]

{Description:  This MATLAB® program was written for the sake of data visualization in relation to Chapter 3 of my Ph.D. Thesis.}

• Statistical Distributions (PDFs, CDFs and Beyond). [MATLAB® Script] [MATLAB® Output]

{Description:  This MATLAB® program was written  as a part of the class material for FINA 6332: Fundamentals of Financial Math and Financial Markets at Northeastern University.}

• Unconstrained Optimization. [MATLAB® Script] [MATLAB® Output]

{Description:  This MATLAB® program was written  as a part of the class material for FINA 6332: Fundamentals of Financial Math and Financial Markets at Northeastern University.}

• Linear Programming. [MATLAB® Script] [MATLAB® Output]

{Description:  This MATLAB® program was written  as a part of the class material for FINA 6332: Fundamentals of Financial Math and Financial Markets at Northeastern University.}

• Log and Exponential Functions. [MATLAB® Script] [MATLAB® Output]

{Description:  This MATLAB® program was written  as a part of the class material for FINA 6332: Fundamentals of Financial Math and Financial Markets at Northeastern University.}

• Quadratic Forms. [MATLAB® Script] [MATLAB® Output]

{Description:  This MATLAB® program was written  as a part of the class material for FINA 6332: Fundamentals of Financial Math and Financial Markets at Northeastern University.}

• Simulated Returns, Conditional Variance, and Innovations. [MATLAB® Script] [MATLAB® Output]

{Description:  This MATLAB® program was written  as a part of the class material for FINA 6332: Fundamentals of Financial Math and Financial Markets at Northeastern University.}

• Heston Stochastic Volatility Model: Monte Carlo via the QE Scheme. [Julia Output]

{Description:  Simulates the Heston model using Andersen's Quadratic-Exponential scheme to guarantee nonnegative variance, then recovers the implied volatility smile.}

• Fourier Pricing via Riccati Systems vs. Hermite-Edgeworth Expansion. [Julia Output]

{Description:  Prices options by integrating the Heston Riccati ODEs directly via RK4 and Fourier inversion, then shows where a Hermite-Edgeworth approximation departs from this exact price. }

• Finite Element Method for the Black-Scholes PDE. [Julia Output]

{Description:  Solves the Black-Scholes PDE with linear finite elements and Crank-Nicolson time-stepping, validated against the closed-form price and delta. }

• Bayesian Stochastic Volatility Estimation. [Julia Output]

{Description:  Recovers latent, time-varying volatility and its parameters from return data using Metropolis-within-Gibbs MCMC. }

• Black-Litterman Portfolio Optimization. [Julia Output]

{Description:  Blends market-implied equilibrium returns with investor views to produce more stable portfolio weights than raw mean-variance optimization. }

• Semi-Numerical Mean-Variance (Markowitz) Portfolio Optimization.  [Maple® Worksheet] [Maple® Output]

{Description:  I designed this Maple® worksheet as part of a quantitative project for ECON 647:  Optimal Portfolio Choice.  The worksheet explores both symbolic and numerical computations of Mean-Variance (Markowitz) efficient portfolios.}

• Symbolic Computation of Risk Parity and Risk-Budgeted Portfolios.  [Maple® Worksheet] [Maple® Output]

{Description:  I wrote this Maple® worksheet as part of a computational research project for ECON 647:  Optimal Portfolio Choice.  The worksheet focuses on symbolic and numerical computation of Risk Parity (and more generally, Risk-Budgeted) portfolios.}

• Model Selection in Survival Analysis. [SAS® Script] [SAS® Output]

{Description:  This SAS® program was a vital part of my research project for STAT 644: Generalized Linear Models.}

• Panel Data Fixed Effect, Random Effect, and Mixed-Effect Models. [SAS® Script] [SAS® Output]

{Description:  This block of SAS® code was vital for my empirical research project in STAT 640: Longitudinal Data Analysis.}

• Panel Data Poisson Regression Models. [SAS® Script] [SAS® Output]

{Description:  This SAS® code was written for the sake of my applied research project in STAT 640: Longitudinal Data Analysis.}