The tidyquant package provides tools and data for visualizing and analysing equities. Here is an example using data from EXPO.
dat <- tq_get(toString(params$ticker))
dat %>% ggplot(aes(x = date, y = close)) +
geom_barchart(aes(open = open, high = high, low = low, close = close)) +
labs(title = paste(params$ticker,"Bar Chart"), y = "Closing Price", x = "") +
theme_tq()
Or functions of the data, like returns.
dat.new <- dat %>% tq_transmute(select= adjusted,
mutate_fun = periodReturn,
period = "daily",
col_rename = "Ra") %>% as_tsibble(index=date)
dat.new %>% autoplot()
The following are a few quick interactive plots.
library(tidyquant)
library(tidyverse)
library(magrittr)
# Use tidyquant to get the data
# Slice off the most recent 120 days
dat.tail <- tail(dat, 120)
dat.tail %<>% mutate(
open = round(open, digits=2),
close = round(close, digits=2),
high = round(high, digits=2),
low = round(low, digits=2),
adjusted = round(adjusted, digits=2)
)Let’s have a look at the data.
library(DT)
datatable(dat.tail)There are a few charts specifically designed for OHLC data that are included in plotly. Here I want to deploy a basic one with one modification. I want daily increases in black and daily decreases in red.
library(plotly)
# basic example of ohlc charts
# custom colors
i <- list(line = list(color = '#000000')) # black
d <- list(line = list(color = '#FF0000')) # red
# Create the figure
fig.2 <- dat.tail %>%
plot_ly(x = ~date, type="ohlc",
open = ~open, close = ~close,
high = ~high, low = ~low,
increasing = i, decreasing = d)
fig.2ggplot candlestickdat %>%
ggplot(aes(x = date, y = close)) +
geom_candlestick(aes(open = open, high = high, low = low, close = close)) +
labs(title = paste0(params$ticker," Candlestick Chart", sep=""), y = "Closing Price", x = "") +
theme_tq()
dat %>%
ggplot(aes(x = date, y = close)) +
geom_barchart(aes(open = open, high = high, low = low, close = close)) +
geom_ma(ma_fun = EMA, n = 50, wilder = TRUE, linetype = 5, size = 1.25) +
geom_ma(ma_fun = EMA, n = 200, wilder = TRUE, color = "red", size = 1.25) +
labs(title = paste0(dat$symbol," Bar Chart", sep=""),
subtitle = "50 and 200-Day EMA",
y = "Closing Price", x = "") +
coord_x_date() +
theme_tq()