tidyquant::tq_get
Damian Senesac
2022-09-20
# Load Packages
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## ✔ readr 2.1.2 ✔ forcats 0.5.2
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## Loading required package: quantmod
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## as.zoo.data.frame zooStock Index
tq_index_options()## [1] "DOW" "DOWGLOBAL" "SP400" "SP500" "SP600"data <- tq_index("SP400")## Getting holdings for SP400Stock Exchanges
tq_exchange_options()## [1] "AMEX" "NASDAQ" "NYSE"data_NYSE <- tq_exchange("NYSE")## Getting data...tq_get
Stock prices from Yahoo Finance
stock <- tq_get("TSLA")Economic data from FRED
unemployment_nh <- tq_get("NHUR", get = "economic.data")Charts
Prerequsites
data("FANG") AAPL <- tq_get("AAPL", get = "stock.prices", from = "2015-09-01", to = "2016-12-31")
AMZN <- tq_get("AMZN", get = "stock.prices", from = "2000-01-01", to = "2016-12-31")end <- as_date("2016-12-31")aapl_range_60_tbl <- AAPL %>%
tail(60) %>%
summarise(
max_high = max(high),
min_low = min(low)
)Chart Types
Line Chart
AAPL %>%
ggplot(aes(x = date, y = close)) +
geom_line() +
labs(title = "AAPL Line Chart", y = "Closing Price", x = "") +
theme_tq()
### Bar Chart
AAPL %>%
ggplot(aes(x = date, y = close)) +
geom_barchart(aes(open = open, high = high, low = low, close = close)) +
labs(title = "AAPL Bar Chart", y = "Closing Price", x = "") +
theme_tq()
AAPL %>%
ggplot(aes(x = date, y = close)) +
geom_barchart(aes(open = open, high = high, low = low, close = close)) +
labs(title = "AAPL Bar Chart",
subtitle = "Zoomed in using coord_x_date",
y = "Closing Price", x = "") +
coord_x_date(xlim = c(end - weeks(6), end),
ylim = c(aapl_range_60_tbl$min_low, aapl_range_60_tbl$max_high)) +
theme_tq()
AAPL %>%
ggplot(aes(x = date, y = close)) +
geom_barchart(aes(open = open, high = high, low = low, close = close),
colour_up = "darkgreen", colour_down = "darkred", size = 1) +
labs(title = "AAPL Bar Chart",
subtitle = "Zoomed in, Experimenting with Formatting",
y = "Closing Price", x = "") +
coord_x_date(xlim = c(end - weeks(6), end),
c(aapl_range_60_tbl$min_low, aapl_range_60_tbl$max_high)) +
theme_tq()
### Candlestick Chart
AAPL %>%
ggplot(aes(x = date, y = close)) +
geom_candlestick(aes(open = open, high = high, low = low, close = close)) +
labs(title = "AAPL Candlestick Chart", y = "Closing Price", x = "") +
theme_tq()
AAPL %>%
ggplot(aes(x = date, y = close)) +
geom_candlestick(aes(open = open, high = high, low = low, close = close)) +
labs(title = "AAPL Candlestick Chart",
subtitle = "Zoomed in using coord_x_date",
y = "Closing Price", x = "") +
coord_x_date(xlim = c(end - weeks(6), end),
c(aapl_range_60_tbl$min_low, aapl_range_60_tbl$max_high)) +
theme_tq()
AAPL %>%
ggplot(aes(x = date, y = close)) +
geom_candlestick(aes(open = open, high = high, low = low, close = close),
colour_up = "darkgreen", colour_down = "darkred",
fill_up = "darkgreen", fill_down = "darkred") +
labs(title = "AAPL Candlestick Chart",
subtitle = "Zoomed in, Experimenting with Formatting",
y = "Closing Price", x = "") +
coord_x_date(xlim = c(end - weeks(6), end),
c(aapl_range_60_tbl$min_low, aapl_range_60_tbl$max_high)) +
theme_tq()
### Charting Multiple Securities
start <- end - weeks(6)
FANG %>%
filter(date >= start - days(2 * 15)) %>%
ggplot(aes(x = date, y = close, group = symbol)) +
geom_candlestick(aes(open = open, high = high, low = low, close = close)) +
labs(title = "FANG Candlestick Chart",
subtitle = "Experimenting with Mulitple Stocks",
y = "Closing Price", x = "") +
coord_x_date(xlim = c(start, end)) +
facet_wrap(~ symbol, ncol = 2, scale = "free_y") +
theme_tq()
start <- end - weeks(6)
FANG %>%
filter(date >= start - days(2 * 15)) %>%
ggplot(aes(x = date, y = close, group = symbol)) +
geom_candlestick(aes(open = open, high = high, low = low, close = close)) +
geom_ma(ma_fun = SMA, n = 15, color = "darkblue", size = 1) +
labs(title = "FANG Candlestick Chart",
subtitle = "Experimenting with Mulitple Stocks",
y = "Closing Price", x = "") +
coord_x_date(xlim = c(start, end)) +
facet_wrap(~ symbol, ncol = 2, scale = "free_y") +
theme_tq()
## Visualizing Trends ### Moving Averages
AAPL %>%
ggplot(aes(x = date, y = close)) +
geom_candlestick(aes(open = open, high = high, low = low, close = close)) +
geom_ma(ma_fun = SMA, n = 50, linetype = 5, size = 1.25) +
geom_ma(ma_fun = SMA, n = 200, color = "red", size = 1.25) +
labs(title = "AAPL Candlestick Chart",
subtitle = "50 and 200-Day SMA",
y = "Closing Price", x = "") +
coord_x_date(xlim = c(end - weeks(24), end),
c(aapl_range_60_tbl$min_low * 0.9, aapl_range_60_tbl$max_high)) +
theme_tq()
start <- end - weeks(6)
FANG %>%
filter(date >= start - days(2 * 50)) %>%
ggplot(aes(x = date, y = close, volume = volume, group = symbol)) +
geom_candlestick(aes(open = open, high = high, low = low, close = close)) +
geom_ma(ma_fun = VWMA, n = 15, wilder = TRUE, linetype = 5) +
geom_ma(ma_fun = VWMA, n = 50, wilder = TRUE, color = "red") +
labs(title = "FANG Bar Chart",
subtitle = "50 and 200-Day EMA, Experimenting with Multiple Stocks",
y = "Closing Price", x = "") +
coord_x_date(xlim = c(start, end)) +
facet_wrap(~ symbol, ncol = 2, scales = "free_y") +
theme_tq()
### Bollinger Bands
AAPL %>%
ggplot(aes(x = date, y = close, open = open,
high = high, low = low, close = close)) +
geom_candlestick() +
geom_bbands(ma_fun = SMA, sd = 2, n = 20) +
labs(title = "AAPL Candlestick Chart",
subtitle = "BBands with SMA Applied",
y = "Closing Price", x = "") +
coord_x_date(xlim = c(end - weeks(24), end),
ylim = c(aapl_range_60_tbl$min_low * 0.85,
aapl_range_60_tbl$max_high) * 1.05) +
theme_tq()
AAPL %>%
ggplot(aes(x = date, y = close, open = open,
high = high, low = low, close = close)) +
geom_candlestick() +
geom_bbands(ma_fun = SMA, sd = 2, n = 20,
linetype = 4, size = 1, alpha = 0.2,
fill = palette_light()[[1]],
color_bands = palette_light()[[1]],
color_ma = palette_light()[[2]]) +
labs(title = "AAPL Candlestick Chart",
subtitle = "BBands with SMA Applied, Experimenting with Formatting",
y = "Closing Price", x = "") +
coord_x_date(xlim = c(end - weeks(24), end),
ylim = c(aapl_range_60_tbl$min_low * 0.85,
aapl_range_60_tbl$max_high) * 1.05) +
theme_tq()
start <- end - weeks(24)
FANG %>%
filter(date >= start - days(2 * 20)) %>%
ggplot(aes(x = date, y = close,
open = open, high = high, low = low, close = close,
group = symbol)) +
geom_barchart() +
geom_bbands(ma_fun = SMA, sd = 2, n = 20, linetype = 5) +
labs(title = "FANG Bar Chart",
subtitle = "BBands with SMA Applied, Experimenting with Multiple Stocks",
y = "Closing Price", x = "") +
coord_x_date(xlim = c(start, end)) +
facet_wrap(~ symbol, ncol = 2, scales = "free_y") +
theme_tq()
## ggplot2 Functionality
AMZN %>%
ggplot(aes(x = date, y = adjusted)) +
geom_line(color = palette_light()[[1]]) +
scale_y_continuous() +
labs(title = "AMZN Line Chart",
subtitle = "Continuous Scale",
y = "Closing Price", x = "") +
theme_tq()
AMZN %>%
ggplot(aes(x = date, y = adjusted)) +
geom_line(color = palette_light()[[1]]) +
scale_y_log10() +
labs(title = "AMZN Line Chart",
subtitle = "Log Scale",
y = "Closing Price", x = "") +
theme_tq()
AMZN %>%
ggplot(aes(x = date, y = adjusted)) +
geom_line(color = palette_light()[[1]]) +
scale_y_log10() +
geom_smooth(method = "lm") +
labs(title = "AMZN Line Chart",
subtitle = "Log Scale, Applying Linear Trendline",
y = "Adjusted Closing Price", x = "") +
theme_tq()## `geom_smooth()` using formula 'y ~ x'
AMZN %>%
ggplot(aes(x = date, y = volume)) +
geom_segment(aes(xend = date, yend = 0, color = volume)) +
geom_smooth(method = "loess", se = FALSE) +
labs(title = "AMZN Volume Chart",
subtitle = "Charting Daily Volume",
y = "Volume", x = "") +
theme_tq() +
theme(legend.position = "none")## `geom_smooth()` using formula 'y ~ x'
start <- end - weeks(24)
AMZN %>%
filter(date >= start - days(50)) %>%
ggplot(aes(x = date, y = volume)) +
geom_segment(aes(xend = date, yend = 0, color = volume)) +
geom_smooth(method = "loess", se = FALSE) +
labs(title = "AMZN Bar Chart",
subtitle = "Charting Daily Volume, Zooming In",
y = "Volume", x = "") +
coord_x_date(xlim = c(start, end)) +
scale_color_gradient(low = "red", high = "darkblue") +
theme_tq() +
theme(legend.position = "none")## `geom_smooth()` using formula 'y ~ x'
## Themes
n_mavg <- 50 # Number of periods (days) for moving average
FANG %>%
filter(date >= start - days(2 * n_mavg)) %>%
ggplot(aes(x = date, y = close, color = symbol)) +
geom_line(size = 1) +
geom_ma(n = 15, color = "darkblue", size = 1) +
geom_ma(n = n_mavg, color = "red", size = 1) +
labs(title = "Dark Theme",
x = "", y = "Closing Price") +
coord_x_date(xlim = c(start, end)) +
facet_wrap(~ symbol, scales = "free_y") +
theme_tq_dark() +
scale_color_tq(theme = "dark") +
scale_y_continuous(labels = scales::dollar)