https://github.com/tbeason/financialportfolios.jl

Julia package for working with simple portfolios of financial assets
https://github.com/tbeason/financialportfolios.jl

finance julia julialang portfolio-management

Last synced: 6 months ago
JSON representation

Julia package for working with simple portfolios of financial assets

• Host: GitHub
• URL: https://github.com/tbeason/financialportfolios.jl
• Owner: tbeason
• License: other
• Created: 2020-04-30T06:47:16.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2022-01-12T16:18:09.000Z (almost 4 years ago)
• Last Synced: 2025-05-07T04:02:40.988Z (6 months ago)
• Topics: finance, julia, julialang, portfolio-management
• Language: Julia
• Homepage:
• Size: 18.6 KB
• Stars: 4
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.md

Awesome Lists containing this project

README

          
# FinancialPortfolios.jl

![Lifecycle](https://img.shields.io/badge/lifecycle-experimental-orange.svg)

[![build](https://github.com/tbeason/FinancialPortfolios.jl/workflows/CI/badge.svg)](https://github.com/tbeason/FinancialPortfolios.jl/actions?query=workflow%3ACI)

[![codecov.io](http://codecov.io/github/tbeason/FinancialPortfolios.jl/coverage.svg?branch=master)](http://codecov.io/github/tbeason/FinancialPortfolios.jl?branch=master)

A minimalist Julia package for working with simple portfolios of financial assets. Really only provides the barebones.

### Example

Example without rebalancing.

```julia

using FinancialPortfolios, DataFrames, Dictionaries

stockA = 0.06/12 .+ 0.1/sqrt(12) .* randn(120)

stockB = 0.01/12 .+ 0.02/sqrt(12) .* randn(120)

df = DataFrame(stockA=stockA,stockB=stockB)

FP = FinancialPortfolio(dictionary(["stockA"=>0.8,"stockB"=>0.2]))  # initial portfolio weights

df.portfolioreturns = [update!(FP,r) for r in eachrow(df)]

df

FP

```

Example with rebalancing every January.

```julia

using FinancialPortfolios, DataFrames, Dictionaries

months = repeat(1:12,10)

stockA = 0.06/12 .+ 0.1/sqrt(12) .* randn(120)

stockB = 0.01/12 .+ 0.02/sqrt(12) .* randn(120)

df = DataFrame(month=months,stockA=stockA,stockB=stockB)

FP = FinancialPortfolio(dictionary(["stockA"=>0.8,"stockB"=>0.2]))  # initial portfolio weights

function runportfolio!(FP0,df0)

    T = nrow(df0)

    df0[!,:portfolioreturns] = missings(Float64,T)

    FPreb = copy(FP0)

    

    for row in eachrow(df0)

        if row.month == 1   # rebalances each January

            FP0 = copy(FPreb)

        end

        row.portfolioreturns = update!(FP0,row)

    end

    return FP0

end

runportfolio!(FP,df)

```