Portfolio

About Me

MSc Investment Management graduate with distinction, combining strong foundations in econometrics and statistical modeling, with proficiency in multiple languages/software/frameworks (see next section).

My work includes ongoing formal research on oil price dynamics and factors driving AI adoption in UAE higher education, alongside independent interactive dashboard projects in options pricing and strategy visualisation hosted on Streamlit.

Professionally, I have worked as a Crude Oil Market Research Analyst, analysing global supply-demand dynamics, and provided regular insights on pricing structures, refinery outages, trade dynamics, and their implications on regional markets. I also investigated shadow fleet activity across key geopolitical regions of interest.

I am currently focused on deepening my machine learning expertise and targeting graduate/trainee roles across the following verticals:

• Quantitative Investing
• Portfolio Analytics & Management
• Risk Analytics
• Systematic Trading
• Macro Strategy

For more information, please scroll through the page — my CV and academic recommendation letters are available at the bottom.

Technical Skills

• Please refer to ‘On-going certifications’ section for technical skills I am currently learning/developing.
• Note that conceptual/modelling list is not exhaustive as it does not include financial models.

Languages / Software

• Python, STATA, EViews, LaTeX, CLI, Git, GitHub, Kpler, Refinitiv Eikon, S&P Global (Platts, Capital IQ), Power BI, Power Automate, Excel, Google Cloud (Basic)

Libraries / Frameworks

• pandas, NumPy, matplotlib, seaborn, scipy, statsmodels, scikit-learn, streamlit, plotly

Conceptual / Modelling

• Data Pre-processing, EDA, Feature Engineering, Probability Distributions (Normal, Binomial, Poisson – PMF/PDF/CDF), Statistical Validation (t-tests 1- & 2-sided, chi-square, ANOVA, Tukey HSD, binomial tests), Time Series Modeling (ARIMA, VAR, VECM, GARCH), Econometric Causality (Cointegration, Granger causality, Impulse Response, FEVD), Machine Learning (Regression (Linear, Logistic), K-Nearest Neighbors (Classifier, Regressor))

Publications (Working Papers)

• “Exploring Short and Long Run Causal Relationships between Oil Prices, Macroeconomic Factors, and Uncertainty Measures (Working Title)”
  • Co-Authoring a research paper with Dr. Athanasia Kalaitzi (Senior Lecturer Quantitative Finance and Economics at Middlesex University Dubai)
  • Focal point of the paper is investigating the transmission mechanisms uncertainty measures utilise to directly or indirectly affect oil price dynamics alongside other macroeconomic factors
• “Redefining Learning: AI and the Future of EdTech Innovation (Working Title)”
  • Co-Authoring a research paper with Dr. Monita Baruah (Associate Professor - MSc Financial Data Science Program at the University of Birmingham Dubai)
  • Focal point of the paper is to uncover key drivers of AI adoption across UAE universities using survey data that is analysed using a combination of supervised/unsupervised ML models to gather predictive insights and identify patterns in stakeholder responses.

Completed Projects

Options Strategy Payoff Calculator

• Developed a robust web application that allows users to analyze a wide range of options trading strategies, including Long Call, Short Call, Long Put, Short Put, Bull Call Spread, Bear Put Spread, and more.
• Empowers users to easily input key parameters such as strike price, premium, and expiration prices. The application generates detailed net-payoff tables and dynamic graphs, aiding seasoned analysts and students alike in making informed decisions.
• Utilised popular libraries such as numpy, pandas, matplotlib, and streamlit to create a user-friendly interface. This enhances strategy interpretation, providing valuable insights into payoffs and break-even points for various options strategies.

Options Pricing and Greeks Analysis

• Developed an options pricing tool using Black-Scholes and Monte Carlo methods, comparing options price sensitivity to volatility, time to expiration, and strike price, with visualisations of Monte Carlo price paths and distributions.
• Implemented Greek analysis for both methods, and created multi-dimensional sensitivity plots for deeper insights into option pricing dynamics.

Pairs Trading Simulator

• Built a rudimentary pairs trading sim for an aluminium and lead asset pair with customisable parameters like z-score threshold, lookback period, lot sizes, stop loss, and take profit, enabling flexible strategy testing.

A VAR Analysis of the Nominal Broad US Dollar Index (NBUSDI), Dow Jones Industrial Average (DJI), and S&P 500 (SPX)

• Explored the impact of changes in the NBUSDI, DJI, and SPX on each other, aiming to understand the short-term interactions and causal dynamics among these key financial indicators.
• Identified robust autocorrelation in NBUSDI, suggesting enduring shocks influencing the index, while DJI and SPX exhibited limited immediate influence on NBUSDI, emphasising their relative independence.
• Granger causality tests revealed significant evidence that lagged variables collectively Granger-cause changes in NBUSDI, highlighting the importance of external factors and predictive relationships among financial variables.

Assessing the impact of oil rents on UAE GDP: A multivariate time series regression analysis

• A study exploring the impact of oil rents on the economic growth of the United Arab Emirates (UAE), focusing on the effectiveness of existing strategies.
• Addressed the model’s limitations, including non-stationarity and multicollinearity, and proposed solutions such as the inclusion of new variables like merchandise imports to enhance model robustness and reliability.
• Found that oil rents significantly influence the UAE’s economic growth, with a notable contribution to GDP despite government strategies aimed at diversification.

On-going Projects

• ‘Debunking Theories’
  • A repository containing Jupyter notebooks that dissect a particular financial theory or mathematical construct by examining its notation/derivation, practical use-cases, limitations & implications, while also providing an alternative solution for consideration.
• ‘Macro Dashboard’
  • An interactive dashboard that applies econometric techniques to analyse the interdependencies between key indicators.
  • Insights are dynamically generated based on predefined template-driven interpretations aligned to detected patterns.
  • Threshold conditions are systematically evaluated to determine breaches, ensuring that the appropriate insights are selected and delivered in response to significant economic shifts.
• ‘The Portfolio Trifecta’
  • An interactive dashboard allowing you to construct, analyse, and optimise your equity investments with great transaction, performance, risk, attribution, and simulation insights.

And more…

On-going Certifications

• Note that I am not pursuing all of these certifications at once.
• I have a systematic learning plan where I attempt to complete short ‘courses’ frequently whilst making progress towards skill/career path certifications and balancing my research commitments.

Career Path (50-150 hours -> with exams)

• Machine Learning / AI Engineer
• Data Scientist: Machine Learning Specialist
• Data Scientist: NLP Specialist
• Data Scientist: Inference Specialist
• Data Scientist: Analytics
• Data Engineer
• Fullstack Engineer

Skill Path (>20 hours)

• Analyze Data with SQL
• Analyze Data with R
• Feature Engineering
• Build a Machine Learning Model
• Intermediate Machine Learning
• Build Deep Learning Models with TensorFlow

Courses (1-20 hours)

• Learn SQL
• Learn MongoDB
• kdb+/q Developer – Level 1
• kdb+/q Developer – Level 2
• kdb+/q Developer – Level 3
• Learn R
• Generative AI Models: Generating Data Using Generative Adversarial Networks (GANs)
• Intro to PyTorch and Neural Networks
• Creating AI Applications using Retrieval-Augmented Generation (RAG)
• Generative AI Models: Getting Started with Autoencoders
• Generative AI Models: Generating Data Using Variational Autoencoders
• Learn Image Classification with PyTorch

Algorithm Trading Courses (1-20 hours)

• Python for Trading
• Introduction to Machine Learning for Trading
• Trading with Machine Learning: Classification and SVM
• Options Trading Strategies in Python: Advanced
• Trading with Machine Learning: Regression
• Python for Machine Learning in Finance
• Mean Reversion Strategies in Python
• Backtesting Trading Strategies
• Event Driven Trading Strategies
• Financial Time Series Analysis for Trading
• Futures: Concepts & Strategies
• Systematic Options Trading
• Options Volatility Trading: Concepts and Strategies
• Data and Feature Engineering for Trading
• Decision Trees in Trading
• Natural Language Processing in Trading
• Unsupervised Learning in Trading
• Neural Networks in Trading
• Deep Reinforcement Learning in Trading
• Machine Learning for Options Trading
• Quantitative Portfolio Management
• Position sizing in Trading
• Factor Investing: Concepts and Strategies
• Portfolio Management using Machine Learning: Hierarchal Risk Parity
• AI for Portfolio Management: LSTM Networks
• News Sentiment Trading Strategies
• Momentum Trading Strategies
• Trading Alphas: Mining, Optimisation, and System Design
• Trading in Milliseconds: MFT Strategies and Setup

Completed Certifications

Skill Path (>20 hours)

• Data and Programming Foundations for AI
• Fundamental Math for Data Science
• Master Statistics with Python

Courses (1-20 hours)

• Learn Python 3
• Learn the Command Line
• Learn Git and GitHub
• Level 4 Diploma in Investment Bank Sales and Trading
• Finance Accelerator Simulation Participant in Partnership with Morgan Stanley
• Getting Started with Refinitiv Eikon

Algorithm Trading Courses (1-20 hours)

• Python for Trading Basic
• Getting Started with Algorithmic Trading
• Statistical Arbitrage Trading
• Getting Market Data: Stocks, Crypto, News & Fundamentals
• Quantitative Trading Strategies and Models
• Options Trading Strategies in Python: Basic
• Options Trading Strategies in Python: Intermediate
• Trading using Options Sentiment Indicators
• Value Strategy in Forex
• Forex Trading using Python: Basic

Finance/Industry Experience Courses (1-10 hours)

• JP Morgan: Investment Banking Virtual Experience Program Participant
• JPMorgan Chase: Commercial Banking Virtual Experience Program Participant
• ACCA: Sustainability in Banking Virtual Experience Program Participant
• JPMorgan Chase: Markets (Sales & Trading) Virtual Experience Program Participant
• Fidelity International: Investment Management Virtual Experience Program Participant
• JP Morgan: Global Private Bank Virtual Experience Program
• Goldman Sachs: Excel Skills for Business Virtual Experience Program Participant
• JPMorgan Chase: Asset Management Virtual Experience Program Participant
• HSBC: Global Banking & Markets Virtual Experience
• Bank of America: Investment Banking Virtual Experience Program Participant
• Code and Standards Certifications on the CFA Institute Code of Ethics (Total of 22)

CV

Academic Recommendation Letters