At FidelCrest Prop Firm, I managed a proprietary trading portfolio under strict risk parameters and passed the evaluation challenge with a 10% return in one month. I currently manage a family account.
For my algorithmic trading system project, I developed an automated execution and historical backtesting engine in Python and MQL5, with pre-trade risk controls and exit logic. It achieved estimated returns of around 30ā40% in favorable conditions, while risk controls capped drawdown at around 7% in adverse or volatile regimes.
I also analyzed financial time-series data with a quantitative statistical model and explored automotive pricing data, including classification models that achieved around 63% accuracy. Iām pursuing a BS in Economics at Institute of Business Administration (IBA), Karachi, and have completed courses in investment management and finance and quantitative modeling.
