Hey, I’m Samanvay
Welcome to my personal website! I am a Graduate Student in Financial Engineering at the University of Illinois Urbana-Champaign. With a strong foundation in Machine Learning and Quantitative Finance, I am deeply passionate about leveraging technology and data-driven techniques to find innovative solutions for problems in Finance, Trading and other data-Intensive fields.
Skills and Interests
Machine Learning and Artificial intelligence
- Regression and Classification :- Linear Regression, Logistic Regression, Lasso Regression, Ridge Regression
- Decision Trees and Ensemble Learning (Bagging and Boosting) :- Decision Trees, Random Forests, Gradient Boosting, AdaBoost, XGBoost
- Clustering and Dimensionality Reduction :- K-Means Clustering, Hierarchical Clustering, PCA, t-SNE, LDA
- Natural Language Processing :- Text Preprocessing, Text Classification, Sentiment Analysis, Word Embeddings, Word to Vec
- Deep Learning :- Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, LSTM, GRU, Transformers
- Generative AI :- Variational Autoencoders, Generative Adversarial Networks
- Reinforcement Learning :- Q-Learning, Deep Q-Learning, Policy Gradient Methods, Actor-Critic Methods, DQN, DDPG, PPO
Big Data and Cloud Computing
- Data Techniques :- Data Cleaning, Data Preprocessing, Data Visualization, Exploratory Data Analysis, ETL Pipelines, MapReduce
- Cloud Computing :- AWS, Google Cloud, Azure
- Big Data Technologies :- Hadoop, Airflow, Kafka, Spark
- Databases :- SQL, NoSQL (MongoDB, MySQL, PostgreSQL, MS SQL Server, sqlite)
- Data Warehousing :- Snowflake, Redshift, BigQuery, Databricks
- CI/CD Pipelines :- Jenkins, Cloud Run
Econometric and Statistical Analysis
- Time Series Analysis :- ARIMA, SARIMA, Seasonal Decomposition, Exponential Smoothing, GARCH, Sequence Models
- Statistical Inference :- Hypothesis Testing, Confidence Intervals, ANOVA, Chi-Square Tests, Goodness of Fit Tests, Correlation Analysis
- Game Theory :- Nash Equilibrium, Auction Theory, Mechanism Design, Mean Field Games, Evolutionary Game Theory, Cooperative Game Theory, Stochastic Games, Strategic Learning
Quantitative Finance and Algorithmic Trading
- Financial Modeling :- CAPM, Fama-French Model, Black-Scholes Model, Binomial Option Pricing Model, Monte Carlo Simulation, Interest Rate Modelling , Implied Volatility Surface Modelling
- Financial Derivatives :- Options, Futures, Swaps, Forwards, Interest Rate Derivatives, Mortage-Backed Securities, Credit Derivatives
- Risk Management :- Value at Risk, Conditional Value at Risk, Stress Testing, Backtesting, Risk Parity, Portfolio Optimization
- Algorithmic Trading :- Momentum Trading, Mean Reversion Trading, Pairs Trading, Statistical Arbitrage, Market Making, High-Frequency Trading, Sentiment Analysis
- Quantitative skills :- Stochastic Calculus, Portfolio Management, Market Microstructure, Numerical methods, Trading Sytems Design, Financial Machine Learning
Research Interests:-
- Fractal Geometry in Finance :- Fractal Time Series Analysis with BPE Tokenizers for Improved Montecarlo Asset Pricing.
- Reinforcement Learning Trading Strategies :- Deep Reinforcement Learning for Portfolio Optimization and medium and high frequency trading.
- Mean Field Games in Finance :- Mean Field Games for Optimal Portfolio Allocation and Investing Strategies.
- Generative AI for Finance :- Generative Adversarial Networks for Synthetic Data Generation in Finance and Trading.