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LOOKING_AT_DAILY.Rmd
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LOOKING_AT_DAILY.Rmd
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---
title: "DAILY PROCESSING with more data"
#author: "CHENRUJIE"
#date: "2022/7/6"
output:
flexdashboard::flex_dashboard:
orientation: rows
vertical_layout: scroll
theme: united
---
```{r setup, include=FALSE}
#Loading All Libraries At Once--------------------------------------------------
library(flexdashboard)
library(lubridate)
library(readxl)
library(readr)
library(zoo)
library(xts)
library(mFilter)
library(timeDate)
library(timeSeries)
library(numDeriv)
library(coda)
library(bayesDccGarch)
library(keras)
library(ggplot2)
library(gridExtra)
library(imputeTS)
library(magrittr)
library(ggpubr)
#Rmarkdown Global Setup--------------------------------------------------
library(knitr)
knitr::opts_chunk$set(echo = FALSE,
message = FALSE,
warning = FALSE,
fig.width = 16,
fig.height = 7)
#Global Enviornment Setup---------------------------------------------------
globalWD <- getwd()
globalWD.data <- file.path(globalWD, "DATA")
globalStartYear <- c(2010)
globalEndYear <- c(as.numeric(year(Sys.Date())))
midtermYear1 <- c(5) #Parameter for midterm output calculation.
AssFun <- new.env() #Enviornment to store assistant functions.
```
```{r MAJOR TARGET DEFINE}
##Defining Variables for Trend and Cycle analysis and comparing.
T1 <- "CU0"
T2 <- "RB0"
T3 <- "CL00Y"
UP1 <- "AL0"
UP2 <- "I0"
UP3 <- "CF0"
UP4 <- "FG0"
UP5 <- "SA0"
DN1 <- "P0"
DN2 <- "Y0"
DN3 <- "I0"
DN4 <- "V0"
DN5 <- "TA0"
CMD.ind <- c(T1, T2, T3,
UP1, UP2, UP3, UP4, UP5,
DN1, DN2, DN3, DN4, DN5)
CUR.ind <- c("GBPUSD", "EURUSD", "AUDUSD", "USDJPY")
```
MacroEco {data-height=3000}
==================================================
### BUILD AT: `r Sys.time()`
All Rights Reserved <br> Rujie Chen <br> 18666712666 <br>
MacroEcoBaselines...... {.tabset .tabset-pills .tabset-fade}
-------------------------------------
### YIELDS PROSPECTS
```{r YIELDS PROSPECT}
Yields.Prospect.text <- matrix(
c("Above 3.00 \n
",
"2.80 \n
",
"Above 2.8 \n
",
"Above 4.00 \n
",
"3.50 \n
",
"Below 3.00 \n
"),
nrow = 3, ncol = 2)
Yields.Prospect.gg <- ggtexttable(Yields.Prospect.text,
rows = c("Harkwish", "Moderate", "Dovish"),
cols = c("CN 10 Year Treasury Yield", "US 10 Year Treasury Yield"),
theme = ttheme(colnames.style = colnames_style(color = "black",
fill = "orange",
size = 18),
rownames.style = rownames_style(color = "black",
fill = "lightblue",
size = 18),
tbody.style = tbody_style(size = 16)))
Yields.Prospect.gg
```
### CURRENCIES PROSPECTS
```{r CURRENCIES PROSPECT}
Currencies.Prospect.text <- matrix(
c("Above 7.00: \n
(1) . \t
(2) Picking up inflation.
",
"Below 7.0: \n
(1) .\t
(2) US Dollar above 100.
",
"6.5: \n
(1) US Dollar Turmoil. \t
(2) Rate cuts. \n
",
"
Above 110: \n
(1) Monetary Tightening. \t
(2) More rate hikes. \n
",
"
100: \n
(1) . \t
(2) Rate cuts. \n
",
"
below 100: \n
(1) . \t
(2) Easing. \n
"),
nrow = 3, ncol = 2)
Currencies.Prospect.gg <- ggtexttable(Currencies.Prospect.text,
rows = c("Harkwish", "Moderate", "Dovish"),
cols = c("CHINA YUAN Offshore", "US Dollar Index"),
theme = ttheme(colnames.style = colnames_style(color = "purple",
fill = "lightgreen",
size = 18),
rownames.style = rownames_style(color = "yellow",
fill = "darkgreen",
size = 18),
tbody.style = tbody_style(size = 16)))
Currencies.Prospect.gg
```
### FS OF YIELDS~CMD_PRICE
```{r Commordity Four Stages}
#In order to depict the model of 4 stages, I used package ggpubr and try to output tabel form of the model.
FourStages_CMD.text <- matrix(
c("
(1) Economic growth. \t
(2) Inflation.
(3) Wars / Trade War. \t
(4) Pandemic Resilient.",
"
(1) Monetary Easing. \t
(2) Global Supply Chain Crunch. \n
",
"
(1) Monetary Tightening. \t
(2) Recession and Deflation. \t
(3) Fighting Inflation. \n
",
"
(1) Economies Slow Down. \t
(2) Political Uncertainties. \t
(3) Unprecedentic Risks. \t"),
nrow = 2, ncol = 2)
FourStage.gg <- ggtexttable(FourStages_CMD.text, rows = c("Yields Rise", "Yield Decline"),
cols = c("CMD UP", "CMD DOWN"),
theme = ttheme(colnames.style = colnames_style(color = "white",
fill = "purple",
size = 18),
rownames.style = rownames_style(color = "blue",
fill = "gold",
size = 18),
tbody.style = tbody_style(size = 16)))
FourStage.gg
```
Status
==================================================
yields STATUS.......... {.tabset .tabset-pills .tabset-fade}
-------------------------------------
1) Status of yields.
```{r Data Preparation: yields}
#Functions---------------------------------------
#Functions to Read yields Data From Excel File
AssFun$read_excel_yields <- function(treasury_name){
#Read Excel File Data.
TD.read <- read_excel(file.path(globalWD.data, "yields.xls"),
col_types = c("text", rep("numeric", length(treasury_name))),
col_names = TRUE
)
colnames(TD.read) <- c("Date", treasury_name)
#Subsetting Into 10 Year Window.
TD.read <- subset.data.frame(TD.read, year(strptime(TD.read[[1]], format = "%Y-%m-%d")) >= globalStartYear)
#Dealing with NAs.
TD.read.na <- as.data.frame(na.approx(TD.read[,2:length(TD.read)]))
TD.read.na <- cbind(TD.read[, 1], TD.read.na)
colnames(TD.read.na) <- c("Date", treasury_name)
#Return Dataframe without NAs.
return(TD.read.na)
}
#Functions for yields to Apply HP Filter and Save to csv Files.
AssFun$hpf_save_yield <- function(proc_data, data_name = NULL, data_date = NULL){
#Applying HP Filter to yields
data.HPF <- hpfilter(na.approx(proc_data), freq=2419200, type=c("lambda"), drift = FALSE)
#Output and Save to csv File if Given the Name.
if(!is.null(data_name)){
data.HPF.output <- as.data.frame(data_date[1:length(data.HPF$cycle)])
data.HPF.output <- cbind(data.HPF.output,
proc_data[1:length(data.HPF$cycle)],
data.HPF$trend,
data.HPF$cycle)
colnames(data.HPF.output) <- c(paste0(data_name, "Date"),
paste0(data_name, "Close"),
paste0(data_name, "_hpft"),
paste0(data_name, "_hpfc"))
write.csv(data.HPF.output,file=paste0(file.path(globalWD, "DailyTDs/"), data_name, "DailyTD.csv"), row.names=FALSE)
}
#Convert the Output Into xts Object and Return.
data.HPF.output.xts <- xts(data.HPF.output[, -1], order.by = data.HPF.output[[1]])
return(data.HPF.output.xts)
}
#Processing--------------------------------------
#Read yields
ref_yields <- c("CN_10yry", "US_10yry", "UK_10yry", "GR_10yry", "IT_10yry", "AU_10yry", #10 year
"CN_5yry", #5 year
"CN_2yry", "US_2yry", #2 year
"INA_10yry", "IND_10yry") #Other Asia Nations.
ref_yields.text <- c("China 10yr Yield",
"US 10yr Yield",
"UK 10yr Yield",
"Germany 10yr Yield",
"Italy 10yr Yield",
"Australia 10yr Yield",
"China 5yr Yield",
"China 2yr Yield",
"US 2yr Yield",
"Indonesia 10yr Yield",
"India 10yr Yield"
)
yields <- AssFun$read_excel_yields(ref_yields)
#Processing Data without India 10yr yield.
yields.HPFs <- list(NULL)
for(i in 1:(length(ref_yields)-1)){
#Processing with Hodrick Prescott Filter and Save to csv Files.
yields.HPFs[i] <- list(AssFun$hpf_save_yield(yields[,i+1], ref_yields[i], as.Date(yields[,1])))
names(yields.HPFs)[i] <- c(paste0(ref_yields[i],"DailyTD.hpf"))
}
#Processing India 10yr yield.
IND.i <- length(ref_yields)
IND.proc_data <- yields[, IND.i + 1]
IND.data_name <- ref_yields[IND.i]
IND.data_date <- as.Date(yields[, 1])
#For IND_10yry, correct mitaken data inputs.
#Applying HP Filter to India 10yr yield
IND.data.HPF <- hpfilter(na.interpolation(IND.proc_data), freq=2419200, type=c("lambda"), drift = FALSE)
#Creating HPF output
IND.data.HPF.output <- as.data.frame(IND.data_date[1:length(IND.data.HPF$cycle)])
IND.data.HPF.output <- cbind(IND.data.HPF.output,
IND.proc_data[1:length(IND.data.HPF$cycle)],
IND.data.HPF$trend,
IND.data.HPF$cycle)
colnames(IND.data.HPF.output) <- c(paste0(IND.data_name, "Date"),
paste0(IND.data_name, "Close"),
paste0(IND.data_name, "_hpft"),
paste0(IND.data_name, "_hpfc"))
#Creating xts output
IND.data.HPF.output.xts <- xts(IND.data.HPF.output[, -1], order.by = IND.data.HPF.output[[1]])
#Bind to yields.HPFs
yields.HPFs[IND.i] <- list(IND.data.HPF.output.xts)
names(yields.HPFs)[IND.i] <- c(paste0(ref_yields[IND.i],"DailyTD.hpf"))
#Data correction process. For dozens of mistaken data inputs.
#For UK_10yry------------------------------------
correct.UK_10yry <- as.data.frame(yields.HPFs$UK_10yryDailyTD.hpf, stringsAsFactors = FALSE)
#"2018-09-11"
correct.UK_10yry[rownames(correct.UK_10yry) == "2018-09-11", ] <-
correct.UK_10yry[rownames(correct.UK_10yry) == "2018-09-10", ]
#"2018-12-03"
correct.UK_10yry[rownames(correct.UK_10yry) == "2018-12-03", ] <-
correct.UK_10yry[rownames(correct.UK_10yry) == "2018-11-30", ]
correct.UK_10yry[rownames(correct.UK_10yry) == "2018-12-02", ] <-
correct.UK_10yry[rownames(correct.UK_10yry) == "2018-11-30", ]
correct.UK_10yry[rownames(correct.UK_10yry) == "2018-12-01", ] <-
correct.UK_10yry[rownames(correct.UK_10yry) == "2018-11-30", ]
#Convert back to xts.
yields.HPFs$UK_10yryDailyTD.hpf <- as.xts(correct.UK_10yry, order.by = as.Date(rownames(correct.UK_10yry)))
#For GR_10yry------------------------------------
correct.GR_10yry <- as.data.frame(yields.HPFs$GR_10yryDailyTD.hpf, stringsAsFactors = FALSE)
#"2018-11-16" to "2018-10-19"
correct.GR_10yry[rownames(correct.GR_10yry) == "2018-11-19", ] <-
correct.GR_10yry[rownames(correct.GR_10yry) == "2018-11-16", ]
correct.GR_10yry[rownames(correct.GR_10yry) == "2018-11-18", ] <-
correct.GR_10yry[rownames(correct.GR_10yry) == "2018-11-16", ]
correct.GR_10yry[rownames(correct.GR_10yry) == "2018-11-17", ] <-
correct.GR_10yry[rownames(correct.GR_10yry) == "2018-11-16", ]
#Convert back to xts.
yields.HPFs$GR_10yryDailyTD.hpf <- as.xts(correct.GR_10yry, order.by = as.Date(rownames(correct.GR_10yry)))
#For IND_10yry------------------------------------
#correct.IND_10yry <- as.data.frame(yields.HPFs$IND_10yryDailyTD.hpf, stringsAsFactors = FALSE)
#"2018-03-01" to "2018-03-02"
#correct.IND_10yry[rownames(correct.IND_10yry) == "2018-03-02", ] <-
# correct.IND_10yry[rownames(correct.IND_10yry) == "2018-03-01", ]
#Convert back to xts.
#yields.HPFs$IND_10yryDailyTD.hpf <- as.xts(correct.IND_10yry, order.by = as.Date(rownames(correct.IND_10yry)))
#Set the yields to be focused on.
ref_yields.major <- c("CN_10yry", "US_10yry", "UK_10yry", "GR_10yry", "CN_5yry", "CN_2yry")
ref_yields.major.text <- c("China 10yr Yield",
"US 10yr Yield",
"UK 10yr Yield",
"GR_10yr Yield",
"China 10yr Yield",
"China 2yr Yield")
## Step to write down the reference index and text of commoredity trading data for further use.
ref_yields.output.df <- rbind(ref_yields, ref_yields.text)
write.csv(ref_yields.output.df, file=paste0("DailyTDs/ref_yields.csv"), row.names=FALSE)
```
```{r}
#At This Chunks, we Defined i2 for Automatic Output
i2 <- 1
```
### `r ref_yields[i2]`
```{r include=FALSE}
par(mai=c(0.5,0.5,0.5,0.5))
par(mfcol=c(1,1))
plot(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][, -3],
main=ref_yields.text[i2],observation.based = TRUE)
```
```{r}
addSeries(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][, 3],
main=paste0(ref_yields.text[i2], " HPFC"))
```
### `r ref_yields[i2]`[CL]
```{r}
par(mfcol=c(1,2))
plot(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][,-3][paste(toString(globalEndYear-1),
toString(globalEndYear),sep="/")],
main=paste0(ref_yields.text[i2]," in 1 Year."),
observation.based = TRUE)
addSeries(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][,3][paste(toString(globalEndYear-1),
toString(globalEndYear),sep="/")],
main=paste0(ref_yields.text[i2]," HPFC in 1 Year."))
```
```{r}
#At This Chunks, we Defined i2 for Automatic Output
i2 <- 2
```
### `r ref_yields[i2]`
```{r include=FALSE}
par(mai=c(0.5,0.5,0.5,0.5))
par(mfcol=c(1,1))
plot(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][, -3],
main=ref_yields.text[i2],observation.based = TRUE)
```
```{r}
addSeries(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][, 3],
main=paste0(ref_yields.text[i2], " HPFC"))
```
### `r ref_yields[i2]`[CL]
```{r}
par(mfcol=c(1,2))
plot(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][,-3][paste(toString(globalEndYear-1),
toString(globalEndYear),sep="/")],
main=paste0(ref_yields.text[i2]," in 1 Year."),
observation.based = TRUE)
addSeries(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][,3][paste(toString(globalEndYear-1),
toString(globalEndYear),sep="/")],
main=paste0(ref_yields.text[i2]," HPFC in 1 Year."))
```
```{r}
#At This Chunks, we Defined i2 for Automatic Output
i2 <- 3
```
### `r ref_yields[i2]`
```{r include=FALSE}
par(mai=c(0.5,0.5,0.5,0.5))
par(mfcol=c(1,1))
plot(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][, -3],
main=ref_yields.text[i2],observation.based = TRUE)
```
```{r}
addSeries(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][, 3],
main=paste0(ref_yields.text[i2], " HPFC"))
```
### `r ref_yields[i2]`[CL]
```{r}
par(mfcol=c(1,2))
plot(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][,-3][paste(toString(globalEndYear-1),
toString(globalEndYear),sep="/")],
main=paste0(ref_yields.text[i2]," in 1 Year."),
observation.based = TRUE)
addSeries(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][,3][paste(toString(globalEndYear-1),
toString(globalEndYear),sep="/")],
main=paste0(ref_yields.text[i2]," HPFC in 1 Year."))
```
```{r}
#At This Chunks, we Defined i2 for Automatic Output
i2 <- 4
```
### `r ref_yields[i2]`
```{r include=FALSE}
par(mai=c(0.5,0.5,0.5,0.5))
par(mfcol=c(1,1))
plot(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][, -3],
main=ref_yields.text[i2],observation.based = TRUE)
```
```{r}
addSeries(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][, 3],
main=paste0(ref_yields.text[i2], " HPFC"))
```
### `r ref_yields[i2]`[CL]
```{r}
par(mfcol=c(1,2))
plot(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][,-3][paste(toString(globalEndYear-1),
toString(globalEndYear),sep="/")],
main=paste0(ref_yields.text[i2]," in 1 Year."),
observation.based = TRUE)
addSeries(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][,3][paste(toString(globalEndYear-1),
toString(globalEndYear),sep="/")],
main=paste0(ref_yields.text[i2]," HPFC in 1 Year."))
```
```{r}
#At This Chunks, we Defined i2 for Automatic Output
i2 <- 5
```
### `r ref_yields[i2]`
```{r include=FALSE}
par(mai=c(0.5,0.5,0.5,0.5))
par(mfcol=c(1,1))
plot(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][, -3],
main=ref_yields.text[i2],observation.based = TRUE)
```
```{r}
addSeries(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][, 3],
main=paste0(ref_yields.text[i2], " HPFC"))
```
### `r ref_yields[i2]`[CL]
```{r}
par(mfcol=c(1,2))
plot(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][,-3][paste(toString(globalEndYear-1),
toString(globalEndYear),sep="/")],
main=paste0(ref_yields.text[i2]," in 1 Year."),
observation.based = TRUE)
addSeries(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][,3][paste(toString(globalEndYear-1),
toString(globalEndYear),sep="/")],
main=paste0(ref_yields.text[i2]," HPFC in 1 Year."))
```
```{r}
#At This Chunks, we Defined i2 for Automatic Output
i2 <- 6
```
### `r ref_yields[i2]`
```{r include=FALSE}
par(mai=c(0.5,0.5,0.5,0.5))
par(mfcol=c(1,1))
plot(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][, -3],
main=ref_yields.text[i2],observation.based = TRUE)
```
```{r}
addSeries(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][, 3],
main=paste0(ref_yields.text[i2], " HPFC"))
```
### `r ref_yields[i2]`[CL]
```{r}
par(mfcol=c(1,2))
plot(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][,-3][paste(toString(globalEndYear-1),
toString(globalEndYear),sep="/")],
main=paste0(ref_yields.text[i2]," in 1 Year."),
observation.based = TRUE)
addSeries(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][,3][paste(toString(globalEndYear-1),
toString(globalEndYear),sep="/")],
main=paste0(ref_yields.text[i2]," HPFC in 1 Year."))
```
```{r}
#At This Chunks, we Defined i2 for Automatic Output
i2 <- 7
```
### `r ref_yields[i2]`
```{r include=FALSE}
par(mai=c(0.5,0.5,0.5,0.5))
par(mfcol=c(1,1))
plot(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][, -3],
main=ref_yields.text[i2],observation.based = TRUE)
```
```{r}
addSeries(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][, 3],
main=paste0(ref_yields.text[i2], " HPFC"))
```
### `r ref_yields[i2]`[CL]
```{r}
par(mfcol=c(1,2))
plot(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][,-3][paste(toString(globalEndYear-1),
toString(globalEndYear),sep="/")],
main=paste0(ref_yields.text[i2]," in 1 Year."),
observation.based = TRUE)
addSeries(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][,3][paste(toString(globalEndYear-1),
toString(globalEndYear),sep="/")],
main=paste0(ref_yields.text[i2]," HPFC in 1 Year."))
```
```{r}
#At This Chunks, we Defined i2 for Automatic Output
i2 <- 8
```
### `r ref_yields[i2]`
```{r include=FALSE}
par(mai=c(0.5,0.5,0.5,0.5))
par(mfcol=c(1,1))
plot(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][, -3],
main=ref_yields.text[i2],observation.based = TRUE)
```
```{r}
addSeries(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][, 3],
main=paste0(ref_yields.text[i2], " HPFC"))
```
### `r ref_yields[i2]`[CL]
```{r}
par(mfcol=c(1,2))
plot(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][,-3][paste(toString(globalEndYear-1),
toString(globalEndYear),sep="/")],
main=paste0(ref_yields.text[i2]," in 1 Year."),
observation.based = TRUE)
addSeries(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][,3][paste(toString(globalEndYear-1),
toString(globalEndYear),sep="/")],
main=paste0(ref_yields.text[i2]," HPFC in 1 Year."))
```
```{r}
#At This Chunks, we Defined i2 for Automatic Output
i2 <- 9
```
### `r ref_yields[i2]`
```{r include=FALSE}
par(mai=c(0.5,0.5,0.5,0.5))
par(mfcol=c(1,1))
plot(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][, -3],
main=ref_yields.text[i2],observation.based = TRUE)
```
```{r}
addSeries(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][, 3],
main=paste0(ref_yields.text[i2], " HPFC"))
```
### `r ref_yields[i2]`[CL]
```{r}
par(mfcol=c(1,2))
plot(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][,-3][paste(toString(globalEndYear-1),
toString(globalEndYear),sep="/")],
main=paste0(ref_yields.text[i2]," in 1 Year."),
observation.based = TRUE)
addSeries(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][,3][paste(toString(globalEndYear-1),
toString(globalEndYear),sep="/")],
main=paste0(ref_yields.text[i2]," HPFC in 1 Year."))
```
```{r}
#At This Chunks, we Defined i2 for Automatic Output
i2 <- 10
```
### `r ref_yields[i2]`
```{r include=FALSE}
par(mai=c(0.5,0.5,0.5,0.5))
par(mfcol=c(1,1))
plot(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][, -3],
main=ref_yields.text[i2],observation.based = TRUE)
```
```{r}
addSeries(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][, 3],
main=paste0(ref_yields.text[i2], " HPFC"))
```
### `r ref_yields[i2]`[CL]
```{r}
par(mfcol=c(1,2))
plot(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][,-3][paste(toString(globalEndYear-1),
toString(globalEndYear),sep="/")],
main=paste0(ref_yields.text[i2]," in 1 Year."),
observation.based = TRUE)
addSeries(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][,3][paste(toString(globalEndYear-1),
toString(globalEndYear),sep="/")],
main=paste0(ref_yields.text[i2]," HPFC in 1 Year."))
```
```{r}
#At This Chunks, we Defined i2 for Automatic Output
i2 <- 11
```
### `r ref_yields[i2]`
```{r include=FALSE}
par(mai=c(0.5,0.5,0.5,0.5))
par(mfcol=c(1,1))
plot(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][, -3],
main=ref_yields.text[i2],observation.based = TRUE)
```
```{r}
addSeries(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][, 3],
main=paste0(ref_yields.text[i2], " HPFC"))
```
### `r ref_yields[i2]`[CL]
```{r}
par(mfcol=c(1,2))
plot(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][,-3][paste(toString(globalEndYear-1),
toString(globalEndYear),sep="/")],
main=paste0(ref_yields.text[i2]," in 1 Year."),
observation.based = TRUE)
addSeries(yields.HPFs[[paste0(ref_yields[i2], 'DailyTD.hpf')]][,3][paste(toString(globalEndYear-1),
toString(globalEndYear),sep="/")],
main=paste0(ref_yields.text[i2]," HPFC in 1 Year."))
```
COMMORDITIES(1) {.tabset .tabset-fade}
-------------------------------------
2) Status of Trade Data.(1)
```{r Data Preparation: Trade Data}
setwd(globalWD)
#Functions---------------------------------------
#Functions to Read Trading Data From Excel File
AssFun$read_excel_TD <- function(contract_name){
#Read Excel File Data.
TD.read <- read_excel(file.path(globalWD.data, paste0(contract_name, ".xls")),
col_types = c("text", "text", "date",
"numeric", "numeric", "numeric",
"numeric", "numeric", "numeric",
"numeric", "numeric", "numeric"),
col_names = TRUE
)
colnames(TD.read) <- c(paste0(contract_name, "Code"),
paste0(contract_name, "Contract"),
paste0(contract_name, "Date"),
paste0(contract_name, "Open"),
paste0(contract_name, "High"),
paste0(contract_name, "Low"),
paste0(contract_name, "Close"),
paste0(contract_name, "Chg"),
paste0(contract_name, "RateofChg"),
paste0(contract_name, "Vol"),
paste0(contract_name, "Amn"),
paste0(contract_name, "Settle"))
TD.read <- TD.read[, -12]
TD.read.na <- na.omit(TD.read)
#Subsetting Into 10 Year Window.
TD.read.na <- subset.data.frame(TD.read.na,
year(TD.read.na[[3]]) >= globalStartYear)
#Return Dataframe without NA.
return(TD.read.na)
}
AssFun$read_excel_TD2 <- function(contract_name){
#Read Excel File Data.
TD.read <- read_excel(file.path(globalWD.data, paste0(contract_name, ".xls")),
col_types = c("text", "text", "date",
"numeric", "numeric", "numeric",
"numeric", "numeric", "numeric",
"numeric", "numeric"),
col_names = TRUE
)
colnames(TD.read) <- c(paste0(contract_name, "Code"),
paste0(contract_name, "Contract"),
paste0(contract_name, "Date"),
paste0(contract_name, "Open"),
paste0(contract_name, "High"),
paste0(contract_name, "Low"),
paste0(contract_name, "Close"),
paste0(contract_name, "Chg"),
paste0(contract_name, "RateofChg"),
paste0(contract_name, "Vol"),
paste0(contract_name, "Amn"))
TD.read.na <- na.omit(TD.read)
#Subsetting Into 10 Year Window.
TD.read.na <- subset.data.frame(TD.read.na,
year(TD.read.na[[3]]) >= globalStartYear)
#Return Dataframe without NA.
return(TD.read.na)
}
#Functions to Apply HPfilters to Data And Save it to csv Files
AssFun$hpf_save_TD <- function(proc_data, data_name = NULL, data_date = NULL){
#Applying HP Filter
data.HPF <- hpfilter(proc_data, freq=2419200, type=c("lambda"), drift = FALSE)
#Make sure file storage dirctor be created.
if(!dir.exists("DailyTDs")){
dir.create("DailyTDs")
}
#Output and Save to csv File if Given the Name.
if(!is.null(data_name)){
data.HPF.output <- as.data.frame(data_date)
data.HPF.output <- cbind(data.HPF.output,
proc_data,
data.HPF$trend,
data.HPF$cycle)
colnames(data.HPF.output) <- c(paste0(data_name, "Date"),
paste0(data_name, "Close"),
paste0(data_name, "_hpft"),
paste0(data_name, "_hpfc"))
write.csv(data.HPF.output,file=paste0("DailyTDs/", data_name, "DailyTD.csv"), row.names=FALSE)
}
#Convert the Output Into xts Object and Return.
data.HPF.output.xts <- xts(data.HPF.output[, -1], order.by = data.HPF.output[[1]])
return(data.HPF.output.xts)
}
#Processing--------------------------------------
#Read Trade Data.
ref_TD1 <- c("IF00C1", "IH00C1", "CU0", "T00C1", "TF00C1",
"CL00Y", "AU0", "AG0", "HC0",
"TA0", "L0", "CF0", "UR0", "JM0",
"TY00Y", "AL0", "MA0", "FV00Y", "V0", "RB0",
"FU0", "BU0", "ZN0", "LCPT", "RU0", "LH0", "ZS00Y", "PK0",
"C0", "SR0", "PP0", "FG0", "SA0", "P0", "I0", "M0", "PG0", "Y0", "RM0", "EB0", "EG0")
ref_TD2 <- c("SCM", "SPX", "FTSE", "LUM")
ref_TD <- c(ref_TD1, ref_TD2)
ref_TD.text <- c("CFFEX CSI 300 Futures",
"CFFEX A50 Futures",
"SHFE Copper Futures",
"CFFEX 10yr Treasury Futures",
"CFFEX 5yr Treasury Futures",
"NYMEX CRUDE OIL Futures",
"SHFE Gold Futures",
"SHFE SILVER Futures",
"SHFE HOT COIL Futures",
"CZCE Purified Terephthalic Acid Futures",
"DCE Lastic Futures",
"CZCE COTTON Futures",
"CZCE UREA Futures",
"DCE J M Futures",
"U.S. 10y Treasury Bond Futures",
"SHFE ALUMINUM Futures",
"CZCE MATHON Futures",
"U.S. 5y Treasury Bond Futures",
"DCE PVC Futures",
"SHFE Rebar Futures",
"SHFE FUEL Futures",
"SHFE Bitumen Futures",
"SHFE Znic Futures",
"LME COPPER 3Months",
"SHFE RUBBER Futures",
"DCE PORK Futures",
"CBOT SOYBEAN Futurres",
"DCE PEANUTS Futures",
"DCE CORN Futures",
"CZCE SUGAR Futures",
"DCE PP Futures",
"CZCE FIBER GLASS Futures",
"CZCE SODIUM CARBONATE Futures",
"DCE Palm Oil Futures",
"DCE Ironore Futures",
"DCE Soymeal Futures",
"DCE PETROL GAS Futures",
"DCE SoyOil Futures",
"CZCE Rapeseed Meal Futures",
"CZCE EB Futures",
"DCE Ethylene Glycol Futures",
"INE CRUDE Futures",
"S & P 500 Index",
"U.K. FTSE100",
"INE LOW SULFUR FUEL"
)
#Set the targets and locker to be focused on.
ref_TD.major <- c("RB0", "CU0", "CL00Y")
ref_TD.major.text <- c("SHFE REBAR Futures",
"SHFE COPPER Futures",
"NYMEX CRUDE Futures"
)
DailyTD <- list(NULL)
DailyTD.HPFs <- list(NULL)
##ref_TD1
for(i in 1:length(ref_TD1)){
#Reading Data from Excel Files
DailyTD[i] <- list(AssFun$read_excel_TD(ref_TD1[i]))
names(DailyTD)[i] <- c(paste0(ref_TD1[i],"DailyTD"))
#Processing with Hodrick Prescott Filter and Save to csv Files.
DailyTD.HPFs[i] <- list(AssFun$hpf_save_TD(DailyTD[[paste0(ref_TD1[i],'DailyTD')]][[paste0(ref_TD1[i], 'Close')]],
ref_TD1[i],
DailyTD[[paste0(ref_TD1[i], 'DailyTD')]][[paste0(ref_TD1[i], 'Date')]]))
names(DailyTD.HPFs)[i] <- c(paste0(ref_TD1[i],"DailyTD.hpf"))
}
##ref_TD2
ref_i <- length(ref_TD1)
for(i in 1:length(ref_TD2)){
#Reading Data from Excel Files
DailyTD[i + ref_i] <- list(AssFun$read_excel_TD2(ref_TD2[i]))
names(DailyTD)[i + ref_i] <- c(paste0(ref_TD2[i],"DailyTD"))
#Processing with Hodrick Prescott Filter and Save to csv Files.
DailyTD.HPFs[i + ref_i] <- list(AssFun$hpf_save_TD(DailyTD[[paste0(ref_TD2[i],'DailyTD')]][[paste0(ref_TD2[i], 'Close')]],
ref_TD2[i],
DailyTD[[paste0(ref_TD2[i], 'DailyTD')]][[paste0(ref_TD2[i], 'Date')]]))
names(DailyTD.HPFs)[i + ref_i] <- c(paste0(ref_TD2[i],"DailyTD.hpf"))
}
## Step to write down the reference index and text of commoredity trading data for further use.
ref_TD.output.df <- rbind(ref_TD, ref_TD.text)
write.csv(ref_TD.output.df, file=paste0("DailyTDs/ref_TD.csv"), row.names=FALSE)
```
```{r}
#At This Chunks, we Defined i2 for Automatic Output
i2 <- 1
```
### `r ref_TD[i2]`
```{r include=FALSE}
par(mai=c(0.5,0.5,0.5,0.5))
par(mfcol=c(1,1))
plot(DailyTD.HPFs[[paste0(ref_TD[i2], 'DailyTD.hpf')]][, -3],main=ref_TD.text[i2],observation.based = TRUE)
```
```{r}
addSeries(DailyTD.HPFs[[paste0(ref_TD[i2], 'DailyTD.hpf')]][, 3],main=paste0(ref_TD.text[i2], " HPFC"))
```
### `r ref_TD[i2]`[CL]
```{r}
par(mfcol=c(1,2))
plot(DailyTD.HPFs[[paste0(ref_TD[i2], 'DailyTD.hpf')]][,-3][paste(toString(globalEndYear-1),
toString(globalEndYear),sep="/")],
main=paste0(ref_TD.text[i2]," in 1 Year."),
observation.based = TRUE)
addSeries(DailyTD.HPFs[[paste0(ref_TD[i2], 'DailyTD.hpf')]][,3][paste(toString(globalEndYear-1),
toString(globalEndYear),sep="/")],main=paste0(ref_TD.text[i2]," HPFC in 1 Year."))
```
```{r}
#At This Chunks, we Defined i2 for Automatic Output
i2 <- 2
```
### `r ref_TD[i2]`
```{r include=FALSE}
par(mai=c(0.5,0.5,0.5,0.5))
par(mfcol=c(1,1))
plot(DailyTD.HPFs[[paste0(ref_TD[i2], 'DailyTD.hpf')]][, -3],main=ref_TD.text[i2],observation.based = TRUE)
```
```{r}
addSeries(DailyTD.HPFs[[paste0(ref_TD[i2], 'DailyTD.hpf')]][, 3],main=paste0(ref_TD.text[i2], " HPFC"))
```
### `r ref_TD[i2]`[CL]
```{r}
par(mfcol=c(1,2))
plot(DailyTD.HPFs[[paste0(ref_TD[i2], 'DailyTD.hpf')]][,-3][paste(toString(globalEndYear-1),
toString(globalEndYear),sep="/")],
main=paste0(ref_TD.text[i2]," in 1 Year."),
observation.based = TRUE)
addSeries(DailyTD.HPFs[[paste0(ref_TD[i2], 'DailyTD.hpf')]][,3][paste(toString(globalEndYear-1),
toString(globalEndYear),sep="/")],main=paste0(ref_TD.text[i2]," HPFC in 1 Year."))
```
```{r}
#At This Chunks, we Defined i2 for Automatic Output
i2 <- 3
```
### `r ref_TD[i2]`
```{r include=FALSE}
par(mai=c(0.5,0.5,0.5,0.5))
par(mfcol=c(1,1))
plot(DailyTD.HPFs[[paste0(ref_TD[i2], 'DailyTD.hpf')]][, -3],main=ref_TD.text[i2],observation.based = TRUE)
```
```{r}
addSeries(DailyTD.HPFs[[paste0(ref_TD[i2], 'DailyTD.hpf')]][, 3],main=paste0(ref_TD.text[i2], " HPFC"))
```
### `r ref_TD[i2]`[CL]
```{r}
par(mfcol=c(1,2))
plot(DailyTD.HPFs[[paste0(ref_TD[i2], 'DailyTD.hpf')]][,-3][paste(toString(globalEndYear-1),
toString(globalEndYear),sep="/")],
main=paste0(ref_TD.text[i2]," in 1 Year."),
observation.based = TRUE)
addSeries(DailyTD.HPFs[[paste0(ref_TD[i2], 'DailyTD.hpf')]][,3][paste(toString(globalEndYear-1),
toString(globalEndYear),sep="/")],main=paste0(ref_TD.text[i2]," HPFC in 1 Year."))
```
```{r}
#At This Chunks, we Defined i2 for Automatic Output
i2 <- 4
```
### `r ref_TD[i2]`
```{r include=FALSE}
par(mai=c(0.5,0.5,0.5,0.5))
par(mfcol=c(1,1))
plot(DailyTD.HPFs[[paste0(ref_TD[i2], 'DailyTD.hpf')]][, -3],main=ref_TD.text[i2],observation.based = TRUE)
```
```{r}
addSeries(DailyTD.HPFs[[paste0(ref_TD[i2], 'DailyTD.hpf')]][, 3],main=paste0(ref_TD.text[i2], " HPFC"))
```