Course: Credit Risk Management (CFRM 542)
Instructor: Dr. Jay Henniger
This course covered the theory, applications, and computational methods for credit risk measurement and management. It also discussed the statistical and mathematical modeling of credit risk, emphasized numerical methods and R programming. These methods included logistic regression, Monte Carlo simulation, and portfolio cash flow modeling. The course also covered default risk regression, analytics, and portfolio models of credit risk.
Course: Machine Learning for Finance (CFRM 521)
Instructor: Dr. Kevin Lu
This course took a hands-on approach to machine learning and focused on gaining the working knowledge of some of the major supervised and unsupervised techniques. The topics included regression techniques, support vector machines, decision trees, random forests, principal component analysis, and artificial neural networks. The course taught me the mathematical constructions of algorithms which I then applied to different financial settings including predicting the Fed rate and stock price in Python with the help of Sklearn and Tensorflows.
Course: Financial Software Development and Integration with C++ (CFRM 521)
Instructor: Dan Hanson
This course focused on developing skills that would be necessary for a quantitative software developer. It taught many essential concepts that were applied to derivative asset pricing and had application in stock trading. The course also focused on developing skills useful to software engineers which included organizing data and optimizing code in order to reduce the time it took for execution. Finally, the course displayed the extensions of C++ to R programming. This is particularly useful in displaying results.
Course: Financial Data Science (CFRM 502)
Instructor: Dr. Jhon Guerard
This course introduced financial modeling and data analysis with a financial application. The focus of this course was on statistical analysis, modeling, and computational techniques in key quantitative finance areas including financial time series, and portfolio analytics. Some of the main topics were regression methods and factor modeling, principal component analysis, ARIMA, and VIF modeling. This course helped me develop data management skills which are essential in dealing with real and often messy data.
Course: Monte Carlo Simulation in Finance (CFRM 505)
Instructor: Dr. Tim Leung
CFRM 505 taught in-depth, the different methods involved in Monte Carlo simulation with a focus on finance using Python and R. I learned many different methods and techniques, including but not limited to the Inverse Transform method, Acceptance Rejection technique, and the Composition method, etc. I applied my learnings to determine financial security prices (including Black Scholes and Black Merton models), greek estimates (Delta, Gamma, etc.), and portfolio valuations. I learned several risk and variance reducing methods using Antithetic, Importance Sampling, and Control Variates. Through this course, I learned to value portfolios with dependent securities using the Gaussian Copula. Lastly, this course also introduced me to machine learning and mean reversion trading strategies.
Course: Optimization Methods in Finance (CFRM 507)
Instructor: Dr. Steve Murray
Through CFRM 507, I improved my financial modeling skills and learned optimization techniques in Excel, R, Python, and AMPL using built-in or externally plugged solvers. I followed a three-step process. First, I formulated constraint-based: linear, non-linear, dynamic and, stochastic optimization problems in mathematical terms. Next, I developed and solved the models by leveraging computing languages. Lastly, I reported and presented the problems to the class. Through these models I solved real-world optimization problems such as portfolio selection, management of cash flows to meet liabilities, determining optimum portfolio weights with new investment amount, or rebalancing existing portfolios based on given constraints. I also incorporated business events and market reactions to carry out a robust analysis.
Course: Options and Other Derivatives (CFRM 504)
Instructor: Dr. Matt Lorig
CFRM 504 was centered around pricing, valuing, and incorporating derivative products (forwards, futures, options, etc.) in the investor portfolio. The main aim of this course was to show the mathematical computations for pricing a derivative contract. These computations included creating a replicating portfolio for investors and, using risk-neutral pricing. The learnings from this course also highlighted the different investor profiles (hedgers, speculators, and arbitragers) that trade derivative products. Finally, the course covered pricing derivative products using Black Scholes and Binomial Lattice Models. A large portion of this course involved determining the price of the derivatives by writing programs in Python.
Course: Investment Science (CFRM 501)
Instructor: Ryan Donnelly
In CFRM 501, I focused on extracting information and mathematically constructing optimally weighted portfolios for investors using data on different publicly traded securities. I determined utility functions and incorporated investor's risk aversion in my analysis. A large part of the course involved mathematically computing results related to CAPM and Factor models. Furthermore, the course introduced key computations within fixed income (such as bootstrapping yield curve) and risk management (value at risk and shortfall measure). The course helped me improve data cleaning, manipulation, and analysis skills in relation to investment finance using R and Python.
Course: Strategic Business Management (MGMT 400)
Instructor: Dr. Adnan Zahid
In MGMT 400, I focused on a set of management decisions and actions that determined the long‐run performance of corporations. These included environmental scanning (both external & internal), strategy formulation (strategic or long‐range planning), strategy implementation, and evaluation and control. During the course, the study of strategic management emphasized monitoring and evaluation of external opportunities and threats in light of the corporation’s strengths and weaknesses.
Course: Applied Corporate Finance (FINN 400)
Instructor: Dr. Fazal Jawad
FINN 400 was a case‐based course in advanced-level finance. It provided insights into the role of the financial manager, whose primary responsibility is acquiring funds needed by the firm and directing these funds into projects that will maximize the value of the firm for its shareholders. I learned the various tasks performed by the financial manager in reaching this objective, such as financial analysis and forecasting of cash flows, analysis of working capital, project evaluation, and risk analysis, evaluating financing choices available to the firm, valuation of financial and real assets including valuation of Merger and Acquisition candidates, and cross‐border transactions involving foreign currencies and global financial markets.
Course: Capital Markets and Corporate Governance (FINN 383)
Instructor: Khalid Aziz Mirza
In this course, I studied the theoretical underpinnings of corporate governance viewed from a historical and contemporary context. I was exposed to the principal aspects/foundations, as well as the diverse and widely acknowledged views of corporate governance. The course was arranged to include Pakistan's approach to corporate governance and I studied the two Codes of Corporate Governance issued by capital markets regulators ( i.e. SECP) in 2002 and 2012.