Advanced Econometric Analysis Tools
Project description
Econkit
Introduction
Econkit is a comprehensive Python library designed for economic and financial data analysis. It offers a wide range of functionalities, from descriptive statistics to advanced portfolio analysis, making it a valuable tool for economists, financial analysts, and researchers.
Installation
pip install econkit
Features
Econkit provides the following functionalities:
Descriptives Function
Perform comprehensive statistical analysis on a DataFrame, computing various descriptive statistics for each numeric column.
Correlation Function
Compute correlation matrices between numerical columns in a DataFrame. Supports Pearson and Spearman methods and provides significance levels.
Stock Function
Download and process stock data from Yahoo Finance, including the computation of percentage growth of the Adjusted Close price.
Table Function
Facilitate the comparison of a specific column across multiple DataFrames by extracting and combining them into a new DataFrame.
Weights Function
Generate portfolio weights for a collection of stocks, creating multiple portfolios with full weight in one stock and additional portfolios with random weights.
Portfolios Function
Calculate the expected return and volatility of various portfolios based on their weight allocations and stock returns.
Frontier Simple Function
Visualize the mean-variance frontier from portfolio data and highlight the portfolio with minimum volatility.
Usage
Below are basic usage examples for each function in Econkit:
Descriptives
# result = descriptives(your_dataframe)
# print(result)
Correlation
# correlation(your_dataframe, method="Pearson", p="F")
Stock
# stock_data = stock("ticker_symbol", "start_date", "end_date", "interval")
Table
# combined_df = table("column_name", dataframe1, dataframe2, ...)
# print(combined_df)
Weights
# weights_df = weights(stocks, extra)
Portfolios
# portfolio_metrics = portfolios(weights_df, returns_df, 'daily')
# print(portfolio_metrics)
Frontier Simple
# frontier_simple(your_dataframe)
Contributing
Contributions to the Econkit library are welcome. Please refer to the contributing guidelines for more information.
License
Econkit is licensed under the MIT License.
Contact
For inquiries or support, please contact contact@stefanstavrianos.eu.
Project details
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