R/trade_trend.R

In skylics/stock_analysis: Predict how price of specific financial asset will change.

#' Buying and Sell trend of foreign and organization
#'
#' \code{trade_trend} returns data frame of trading trends
#'
#' @param ticker a ticker code in the format as "000000" (use find_code())
#' @param from should be given as a format "2011-01-01"
#'
#' @return a data frame
#' @export
#'
#' @examples
#' find_code("stockname") %>% trade_trend("2015-01-01")
trade_trend <- function(ticker, from) {

  library(XML, quietly = TRUE)
  library(stringr, quietly = TRUE)

  theurl <- paste("http://finance.daum.net/item/foreign_yyyymmdd.daum?page=1&code=", ticker, sep = "")
  volumn_html <- readHTMLTable(theurl)
  volumn_table <- volumn_html[[1]][c(2:6, 9:13, 16:20, 23:27, 30:34, 37:41), c(1:5)]
  names(volumn_table) <- c("date", "fore_total", "fore_perc", "fore_buy", "org_buy")
  volumn_table$date <- paste("20", volumn_table$date, sep = "") %>% as.character %>% stringr::str_replace_all(fixed("."), "-") %>% as.Date

  i <- 1

  while (ifelse(is.na(volumn_table$date[nrow(volumn_table)]), FALSE, volumn_table$date[nrow(volumn_table)] > from)) {
    i <- i + 1
    url <- paste("http://finance.daum.net/item/foreign_yyyymmdd.daum?page=", i, "&code=", ticker, sep = "")
    html <- readHTMLTable(url)
    table <- html[[1]][c(2:6, 9:13, 16:20, 23:27, 30:34, 37:41), c(1:5)]
    names(table) <- c("date", "fore_total", "fore_perc", "fore_buy", "org_buy")
    table$date <- paste("20", table$date, sep = "") %>% as.character %>%  str_replace_all(fixed("."), "-") %>% as.Date
    volumn_table <- rbind(volumn_table, table)
  }

  final_table <- volumn_table %>% (function(df) {df %>% complete.cases %>% df[., ]}) %>%
    (function(df2) {(df2$date >= from) %>% df2[., ]})
  final_table[, c(2, 4, 5)] <- final_table[, c(2, 4, 5)] %>%
    apply(2, function(df) {df %>% stringr::str_replace_all(",", "") %>% as.numeric})
  final_table[, 3] <- (final_table[, 3] %>% as.character %>% str_replace_all("%", "") %>% str_replace_all(fixed("."), "") %>% as.numeric)/10000
  final_table$total <- final_table$fore_total/final_table$fore_perc
  final_table[final_table %>% complete.cases, c("date", "fore_total", "fore_perc", "fore_buy", "org_buy")]

}