Best ChatGPT prompts for Financial and Investment Analysts

Create a Python script using scikit-learn and pandas to develop a linear regression model that predicts stock prices based on historical data, including daily highs, lows, and trading volumes, and evaluate its performance using mean squared error and R-squared metrics, considering factors such as data normalization, feature scaling, and hyperparameter tuning.

Design an ETL pipeline using SQL and Snowflake to extract financial data from various sources, including transactional databases and external APIs, transform it into a standardized format, and load it into a data warehouse for analysis and reporting, ensuring data quality, handling errors, and optimizing query performance.

Generate a statistical summary of a portfolio's performance using Python and Tableau, including metrics such as return on investment, Sharpe ratio, and Value-at-Risk, and visualize the results using interactive dashboards and charts, allowing for drill-down analysis and what-if scenario planning.

Develop a data cleaning script using Python and pandas to preprocess financial statement data, including income statements, balance sheets, and cash flow statements, handling missing values, outliers, and inconsistencies, and generating a cleaned dataset for subsequent analysis and modeling.