Aug 2019 – Aug 2021 · 2 yrs · Stony Brook,New York

• Courses taken
• 1. Introduction to Probability
• 2. Linear Algebra and Advanced Calculus
• 3. Linear Programming
• 4. Machine Learning in Quant Finance
• 5. Introduction to Mathematical Statistics
• 6. Natural Language Processing
• 7. Convex Optimisation
• 8. Stochastic Modelling and Analysis.
• 9. Simulation and Modelling
• 10. Bayesian Statistics in Finance
• Project-work:
• 1. Portfolio Optimisation using Convex Optimisation and Simulation - Scope of the Project - Given n financial assets and their price history, maximise portfolio return and minimise downside risk. Steps performed for the project - Market Data was downloaded using the Quandl API, Used Pandas and Numpy to calculate rolling Mean Returns and rolling Covariance matrix (Took care to avoid Survivorship Bias). Sequential Least Squares Programming was used to maximise the sharpe ratio and minimise the portfolio variance. I also used simulation to generate 10000 random portfolios and plotted it using matplotlib. Future goals of the project - I will work on the paper by Prof. Stephen Boyd et al. (https://stanford.edu/~boyd/papers/pdf/cvx_portfolio.pdf).

Jun 2017 – Dec 2018 · 1 yr 6 mos · Mumbai Metropolitan Region

• https://nbviewer.jupyter.org/github/ankit-a-aggarwal/crypto-analysis/blob/master/notebooks/CryptoAnalysis_1.0_D.ipynb
• I formulated and prioritised requirements, built a low-frequency cryptocurrency trading system using the CCXT API(https://github.com/ccxt/ccxt). A single interface was created to download market data from different cryptocurrency exchanges(Binance.com ,HuobiPro.com, bittrex.com, etc), thereby avoiding duplication of code.)
• Level-1 order book data and multiple time-frame data
• (1-hour,4-hour,12-hour and 24-hour data) were analysed together to spot trending and high volume cryptocurrencies. Used Technical Analysis libraries such as Ta-Lib. Added Cron-Jobs which would periodically download market data from the exchange API. Re-sampled data to generate weekly and monthly price trends. Automated the data download and the technical analysis parts. Formed trading rules using technical indicators such as Moving Averages(Moving Averages Cross-Over technique), Relative Strength Index(RSI) to spot trending patterns and Bollinger Bands to spot mean-reverting patterns.
• Future Goals - Will try to implement ideas in this paper. (http://stanford.edu/class/msande448/2018/Final/Reports/gr6.pdf)

Jan 2017 – Mar 2017 · 2 mos · Mumbai Metropolitan Region

• The senior management team gave me the opportunity to be part of a global program(11 analysts were chosen out of 400 globally across US,UK and India) which taught the basics of DevOps to me.
• I worked on automating some part of the Oracle Golden Gate processes using shell scripting, got myself familiarized with different tools such as Geneos, Docker, DynaTrace, Jenkins, etc .

Jul 2015 – Dec 2016 · 1 yr 5 mos · Mumbai Metropolitan Region

• I developed end-to-end Applications for trade finance instruments like Letter of Credit, Rebates, Documentary Collections, etc, using Google Web Toolkit for User Interfaces,Java Spring MVC for web and application services and Hibernate as the Object Relational Mapping Layer. I also wrote code for trade transaction management using Mule.
• I handled productions issues for Rebates.
• I was also part of the winning team that won an internal coding competition designed to improve the existing trade processing system.