A collection of quantitative analysis scripts for financial market research, strategy development, and automated checks, built using R and Python.
This repository focuses on applying computational methods to financial data, emphasizing empirical testing and data-driven investment decision support.
The scripts contained here cover key areas of algorithmic finance:
| Focus Area | Description | Implementation Example |
|---|---|---|
| Strategy Backtesting | Systematic evaluation of trading rules and performance across historical data. | trading_strategies_backtest.R |
| Market Screening | Automated financial checks, such as analyzing stock metrics like Market Capitalization, for investment viability. | Inv201.02_Mrk_Cap_Check_PY.V.01.py |
| Economic Visualization | Data handling and plotting to analyze macro-level trends or global market relationships. | worldpicture.R |
| Investment Style | Projects follow a Value Investing methodology (as tagged on GitHub). |
- Primary Languages: R (77%) and Python (23%).
- Key Skills: Data retrieval, statistical modeling, algorithmic logic, and cross-language development.