将 shiny 与 Quantstrat 回测相结合
Combining shiny with Quantstrat backtests
我正在尝试制作一个网络应用程序，目的是使用 quantstrat。但是，我在整合两者时遇到了一些困难。没有关于此的文档，因此很难找到一个起点。这是我现在拥有的代码。如果您能让我知道我做错了什么，将不胜感激。谢谢
library(shiny)
library(devtools)
library(quantmod)
library(quantstrat)
library(TTR)
library(png)
library(dplyr)
Sys.setenv(TZ = "UTC")
currency('USD')
ui <- fluidPage(
# Application title
titlePanel("myfirst"),
sidebarLayout(
sidebarPanel(
selectInput(
"stocks", label = "chose stock", choices =
c("AAPL", "CAT")
),
dateInput("init_date", "chose init date",
value = Sys.Date() -100),
dateInput("start_date", "chose start date",
value = Sys.Date() - 99),
dateInput("end_date", "chose end date",
value = Sys.Date()),
selectInput("init_equity", "starting
equity", choices = c(1000, 50000))
),
mainPanel(
plotOutput("plot"),
textOutput("text")
)
)
)
server <- function(input, output) {
init_date = reactive({
input$init_date
})
start_date = reactive({
input$start_date
})
end_date = reactive({
input$end_date
})
init_equity = reactive({
input$init_equity
})
V = reactive({
getSymbols(input$stocks, from = start_date(),
to = end_date(), index.class = "POSIXct",
adjust = T)
})
observe({
stock(input$stocks, currency = "USD", multiplier
= 1)
})
portfolio.st = account.st = strategy.st =
"my.first"
rm.strat(portfolio.st)
rm.strat(account.st)
observe({
initPortf(name = portfolio.st,
symbols = "V",
initDate = init_date())
initAcct(name = account.st,
portfolios = portfolio.st,
initDate = init_date(),
initEq = init_equity())
initOrders(portfolio = portfolio.st,
symbols = "V",
initDate = init_date()
)
strategy(strategy.st, store = T)
})
observe({ add.indicator(strategy = strategy.st,
name = "SMA",
arguments = list(x =
quote(Cl(mktdata)),
n = 10),
label = "nFast")
add.indicator(strategy = strategy.st,
name = "SMA",
arguments = list(x =
quote(Cl(mktdata)),
n = 30),
label = "nSlow")
add.signal(strategy = strategy.st,
name="sigCrossover",
arguments = list(columns = c("nFast", "nSlow"),
relationship = "gte"),
label = "long")
add.signal(strategy = strategy.st,
name="sigCrossover",
arguments = list(columns = c("nFast", "nSlow"),
relationship = "lt"),
label = "short")
add.rule(strategy = strategy.st,
name = "ruleSignal",
arguments = list(sigcol = "long",
sigval = TRUE,
orderqty = 100,
ordertype = "stoplimit",
orderside = "long",
threshold = 0.0005,
prefer = "High",
TxnFees = -10,
replace = FALSE),
type = "enter",
label = "EnterLONG")
add.rule(strategy.st,
name = "ruleSignal",
arguments = list(sigcol = "short",
sigval = TRUE,
orderqty = -100,
ordertype = "stoplimit",
threshold = -0.005,
orderside = "short",
replace = FALSE,
TxnFees = -10,
prefer = "Low"),
type = "enter",
label = "EnterSHORT")
add.rule(strategy.st,
name = "ruleSignal",
arguments = list(sigcol = "short",
sigval = TRUE,
orderside = "long",
ordertype = "market",
orderqty = "all",
TxnFees = -10,
replace = TRUE),
type = "exit",
label = "Exit2SHORT")
add.rule(strategy.st,
name = "ruleSignal",
arguments = list(sigcol = "long",
sigval = TRUE,
orderside = "short",
ordertype = "market",
orderqty = "all",
TxnFees = -10,
replace = TRUE),
type = "exit",
label = "Exit2LONG")
applyStrategy(strategy.st, portfolios = portfolio.st)
updatePortf(portfolio.st)
updateAcct(account.st)
updateEndEq(account.st)
})
output$plot = reactive(
chart.Posn(portfolio.st, Symbol = "V")
)
}
# Run the application
shinyApp(ui = ui, server = server)
有趣的想法。由于交易工具的市场数据存储在本地环境中的名称与其 symbols/tickers 相同的变量的性质，您尝试做的事情有点具有挑战性。
此外，您的闪亮应用程序有些奇怪；请注意如何使用 reactive({、isolate({ 和其他服务器组件。例如，当你有像
这样的服务器对象时
start_date = reactive({
input$start_date
})`
是多余的。
这是一个可以实现您想要实现的目标的示例。我尽量使变量名称与您的示例保持一致。
您可能需要重新考虑您的工作流程：我认为您应该 运行 在 quantstrat 中独立于 shiny 进行大批量模拟，然后将结果保存到磁盘。然后在启动 Shiny 应用程序时从磁盘加载这些结果。不过，这个示例有望解决您的任何疑惑。
此外，您应该注意通过 getSymbols 从雅虎请求数据的频率。我在下面所做的是在应用程序首次启动时仅请求一次数据，并将市场数据存储在名为 rawdata 的环境中的符号中。然后，如果您停止并再次重新启动您的应用程序，您将不会继续向雅虎请求数据（当他们限制您在一段时间内可以下载的数量时，这可能会给您带来错误）。
# Could put these in global.R, these global variables are "hard coded" ----------------
min_date_barrier <- "2012-01-01"
max_date_barrier <- "2019-04-17"
stock_universe <- c("AAPL", "CAT", "BB")
# These variables won't change when the app launches, so hard code them too:
Sys.setenv(TZ = "UTC")
currency('USD')
stock(stock_universe, currency = "USD", multiplier = 1)
portfolio.st <- account.st <- strategy.st <- "my.first"
# In here, store the original market data which contains your full range of possible values for the market data:
# Don't keep requesting data frequently otherwise you won't be able to download the data temporarily.
if (!exists("rawdata")) {
rawdata <- new.env()
assign("rawdata", rawdata, envir = .GlobalEnv)
lapply(stock_universe, function(sym) {
# if (exists(sym, envir = rawdata)) {
# message("Have already downloaded data for ", sym)
# return()
# } else {
getSymbols(stock_universe,
env = rawdata, # important to specify environment
from = min_date_barrier,
to = max_date_barrier,
adjust = T, auto.assign = TRUE)
#}
return()
})
}
# UI ----------------------------------------------------------------------
ui <- fluidPage(
# Application title
titlePanel("myfirst"),
sidebarLayout(
sidebarPanel(
selectInput(
"stock", label = "Choose stock", choices = stock_universe
),
dateInput("start_date", "Choose start date",
value = "2018-02-03"),
dateInput("end_date", "Choose end date",
value = "2019-04-10"),
selectInput("init_equity", "starting
equity", choices = c(1000, 50000))
),
mainPanel(
plotOutput("plot_backtest"),
verbatimTextOutput("results")
)
)
)
# server ------------------------------------------------------------------
server <- function(input, output, session) {
# all your reactives don't make sense -- only use the inputs when you need them on the server side
backtest_setup <- reactive({
# need these input variables in this reactive to avoid bugs in the app when you change the time range:
input$start_date
input$end_date
rm.strat(portfolio.st, silent = FALSE)
initPortf(name = portfolio.st,
symbols = input$stock, #------------------------ correct way to apply the "stock" input
initDate = "2000-01-01")
initAcct(name = account.st,
portfolios = portfolio.st,
initDate = "2000-01-01",
initEq = as.numeric(input$init_equity)) # convert equity to numeric from string
initOrders(portfolio = portfolio.st,
symbols = input$stock, # ----------------------------------
initDate = "2000-01-01"
)
strategy(strategy.st, store = T)
add.indicator(strategy = strategy.st,
name = "SMA",
arguments = list(x =
quote(Cl(mktdata)),
n = 10),
label = "nFast")
add.indicator(strategy = strategy.st,
name = "SMA",
arguments = list(x =
quote(Cl(mktdata)),
n = 30),
label = "nSlow")
add.signal(strategy = strategy.st,
name="sigCrossover",
arguments = list(columns = c("nFast", "nSlow"),
relationship = "gte"),
label = "long")
add.signal(strategy = strategy.st,
name="sigCrossover",
arguments = list(columns = c("nFast", "nSlow"),
relationship = "lt"),
label = "short")
add.rule(strategy = strategy.st,
name = "ruleSignal",
arguments = list(sigcol = "long",
sigval = TRUE,
orderqty = 100,
ordertype = "stoplimit",
orderside = "long",
threshold = 0.0005,
prefer = "High",
TxnFees = -10,
replace = FALSE),
type = "enter",
label = "EnterLONG")
add.rule(strategy.st,
name = "ruleSignal",
arguments = list(sigcol = "short",
sigval = TRUE,
orderqty = -100,
ordertype = "stoplimit",
threshold = -0.005,
orderside = "short",
replace = FALSE,
TxnFees = -10,
prefer = "Low"),
type = "enter",
label = "EnterSHORT")
add.rule(strategy.st,
name = "ruleSignal",
arguments = list(sigcol = "short",
sigval = TRUE,
orderside = "long",
ordertype = "market",
orderqty = "all",
TxnFees = -10,
replace = TRUE),
type = "exit",
label = "Exit2SHORT")
add.rule(strategy.st,
name = "ruleSignal",
arguments = list(sigcol = "long",
sigval = TRUE,
orderside = "short",
ordertype = "market",
orderqty = "all",
TxnFees = -10,
replace = TRUE),
type = "exit",
label = "Exit2LONG")
})
V <- reactive({
validate(need(input$start_date >= as.Date(min_date_barrier), "start date cannot be less than hard coded min_date_barrier"))
validate(need(input$end_date <= as.Date(max_date_barrier), "end date cannot be greater than hard coded max_date_barrier"))
validate(need(as.Date(input$start_date) < as.Date(input$end_date), "start date must be less than end date."))
# assign symbol market data to the global environment for the range of dates you want:
time_rng <- paste0(input$start_date, "/", input$end_date)
mdata <- get(input$stock, envir = rawdata)
mdata <- mdata[time_rng]
validate(need(NROW(mdata) > 0, "no data available, choose an appropriate time range"))
mdata
})
backtest_results <- reactive({
backtest_setup()
mdata <- V()
assign(input$stock, mdata, envir = .GlobalEnv)
# not supplying mktdata as a parameter, so look in global environment for objects with the symbol names (which will exist because V assigns to .GlobalEnv):
applyStrategy(strategy.st, portfolios = portfolio.st)
# alternatively you could pass in the data directly to apply strategy if you're just using one symbol of data in the applyStrategy call, instead of having applyStrategy directly search in the .GlobalEnv for the symbol name
#applyStrategy(strategy.st, portfolios = portfolio.st, mktdata = mdata)
updatePortf(portfolio.st)
updateAcct(account.st)
updateEndEq(account.st)
})
output$plot_backtest = renderPlot({
backtest_results()
chart.Posn(portfolio.st, Symbol = input$stock)
})
output$results = renderPrint({
backtest_setup()
tmpdata <- V() # need this here so that any changes to the inputs will reprint the trade stats table
print(tradeStats(portfolio.st))
})
}
# Run the application
shinyApp(ui = ui, server = server)
该应用程序将如下所示：
我正在尝试制作一个网络应用程序，目的是使用 quantstrat。但是，我在整合两者时遇到了一些困难。没有关于此的文档，因此很难找到一个起点。这是我现在拥有的代码。如果您能让我知道我做错了什么，将不胜感激。谢谢
library(shiny)
library(devtools)
library(quantmod)
library(quantstrat)
library(TTR)
library(png)
library(dplyr)
Sys.setenv(TZ = "UTC")
currency('USD')
ui <- fluidPage(
# Application title
titlePanel("myfirst"),
sidebarLayout(
sidebarPanel(
selectInput(
"stocks", label = "chose stock", choices =
c("AAPL", "CAT")
),
dateInput("init_date", "chose init date",
value = Sys.Date() -100),
dateInput("start_date", "chose start date",
value = Sys.Date() - 99),
dateInput("end_date", "chose end date",
value = Sys.Date()),
selectInput("init_equity", "starting
equity", choices = c(1000, 50000))
),
mainPanel(
plotOutput("plot"),
textOutput("text")
)
)
)
server <- function(input, output) {
init_date = reactive({
input$init_date
})
start_date = reactive({
input$start_date
})
end_date = reactive({
input$end_date
})
init_equity = reactive({
input$init_equity
})
V = reactive({
getSymbols(input$stocks, from = start_date(),
to = end_date(), index.class = "POSIXct",
adjust = T)
})
observe({
stock(input$stocks, currency = "USD", multiplier
= 1)
})
portfolio.st = account.st = strategy.st =
"my.first"
rm.strat(portfolio.st)
rm.strat(account.st)
observe({
initPortf(name = portfolio.st,
symbols = "V",
initDate = init_date())
initAcct(name = account.st,
portfolios = portfolio.st,
initDate = init_date(),
initEq = init_equity())
initOrders(portfolio = portfolio.st,
symbols = "V",
initDate = init_date()
)
strategy(strategy.st, store = T)
})
observe({ add.indicator(strategy = strategy.st,
name = "SMA",
arguments = list(x =
quote(Cl(mktdata)),
n = 10),
label = "nFast")
add.indicator(strategy = strategy.st,
name = "SMA",
arguments = list(x =
quote(Cl(mktdata)),
n = 30),
label = "nSlow")
add.signal(strategy = strategy.st,
name="sigCrossover",
arguments = list(columns = c("nFast", "nSlow"),
relationship = "gte"),
label = "long")
add.signal(strategy = strategy.st,
name="sigCrossover",
arguments = list(columns = c("nFast", "nSlow"),
relationship = "lt"),
label = "short")
add.rule(strategy = strategy.st,
name = "ruleSignal",
arguments = list(sigcol = "long",
sigval = TRUE,
orderqty = 100,
ordertype = "stoplimit",
orderside = "long",
threshold = 0.0005,
prefer = "High",
TxnFees = -10,
replace = FALSE),
type = "enter",
label = "EnterLONG")
add.rule(strategy.st,
name = "ruleSignal",
arguments = list(sigcol = "short",
sigval = TRUE,
orderqty = -100,
ordertype = "stoplimit",
threshold = -0.005,
orderside = "short",
replace = FALSE,
TxnFees = -10,
prefer = "Low"),
type = "enter",
label = "EnterSHORT")
add.rule(strategy.st,
name = "ruleSignal",
arguments = list(sigcol = "short",
sigval = TRUE,
orderside = "long",
ordertype = "market",
orderqty = "all",
TxnFees = -10,
replace = TRUE),
type = "exit",
label = "Exit2SHORT")
add.rule(strategy.st,
name = "ruleSignal",
arguments = list(sigcol = "long",
sigval = TRUE,
orderside = "short",
ordertype = "market",
orderqty = "all",
TxnFees = -10,
replace = TRUE),
type = "exit",
label = "Exit2LONG")
applyStrategy(strategy.st, portfolios = portfolio.st)
updatePortf(portfolio.st)
updateAcct(account.st)
updateEndEq(account.st)
})
output$plot = reactive(
chart.Posn(portfolio.st, Symbol = "V")
)
}
# Run the application
shinyApp(ui = ui, server = server)
有趣的想法。由于交易工具的市场数据存储在本地环境中的名称与其 symbols/tickers 相同的变量的性质，您尝试做的事情有点具有挑战性。
此外，您的闪亮应用程序有些奇怪；请注意如何使用 reactive({、isolate({ 和其他服务器组件。例如，当你有像
start_date = reactive({
input$start_date
})`
是多余的。
这是一个可以实现您想要实现的目标的示例。我尽量使变量名称与您的示例保持一致。
您可能需要重新考虑您的工作流程：我认为您应该 运行 在 quantstrat 中独立于 shiny 进行大批量模拟，然后将结果保存到磁盘。然后在启动 Shiny 应用程序时从磁盘加载这些结果。不过，这个示例有望解决您的任何疑惑。
此外，您应该注意通过 getSymbols 从雅虎请求数据的频率。我在下面所做的是在应用程序首次启动时仅请求一次数据，并将市场数据存储在名为 rawdata 的环境中的符号中。然后，如果您停止并再次重新启动您的应用程序，您将不会继续向雅虎请求数据（当他们限制您在一段时间内可以下载的数量时，这可能会给您带来错误）。
# Could put these in global.R, these global variables are "hard coded" ----------------
min_date_barrier <- "2012-01-01"
max_date_barrier <- "2019-04-17"
stock_universe <- c("AAPL", "CAT", "BB")
# These variables won't change when the app launches, so hard code them too:
Sys.setenv(TZ = "UTC")
currency('USD')
stock(stock_universe, currency = "USD", multiplier = 1)
portfolio.st <- account.st <- strategy.st <- "my.first"
# In here, store the original market data which contains your full range of possible values for the market data:
# Don't keep requesting data frequently otherwise you won't be able to download the data temporarily.
if (!exists("rawdata")) {
rawdata <- new.env()
assign("rawdata", rawdata, envir = .GlobalEnv)
lapply(stock_universe, function(sym) {
# if (exists(sym, envir = rawdata)) {
# message("Have already downloaded data for ", sym)
# return()
# } else {
getSymbols(stock_universe,
env = rawdata, # important to specify environment
from = min_date_barrier,
to = max_date_barrier,
adjust = T, auto.assign = TRUE)
#}
return()
})
}
# UI ----------------------------------------------------------------------
ui <- fluidPage(
# Application title
titlePanel("myfirst"),
sidebarLayout(
sidebarPanel(
selectInput(
"stock", label = "Choose stock", choices = stock_universe
),
dateInput("start_date", "Choose start date",
value = "2018-02-03"),
dateInput("end_date", "Choose end date",
value = "2019-04-10"),
selectInput("init_equity", "starting
equity", choices = c(1000, 50000))
),
mainPanel(
plotOutput("plot_backtest"),
verbatimTextOutput("results")
)
)
)
# server ------------------------------------------------------------------
server <- function(input, output, session) {
# all your reactives don't make sense -- only use the inputs when you need them on the server side
backtest_setup <- reactive({
# need these input variables in this reactive to avoid bugs in the app when you change the time range:
input$start_date
input$end_date
rm.strat(portfolio.st, silent = FALSE)
initPortf(name = portfolio.st,
symbols = input$stock, #------------------------ correct way to apply the "stock" input
initDate = "2000-01-01")
initAcct(name = account.st,
portfolios = portfolio.st,
initDate = "2000-01-01",
initEq = as.numeric(input$init_equity)) # convert equity to numeric from string
initOrders(portfolio = portfolio.st,
symbols = input$stock, # ----------------------------------
initDate = "2000-01-01"
)
strategy(strategy.st, store = T)
add.indicator(strategy = strategy.st,
name = "SMA",
arguments = list(x =
quote(Cl(mktdata)),
n = 10),
label = "nFast")
add.indicator(strategy = strategy.st,
name = "SMA",
arguments = list(x =
quote(Cl(mktdata)),
n = 30),
label = "nSlow")
add.signal(strategy = strategy.st,
name="sigCrossover",
arguments = list(columns = c("nFast", "nSlow"),
relationship = "gte"),
label = "long")
add.signal(strategy = strategy.st,
name="sigCrossover",
arguments = list(columns = c("nFast", "nSlow"),
relationship = "lt"),
label = "short")
add.rule(strategy = strategy.st,
name = "ruleSignal",
arguments = list(sigcol = "long",
sigval = TRUE,
orderqty = 100,
ordertype = "stoplimit",
orderside = "long",
threshold = 0.0005,
prefer = "High",
TxnFees = -10,
replace = FALSE),
type = "enter",
label = "EnterLONG")
add.rule(strategy.st,
name = "ruleSignal",
arguments = list(sigcol = "short",
sigval = TRUE,
orderqty = -100,
ordertype = "stoplimit",
threshold = -0.005,
orderside = "short",
replace = FALSE,
TxnFees = -10,
prefer = "Low"),
type = "enter",
label = "EnterSHORT")
add.rule(strategy.st,
name = "ruleSignal",
arguments = list(sigcol = "short",
sigval = TRUE,
orderside = "long",
ordertype = "market",
orderqty = "all",
TxnFees = -10,
replace = TRUE),
type = "exit",
label = "Exit2SHORT")
add.rule(strategy.st,
name = "ruleSignal",
arguments = list(sigcol = "long",
sigval = TRUE,
orderside = "short",
ordertype = "market",
orderqty = "all",
TxnFees = -10,
replace = TRUE),
type = "exit",
label = "Exit2LONG")
})
V <- reactive({
validate(need(input$start_date >= as.Date(min_date_barrier), "start date cannot be less than hard coded min_date_barrier"))
validate(need(input$end_date <= as.Date(max_date_barrier), "end date cannot be greater than hard coded max_date_barrier"))
validate(need(as.Date(input$start_date) < as.Date(input$end_date), "start date must be less than end date."))
# assign symbol market data to the global environment for the range of dates you want:
time_rng <- paste0(input$start_date, "/", input$end_date)
mdata <- get(input$stock, envir = rawdata)
mdata <- mdata[time_rng]
validate(need(NROW(mdata) > 0, "no data available, choose an appropriate time range"))
mdata
})
backtest_results <- reactive({
backtest_setup()
mdata <- V()
assign(input$stock, mdata, envir = .GlobalEnv)
# not supplying mktdata as a parameter, so look in global environment for objects with the symbol names (which will exist because V assigns to .GlobalEnv):
applyStrategy(strategy.st, portfolios = portfolio.st)
# alternatively you could pass in the data directly to apply strategy if you're just using one symbol of data in the applyStrategy call, instead of having applyStrategy directly search in the .GlobalEnv for the symbol name
#applyStrategy(strategy.st, portfolios = portfolio.st, mktdata = mdata)
updatePortf(portfolio.st)
updateAcct(account.st)
updateEndEq(account.st)
})
output$plot_backtest = renderPlot({
backtest_results()
chart.Posn(portfolio.st, Symbol = input$stock)
})
output$results = renderPrint({
backtest_setup()
tmpdata <- V() # need this here so that any changes to the inputs will reprint the trade stats table
print(tradeStats(portfolio.st))
})
}
# Run the application
shinyApp(ui = ui, server = server)
该应用程序将如下所示：