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This Tortoise is in Hibernation for indefinite time (Not Avaliable)
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This Tortoise is in Hibernation for indefinite time (Not Avaliable)
356 followers · 0 following
  • Citadel
  • NEW YORK, NY
  • 09:14 (UTC -04:00)

Achievements

Achievement: Starstruckx3Achievement: Pull Shark

Achievements

Achievement: Starstruckx3Achievement: Pull Shark

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Organizations

@collective @NVIDIAGameWorks @dwyl @zero-to-mastery @github-craftwork @EddieHubCommunity @MakeContributions

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shsarv/README.md

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⚠️Info: This Tortoise 🐢 is in Hibernation for Indefinite Time⚠️

👨‍💻 About Me

Hello, I'm a Quantitative Researcher and former Data Scientist with an M.S. in Data Science from the University of Illinois , building systematic strategies at the intersection of statistical theory, machine learning, and market microstructure. My work spans factor model construction, stochastic volatility modeling, and ML-driven signal research, with one consistent obsession: extracting durable edge from structure that others mistake for noise.

My background bridges both worlds production-grade data science across Transformer models, large-scale NLP, and deep learning systems, grounded in the mathematical foundations that quantitative research demands. The combination shapes how I think: rigorously about markets, and practically about the systems built to trade them.

Current research:
  • regime-conditioned factor models, RL-based execution
  • optimization, and Transformer architectures on high-frequency financial sequences.
I don't optimize for impressive backtests. I optimize for strategies that survive.

🔬 Core Research Areas

📊 Quantitative Finance

  • Statistical Arbitrage & Pairs Trading
  • Factor Model Construction (Fama-French, PCA)
  • Derivatives Pricing — Monte Carlo, Finite Difference
  • Portfolio Optimization (Black-Litterman, Kelly)
  • Regime Detection & Hidden Markov Models
  • Volatility Surface Modeling & Term Structure

🤖 Machine Learning & AI

  • Reinforcement Learning — PPO, MADDPG
  • Transformers on sequential financial data
  • Graph Neural Networks for market structure
  • Explainable AI — SHAP, LIME, XAI frameworks
  • NLP on alternative data (earnings calls, filings)
  • Causal Inference for strategy validation
🧰 Tech Stack

Python C++ R Julia SQL MATLAB QuantLib CVXPY statsmodels ARCH PyPortfolioOpt Zipline Backtrader PyTorch TensorFlow scikit-learn XGBoost LightGBM CatBoost Optuna HuggingFace LangChain OpenAI FAISS spaCy NumPy SciPy Pandas Matplotlib Seaborn Plotly Spark Kafka Airflow dbt Redis PostgreSQL MongoDB AWS GCP Docker Kubernetes Git Linux React TypeScript Django Flask
📊 GitHub Stats

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