pedquant
(Public Economic Data and QUANTitative analysis) provides an interface to access public economic and financial data for economic research and quantitative analysis. The functions are grouped into three main categories,
The functions in this package are designed to write minimum codes for some common tasks in quantitative analysis process. Since the parameters to get data can be interactively specify, it’s very easy to start. The loaded data have been carefully cleansed and provided in a unified format.
pedquant
package has advantages on multiple aspects, such as the format of loaded data is a list of data frames, which can be easily manipulated in data.table or tidyverse packages; high performance on speed by using data.table and TTR; and interactive charts by using echarts4r. Similar works including tidyquant or quantmod.
pedquant
from CRAN with:install.packages("pedquant")
pedquant
from github with:::install_github("shichenxie/pedquant") devtools
The following examples show you how to import data.
library(pedquant)
## import eocnomic data
= ed_fred('GDPCA')
dat1 #> 1/1 GDPCA
= ed_nbs(geo_type='nation', freq='quarterly', symbol='A010101')
dat2
## import market data
= md_stock(c('FB', 'AMZN', 'AAPL', 'GOOG'), date_range = '10y')
FAAG #> 1/4 fb
#> 2/4 amzn
#> 3/4 aapl
#> 4/4 goog
= md_stock(c('^000001','^399001'), date_range = '10y')
INDX #> 1/2 ^000001
#> 2/2 ^399001
# moving average crossover strategy
library(data.table)
# load data
data("dt_banks")
= md_stock_adjust(setDT(dt_banks)[symbol=='601988.SS'])
dtboc # added technical indicators
= pq_addti(dtboc, x='close_adj', sma=list(n=200), sma=list(n=50))
bocti
# crossover signal
= copy(bocti[[1]])[,.(symbol, name, date, close_adj, sma_50, sma_200)
dtorders %x>% sma_200, `:=`(
][sma_50 type = 'buy', prices = close_adj
%x<% sma_200, `:=`(
)][sma_50 type = 'sell', prices = close_adj
order(date)
)][c('type', 'prices')) := lapply(.SD, shift), .SDcols = c('type', 'prices')]
][, (head(dtorders[!is.na(type)])
#> symbol name date close_adj sma_50 sma_200 type prices
#> 1: 601988.SS 中国银行 2009-04-27 2.175686 2.159212 2.154464 buy 2.169398
#> 2: 601988.SS 中国银行 2010-03-23 2.682837 2.685811 2.690783 sell 2.689302
#> 3: 601988.SS 中国银行 2010-05-06 2.618190 2.695508 2.694150 buy 2.669908
#> 4: 601988.SS 中国银行 2010-05-20 2.514756 2.677794 2.679346 sell 2.521220
#> 5: 601988.SS 中国银行 2011-04-27 2.332291 2.302393 2.299774 buy 2.318449
#> 6: 601988.SS 中国银行 2011-07-21 2.231820 2.285567 2.288007 sell 2.239067
# charting
= pq_plot(dtboc, y='close_adj', addti = list(sma=list(n=200), sma=list(n=50)), orders = dtorders[!is.na(type)])
e 1]]
e[[#> NULL
This package still on the developing stage. If you have any issue when using this package, please update to the latest version from github. If the issue still exists, report it at github page. Contributions in any forms to this project are welcome.