server.r

###################################
# Server functions
# 
# [email protected] - June 2014
###################################

shinyServer(function(input, output) {
  
  getData <- function(inputPath=inputPath,inputFile=inputFile,keepColumns=keepColumns){
    data <- read.csv(paste(inputPath,inputFile,sep=""),sep=",")
    keepColumns <- keepColumns
    dataDaily <- data[,keepColumns]
    colnames(dataDaily) <- c("date","rtn")
    days <- as.Date(dataDaily[,"date"],"%m/%d/%Y")
    dailyRtn <- as.numeric(substring(dataDaily[,"rtn"],1,nchar(as.character(dataDaily[,"rtn"]))-1)) ##
    return(list(date=days,rtn=dailyRtn))
  }
  
  data <- reactive({
    ### ETF
    if (input$strategy == "ETF"){
      dt <- getData(inputPath="yourPath1",
                      inputFile="yourFile1.csv",
                      keepColumns=c("date","rtn"))
    }
    ### EQUITY BOND ALLOCATION  
    if (input$strategy == "Equity Bond Allocation"){
      dt <- getData(inputPath="yourPath2",
                      inputFile="yourFile2.csv",
                      keepColumns=c("date","rtn"))
    }
    ### EQUITY LONG SHORT  
    if (input$strategy == "Equity Index"){
      dt <- getData(inputPath="yourPath3",
                    inputFile="yourFile3.csv",
                    keepColumns=c("date","rtn"))
    }
    return(dt)
  })

  output$plot1 <- renderPlot({
    data <- data()
    pos <- min(which(as.Date(data$date,format="%Y-%m-%d") >= as.Date(input$startDate,format="%Y-%m-%d")))
    x <- data$date[pos:length(data$date)]
    y <- data$rtn[pos:length(data$rtn)]
    
    xDD <- as.vector(Drawdowns(y/100))
    
    par(mfrow=c(2,1),cex=0.9,mex=0.4)
    
    plot(x,cumsum(y),
         type="l",
         main=" Equity Curve (%)",
         xlab="",
         ylab="",
         col="royal blue",
         lwd=1.5)
    grid(col="dark grey")
    
    plot(x,100*xDD,
         type="l",
         xlab="",
         ylab="",
         main="DrawDowns (%)",
         col="royal blue",
         lwd=1.5)
    grid(col="dark grey")
  })
  
  
  output$tablePerformance <- renderTable({  
    data <- data()
    pos <- min(which(as.Date(data$date,format="%Y-%m-%d") >= as.Date(input$startDate,format="%Y-%m-%d")))
    x <- data$date[pos:length(data$date)]
    y <- data$rtn[pos:length(data$rtn)]
    
    dailyDD <- as.vector(Drawdowns(y/100))
    nbDays <- length(x)
    nbYears <- nbDays/252
    totalReturn <- sum(y)
    annualizedReturn <- round(totalReturn/nbYears,2)
    annualizedVolatility <- round(sd(y)*sqrt(252),2)
    sharpeRatio <- round(annualizedReturn/annualizedVolatility,2)
    profitFactor <- round(sum(y[y > 0])/abs(sum(y[y < 0])),2)
    
    rtnTable <- rbind(paste(annualizedReturn,"%",sep=""),paste(annualizedVolatility,"%",sep=""),sharpeRatio,profitFactor)
    rownames(rtnTable) <- c("Ann.Return","Ann.Volatility","Sharpe Ratio","Profit Factor")
    colnames(rtnTable) <- c("Performance")
    
    rtnTable                                 
  })

  output$tableRisk <- renderTable({  
    data <- data()
    pos <- min(which(as.Date(data$date,format="%Y-%m-%d") >= as.Date(input$startDate,format="%Y-%m-%d")))
    x <- data$date[pos:length(data$date)]
    y <- data$rtn[pos:length(data$rtn)]
    
    dailyDD <- as.vector(Drawdowns(y/100))
    maxDD <- 100*round(min(dailyDD),3)
    recoveryTime <- round(min(which(dailyDD[match(min(dailyDD),dailyDD):length(dailyDD)] == 0)),0)
    painIndex <- round(PainIndex(y),2)
    timeInMarket <- 100*round(length(which(y != 0))/length(y),2)
    
    riskTable <- rbind(paste(maxDD,"%",sep=""),paste(recoveryTime," days",sep=""),painIndex,paste(timeInMarket,"%",sep=""))
    rownames(riskTable) <- c("Max.DD","Recovery Time","Pain Index","% Time Invested")
    colnames(riskTable) <- c("Risk")
    
    riskTable                                 
  })
  
  output$tableDaily <- renderTable({  
    data <- data()
    pos <- min(which(as.Date(data$date,format="%Y-%m-%d") >= as.Date(input$startDate,format="%Y-%m-%d")))
    x <- data$date[pos:length(data$date)]
    y <- data$rtn[pos:length(data$rtn)]
    
    avRtn <- round(mean(y,na.rm=TRUE),2)
    avRtnPos <- round(mean(y[y >0],na.rm=TRUE),2)
    avRtnNeg <- round(mean(y[y <0],na.rm=TRUE),2)
    hitRatio <- 100*round(length(which(y > 0))/length(which(y != 0)),2)
    worstDay <- round(min(y),2)
    bestDay <- round(max(y),2)
    
    dailyTable <- rbind(paste(avRtn,"%",sep=""),paste(avRtnPos,"%",sep=""),paste(avRtnNeg,"%",sep=""),paste(hitRatio,"%",sep=""),paste(worstDay,"%",sep=""),paste(bestDay,"%",sep=""))
    rownames(dailyTable) <- c("Av. Rtn","Av. Rtn > 0","Av. Rtn < 0","Hit Ratio","Worst Day","Best Day")
    colnames(dailyTable) <- c("Daily")
    
    dailyTable                                 
  })
  
  output$tableMonthly <- renderTable({  
    data <- data()
    pos <- min(which(as.Date(data$date,format="%Y-%m-%d") >= as.Date(input$startDate,format="%Y-%m-%d")))
    x <- data$date[pos:length(data$date)]
    y <- data$rtn[pos:length(data$rtn)]
    
    months <- sort(unique(substring(x,1,7)))
    monthlyRtn <- aggregate(y,by=list(substring(x,1,7)),sum)[,2]
    
    monthlyHitRate <- 100*round(length(which(monthlyRtn > 0))/length(monthlyRtn),2)
    monthlyRtnAverage <- round(mean(monthlyRtn),2) 
    monthlyRtnPositive <- round(mean(monthlyRtn[which(monthlyRtn > 0)]),2) 
    monthlyRtnNegative <- round(mean(monthlyRtn[which(monthlyRtn < 0)]) ,2)
    worstMonth <- round(min(monthlyRtn),2)
    bestMonth <- round(max(monthlyRtn),2)
    
    monthlyTable <- rbind(paste(monthlyRtnAverage,"%",sep=""),paste(monthlyRtnPositive,"%",sep=""),paste(monthlyRtnNegative,"%",sep=""),paste(monthlyHitRate,"%",sep=""),paste(worstMonth,"%",sep=""),paste(bestMonth,"%",sep=""))
    rownames(monthlyTable) <- c("Av. Rtn","Av. Rtn > 0","Av. Rtn < 0","Hit Ratio","Worst Month","Best Month")
    colnames(monthlyTable) <- c("Monthly")
    
    monthlyTable                                 
  })
}) 

ShinyForTradingStrategies

###############################################################################
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# Please visit: <http://www.gnu.org/licenses/>.
###############################################################################
# Copyright (C) 2014 The R Trader
#
# For more information please visit my blog at www.thertrader.com
# or you can reach me at: TheRTrader at gmail
###############################################################################

shinyStrategyGeneral.r

###################################
# Launch Shiny App
# 
# [email protected] - June 2014
###################################
library(PerformanceAnalytics)
library(shiny)
library(xts)

runApp("D:\\daily\\shinyApps")

ui.r

###################################
# UI functions
# 
# [email protected] - June 2014
###################################

shinyUI(
  fluidPage(
    headerPanel(""),
    
    sidebarPanel(
      selectInput("strategy", 
                  "Strategy:", 
                  choices = c("ETF","Equity Bond Allocation","Equity Index")),
      
      selectInput("startDate", 
                  "Starting Date:", 
                  choices = seq(as.Date("2000-01-01"),Sys.Date(),by="months")),
    
    div(HTML("<br>This app was created by the R Trader.
              <br><a href='http://thertrader.com' target='_blank'>www.thertrader.com</a>"))
  ),
      
  mainPanel(  
    tabsetPanel(
      tabPanel("Overview", plotOutput("plot1",height = 550, width = 550)),
      tabPanel("Trading Statistics",
               fixedRow(
                 column(8,
                        fixedRow(column(4,tableOutput("tablePerformance")),
                                 column(4,tableOutput("tableRisk"))),
                        fixedRow(column(4,tableOutput("tableDaily")),
                                 column(4,tableOutput("tableMonthly"))))
               )
               ),
      tabPanel("About",
               HTML("<div> This Shiny application is the first version of an app designed to help analysing trading strategies. I will certainly improve it in the future.</div>
<p>The code used to create this app is available on <a href='https://gist.github.com/thertrader/8e777452b8e0e10320ee' target='_blank'>Github</a>. There are essentially 3 files.</p>
                    <li><i>ui.R</i>:  controls the layout and appearance of the app</li>
                    <li><i>server.R</i>: contains the instructions needed to build the app. You can load as much strategies as you want as long as they have the right format.</li>
                    <li><i>shinyStrategyGeneral.R</i>: loads the required packages and launches the app</li>"))
      )  
  )
))