index.md (2599B)
1 # FinanceRoutines.jl 2 3 *Some useful tools to work with academic financial data in Julia* 4 5 ## Introduction 6 7 This package provides a collection of routines for academic finance work. 8 It gives you a clean pipeline from raw WRDS data (CRSP, Compustat) through to standard research datasets, plus tools for Fama-French factors, treasury yield curves, portfolio construction, and data diagnostics. 9 10 File [issues](https://github.com/louloulibs/FinanceRoutines.jl/issues) for comments. 11 12 13 ## Installation 14 15 `FinanceRoutines.jl` is a registered package in the [`loulouJL`](https://github.com/LouLouLibs/loulouJL) registry. 16 You can install it via the Julia package manager: 17 18 ```julia 19 using Pkg 20 pkg"registry add https://github.com/LouLouLibs/loulouJL.git" 21 Pkg.add("FinanceRoutines") 22 ``` 23 24 Or install directly from GitHub: 25 ```julia 26 import Pkg 27 Pkg.add("https://github.com/louloulibs/FinanceRoutines.jl") 28 ``` 29 30 ## Usage 31 32 - WRDS (CRSP, Compustat) 33 + [WRDS User Guide](@ref) — download and merge CRSP/Compustat data 34 + [Transitioning to the new CRSP file format](@ref) — SIZ to CIZ migration 35 36 - Fama-French factors 37 + `import_FF3()` — 3-factor model (market, size, value) 38 + `import_FF5()` — 5-factor model (adds profitability, investment) 39 + `import_FF_momentum()` — momentum factor 40 + All support `:daily`, `:monthly`, `:annual` frequencies 41 42 - Treasury yield curves 43 + [Import Yield Curve Data](@ref) — GSW parameters, yields, prices, bond returns 44 45 - Portfolio analytics 46 + `calculate_portfolio_returns` — equal/value-weighted returns with optional grouping 47 + `calculate_rolling_betas` — rolling window factor regressions 48 + `event_study` — CARs and BHARs with market-adjusted, market model, or mean-adjusted methods (experimental) 49 + `diagnose` — missing rates, duplicates, suspicious values 50 51 - Demos 52 + [Estimating Stock Betas](@ref) — unconditional and rolling betas 53 + [Advanced WRDS](@ref) — custom Postgres queries 54 55 ## Other Resources 56 57 There are multiple online resources on using the WRDS Postgres database and build the standard finance and accounting datasets: 58 59 - Ian D. Gow and Tony Ding: *"Empirical Research in Accounting: Tools and Methods"*; available [here](https://iangow.github.io/far_book/) 60 - Chen, Andrew Y. and Tom Zimmermann: *"Open Source Cross-Sectional Asset Pricing"*; 2022, 27:2; available [here](https://www.openassetpricing.com/code/) 61 - Christoph Scheuch, Stefan Voigt, Patrick Weiss: *"Tidy Finance with R"*; 2023; Chapman & Hall; available [here](https://www.tidy-finance.org/r/) 62 63 64 65 ## Index 66 67 ```@index 68 ```