README.Rmd

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# fmpapi: An R package for interfacing with the Financial Modeling Prep API <img src='man/figures/logo.png' align="right" height="202.5" />

<!-- badges: start -->
[![CRAN status](https://www.r-pkg.org/badges/version/fmpapi)](https://CRAN.R-project.org/package=fmpapi)
[![Lifecycle: maturing](https://img.shields.io/badge/lifecycle-maturing-blue.svg)](https://www.tidyverse.org/lifecycle/#maturing)
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The goal of `fmpapi` is to provide a simple and consistent interface to the **Financial Modeling Prep** [Financial Data API](https://financialmodelingprep.com/) that can be used along side and integrated with other common R resources 
for collecting and analyzing financial data, such as `tidyquant`, `xts`, `TTR`, and `quantmod`.

## Installation

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You can install the latest development version of fmp from [Github](https://github.com) with:

``` r
remotes::install_github('jpiburn/fmpapi')
```

## Getting Started

Before getting started with `fmpapi` you first must obtain an API key for the Financial Modeling Prep Financial Data API. For details, see [here](https://financialmodelingprep.com/developer/docs/pricing/).

Once you sign up, you can add your API key to your `.Renviron` file by using `fmp_api_key()`. This will add a `FMP_API_KEY` entry to your `.Renviron` file so it will automatically be available in future sessions. When first installed however, you will need to reload your .Renviron file by either restarting R or running `readRenviron('~/.Renviron')`

```{r api-key, eval=FALSE}
library(fmpapi)

api_key <- 'my_api_key'
fmp_api_key(api_key)

# reload
readRenviron('~/.Renviron')
```


## Company Information and Financials

```{r company-info, message=FALSE, warning=FALSE}
library(fmpapi)
library(tidyverse)

my_stocks <- c("AAPL", "GE")

d <- fmp_profile(my_stocks)

glimpse(d)
```


## Discounted Cash Flow Valuation
```{r company-dcf, message=FALSE, warning=FALSE}

fmp_dcf(my_stocks, historical = TRUE, quarterly = TRUE) %>%
  ggplot(
    aes(x = date, y = dcf, colour = symbol)
    ) +
  geom_line(size = 1) +
  theme_minimal() +
  labs(
    title = "Historical Discounted Cash Flow Valuation",
    y = "Discounted Cash Flow Value"
  )
```


## Key Metrics
```{r key-metrics}
d <- fmp_key_metrics(my_stocks)

glimpse(d)
```

## Balance Sheets
```{r}
d <- fmp_balance_sheet(my_stocks, quarterly = TRUE)

glimpse(d)
```


## Form 13-F Statements
```{r}
berkshire_cik <- '0001067983'
d <- fmp_13f(berkshire_cik)

glimpse(d)
```

## Earnings Calendar
```{r}
d <- fmp_earnings_calendar()

glimpse(d)
```

## SEC RSS Feed
```{r}
d <- fmp_sec_filings()

glimpse(d)
```

## Quoting Cryptocurrencies
```{r}
d <- fmp_quote_cryptos()

glimpse(d)
```