The IBKR Quant Blog helps quantitative professionals understand how R, Python, IBKR API, AI, Blockchain and other technologies are transforming financial markets. Here are some of the February 2023 highlights:
- Can ChatGPT Self-Improve Self-Written Python Code for Cholesky Decomposition? – Quant at Risk. Dr. Pawel Lachowicz from Quant at Risk explores if ChatGPT can be used for writing Python code for financial applications.
- Equity & Bond Correlations – Higher than Assumed? – Finominal. Nicolas Rabener, Founder and CEO of Finominal, shares insights on S&P 500’s correlations with other markets on both a daily and monthly return basis.
- How to Deal With Missing Financial Data – Quantpedia. See their review of a novel research paper that focuses on missing financial data.
- Guide to Fuzzy Matching with Python – TheAutomatic.net. Andrew Treadway demonstrates the textdistance package, which is used for fuzzy matching.
- NYED Data Explorer Shows 15 Years of Charter School Success – Redwall Analytics. David Lucey, Founder, Redwall Analytics, offers insights on using NYED Data Explorer and charter school success.
- Nonfarm Payrolls January 2023 – Total Wealth Partners. Will Klinke, Principal at the firm, analyzes the Nonfarm Payrolls January 2023 data.
- Python Troubleshooting Q&A SH Fintech Modeling – SH Fintech Modeling. Sang-Heon Lee delivers a collection of common error messages in Python.
- Applied Finance with R 2023 – Interactive Brokers. Learn more about this annual event, which is run by R programming language enthusiasts in Chicago.
- Jupyter Notebook Tutorial: Installation, Components and Magic Commands QuantInsti. Find out how to install and run Jupyter Notebook with this series of tutorials contributed by Jay Parmar.
Visit the IBKR Quant Blog main page to see all of the February 2023 articles.
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