DEEP PATEL

MSc FinTech with Business Analytics graduate with strong quantitative research experience in high-frequency trading, algorithmic strategies, and statistical arbitrage. Skilled in applying stochastic calculus, optimization techniques, and Python-based simulations to model financial markets. Hands-on exposure to equity trading, derivatives, and cryptocurrency markets. Seeking a quantitative analyst/trader role in a global financial institution.

• NSE’s Financial Markets Certification – Beginner Module
• Basics of Options Trading – Zerodha
• Technical Analysis – ElearnMarkets
• Python (NumPy, Pandas, Matplotlib, Jupyter), stochastic modeling, optimization
• Excel automation, market microstructure analysis, algorithmic trading strategies
• Blockchain: Project tokenization, NFT creation, crypto development
• Mailchimp, LinkedIn prospecting, market data tools

• Master’s Thesis – High-Frequency Trading and Market Efficiency, University of Westminster, 05/23, Designed and tested optimal liquidation strategies for large equity positions using the Hamilton-Jacobi-Bellman framework and dynamic programming., Modeled stochastic price impacts (temporary and permanent) to evaluate execution costs and liquidity constraints., Implemented Python-based simulations on Amazon (AMZN) market data to analyze market microstructure (mid-price, micro-price, spreads, volume imbalance)., Developed and simulated a pairs trading strategy for Bitcoin and Ethereum using co-integration, Ornstein-Uhlenbeck processes, and optimal control methods., Conducted comparative analysis against the Almgren-Chriss model to validate performance of the proposed strategies.
• Other Projects, Developed and issued NFTs on blockchain as a hobby project., Built automation spreadsheets for financial projections.