Tidy Finance Helper Functions
Add Lagged Versions of Columns to a Data Frame
Assign Portfolios Based on Sorting Variable
Create Breakpoint Options for Portfolio Sorting
Check if a Dataset Type is Supported
Compute Breakpoints Based on Sorting Variable
Compute Long-Short Returns
Compute Portfolio Returns
Create Summary Statistics for Specified Variables
Create WRDS Dummy Database
Create Data Options
Disconnect Database Connection
Download Constituent Data
Download and Process Fama-French Factor Data
Download and Process Global Q Factor Data
Download and Process Factor Data
Download and Process Data from FRED
Download and Process Macro Predictor Data
Download and Process Open Source Asset Pricing Data
Download Stock Data
Download CCM Links from WRDS
Download Data from WRDS Compustat
Download Data from WRDS CRSP
Download Filtered FISD Data from WRDS
Download Enhanced TRACE Data from WRDS
Download Data from WRDS
Download and Process Data Based on Type
Estimate Rolling Betas
Estimate Fama-MacBeth Regressions
Estimate Model Coefficients
Get a Random User Agent
Establish a Connection to the WRDS Database
Lag a Column Based on Date and Time Range
List Supported Indexes
List Supported Legacy Fama-French Dataset Types
List Supported Fama-French Dataset Types
List Supported Macro Predictor Dataset Types
List Supported Other Data Types
List Supported Global Q Dataset Types
List Supported WRDS Dataset Types
List All Supported Dataset Types
List Chapters of Tidy Finance
Open Tidy Finance Website or Specific Chapter in Browser
Set WRDS Credentials
tidyfinance: Tidy Finance Helper Functions
Trim a Numeric Vector
Winsorize a Numeric Vector
Helper functions for empirical research in financial economics, addressing a variety of topics covered in Scheuch, Voigt, and Weiss (2023) <doi:10.1201/b23237>. The package is designed to provide shortcuts for issues extensively discussed in the book, facilitating easier application of its concepts. For more information and resources related to the book, visit <https://www.tidy-finance.org/r/index.html>.
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