• I am a 23-year-old Quant working in Liquidity Stress Testing. I gradutated from NC State with a masters in Financial Mathermatics. I wish to puruse a career as a Quantitative Trader or Researcher, specifically with Equities and Equity derivatives. I also interned as a Data Analyst at a Mortgage Insurance Company. Another one of notable experiences was as a quantitative trading intern at a prop trading firm. Looking for opportunities to learn and build new trading strategies. I am available for contact at the links below.

1. I am currently working on building backtests and also a backtesting library using the Interactive Brokers API.

2. I am currently learning C++ for Quantitative Finance and Probability

3. All of my projects can be found here at My repositories

4. Ask me anything about Python, R, Statistical Data Analysis, Technical Analysis, Portfolio Management and Probability theory.

5. An ongoing long project of mine which I just started again is my technical analysis visualization tool. In recent times I did find that technical analysis has been a tool that hasn't been of much help in the industry but I hope that this can be the beginning of a tool for Quant trading.

1. Visualising Technical Analysis Indicators using Dash : With this web application I aim to provide a free open source method for new learners or technical analysts to visualize and understand various technical indicators. Learners and traders can use this application to select various technical indicators and then visualize and interact with them. This can help new financial engineers get a better understanding of how various parameters of a technical indicator will affect the way we execute trades. It uses the technical analysis library available for python and Plotly's interactive visualization tools to provide the user with a dynamically changing and interactive tool. Source Code can be found here

2. Pairs Trading : Implementing Pairs Trading using time series analysis. Conducted data extraction for 200 Stocks and ETFs spanning various industries to identify highly correlated and cointegrated stock pairs. Performed stationarity tests on the spread between selected pairs using the Augmented Dickey Fuller Test. Generated trading signals and evaluated the profitability of the Pairs Trading Strategy, achieving an impressive 21% Compound Annual Growth Rate (CAGR) on a potential pair. Source code can be found here I want to work on a live trading API for Interactive brokers and perform the computations for Pairs trading with C++.

3. Sentiment Analysis for Evenet Driven Stock price Prediction : Led a team in developing a novel neural tensor network for event embedding. Utilized innovative web scraping and NLP techniques to gather and preprocess extensive news data. Achieved a 97% accuracy rate in predicting sentiment from news headlines using a convolutional neural network. Source code can be found here

4. Flight Delay Prediction: During my time at the Solarillion Foundation as a Research Assistant I developed a two stage machine learning model after data wrangling that predicts the time, in minutes, by which a flight will arrive late or not. Source code can be found here

5. Credit Risk analysis and Predictive Modelling : To expand my programming skills I implemented various R functions to bring about a report on the german credit data, which contains information about people who have taken loans and have either defaulted or paid them duely. Source code can be found here

6. Portfolio Optimization using R : This is second web application I had deployed using RStudio and shiny. It uses Perfomance Analytics and Portfolio Optimzation to reduce a user's risk and gives them the optimal percentage weight of each stock in their portfolio. This is a reactive application and can be used on any device. Source code and applicaiton can be found here

7. My first Web application using Shiny : This is my first project and first shiny web application. I wanted to explore the Shiny package in R, which led me to make an interactive visualization of the movement of the Collatz Conjecture. Source code and application can be found here