Update 10-2021
I just update the function get_cefeF2() which using async request (from {crul} package). The new function seem to be way faster compare with the old get_cafeF().
# New
system.time(vnstockr::get_cafeF2("ACB", "1/1/2020", "1/1/2021"))
## user system elapsed
## 1.246 0.013 1.832
# Old
system.time(vnstockr::get_cafeF("ACB", "1/1/2020", "1/1/2021"))
## user system elapsed
## 1.162 0.146 14.703
Why
It is convenience to import stock data directly into R because there are multiple advance tools in R allow you to analyzing or run machine learning model with time series such as {modeltime} {fable}.
The{tidyquant} package made it simple by let user get stock data in Yahoo Finance to R in the “tidy” format. However, most of Vietnamese company does not listed in Yahoo Finance, hence user must manually download the data and import it into R before take advantage of R packages.
To automate this boring task, I write a simple package that allow user to get the Vietnam stock data from cafef.vn and vndirect.com.vn. This package is the wrap around of {httr} package which send request to these two data sources and parse the respond to R data frame (tibble).
You can browse the package source code here
Install
To install this package, use:
devtools::install_github("https://github.com/vohai611/vnstockr")
Usage
This package only contain two function get_cafeF() and get_vndirect(). User just need to specify stock code (symbol) and time frame. For example:
library(vnstockr)
acb <- get_vndirect('ACB', '1/5/2020', '1/5/2021')
acb |>
head(5)
## # A tibble: 5 × 25
## code date time floor type basicPrice ceilingPrice floorPrice open
## <chr> <date> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
## 1 ACB 2021-04-29 15:04:05 HOSE STOCK 33.8 36.2 31.4 33.8
## 2 ACB 2021-04-28 15:04:02 HOSE STOCK 34 36.4 31.6 33.5
## 3 ACB 2021-04-27 15:04:02 HOSE STOCK 33.3 35.6 31 33
## 4 ACB 2021-04-26 15:04:04 HOSE STOCK 33.4 35.7 31.1 33.4
## 5 ACB 2021-04-23 15:04:04 HOSE STOCK 32.5 34.8 30.2 32.4
## # … with 16 more variables: high <dbl>, low <dbl>, close <dbl>, average <dbl>,
## # adOpen <dbl>, adHigh <dbl>, adLow <dbl>, adClose <dbl>, adAverage <dbl>,
## # nmVolume <dbl>, nmValue <dbl>, ptVolume <dbl>, ptValue <dbl>, change <dbl>,
## # adChange <dbl>, pctChange <dbl>
Data retrieve are in the same “tidy” format as {tidyquant} package and could easily integrate with other R package quickly. For example, data could be visualized with ggplot2:
library(ggplot2)
library(plotly)
acb_plot <- acb |>
ggplot(aes(date, close))+
geom_line()+
scale_x_date(date_breaks = "4 weeks")+
theme_light()+
theme(axis.text.x = element_text(angle = 45, hjust =1))+
expand_limits(y = 0)+
labs(title = "ACB stock price from 1/5/2020 to 1/5/2021\n", x= NULL)
ggplotly(acb_plot) |>
config(displayModeBar = FALSE)
Note
get_cafeF() have to send multiple requests to cafef.vn, depend on the time frame user specified. Although I use {furrr} to send request in parallel but the the speed is much slower compare with get_vndirect() which is only send one request.