About

Background, methodology, and approach

Background

Quantitative researcher focused on options strategies, volatility analysis, and systematic equity research within the technology and semiconductor sectors.

This site serves as a personal research dashboard — aggregating portfolio analytics, options strategy tools, and industry mapping into a single interactive platform. All data is derived from pre-processed snapshots and public market data.

Core focus areas include AI infrastructure supply chain analysis, semiconductor capex cycle modeling, and volatility regime-based options portfolio construction.

Skills & Tools

Languages

PythonRTypeScriptSQLC++

Quant Tools

NumPy/PandasSciPystatsmodelsQuantLibBacktrader

ML/AI

PyTorchscikit-learnXGBoostLSTM/Transformers

Data & Viz

D3.jsMatplotlibPlotlyBloomberg TerminalRefinitiv

Platforms

Interactive BrokersBloombergAWSPostgreSQLRedis

Methodology

Statistical Arbitrage

Pairs trading and mean-reversion strategies using cointegration analysis, Kalman filters, and regime-switching models.

Volatility Modeling

GARCH family models, implied vs realized vol analysis, volatility surface fitting, and regime classification for options strategy selection.

Monte Carlo Simulation

Path-dependent option pricing, portfolio VaR/CVaR estimation, and scenario analysis with correlated asset dynamics.

Greeks Risk Management

Portfolio-level Greeks aggregation, delta-gamma-vega hedging, and theta decay optimization for multi-leg options books.

Scenario Analysis

Multi-scenario frameworks for equity positions with probability-weighted target prices, trigger conditions, and systematic entry/exit rules.

Supply Chain Mapping

Industry graph analysis for semiconductor/AI ecosystem, identifying chokepoints, revenue dependencies, and geopolitical risk concentrations.

Contact

For inquiries about research collaboration or methodology discussions, please reach out via the channels below.

Email — contact@example.comGitHub — github.com/usernameLinkedIn — linkedin.com/in/username