About Me: Finance & Trading Automation

I specialize in algorithmic trading, options analysis, backtesting, and financial data automation. With a strong background in Python, Excel (PyXLL), APIs, and data engineering, I have built tools that enhance trading efficiency, automate decision-making, and optimize financial workflows. My work spans across equities, options, and cryptocurrencies, with a focus on systematic strategies, real-time data processing, and analytics

Algorithmic Trading & Quant Research

• SPY 0DTE Options Trading Bot
  Developed an automated SPY 0DTE options trading strategy that executes trades based on pre-defined market conditions, bid-ask spread, and real-time price movements.

• Machine Learning for Options Chain Analysis
  Built an ML-based framework to analyze SPY options chains, test hypotheses, and detect arbitrage opportunities. Includes data cleaning, feature engineering, and backtesting.

• SPY Seasonal Analysis (Work in Progress)
  Conducting research on SPY seasonality patterns to create a machine learning-based model for trading strategy optimization.

Trading Tools & Fintech Automation

• Excel-Based Trading Tool for Alpaca
  Created an Excel front-end tool integrated with PyXLL and Alpaca API, allowing real-time market data streaming and order execution.

• Options Screeners
  Designed a Python-based options screeners that identifies put-call parity violations, IV discrepancies, skewed delta, and liquidity mispricing for potential trading opportunities.

• Fundamental Analysis Tool Using FMP API
  Developed a tool that pulls key fundamental data (balance sheets, income statements, cash flows) from the FMP API for S&P 500 companies.

• Discounted Cash Flow (DCF) Model Template
  Developed an Excel-based DCF tool using PyXLL and Python that allows users to enter a ticker and key assumptions to generate a fully structured valuation model.

Data Engineering & Market Analytics

• Automated Stock & Crypto Screener
  A real-time screener for stocks & crypto using technical indicators such as RSI, MACD, and Bollinger Bands.

• Backtesting Framework for Equities & Options
  Developed a modular backtesting framework that enables simulation of trading strategies on historical market data.

• Benchmarking Study: CSV vs. Parquet vs. SQL for Market Data
  Conducted performance analysis on financial data storage formats to optimize handling of large-scale trading datasets.