In yunching/tidymas: A collection of RMD utilities
library(tidyverse)
library(tidymas)
# library(Rblpapi)
library(zoo)
library(devtools)
library(gridExtra)
library(knitr)
# blpConnect()
# Downloads data from BBG - Yun Ching
# sec_list <- c("RX1 Comdty", "G 1 Comdty", "IK1 Comdty", "OAT1 Comdty",
# "ES1 Index", "VG1 Index", "Z 1 Index",
# "TY1 Comdty")
# bbg_data_raw <- bdh(sec_list, c("PX_OPEN", "PX_HIGH", "PX_LOW", "PX_LAST", "Volume"), start.date = Sys.Date() - 1095)
#
# bbg_data_raw %>%
# bind_rows(.id = "Ticker") %>%
# as_tibble() %>%
# na.omit ->
# bbg_data
# load_bbg_data(dbname = "../../inst/extdata/mydatabase.db")
load_db(dbname = "../../inst/extdata/mydatabase.db") %>%
mutate(Date = lubridate::as_date(date)) %>%
select(Ticker, Date, PX_OPEN, PX_HIGH, PX_LOW, PX_LAST, VOLUME) %>%
filter(Ticker %in% c("RX1 Comdty", "G 1 Comdty", "IK1 Comdty", "OAT1 Comdty", "ES1 Index", "VG1 Index", "Z 1 Index", "TY1 Comdty")) %>%
filter(Date >= Sys.Date() - 1095) %>%
rename(date = Date, Volume = VOLUME) %>%
# bind_rows(.id = "Ticker") %>%
as_tibble() %>%
na.omit ->
bbg_data2
#Calculate analytics - Stanley Neo
# bbg_data %>%
# group_by(Ticker) %>%
# nest() %>%
# mutate(ewma_10 = map_dbl(data, ~ tail(ema(.x$PX_LAST, 10), 1)),
# ewma_20 = map(data, ~ ema(.x$PX_LAST, 20)),
# ewma_30 = map(data, ~ ema(.x$PX_LAST, 30))
# )
asset. = bbg_data2 %>% select(-Volume) %>% group_by(Ticker) %>% nest()
# nest(data = c(date, PX_OPEN, PX_HIGH, PX_LOW, PX_LAST))
# Required as ttool functions not exported from tidymas yet
source("../../R/ttool.R")
asset = asset. %>% mutate(
PIVOT = map(data, ~ select(tidy.ZOO(as.zoo(ta.PIVOT(tidy.ZOO(.x, tidy=TRUE))), zoo=TRUE), -date)),
ATR = map(data, ~ select(tidy.ZOO(ta.ATR(tidy.ZOO(.x, tidy=TRUE), 20, smooth='e', wilder=TRUE), zoo=TRUE, tname='ATR'), -date)),
EMA10 = map(data, ~ select(tidy.ZOO(ta.EMA(tidy.ZOO(.x, tidy=TRUE)$PX_LAST, 10), zoo=TRUE, tname='EMA10'), -date)),
EMA40 = map(data, ~ select(tidy.ZOO(ta.EMA(tidy.ZOO(.x, tidy=TRUE)$PX_LAST, 40), zoo=TRUE, tname='EMA40'), -date)),
EMA144= map(data, ~ select(tidy.ZOO(ta.EMA(tidy.ZOO(.x, tidy=TRUE)$PX_LAST, 144), zoo=TRUE, tname='EMA144'), -date)),
RSI = map(data, ~ select(tidy.ZOO(ta.RSI(tidy.ZOO(.x, tidy=TRUE)$PX_LAST, 7), zoo=TRUE, tname='RSI'), -date)),
STOCH = map(data, ~ select(tidy.ZOO(ta.STOCH(tidy.ZOO(.x, tidy=TRUE), 5,5,3,1), zoo=TRUE), -date)),
TTMSQ = map(data, ~ select(tidy.ZOO(ta.TTMSQ(tidy.ZOO(.x, tidy=TRUE), 20, smooth='e', wilder=TRUE), zoo=TRUE), -date))
) %>% unnest %>% nest(-Ticker)
# Draw grobs for all data in step above - Jie Rong
#Calling data
RX1.df = asset %>% tidy.SELECT("RX1 Comdty") %>% tidy.VIEW(type = "t", rows = 252)
G1.df = asset %>% tidy.SELECT("G 1 Comdty") %>% tidy.VIEW(type = "t", rows = 252)
IK1.df = asset %>% tidy.SELECT("IK1 Comdty") %>% tidy.VIEW(type = "t", rows = 252)
OAT1.df = asset %>% tidy.SELECT("OAT1 Comdty") %>% tidy.VIEW(type = "t", rows = 252)
ES1.df = asset %>% tidy.SELECT("ES1 Index") %>% tidy.VIEW(type = "t", rows = 252)
VG1.df = asset %>% tidy.SELECT("VG1 Index") %>% tidy.VIEW(type = "t", rows = 252)
Z1.df = asset %>% tidy.SELECT("Z 1 Index") %>% tidy.VIEW(type = "t", rows = 252)
TY1.df = asset %>% tidy.SELECT("TY1 Comdty") %>% tidy.VIEW(type = "t", rows = 252)
#RX1 Comdty
# Price chart
RX1_pricechart =
ggplot(data= RX1.df, aes(x=date, y = PX_LAST)) +
geom_linerange(aes(ymin=PX_LOW, ymax=PX_HIGH)) +
theme_bw() +
labs(title="RX1 Price Range") +
labs(x = "Date", y = "Price")+
geom_line(aes(x=date, y=EMA10), colour = "red") +
geom_line(aes(x=date,y=EMA40), color = "blue") +
geom_line(aes(x=date,y=EMA144), color = "green")
# Daily Close
RX1_dailyclose =
ggplot(data = RX1.df, aes(x = date, y = PX_LAST)) +
geom_line() +
labs(x = "Date", y = "Price") +
labs(title = "RX1 Daily Close") +
geom_line(aes(x=date, y=EMA10), colour = "red") +
geom_line(aes(x=date,y=EMA40), color = "blue") +
geom_line(aes(x=date,y=EMA144), color = "green")
# RSI Chart
RX1_RSI =
ggplot(data = RX1.df) +
geom_line(aes(x=date,y=RSI),colour="red") +
geom_hline(aes(yintercept = 70),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) +
geom_hline(aes(yintercept = 30),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) +
scale_y_continuous(breaks= c(30,50,70)) +
labs(x = "Date", y = "RSI") +
labs(title = "RX1 RSI")
# Stochastic
RX1_stoc =
ggplot(data = RX1.df) +
geom_line(aes(x=date,y=fastD),colour="red") +
geom_line(aes(x=date,y=slowD), colour="blue") +
geom_hline(aes(yintercept = 80),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) +
geom_hline(aes(yintercept = 20),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) +
scale_y_continuous(breaks= c(20,50,80)) +
labs(x = "Date", y = "Stochastic") +
labs(title = "RX1 Stochastic")
# ATR
RX1_ATR =
ggplot(data = RX1.df) +
geom_line(aes(x=date,y=ATR),colour="black") +
labs(x = "Date", y = "ATR") +
labs(title = "RX1 ATR")
# Price frequencies
RX1_pricefrequencies =
ggplot(data=RX1.df, aes(x=RX1.df$PX_LAST)) +
geom_histogram(breaks=seq(155, 170, by=0.5), col="red", fill="green", alpha = .2) +
labs(title="RX1 Price frequencies", x="Price", y="Density")
# HistSQ
RX1_dotsq0 = RX1.df$dotSQ
RX1_dotsq0[RX1_dotsq0 == 1] = NA
RX1_dotsq1 = RX1.df$dotSQ
RX1_dotsq1[RX1_dotsq1 == 0] = NA
RX1_dotsq1[RX1_dotsq1 == 1] = 0
RX1_histSQ =
ggplot(data=RX1.df) +
geom_line(aes(x=date,y=histSQ), colour = "black", linetype = "solid", size = 0.5, alpha =1) +
geom_hline(aes(yintercept = 0),colour ="black", linetype = "solid", size = 0.5, alpha =0.5)+
geom_point(aes(x=date, y=RX1_dotsq0),colour = "red", size = 0.5, alpha =1) +
geom_point(aes(x=date, y=RX1_dotsq1),colour = "green", size = 0.5, alpha =1) +
labs(title = "RX1 HistSQ", x="Date", y= "HistSQ")
# Interactive viewer using plotly
##RX1.df %>%
##plot_ly(x = ~date, type = "ohlc",
## open = ~PX_OPEN, close = ~PX_LAST,
## high = ~PX_HIGH, low = ~PX_LOW) %>%
## layout(title="RX1 OHLC",
## xaxis = list(rangeslider = list (visible = F)))
#G1 Comdty
# Price chart
G1_pricechart =
ggplot(data= G1.df, aes(x=date, y = PX_LAST)) +
geom_linerange(aes(ymin=PX_LOW, ymax=PX_HIGH)) +
theme_bw() +
labs(title="G1 Price Range") +
labs(x = "Date", y = "Price")+
geom_line(aes(x=date, y=EMA10), colour = "red") +
geom_line(aes(x=date,y=EMA40), color = "blue") +
geom_line(aes(x=date,y=EMA144), color = "green")
# Daily Close
G1_dailyclose =
ggplot(data = G1.df, aes(x = date, y = PX_LAST)) +
geom_line() +
labs(x = "Date", y = "Price") +
labs(title = "G1 Daily Close") +
geom_line(aes(x=date, y=EMA10), colour = "red") +
geom_line(aes(x=date,y=EMA40), color = "blue") +
geom_line(aes(x=date,y=EMA144), color = "green")
# RSI Chart
G1_RSI =
ggplot(data = G1.df) +
geom_line(aes(x=date,y=RSI),colour="red") +
geom_hline(aes(yintercept = 70),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) +
geom_hline(aes(yintercept = 30),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) +
scale_y_continuous(breaks= c(30,50,70)) +
labs(x = "Date", y = "RSI") +
labs(title = "G1 RSI")
# Stochastic
G1_stoc =
ggplot(data = G1.df) +
geom_line(aes(x=date,y=fastD),colour="red") +
geom_line(aes(x=date,y=slowD), colour="blue") +
geom_hline(aes(yintercept = 80),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) +
geom_hline(aes(yintercept = 20),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) +
scale_y_continuous(breaks= c(20,50,80)) +
labs(x = "Date", y = "Stochastic") +
labs(title = "G1 Stochastic")
# ATR
G1_ATR =
ggplot(data = G1.df) +
geom_line(aes(x=date,y=ATR),colour="black") +
labs(x = "Date", y = "ATR") +
labs(title = "G1 ATR")
# Price frequencies
G1_pricefrequencies =
ggplot(data=G1.df, aes(x=G1.df$PX_LAST)) +
geom_histogram(breaks=seq(115, 135, by=0.5), col="red", fill="green", alpha = .2) +
labs(title="G1 Price frequencies", x="Price", y="Density")
# HistSQ
G1_dotsq0 = G1.df$dotSQ
G1_dotsq0[G1_dotsq0 == 1] = NA
G1_dotsq1 = G1.df$dotSQ
G1_dotsq1[G1_dotsq1 == 0] = NA
G1_dotsq1[G1_dotsq1 == 1] = 0
G1_histSQ =
ggplot(data=G1.df) +
geom_line(aes(x=date,y=histSQ), colour = "black", linetype = "solid", size = 0.5, alpha =1) +
geom_hline(aes(yintercept = 0),colour ="black", linetype = "solid", size = 0.5, alpha =0.5)+
geom_point(aes(x=date, y=G1_dotsq0),colour = "red", size = 0.5, alpha =1) +
geom_point(aes(x=date, y=G1_dotsq1),colour = "green", size = 0.5, alpha =1) +
labs(title = "G1 HistSQ", x="Date", y= "HistSQ")
# Interactive viewer using plotly
##G1.df %>%
##plot_ly(x = ~date, type = "ohlc",
## open = ~PX_OPEN, close = ~PX_LAST,
## high = ~PX_HIGH, low = ~PX_LOW) %>%
## layout(title="G1 OHLC",
## xaxis = list(rangeslider = list (visible = F)))
#IK1 Comdty
# Price chart
IK1_pricechart =
ggplot(data= IK1.df, aes(x=date, y = PX_LAST)) +
geom_linerange(aes(ymin=PX_LOW, ymax=PX_HIGH)) +
theme_bw() +
labs(title="IK1 Price Range") +
labs(x = "Date", y = "Price")+
geom_line(aes(x=date, y=EMA10), colour = "red") +
geom_line(aes(x=date,y=EMA40), color = "blue") +
geom_line(aes(x=date,y=EMA144), color = "green")
# Daily Close
IK1_dailyclose =
ggplot(data = IK1.df, aes(x = date, y = PX_LAST)) +
geom_line() +
labs(x = "Date", y = "Price") +
labs(title = "IK1 Daily Close") +
geom_line(aes(x=date, y=EMA10), colour = "red") +
geom_line(aes(x=date,y=EMA40), color = "blue") +
geom_line(aes(x=date,y=EMA144), color = "green")
# RSI Chart
IK1_RSI =
ggplot(data = IK1.df) +
geom_line(aes(x=date,y=RSI),colour="red") +
geom_hline(aes(yintercept = 70),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) +
geom_hline(aes(yintercept = 30),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) +
scale_y_continuous(breaks= c(30,50,70)) +
labs(x = "Date", y = "RSI") +
labs(title = "IK1 RSI")
# Stochastic
IK1_stoc =
ggplot(data = IK1.df) +
geom_line(aes(x=date,y=fastD),colour="red") +
geom_line(aes(x=date,y=slowD), colour="blue") +
geom_hline(aes(yintercept = 80),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) +
geom_hline(aes(yintercept = 20),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) +
scale_y_continuous(breaks= c(20,50,80)) +
labs(x = "Date", y = "Stochastic") +
labs(title = "IK1 Stochastic")
# ATR
IK1_ATR =
ggplot(data = IK1.df) +
geom_line(aes(x=date,y=ATR),colour="black") +
labs(x = "Date", y = "ATR") +
labs(title = "IK1 ATR")
# Price frequencies
IK1_pricefrequencies =
ggplot(data=IK1.df, aes(x=IK1.df$PX_LAST)) +
geom_histogram(breaks=seq(115, 145, by=0.5), col="red", fill="green", alpha = .2) +
labs(title="IK1 Price frequencies", x="Price", y="Density")
# HistSQ
IK1_dotsq0 = IK1.df$dotSQ
IK1_dotsq0[IK1_dotsq0 == 1] = NA
IK1_dotsq1 = IK1.df$dotSQ
IK1_dotsq1[IK1_dotsq1 == 0] = NA
IK1_dotsq1[IK1_dotsq1 == 1] = 0
IK1_histSQ =
ggplot(data=IK1.df) +
geom_line(aes(x=date,y=histSQ), colour = "black", linetype = "solid", size = 0.5, alpha =1) +
geom_hline(aes(yintercept = 0),colour ="black", linetype = "solid", size = 0.5, alpha =0.5)+
geom_point(aes(x=date, y=IK1_dotsq0),colour = "red", size = 0.5, alpha =1) +
geom_point(aes(x=date, y=IK1_dotsq1),colour = "green", size = 0.5, alpha =1) +
labs(title = "IK1 HistSQ", x="Date", y= "HistSQ")
# Interactive viewer using plotly
##IK1.df %>%
##plot_ly(x = ~date, type = "ohlc",
## open = ~PX_OPEN, close = ~PX_LAST,
## high = ~PX_HIGH, low = ~PX_LOW) %>%
## layout(title="IK1 OHLC",
## xaxis = list(rangeslider = list (visible = F)))
#OAT1 Comdty
# Price chart
OAT1_pricechart =
ggplot(data= OAT1.df, aes(x=date, y = PX_LAST)) +
geom_linerange(aes(ymin=PX_LOW, ymax=PX_HIGH)) +
theme_bw() +
labs(title="OAT1 Price Range") +
labs(x = "Date", y = "Price")+
geom_line(aes(x=date, y=EMA10), colour = "red") +
geom_line(aes(x=date,y=EMA40), color = "blue") +
geom_line(aes(x=date,y=EMA144), color = "green")
# Daily Close
OAT1_dailyclose =
ggplot(data = OAT1.df, aes(x = date, y = PX_LAST)) +
geom_line() +
labs(x = "Date", y = "Price") +
labs(title = "OAT1 Daily Close") +
geom_line(aes(x=date, y=EMA10), colour = "red") +
geom_line(aes(x=date,y=EMA40), color = "blue") +
geom_line(aes(x=date,y=EMA144), color = "green")
# RSI Chart
OAT1_RSI =
ggplot(data = OAT1.df) +
geom_line(aes(x=date,y=RSI),colour="red") +
geom_hline(aes(yintercept = 70),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) +
geom_hline(aes(yintercept = 30),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) +
scale_y_continuous(breaks= c(30,50,70)) +
labs(x = "Date", y = "RSI") +
labs(title = "OAT1 RSI")
# Stochastic
OAT1_stoc =
ggplot(data = OAT1.df) +
geom_line(aes(x=date,y=fastD),colour="red") +
geom_line(aes(x=date,y=slowD), colour="blue") +
geom_hline(aes(yintercept = 80),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) +
geom_hline(aes(yintercept = 20),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) +
scale_y_continuous(breaks= c(20,50,80)) +
labs(x = "Date", y = "Stochastic") +
labs(title = "OAT1 Stochastic")
# ATR
OAT1_ATR =
ggplot(data = OAT1.df) +
geom_line(aes(x=date,y=ATR),colour="black") +
labs(x = "Date", y = "ATR") +
labs(title = "OAT1 ATR")
# Price frequencies
OAT1_pricefrequencies =
ggplot(data=OAT1.df, aes(x=OAT1.df$PX_LAST)) +
geom_histogram(breaks=seq(145, 165, by=0.5), col="red", fill="green", alpha = .2) +
labs(title="OAT1 Price frequencies", x="Price", y="Density")
# HistSQ
OAT1_dotsq0 = OAT1.df$dotSQ
OAT1_dotsq0[OAT1_dotsq0 == 1] = NA
OAT1_dotsq1 = OAT1.df$dotSQ
OAT1_dotsq1[OAT1_dotsq1 == 0] = NA
OAT1_dotsq1[OAT1_dotsq1 == 1] = 0
OAT1_histSQ =
ggplot(data=OAT1.df) +
geom_line(aes(x=date,y=histSQ), colour = "black", linetype = "solid", size = 0.5, alpha =1) +
geom_hline(aes(yintercept = 0),colour ="black", linetype = "solid", size = 0.5, alpha =0.5)+
geom_point(aes(x=date, y=OAT1_dotsq0),colour = "red", size = 0.5, alpha =1) +
geom_point(aes(x=date, y=OAT1_dotsq1),colour = "green", size = 0.5, alpha =1) +
labs(title = "OAT1 HistSQ", x="Date", y= "HistSQ")
# Interactive viewer using plotly
##OAT1.df %>%
##plot_ly(x = ~date, type = "ohlc",
## open = ~PX_OPEN, close = ~PX_LAST,
## high = ~PX_HIGH, low = ~PX_LOW) %>%
## layout(title="OAT1 OHLC",
## xaxis = list(rangeslider = list (visible = F)))
#ES1 Comdty
# Price chart
ES1_pricechart =
ggplot(data= ES1.df, aes(x=date, y = PX_LAST)) +
geom_linerange(aes(ymin=PX_LOW, ymax=PX_HIGH)) +
theme_bw() +
labs(title="ES1 Price Range") +
labs(x = "Date", y = "Price")+
geom_line(aes(x=date, y=EMA10), colour = "red") +
geom_line(aes(x=date,y=EMA40), color = "blue") +
geom_line(aes(x=date,y=EMA144), color = "green")
# Daily Close
ES1_dailyclose =
ggplot(data = ES1.df, aes(x = date, y = PX_LAST)) +
geom_line() +
labs(x = "Date", y = "Price") +
labs(title = "ES1 Daily Close") +
geom_line(aes(x=date, y=EMA10), colour = "red") +
geom_line(aes(x=date,y=EMA40), color = "blue") +
geom_line(aes(x=date,y=EMA144), color = "green")
# RSI Chart
ES1_RSI =
ggplot(data = ES1.df) +
geom_line(aes(x=date,y=RSI),colour="red") +
geom_hline(aes(yintercept = 70),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) +
geom_hline(aes(yintercept = 30),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) +
scale_y_continuous(breaks= c(30,50,70)) +
labs(x = "Date", y = "RSI") +
labs(title = "ES1 RSI")
# Stochastic
ES1_stoc =
ggplot(data = ES1.df) +
geom_line(aes(x=date,y=fastD),colour="red") +
geom_line(aes(x=date,y=slowD), colour="blue") +
geom_hline(aes(yintercept = 80),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) +
geom_hline(aes(yintercept = 20),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) +
scale_y_continuous(breaks= c(20,50,80)) +
labs(x = "Date", y = "Stochastic") +
labs(title = "ES1 Stochastic")
# ATR
ES1_ATR =
ggplot(data = ES1.df) +
geom_line(aes(x=date,y=ATR),colour="black") +
labs(x = "Date", y = "ATR") +
labs(title = "ES1 ATR")
# Price frequencies
ES1_pricefrequencies =
ggplot(data=ES1.df, aes(x=ES1.df$PX_LAST)) +
geom_histogram(breaks=seq(2250, 3000, by=10), col="red", fill="green", alpha = 0.2) +
labs(title="ES1 Price frequencies", x="Price", y="Density")
# HistSQ
ES1_dotsq0 = ES1.df$dotSQ
ES1_dotsq0[ES1_dotsq0 == 1] = NA
ES1_dotsq1 = ES1.df$dotSQ
ES1_dotsq1[ES1_dotsq1 == 0] = NA
ES1_dotsq1[ES1_dotsq1 == 1] = 0
ES1_histSQ =
ggplot(data=ES1.df) +
geom_line(aes(x=date,y=histSQ), colour = "black", linetype = "solid", size = 0.5, alpha =1) +
geom_hline(aes(yintercept = 0),colour ="black", linetype = "solid", size = 0.5, alpha =0.5)+
geom_point(aes(x=date, y=ES1_dotsq0),colour = "red", size = 0.5, alpha =1) +
geom_point(aes(x=date, y=ES1_dotsq1),colour = "green", size = 0.5, alpha =1) +
labs(title = "ES1 HistSQ", x="Date", y= "HistSQ")
# Interactive viewer using plotly
##ES1.df %>%
##plot_ly(x = ~date, type = "ohlc",
## open = ~PX_OPEN, close = ~PX_LAST,
## high = ~PX_HIGH, low = ~PX_LOW) %>%
## layout(title="ES1 OHLC",
## xaxis = list(rangeslider = list (visible = F)))
#VG1 Comdty
# Price chart
VG1_pricechart =
ggplot(data= VG1.df, aes(x=date, y = PX_LAST)) +
geom_linerange(aes(ymin=PX_LOW, ymax=PX_HIGH)) +
theme_bw() +
labs(title="VG1 Price Range") +
labs(x = "Date", y = "Price")+
geom_line(aes(x=date, y=EMA10), colour = "red") +
geom_line(aes(x=date,y=EMA40), color = "blue") +
geom_line(aes(x=date,y=EMA144), color = "green")
# Daily Close
VG1_dailyclose =
ggplot(data = VG1.df, aes(x = date, y = PX_LAST)) +
geom_line() +
labs(x = "Date", y = "Price") +
labs(title = "VG1 Daily Close") +
geom_line(aes(x=date, y=EMA10), colour = "red") +
geom_line(aes(x=date,y=EMA40), color = "blue") +
geom_line(aes(x=date,y=EMA144), color = "green")
# RSI Chart
VG1_RSI =
ggplot(data = VG1.df) +
geom_line(aes(x=date,y=RSI),colour="red") +
geom_hline(aes(yintercept = 70),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) +
geom_hline(aes(yintercept = 30),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) +
scale_y_continuous(breaks= c(30,50,70)) +
labs(x = "Date", y = "RSI") +
labs(title = "VG1 RSI")
# Stochastic
VG1_stoc =
ggplot(data = VG1.df) +
geom_line(aes(x=date,y=fastD),colour="red") +
geom_line(aes(x=date,y=slowD), colour="blue") +
geom_hline(aes(yintercept = 80),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) +
geom_hline(aes(yintercept = 20),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) +
scale_y_continuous(breaks= c(20,50,80)) +
labs(x = "Date", y = "Stochastic") +
labs(title = "VG1 Stochastic")
# ATR
VG1_ATR =
ggplot(data = VG1.df) +
geom_line(aes(x=date,y=ATR),colour="black") +
labs(x = "Date", y = "ATR") +
labs(title = "VG1 ATR")
# Price frequencies
VG1_pricefrequencies =
ggplot(data=VG1.df, aes(x=VG1.df$PX_LAST)) +
geom_histogram(breaks=seq(2900, 3600, by=10), col="red", fill="green", alpha = .2) +
labs(title="VG1 Price frequencies", x="Price", y="Density")
# HistSQ
VG1_dotsq0 = VG1.df$dotSQ
VG1_dotsq0[VG1_dotsq0 == 1] = NA
VG1_dotsq1 = VG1.df$dotSQ
VG1_dotsq1[VG1_dotsq1 == 0] = NA
VG1_dotsq1[VG1_dotsq1 == 1] = 0
VG1_histSQ =
ggplot(data=VG1.df) +
geom_line(aes(x=date,y=histSQ), colour = "black", linetype = "solid", size = 0.5, alpha =1) +
geom_hline(aes(yintercept = 0),colour ="black", linetype = "solid", size = 0.5, alpha =0.5)+
geom_point(aes(x=date, y=VG1_dotsq0),colour = "red", size = 0.5, alpha =1) +
geom_point(aes(x=date, y=VG1_dotsq1),colour = "green", size = 0.5, alpha =1) +
labs(title = "VG1 HistSQ", x="Date", y= "HistSQ")
# Interactive viewer using plotly
##VG1.df %>%
##plot_ly(x = ~date, type = "ohlc",
## open = ~PX_OPEN, close = ~PX_LAST,
## high = ~PX_HIGH, low = ~PX_LOW) %>%
## layout(title="VG1 OHLC",
## xaxis = list(rangeslider = list (visible = F)))
#Z1 Comdty
# Price chart
Z1_pricechart =
ggplot(data= Z1.df, aes(x=date, y = PX_LAST)) +
geom_linerange(aes(ymin=PX_LOW, ymax=PX_HIGH)) +
theme_bw() +
labs(title="Z1 Price Range") +
labs(x = "Date", y = "Price")+
geom_line(aes(x=date, y=EMA10), colour = "red") +
geom_line(aes(x=date,y=EMA40), color = "blue") +
geom_line(aes(x=date,y=EMA144), color = "green")
# Daily Close
Z1_dailyclose =
ggplot(data = Z1.df, aes(x = date, y = PX_LAST)) +
geom_line() +
labs(x = "Date", y = "Price") +
labs(title = "Z1 Daily Close") +
geom_line(aes(x=date, y=EMA10), colour = "red") +
geom_line(aes(x=date,y=EMA40), color = "blue") +
geom_line(aes(x=date,y=EMA144), color = "green")
# RSI Chart
Z1_RSI =
ggplot(data = Z1.df) +
geom_line(aes(x=date,y=RSI),colour="red") +
geom_hline(aes(yintercept = 70),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) +
geom_hline(aes(yintercept = 30),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) +
scale_y_continuous(breaks= c(30,50,70)) +
labs(x = "Date", y = "RSI") +
labs(title = "Z1 RSI")
# Stochastic
Z1_stoc =
ggplot(data = Z1.df) +
geom_line(aes(x=date,y=fastD),colour="red") +
geom_line(aes(x=date,y=slowD), colour="blue") +
geom_hline(aes(yintercept = 80),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) +
geom_hline(aes(yintercept = 20),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) +
scale_y_continuous(breaks= c(20,50,80)) +
labs(x = "Date", y = "Stochastic") +
labs(title = "Z1 Stochastic")
# ATR
Z1_ATR =
ggplot(data = Z1.df) +
geom_line(aes(x=date,y=ATR),colour="black") +
labs(x = "Date", y = "ATR") +
labs(title = "Z1 ATR")
# Price frequencies
Z1_pricefrequencies =
ggplot(data=Z1.df, aes(x=Z1.df$PX_LAST)) +
geom_histogram(breaks=seq(6500, 8000, by=20), col="red", fill="green", alpha = .2) +
labs(title="Z1 Price frequencies", x="Price", y="Density")
# HistSQ
Z1_dotsq0 = Z1.df$dotSQ
Z1_dotsq0[Z1_dotsq0 == 1] = NA
Z1_dotsq1 = Z1.df$dotSQ
Z1_dotsq1[Z1_dotsq1 == 0] = NA
Z1_dotsq1[Z1_dotsq1 == 1] = 0
Z1_histSQ =
ggplot(data=Z1.df) +
geom_line(aes(x=date,y=histSQ), colour = "black", linetype = "solid", size = 0.5, alpha =1) +
geom_hline(aes(yintercept = 0),colour ="black", linetype = "solid", size = 0.5, alpha =0.5)+
geom_point(aes(x=date, y=Z1_dotsq0),colour = "red", size = 0.5, alpha =1) +
geom_point(aes(x=date, y=Z1_dotsq1),colour = "green", size = 0.5, alpha =1) +
labs(title = "Z1 HistSQ", x="Date", y= "HistSQ")
# Interactive viewer using plotly
##Z1.df %>%
##plot_ly(x = ~date, type = "ohlc",
## open = ~PX_OPEN, close = ~PX_LAST,
## high = ~PX_HIGH, low = ~PX_LOW) %>%
## layout(title="Z1 OHLC",
## xaxis = list(rangeslider = list (visible = F)))
#TY1 Comdty
# Price chart
TY1_pricechart =
ggplot(data= TY1.df, aes(x=date, y = PX_LAST)) +
geom_linerange(aes(ymin=PX_LOW, ymax=PX_HIGH)) +
theme_bw() +
labs(title="TY1 Price Range") +
labs(x = "Date", y = "Price")+
geom_line(aes(x=date, y=EMA10), colour = "red") +
geom_line(aes(x=date,y=EMA40), color = "blue") +
geom_line(aes(x=date,y=EMA144), color = "green")
# Daily Close
TY1_dailyclose =
ggplot(data = TY1.df, aes(x = date, y = PX_LAST)) +
geom_line() +
labs(x = "Date", y = "Price") +
labs(title = "TY1 Daily Close") +
geom_line(aes(x=date, y=EMA10), colour = "red") +
geom_line(aes(x=date,y=EMA40), color = "blue") +
geom_line(aes(x=date,y=EMA144), color = "green")
# RSI Chart
TY1_RSI =
ggplot(data = TY1.df) +
geom_line(aes(x=date,y=RSI),colour="red") +
geom_hline(aes(yintercept = 70),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) +
geom_hline(aes(yintercept = 30),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) +
scale_y_continuous(breaks= c(30,50,70)) +
labs(x = "Date", y = "RSI") +
labs(title = "TY1 RSI")
# Stochastic
TY1_stoc =
ggplot(data = TY1.df) +
geom_line(aes(x=date,y=fastD),colour="red") +
geom_line(aes(x=date,y=slowD), colour="blue") +
geom_hline(aes(yintercept = 80),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) +
geom_hline(aes(yintercept = 20),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) +
scale_y_continuous(breaks= c(20,50,80)) +
labs(x = "Date", y = "Stochastic") +
labs(title = "TY1 Stochastic")
# ATR
TY1_ATR =
ggplot(data = TY1.df) +
geom_line(aes(x=date,y=ATR),colour="black") +
labs(x = "Date", y = "ATR") +
labs(title = "TY1 ATR")
# Price frequencies
TY1_pricefrequencies =
ggplot(data=TY1.df, aes(x=TY1.df$PX_LAST)) +
geom_histogram(breaks=seq(115, 130, by=0.5), col="red", fill="green", alpha = .2) +
labs(title="TY1 Price frequencies", x="Price", y="Density")
# HistSQ
TY1_dotsq0 = TY1.df$dotSQ
TY1_dotsq0[TY1_dotsq0 == 1] = NA
TY1_dotsq1 = TY1.df$dotSQ
TY1_dotsq1[TY1_dotsq1 == 0] = NA
TY1_dotsq1[TY1_dotsq1 == 1] = 0
TY1_histSQ =
ggplot(data=TY1.df) +
geom_line(aes(x=date,y=histSQ), colour = "black", linetype = "solid", size = 0.5, alpha =1) +
geom_hline(aes(yintercept = 0),colour ="black", linetype = "solid", size = 0.5, alpha =0.5)+
geom_point(aes(x=date, y=TY1_dotsq0),colour = "red", size = 0.5, alpha =1) +
geom_point(aes(x=date, y=TY1_dotsq1),colour = "green", size = 0.5, alpha =1) +
labs(title = "TY1 HistSQ", x="Date", y= "HistSQ")
# Interactive viewer using plotly
##TY1.df %>%
##plot_ly(x = ~date, type = "ohlc",
## open = ~PX_OPEN, close = ~PX_LAST,
## high = ~PX_HIGH, low = ~PX_LOW) %>%
## layout(title="TY1 OHLC",
## xaxis = list(rangeslider = list (visible = F)))
# Arrange generated grobs for pretty printing and generate PDF - Ethel Ngiam
colnames1 <- c("Date", "Open", "High", "Low", "Close", "ATR", "sd.ATR", "EMA10", "EMA40", "EMA144", "RSI")
colnames2 <- c("Date", "S3", "S2", "S1", "Pivot", "R1", "R2", "R3", "fastK", "fastD", "slowD", "SQ", "histSQ")
table1 <- function(tibbledata){
tibbledata %>%
ungroup() %>%
select(date, PX_OPEN, PX_HIGH, PX_LOW, PX_LAST, ATR, sd.ATR, EMA10, EMA40, EMA144, RSI) %>%
tail(21) -> tibbledata2
kable(tibbledata2,
col.names = colnames1,
align = rep('c', 11))}
table2 <- function(tibbledata) {
tibbledata %>%
ungroup() %>%
select(date, S3, S2, S1, Pivot, R1, R2, R3, fastK, fastD, slowD, dotSQ, histSQ) %>%
tail(21) -> tibbledata2
kable(tibbledata2,
col.names = colnames2,
align = rep('c', 13))}
cat("RX1")
table1(RX1.df)
table2(RX1.df)
grid.arrange(RX1_pricechart, RX1_dailyclose, RX1_ATR, RX1_RSI, RX1_stoc, RX1_histSQ, nrow=3)
cat("\n\n\\pagebreak\n")
cat("OAT1")
table1(OAT1.df)
table2(OAT1.df)
grid.arrange(OAT1_pricechart, OAT1_dailyclose, OAT1_ATR, OAT1_RSI, OAT1_stoc, OAT1_histSQ, nrow=3)
cat("\n\n\\pagebreak\n")
cat("ES1")
table1(ES1.df)
table2(ES1.df)
grid.arrange(ES1_pricechart, ES1_dailyclose, ES1_ATR, ES1_RSI, ES1_stoc, ES1_histSQ, nrow=3)
cat("\n\n\\pagebreak\n")
cat("IK1")
table1(IK1.df)
table2(IK1.df)
grid.arrange(IK1_pricechart, IK1_dailyclose, IK1_ATR, IK1_RSI, IK1_stoc, IK1_histSQ, nrow=3)
cat("\n\n\\pagebreak\n")
cat("G 1")
table1(G1.df)
table2(G1.df)
grid.arrange(G1_pricechart, G1_dailyclose, G1_ATR, G1_RSI, G1_stoc, G1_histSQ, nrow=3)
cat("\n\n\\pagebreak\n")
cat("VG1")
table1(VG1.df)
table2(VG1.df)
grid.arrange(VG1_pricechart, VG1_dailyclose, VG1_ATR, VG1_RSI, VG1_stoc, VG1_histSQ, nrow=3)
cat("\n\n\\pagebreak\n")
cat("Z 1")
table1(Z1.df)
table2(Z1.df)
grid.arrange(Z1_pricechart, Z1_dailyclose, Z1_ATR, Z1_RSI, Z1_stoc, Z1_histSQ, nrow=3)
cat("\n\n\\pagebreak\n")
yunching/tidymas documentation built on Feb. 5, 2023, 1:42 p.m.
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library(tidyverse) library(tidymas) # library(Rblpapi) library(zoo) library(devtools) library(gridExtra) library(knitr) # blpConnect()
# Downloads data from BBG - Yun Ching # sec_list <- c("RX1 Comdty", "G 1 Comdty", "IK1 Comdty", "OAT1 Comdty", # "ES1 Index", "VG1 Index", "Z 1 Index", # "TY1 Comdty") # bbg_data_raw <- bdh(sec_list, c("PX_OPEN", "PX_HIGH", "PX_LOW", "PX_LAST", "Volume"), start.date = Sys.Date() - 1095) # # bbg_data_raw %>% # bind_rows(.id = "Ticker") %>% # as_tibble() %>% # na.omit -> # bbg_data # load_bbg_data(dbname = "../../inst/extdata/mydatabase.db") load_db(dbname = "../../inst/extdata/mydatabase.db") %>% mutate(Date = lubridate::as_date(date)) %>% select(Ticker, Date, PX_OPEN, PX_HIGH, PX_LOW, PX_LAST, VOLUME) %>% filter(Ticker %in% c("RX1 Comdty", "G 1 Comdty", "IK1 Comdty", "OAT1 Comdty", "ES1 Index", "VG1 Index", "Z 1 Index", "TY1 Comdty")) %>% filter(Date >= Sys.Date() - 1095) %>% rename(date = Date, Volume = VOLUME) %>% # bind_rows(.id = "Ticker") %>% as_tibble() %>% na.omit -> bbg_data2
#Calculate analytics - Stanley Neo # bbg_data %>% # group_by(Ticker) %>% # nest() %>% # mutate(ewma_10 = map_dbl(data, ~ tail(ema(.x$PX_LAST, 10), 1)), # ewma_20 = map(data, ~ ema(.x$PX_LAST, 20)), # ewma_30 = map(data, ~ ema(.x$PX_LAST, 30)) # ) asset. = bbg_data2 %>% select(-Volume) %>% group_by(Ticker) %>% nest() # nest(data = c(date, PX_OPEN, PX_HIGH, PX_LOW, PX_LAST)) # Required as ttool functions not exported from tidymas yet source("../../R/ttool.R") asset = asset. %>% mutate( PIVOT = map(data, ~ select(tidy.ZOO(as.zoo(ta.PIVOT(tidy.ZOO(.x, tidy=TRUE))), zoo=TRUE), -date)), ATR = map(data, ~ select(tidy.ZOO(ta.ATR(tidy.ZOO(.x, tidy=TRUE), 20, smooth='e', wilder=TRUE), zoo=TRUE, tname='ATR'), -date)), EMA10 = map(data, ~ select(tidy.ZOO(ta.EMA(tidy.ZOO(.x, tidy=TRUE)$PX_LAST, 10), zoo=TRUE, tname='EMA10'), -date)), EMA40 = map(data, ~ select(tidy.ZOO(ta.EMA(tidy.ZOO(.x, tidy=TRUE)$PX_LAST, 40), zoo=TRUE, tname='EMA40'), -date)), EMA144= map(data, ~ select(tidy.ZOO(ta.EMA(tidy.ZOO(.x, tidy=TRUE)$PX_LAST, 144), zoo=TRUE, tname='EMA144'), -date)), RSI = map(data, ~ select(tidy.ZOO(ta.RSI(tidy.ZOO(.x, tidy=TRUE)$PX_LAST, 7), zoo=TRUE, tname='RSI'), -date)), STOCH = map(data, ~ select(tidy.ZOO(ta.STOCH(tidy.ZOO(.x, tidy=TRUE), 5,5,3,1), zoo=TRUE), -date)), TTMSQ = map(data, ~ select(tidy.ZOO(ta.TTMSQ(tidy.ZOO(.x, tidy=TRUE), 20, smooth='e', wilder=TRUE), zoo=TRUE), -date)) ) %>% unnest %>% nest(-Ticker)
# Draw grobs for all data in step above - Jie Rong #Calling data RX1.df = asset %>% tidy.SELECT("RX1 Comdty") %>% tidy.VIEW(type = "t", rows = 252) G1.df = asset %>% tidy.SELECT("G 1 Comdty") %>% tidy.VIEW(type = "t", rows = 252) IK1.df = asset %>% tidy.SELECT("IK1 Comdty") %>% tidy.VIEW(type = "t", rows = 252) OAT1.df = asset %>% tidy.SELECT("OAT1 Comdty") %>% tidy.VIEW(type = "t", rows = 252) ES1.df = asset %>% tidy.SELECT("ES1 Index") %>% tidy.VIEW(type = "t", rows = 252) VG1.df = asset %>% tidy.SELECT("VG1 Index") %>% tidy.VIEW(type = "t", rows = 252) Z1.df = asset %>% tidy.SELECT("Z 1 Index") %>% tidy.VIEW(type = "t", rows = 252) TY1.df = asset %>% tidy.SELECT("TY1 Comdty") %>% tidy.VIEW(type = "t", rows = 252) #RX1 Comdty # Price chart RX1_pricechart = ggplot(data= RX1.df, aes(x=date, y = PX_LAST)) + geom_linerange(aes(ymin=PX_LOW, ymax=PX_HIGH)) + theme_bw() + labs(title="RX1 Price Range") + labs(x = "Date", y = "Price")+ geom_line(aes(x=date, y=EMA10), colour = "red") + geom_line(aes(x=date,y=EMA40), color = "blue") + geom_line(aes(x=date,y=EMA144), color = "green") # Daily Close RX1_dailyclose = ggplot(data = RX1.df, aes(x = date, y = PX_LAST)) + geom_line() + labs(x = "Date", y = "Price") + labs(title = "RX1 Daily Close") + geom_line(aes(x=date, y=EMA10), colour = "red") + geom_line(aes(x=date,y=EMA40), color = "blue") + geom_line(aes(x=date,y=EMA144), color = "green") # RSI Chart RX1_RSI = ggplot(data = RX1.df) + geom_line(aes(x=date,y=RSI),colour="red") + geom_hline(aes(yintercept = 70),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) + geom_hline(aes(yintercept = 30),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) + scale_y_continuous(breaks= c(30,50,70)) + labs(x = "Date", y = "RSI") + labs(title = "RX1 RSI") # Stochastic RX1_stoc = ggplot(data = RX1.df) + geom_line(aes(x=date,y=fastD),colour="red") + geom_line(aes(x=date,y=slowD), colour="blue") + geom_hline(aes(yintercept = 80),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) + geom_hline(aes(yintercept = 20),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) + scale_y_continuous(breaks= c(20,50,80)) + labs(x = "Date", y = "Stochastic") + labs(title = "RX1 Stochastic") # ATR RX1_ATR = ggplot(data = RX1.df) + geom_line(aes(x=date,y=ATR),colour="black") + labs(x = "Date", y = "ATR") + labs(title = "RX1 ATR") # Price frequencies RX1_pricefrequencies = ggplot(data=RX1.df, aes(x=RX1.df$PX_LAST)) + geom_histogram(breaks=seq(155, 170, by=0.5), col="red", fill="green", alpha = .2) + labs(title="RX1 Price frequencies", x="Price", y="Density") # HistSQ RX1_dotsq0 = RX1.df$dotSQ RX1_dotsq0[RX1_dotsq0 == 1] = NA RX1_dotsq1 = RX1.df$dotSQ RX1_dotsq1[RX1_dotsq1 == 0] = NA RX1_dotsq1[RX1_dotsq1 == 1] = 0 RX1_histSQ = ggplot(data=RX1.df) + geom_line(aes(x=date,y=histSQ), colour = "black", linetype = "solid", size = 0.5, alpha =1) + geom_hline(aes(yintercept = 0),colour ="black", linetype = "solid", size = 0.5, alpha =0.5)+ geom_point(aes(x=date, y=RX1_dotsq0),colour = "red", size = 0.5, alpha =1) + geom_point(aes(x=date, y=RX1_dotsq1),colour = "green", size = 0.5, alpha =1) + labs(title = "RX1 HistSQ", x="Date", y= "HistSQ") # Interactive viewer using plotly ##RX1.df %>% ##plot_ly(x = ~date, type = "ohlc", ## open = ~PX_OPEN, close = ~PX_LAST, ## high = ~PX_HIGH, low = ~PX_LOW) %>% ## layout(title="RX1 OHLC", ## xaxis = list(rangeslider = list (visible = F))) #G1 Comdty # Price chart G1_pricechart = ggplot(data= G1.df, aes(x=date, y = PX_LAST)) + geom_linerange(aes(ymin=PX_LOW, ymax=PX_HIGH)) + theme_bw() + labs(title="G1 Price Range") + labs(x = "Date", y = "Price")+ geom_line(aes(x=date, y=EMA10), colour = "red") + geom_line(aes(x=date,y=EMA40), color = "blue") + geom_line(aes(x=date,y=EMA144), color = "green") # Daily Close G1_dailyclose = ggplot(data = G1.df, aes(x = date, y = PX_LAST)) + geom_line() + labs(x = "Date", y = "Price") + labs(title = "G1 Daily Close") + geom_line(aes(x=date, y=EMA10), colour = "red") + geom_line(aes(x=date,y=EMA40), color = "blue") + geom_line(aes(x=date,y=EMA144), color = "green") # RSI Chart G1_RSI = ggplot(data = G1.df) + geom_line(aes(x=date,y=RSI),colour="red") + geom_hline(aes(yintercept = 70),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) + geom_hline(aes(yintercept = 30),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) + scale_y_continuous(breaks= c(30,50,70)) + labs(x = "Date", y = "RSI") + labs(title = "G1 RSI") # Stochastic G1_stoc = ggplot(data = G1.df) + geom_line(aes(x=date,y=fastD),colour="red") + geom_line(aes(x=date,y=slowD), colour="blue") + geom_hline(aes(yintercept = 80),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) + geom_hline(aes(yintercept = 20),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) + scale_y_continuous(breaks= c(20,50,80)) + labs(x = "Date", y = "Stochastic") + labs(title = "G1 Stochastic") # ATR G1_ATR = ggplot(data = G1.df) + geom_line(aes(x=date,y=ATR),colour="black") + labs(x = "Date", y = "ATR") + labs(title = "G1 ATR") # Price frequencies G1_pricefrequencies = ggplot(data=G1.df, aes(x=G1.df$PX_LAST)) + geom_histogram(breaks=seq(115, 135, by=0.5), col="red", fill="green", alpha = .2) + labs(title="G1 Price frequencies", x="Price", y="Density") # HistSQ G1_dotsq0 = G1.df$dotSQ G1_dotsq0[G1_dotsq0 == 1] = NA G1_dotsq1 = G1.df$dotSQ G1_dotsq1[G1_dotsq1 == 0] = NA G1_dotsq1[G1_dotsq1 == 1] = 0 G1_histSQ = ggplot(data=G1.df) + geom_line(aes(x=date,y=histSQ), colour = "black", linetype = "solid", size = 0.5, alpha =1) + geom_hline(aes(yintercept = 0),colour ="black", linetype = "solid", size = 0.5, alpha =0.5)+ geom_point(aes(x=date, y=G1_dotsq0),colour = "red", size = 0.5, alpha =1) + geom_point(aes(x=date, y=G1_dotsq1),colour = "green", size = 0.5, alpha =1) + labs(title = "G1 HistSQ", x="Date", y= "HistSQ") # Interactive viewer using plotly ##G1.df %>% ##plot_ly(x = ~date, type = "ohlc", ## open = ~PX_OPEN, close = ~PX_LAST, ## high = ~PX_HIGH, low = ~PX_LOW) %>% ## layout(title="G1 OHLC", ## xaxis = list(rangeslider = list (visible = F))) #IK1 Comdty # Price chart IK1_pricechart = ggplot(data= IK1.df, aes(x=date, y = PX_LAST)) + geom_linerange(aes(ymin=PX_LOW, ymax=PX_HIGH)) + theme_bw() + labs(title="IK1 Price Range") + labs(x = "Date", y = "Price")+ geom_line(aes(x=date, y=EMA10), colour = "red") + geom_line(aes(x=date,y=EMA40), color = "blue") + geom_line(aes(x=date,y=EMA144), color = "green") # Daily Close IK1_dailyclose = ggplot(data = IK1.df, aes(x = date, y = PX_LAST)) + geom_line() + labs(x = "Date", y = "Price") + labs(title = "IK1 Daily Close") + geom_line(aes(x=date, y=EMA10), colour = "red") + geom_line(aes(x=date,y=EMA40), color = "blue") + geom_line(aes(x=date,y=EMA144), color = "green") # RSI Chart IK1_RSI = ggplot(data = IK1.df) + geom_line(aes(x=date,y=RSI),colour="red") + geom_hline(aes(yintercept = 70),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) + geom_hline(aes(yintercept = 30),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) + scale_y_continuous(breaks= c(30,50,70)) + labs(x = "Date", y = "RSI") + labs(title = "IK1 RSI") # Stochastic IK1_stoc = ggplot(data = IK1.df) + geom_line(aes(x=date,y=fastD),colour="red") + geom_line(aes(x=date,y=slowD), colour="blue") + geom_hline(aes(yintercept = 80),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) + geom_hline(aes(yintercept = 20),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) + scale_y_continuous(breaks= c(20,50,80)) + labs(x = "Date", y = "Stochastic") + labs(title = "IK1 Stochastic") # ATR IK1_ATR = ggplot(data = IK1.df) + geom_line(aes(x=date,y=ATR),colour="black") + labs(x = "Date", y = "ATR") + labs(title = "IK1 ATR") # Price frequencies IK1_pricefrequencies = ggplot(data=IK1.df, aes(x=IK1.df$PX_LAST)) + geom_histogram(breaks=seq(115, 145, by=0.5), col="red", fill="green", alpha = .2) + labs(title="IK1 Price frequencies", x="Price", y="Density") # HistSQ IK1_dotsq0 = IK1.df$dotSQ IK1_dotsq0[IK1_dotsq0 == 1] = NA IK1_dotsq1 = IK1.df$dotSQ IK1_dotsq1[IK1_dotsq1 == 0] = NA IK1_dotsq1[IK1_dotsq1 == 1] = 0 IK1_histSQ = ggplot(data=IK1.df) + geom_line(aes(x=date,y=histSQ), colour = "black", linetype = "solid", size = 0.5, alpha =1) + geom_hline(aes(yintercept = 0),colour ="black", linetype = "solid", size = 0.5, alpha =0.5)+ geom_point(aes(x=date, y=IK1_dotsq0),colour = "red", size = 0.5, alpha =1) + geom_point(aes(x=date, y=IK1_dotsq1),colour = "green", size = 0.5, alpha =1) + labs(title = "IK1 HistSQ", x="Date", y= "HistSQ") # Interactive viewer using plotly ##IK1.df %>% ##plot_ly(x = ~date, type = "ohlc", ## open = ~PX_OPEN, close = ~PX_LAST, ## high = ~PX_HIGH, low = ~PX_LOW) %>% ## layout(title="IK1 OHLC", ## xaxis = list(rangeslider = list (visible = F))) #OAT1 Comdty # Price chart OAT1_pricechart = ggplot(data= OAT1.df, aes(x=date, y = PX_LAST)) + geom_linerange(aes(ymin=PX_LOW, ymax=PX_HIGH)) + theme_bw() + labs(title="OAT1 Price Range") + labs(x = "Date", y = "Price")+ geom_line(aes(x=date, y=EMA10), colour = "red") + geom_line(aes(x=date,y=EMA40), color = "blue") + geom_line(aes(x=date,y=EMA144), color = "green") # Daily Close OAT1_dailyclose = ggplot(data = OAT1.df, aes(x = date, y = PX_LAST)) + geom_line() + labs(x = "Date", y = "Price") + labs(title = "OAT1 Daily Close") + geom_line(aes(x=date, y=EMA10), colour = "red") + geom_line(aes(x=date,y=EMA40), color = "blue") + geom_line(aes(x=date,y=EMA144), color = "green") # RSI Chart OAT1_RSI = ggplot(data = OAT1.df) + geom_line(aes(x=date,y=RSI),colour="red") + geom_hline(aes(yintercept = 70),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) + geom_hline(aes(yintercept = 30),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) + scale_y_continuous(breaks= c(30,50,70)) + labs(x = "Date", y = "RSI") + labs(title = "OAT1 RSI") # Stochastic OAT1_stoc = ggplot(data = OAT1.df) + geom_line(aes(x=date,y=fastD),colour="red") + geom_line(aes(x=date,y=slowD), colour="blue") + geom_hline(aes(yintercept = 80),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) + geom_hline(aes(yintercept = 20),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) + scale_y_continuous(breaks= c(20,50,80)) + labs(x = "Date", y = "Stochastic") + labs(title = "OAT1 Stochastic") # ATR OAT1_ATR = ggplot(data = OAT1.df) + geom_line(aes(x=date,y=ATR),colour="black") + labs(x = "Date", y = "ATR") + labs(title = "OAT1 ATR") # Price frequencies OAT1_pricefrequencies = ggplot(data=OAT1.df, aes(x=OAT1.df$PX_LAST)) + geom_histogram(breaks=seq(145, 165, by=0.5), col="red", fill="green", alpha = .2) + labs(title="OAT1 Price frequencies", x="Price", y="Density") # HistSQ OAT1_dotsq0 = OAT1.df$dotSQ OAT1_dotsq0[OAT1_dotsq0 == 1] = NA OAT1_dotsq1 = OAT1.df$dotSQ OAT1_dotsq1[OAT1_dotsq1 == 0] = NA OAT1_dotsq1[OAT1_dotsq1 == 1] = 0 OAT1_histSQ = ggplot(data=OAT1.df) + geom_line(aes(x=date,y=histSQ), colour = "black", linetype = "solid", size = 0.5, alpha =1) + geom_hline(aes(yintercept = 0),colour ="black", linetype = "solid", size = 0.5, alpha =0.5)+ geom_point(aes(x=date, y=OAT1_dotsq0),colour = "red", size = 0.5, alpha =1) + geom_point(aes(x=date, y=OAT1_dotsq1),colour = "green", size = 0.5, alpha =1) + labs(title = "OAT1 HistSQ", x="Date", y= "HistSQ") # Interactive viewer using plotly ##OAT1.df %>% ##plot_ly(x = ~date, type = "ohlc", ## open = ~PX_OPEN, close = ~PX_LAST, ## high = ~PX_HIGH, low = ~PX_LOW) %>% ## layout(title="OAT1 OHLC", ## xaxis = list(rangeslider = list (visible = F))) #ES1 Comdty # Price chart ES1_pricechart = ggplot(data= ES1.df, aes(x=date, y = PX_LAST)) + geom_linerange(aes(ymin=PX_LOW, ymax=PX_HIGH)) + theme_bw() + labs(title="ES1 Price Range") + labs(x = "Date", y = "Price")+ geom_line(aes(x=date, y=EMA10), colour = "red") + geom_line(aes(x=date,y=EMA40), color = "blue") + geom_line(aes(x=date,y=EMA144), color = "green") # Daily Close ES1_dailyclose = ggplot(data = ES1.df, aes(x = date, y = PX_LAST)) + geom_line() + labs(x = "Date", y = "Price") + labs(title = "ES1 Daily Close") + geom_line(aes(x=date, y=EMA10), colour = "red") + geom_line(aes(x=date,y=EMA40), color = "blue") + geom_line(aes(x=date,y=EMA144), color = "green") # RSI Chart ES1_RSI = ggplot(data = ES1.df) + geom_line(aes(x=date,y=RSI),colour="red") + geom_hline(aes(yintercept = 70),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) + geom_hline(aes(yintercept = 30),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) + scale_y_continuous(breaks= c(30,50,70)) + labs(x = "Date", y = "RSI") + labs(title = "ES1 RSI") # Stochastic ES1_stoc = ggplot(data = ES1.df) + geom_line(aes(x=date,y=fastD),colour="red") + geom_line(aes(x=date,y=slowD), colour="blue") + geom_hline(aes(yintercept = 80),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) + geom_hline(aes(yintercept = 20),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) + scale_y_continuous(breaks= c(20,50,80)) + labs(x = "Date", y = "Stochastic") + labs(title = "ES1 Stochastic") # ATR ES1_ATR = ggplot(data = ES1.df) + geom_line(aes(x=date,y=ATR),colour="black") + labs(x = "Date", y = "ATR") + labs(title = "ES1 ATR") # Price frequencies ES1_pricefrequencies = ggplot(data=ES1.df, aes(x=ES1.df$PX_LAST)) + geom_histogram(breaks=seq(2250, 3000, by=10), col="red", fill="green", alpha = 0.2) + labs(title="ES1 Price frequencies", x="Price", y="Density") # HistSQ ES1_dotsq0 = ES1.df$dotSQ ES1_dotsq0[ES1_dotsq0 == 1] = NA ES1_dotsq1 = ES1.df$dotSQ ES1_dotsq1[ES1_dotsq1 == 0] = NA ES1_dotsq1[ES1_dotsq1 == 1] = 0 ES1_histSQ = ggplot(data=ES1.df) + geom_line(aes(x=date,y=histSQ), colour = "black", linetype = "solid", size = 0.5, alpha =1) + geom_hline(aes(yintercept = 0),colour ="black", linetype = "solid", size = 0.5, alpha =0.5)+ geom_point(aes(x=date, y=ES1_dotsq0),colour = "red", size = 0.5, alpha =1) + geom_point(aes(x=date, y=ES1_dotsq1),colour = "green", size = 0.5, alpha =1) + labs(title = "ES1 HistSQ", x="Date", y= "HistSQ") # Interactive viewer using plotly ##ES1.df %>% ##plot_ly(x = ~date, type = "ohlc", ## open = ~PX_OPEN, close = ~PX_LAST, ## high = ~PX_HIGH, low = ~PX_LOW) %>% ## layout(title="ES1 OHLC", ## xaxis = list(rangeslider = list (visible = F))) #VG1 Comdty # Price chart VG1_pricechart = ggplot(data= VG1.df, aes(x=date, y = PX_LAST)) + geom_linerange(aes(ymin=PX_LOW, ymax=PX_HIGH)) + theme_bw() + labs(title="VG1 Price Range") + labs(x = "Date", y = "Price")+ geom_line(aes(x=date, y=EMA10), colour = "red") + geom_line(aes(x=date,y=EMA40), color = "blue") + geom_line(aes(x=date,y=EMA144), color = "green") # Daily Close VG1_dailyclose = ggplot(data = VG1.df, aes(x = date, y = PX_LAST)) + geom_line() + labs(x = "Date", y = "Price") + labs(title = "VG1 Daily Close") + geom_line(aes(x=date, y=EMA10), colour = "red") + geom_line(aes(x=date,y=EMA40), color = "blue") + geom_line(aes(x=date,y=EMA144), color = "green") # RSI Chart VG1_RSI = ggplot(data = VG1.df) + geom_line(aes(x=date,y=RSI),colour="red") + geom_hline(aes(yintercept = 70),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) + geom_hline(aes(yintercept = 30),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) + scale_y_continuous(breaks= c(30,50,70)) + labs(x = "Date", y = "RSI") + labs(title = "VG1 RSI") # Stochastic VG1_stoc = ggplot(data = VG1.df) + geom_line(aes(x=date,y=fastD),colour="red") + geom_line(aes(x=date,y=slowD), colour="blue") + geom_hline(aes(yintercept = 80),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) + geom_hline(aes(yintercept = 20),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) + scale_y_continuous(breaks= c(20,50,80)) + labs(x = "Date", y = "Stochastic") + labs(title = "VG1 Stochastic") # ATR VG1_ATR = ggplot(data = VG1.df) + geom_line(aes(x=date,y=ATR),colour="black") + labs(x = "Date", y = "ATR") + labs(title = "VG1 ATR") # Price frequencies VG1_pricefrequencies = ggplot(data=VG1.df, aes(x=VG1.df$PX_LAST)) + geom_histogram(breaks=seq(2900, 3600, by=10), col="red", fill="green", alpha = .2) + labs(title="VG1 Price frequencies", x="Price", y="Density") # HistSQ VG1_dotsq0 = VG1.df$dotSQ VG1_dotsq0[VG1_dotsq0 == 1] = NA VG1_dotsq1 = VG1.df$dotSQ VG1_dotsq1[VG1_dotsq1 == 0] = NA VG1_dotsq1[VG1_dotsq1 == 1] = 0 VG1_histSQ = ggplot(data=VG1.df) + geom_line(aes(x=date,y=histSQ), colour = "black", linetype = "solid", size = 0.5, alpha =1) + geom_hline(aes(yintercept = 0),colour ="black", linetype = "solid", size = 0.5, alpha =0.5)+ geom_point(aes(x=date, y=VG1_dotsq0),colour = "red", size = 0.5, alpha =1) + geom_point(aes(x=date, y=VG1_dotsq1),colour = "green", size = 0.5, alpha =1) + labs(title = "VG1 HistSQ", x="Date", y= "HistSQ") # Interactive viewer using plotly ##VG1.df %>% ##plot_ly(x = ~date, type = "ohlc", ## open = ~PX_OPEN, close = ~PX_LAST, ## high = ~PX_HIGH, low = ~PX_LOW) %>% ## layout(title="VG1 OHLC", ## xaxis = list(rangeslider = list (visible = F))) #Z1 Comdty # Price chart Z1_pricechart = ggplot(data= Z1.df, aes(x=date, y = PX_LAST)) + geom_linerange(aes(ymin=PX_LOW, ymax=PX_HIGH)) + theme_bw() + labs(title="Z1 Price Range") + labs(x = "Date", y = "Price")+ geom_line(aes(x=date, y=EMA10), colour = "red") + geom_line(aes(x=date,y=EMA40), color = "blue") + geom_line(aes(x=date,y=EMA144), color = "green") # Daily Close Z1_dailyclose = ggplot(data = Z1.df, aes(x = date, y = PX_LAST)) + geom_line() + labs(x = "Date", y = "Price") + labs(title = "Z1 Daily Close") + geom_line(aes(x=date, y=EMA10), colour = "red") + geom_line(aes(x=date,y=EMA40), color = "blue") + geom_line(aes(x=date,y=EMA144), color = "green") # RSI Chart Z1_RSI = ggplot(data = Z1.df) + geom_line(aes(x=date,y=RSI),colour="red") + geom_hline(aes(yintercept = 70),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) + geom_hline(aes(yintercept = 30),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) + scale_y_continuous(breaks= c(30,50,70)) + labs(x = "Date", y = "RSI") + labs(title = "Z1 RSI") # Stochastic Z1_stoc = ggplot(data = Z1.df) + geom_line(aes(x=date,y=fastD),colour="red") + geom_line(aes(x=date,y=slowD), colour="blue") + geom_hline(aes(yintercept = 80),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) + geom_hline(aes(yintercept = 20),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) + scale_y_continuous(breaks= c(20,50,80)) + labs(x = "Date", y = "Stochastic") + labs(title = "Z1 Stochastic") # ATR Z1_ATR = ggplot(data = Z1.df) + geom_line(aes(x=date,y=ATR),colour="black") + labs(x = "Date", y = "ATR") + labs(title = "Z1 ATR") # Price frequencies Z1_pricefrequencies = ggplot(data=Z1.df, aes(x=Z1.df$PX_LAST)) + geom_histogram(breaks=seq(6500, 8000, by=20), col="red", fill="green", alpha = .2) + labs(title="Z1 Price frequencies", x="Price", y="Density") # HistSQ Z1_dotsq0 = Z1.df$dotSQ Z1_dotsq0[Z1_dotsq0 == 1] = NA Z1_dotsq1 = Z1.df$dotSQ Z1_dotsq1[Z1_dotsq1 == 0] = NA Z1_dotsq1[Z1_dotsq1 == 1] = 0 Z1_histSQ = ggplot(data=Z1.df) + geom_line(aes(x=date,y=histSQ), colour = "black", linetype = "solid", size = 0.5, alpha =1) + geom_hline(aes(yintercept = 0),colour ="black", linetype = "solid", size = 0.5, alpha =0.5)+ geom_point(aes(x=date, y=Z1_dotsq0),colour = "red", size = 0.5, alpha =1) + geom_point(aes(x=date, y=Z1_dotsq1),colour = "green", size = 0.5, alpha =1) + labs(title = "Z1 HistSQ", x="Date", y= "HistSQ") # Interactive viewer using plotly ##Z1.df %>% ##plot_ly(x = ~date, type = "ohlc", ## open = ~PX_OPEN, close = ~PX_LAST, ## high = ~PX_HIGH, low = ~PX_LOW) %>% ## layout(title="Z1 OHLC", ## xaxis = list(rangeslider = list (visible = F))) #TY1 Comdty # Price chart TY1_pricechart = ggplot(data= TY1.df, aes(x=date, y = PX_LAST)) + geom_linerange(aes(ymin=PX_LOW, ymax=PX_HIGH)) + theme_bw() + labs(title="TY1 Price Range") + labs(x = "Date", y = "Price")+ geom_line(aes(x=date, y=EMA10), colour = "red") + geom_line(aes(x=date,y=EMA40), color = "blue") + geom_line(aes(x=date,y=EMA144), color = "green") # Daily Close TY1_dailyclose = ggplot(data = TY1.df, aes(x = date, y = PX_LAST)) + geom_line() + labs(x = "Date", y = "Price") + labs(title = "TY1 Daily Close") + geom_line(aes(x=date, y=EMA10), colour = "red") + geom_line(aes(x=date,y=EMA40), color = "blue") + geom_line(aes(x=date,y=EMA144), color = "green") # RSI Chart TY1_RSI = ggplot(data = TY1.df) + geom_line(aes(x=date,y=RSI),colour="red") + geom_hline(aes(yintercept = 70),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) + geom_hline(aes(yintercept = 30),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) + scale_y_continuous(breaks= c(30,50,70)) + labs(x = "Date", y = "RSI") + labs(title = "TY1 RSI") # Stochastic TY1_stoc = ggplot(data = TY1.df) + geom_line(aes(x=date,y=fastD),colour="red") + geom_line(aes(x=date,y=slowD), colour="blue") + geom_hline(aes(yintercept = 80),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) + geom_hline(aes(yintercept = 20),colour ="black", linetype = "dashed", size = 0.5, alpha =0.5) + scale_y_continuous(breaks= c(20,50,80)) + labs(x = "Date", y = "Stochastic") + labs(title = "TY1 Stochastic") # ATR TY1_ATR = ggplot(data = TY1.df) + geom_line(aes(x=date,y=ATR),colour="black") + labs(x = "Date", y = "ATR") + labs(title = "TY1 ATR") # Price frequencies TY1_pricefrequencies = ggplot(data=TY1.df, aes(x=TY1.df$PX_LAST)) + geom_histogram(breaks=seq(115, 130, by=0.5), col="red", fill="green", alpha = .2) + labs(title="TY1 Price frequencies", x="Price", y="Density") # HistSQ TY1_dotsq0 = TY1.df$dotSQ TY1_dotsq0[TY1_dotsq0 == 1] = NA TY1_dotsq1 = TY1.df$dotSQ TY1_dotsq1[TY1_dotsq1 == 0] = NA TY1_dotsq1[TY1_dotsq1 == 1] = 0 TY1_histSQ = ggplot(data=TY1.df) + geom_line(aes(x=date,y=histSQ), colour = "black", linetype = "solid", size = 0.5, alpha =1) + geom_hline(aes(yintercept = 0),colour ="black", linetype = "solid", size = 0.5, alpha =0.5)+ geom_point(aes(x=date, y=TY1_dotsq0),colour = "red", size = 0.5, alpha =1) + geom_point(aes(x=date, y=TY1_dotsq1),colour = "green", size = 0.5, alpha =1) + labs(title = "TY1 HistSQ", x="Date", y= "HistSQ") # Interactive viewer using plotly ##TY1.df %>% ##plot_ly(x = ~date, type = "ohlc", ## open = ~PX_OPEN, close = ~PX_LAST, ## high = ~PX_HIGH, low = ~PX_LOW) %>% ## layout(title="TY1 OHLC", ## xaxis = list(rangeslider = list (visible = F)))
# Arrange generated grobs for pretty printing and generate PDF - Ethel Ngiam colnames1 <- c("Date", "Open", "High", "Low", "Close", "ATR", "sd.ATR", "EMA10", "EMA40", "EMA144", "RSI") colnames2 <- c("Date", "S3", "S2", "S1", "Pivot", "R1", "R2", "R3", "fastK", "fastD", "slowD", "SQ", "histSQ") table1 <- function(tibbledata){ tibbledata %>% ungroup() %>% select(date, PX_OPEN, PX_HIGH, PX_LOW, PX_LAST, ATR, sd.ATR, EMA10, EMA40, EMA144, RSI) %>% tail(21) -> tibbledata2 kable(tibbledata2, col.names = colnames1, align = rep('c', 11))} table2 <- function(tibbledata) { tibbledata %>% ungroup() %>% select(date, S3, S2, S1, Pivot, R1, R2, R3, fastK, fastD, slowD, dotSQ, histSQ) %>% tail(21) -> tibbledata2 kable(tibbledata2, col.names = colnames2, align = rep('c', 13))} cat("RX1") table1(RX1.df) table2(RX1.df) grid.arrange(RX1_pricechart, RX1_dailyclose, RX1_ATR, RX1_RSI, RX1_stoc, RX1_histSQ, nrow=3) cat("\n\n\\pagebreak\n") cat("OAT1") table1(OAT1.df) table2(OAT1.df) grid.arrange(OAT1_pricechart, OAT1_dailyclose, OAT1_ATR, OAT1_RSI, OAT1_stoc, OAT1_histSQ, nrow=3) cat("\n\n\\pagebreak\n") cat("ES1") table1(ES1.df) table2(ES1.df) grid.arrange(ES1_pricechart, ES1_dailyclose, ES1_ATR, ES1_RSI, ES1_stoc, ES1_histSQ, nrow=3) cat("\n\n\\pagebreak\n") cat("IK1") table1(IK1.df) table2(IK1.df) grid.arrange(IK1_pricechart, IK1_dailyclose, IK1_ATR, IK1_RSI, IK1_stoc, IK1_histSQ, nrow=3) cat("\n\n\\pagebreak\n") cat("G 1") table1(G1.df) table2(G1.df) grid.arrange(G1_pricechart, G1_dailyclose, G1_ATR, G1_RSI, G1_stoc, G1_histSQ, nrow=3) cat("\n\n\\pagebreak\n") cat("VG1") table1(VG1.df) table2(VG1.df) grid.arrange(VG1_pricechart, VG1_dailyclose, VG1_ATR, VG1_RSI, VG1_stoc, VG1_histSQ, nrow=3) cat("\n\n\\pagebreak\n") cat("Z 1") table1(Z1.df) table2(Z1.df) grid.arrange(Z1_pricechart, Z1_dailyclose, Z1_ATR, Z1_RSI, Z1_stoc, Z1_histSQ, nrow=3) cat("\n\n\\pagebreak\n")
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