Author: Arjun Mehta

Arjun Mehta - Senior Quantitative Researcher Arjun Mehta has 14 years of experience in quantitative finance, working across proprietary trading desks at institutional firms in London and Mumbai before moving to independent research and education. He has built and deployed systematic strategies across equity, futures, and options markets, with a primary focus on statistical arbitrage, factor model research, and execution algorithm design for mid-frequency strategies. Arjun holds a Bachelor of Technology in Computer Science from IIT Bombay, a Master of Science in Financial Engineering from Imperial College London, and the Certificate in Quantitative Finance (CQF). His research interests include factor model alpha decay, realistic transaction cost modeling for retail quantitative traders, and the practical limitations of backtesting under live market conditions — particularly the gap between in-sample results and out-of-sample performance. At QuantVero, Arjun leads tutorial content, trading strategy analysis, and interview preparation material. His work focuses on making institutional-grade quantitative methods accessible to practitioners at all levels — with complete, tested Python code, honest risk disclosures, and the practical caveats that academic papers and platform documentation consistently leave out. Expertise Tags • Statistical Arbitrage and Pairs Trading • Factor Investing and Alpha Research (Momentum, Value, Quality) • Python for Systematic Trading: pandas, NumPy, scipy, backtrader, zipline • Options Pricing and Dynamic Hedging • Execution Algorithms and Market Microstructure • Quant Interview Preparation: probability, statistics, coding challenges