β Implemented βBuying the Loserβ, Decision Tree-based Pairs Trading, LSTM-based Trading and MVP Optimization strategies
β Coded model pipelines in Python while leading the project team of 5 graduate students to nail down an optimal structure
β Calculated and optimized for portfolio risk metrics such as VaR & ES in R and wrote the final report and presented in class
GitHub RepositoryPortfolio Analysis ReportPresentation Pairs Trading
β Performed Variance Ratio and Push Response Tests for market behavior on 5-min price data using R and Python
β Implemented and Backtested Trend-following trading strategy with split transactional costs in Python and MATLAB
- Fitted Levy PDF to the distribution of price changes to obtain coefficients and empirically test the fat-tails hypothesis
GitHub RepositoryPresentation
β Engineered a Sentiment based volatility predictor and trade recommender bot using optimization methods in Call/Put Options.
β Used Python, Twitter API and the Black Scholes Model to estimate the fair prices of options based on the top 100 tweets.
GitHub RepositoryReportPresentation
β Created a note taking web application with edit, delete, and add functionality using HTML, CSS, JavaScript on Netlify
β Scaled to over 100 people; performed quantitative and qualitative UI/UX research by task analysis and writing user stories
GitHub Repository
β Created a time tracking and data analysis tool for better self-evaluation of productivity, physical and mental well-being.
β Performed Data Analysis, Wrangling and k-Means Clustering using R, Shiny, RStudio, and LaTeX
GitHub Repository
β Used distributed computing in Java to make accounts and transactions synchronous and thread-safe
- Used Java, Distributed computing, Threads and Locks, Object Oriented Programming, GitHub and VS Code during the development process.
GitHub Repository
β Created an app and blog in group of 3 as a part of final project of Data Science class to analyze the periodic and spatial trends of COVID-19, mental health and sentiments in the US.
β Performed Twitter Sentiment Analysis, Spatial Data Superposition and statistical analysis using R, Shiny and Twitter API.
GitHub Hosted Blog Website GitHub Repository