fml

An R-package of teaching financial machine learning

https://github.com/quinfer/fml

Keywords

Repository

An R-package of teaching financial machine learning

README.Rmd

---
output: github_document
---



```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# Financial machine learning



The goal of fml is to learning about the emerging field of financial machine learning and its application to algorithmic trading and investment.

This package contains templates for reports, and functions and workshops using in [*Algorithmic trading and investment*](https://canvas.qub.ac.uk/courses/11744)) taught by [Barry Quinn](https://quinference.com/) inb Queen's Management School. 

## Installation

Install/or reinstall the package from [GitHub](https://github.com/) using the following.

``` r
remove.packages('fml')
.rs.restartR()
remotes::install_github("quinfer/fml")
```

## Example

This is a basic example which shows you how to solve a common problem:

```{r example}
library(fml)
library(tidyverse)
## basic example code
fml::daily_factors %>% summary()
```
## Function test

```{r}
?fml::estRMT()
```


## Tutorials
**The tutorials can be run on a local machine only**.  You can start the tutorials in one of two ways. First, in RStudio 1.3 or later, you will find the ATI tutorials listed in the "Tutorial" tab in the top-right pane (by default). Find a tutorial and click "Run Tutorial" to get started. Second, you can run any tutorial from the R console by typing the following line: 

``` r
learnr::run_tutorial("Workshop2","fml")
```

This should bring up a tutorial in your default web browser. You can see the full list of tutorials by running:

``` r
learnr::run_tutorial(package = "fml")
```


## Critical Essay
This package also includes a RMarkdown template for use in the critical essay assessment.
Go to File>New>R Markdown... and choose from `From Template` then `Report`.

## Datasets
### FTSE 350 data
The package includes point in time FTSE350 data from 2016-2020, downloaded from Refinitiv Datastream for teaching purposes only. The data has been used to create two return series
1. A point in time Top 25 by average market value returns series
2. A current Top 30 by market capitalisation returns series


``` r
fml::ftse350
fml::ftse30_returns_mthly
fml::ftse25_rtns_mthly
```
### Daily uk asset pricing risk factors
These are created by Essex university business school and downloaded from UK Data Service API.

```r
fml::daily_factors"
```

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Quinn"
  given-names: "Barry"
  orcid: "https://orcid.org/0000-0002-8637-9060"
title: "Financial Machine Learning"
version: 2.0.4
doi: 10.5281/zenodo.6379925
date-released: 2020-12-18
url: "https://github.com/quinfer/fml"

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