02 : Projects
I am passionate about quantitative research and have developed projects that showcase my expertise in data science, financial modeling, and algorithmic trading. One of my notable projects is the "Value-at-Risk (VaR) Estimation Model for Multi-Asset Portfolio," where I implemented Monte Carlo simulations and historical simulations to compute VaR across diverse asset classes. This project enhanced my skills in risk management and financial analytics. Another significant achievement is the "Counterparty Credit Risk Model using CVA & DVA Adjustments," which involved pricing credit and debit valuation adjustments for OTC derivatives using Monte Carlo methods and hazard rate modeling. These projects highlight my proficiency in financial modeling, quantitative analysis, and Python programming.
001/005
Real-Time News Sentiment Signal Engine for Trading
Skills: NLP, Sentiment Analysis, Signal Engineering, Feature Engineering, Data Streaming Technologies: Python, FinBERT (HuggingFace), NewsAPI, Tweepy, pandas, NumPy, Streamlit
Discover
002/005
VaR-CVaR Estimation for AI Stocks and Bitcoin Correlated Portfolio
Skills: Risk Modeling, Monte Carlo Simulation, Copula Theory, Financial Engineering Technologies: Python, NumPy, pandas, SciPy, matplotlib, yfinance, copulas
Discover
003/005
Counterparty Credit Risk Model using CVA and DVA Adjustments
Skills: Credit Risk, CVA/DVA Modeling, Exposure Simulation, Survival Analysis Technologies: Python, NumPy, pandas, matplotlib, SciPy
Discover.jpg)
004/005
Value-at-Risk (VaR) Estimation Model for Multi-Asset Portfolio
Skills: Quantitative Risk Analysis, Portfolio Analytics, VaR Estimation Technologies: Python, pandas, NumPy, matplotlib, yfinance, SciPy
Discover
005/005
AI-Powered Intraday Market Making Strategy for Bitcoin Futures
Skills: Reinforcement Learning, Market Microstructure, Simulation, Deep Learning Technologies: Python, Stable-Baselines3, OpenAI Gym, NumPy, matplotlib
Discover