Portfolio Analytics Shiny App

server.R

library(PerformanceAnalytics)
library(PortfolioAnalytics)
library(quantmod)

options( error = recover )

fastCovMcdEstimator <- function(x, spec=NULL,...) {
  covMcdEstimate
}

get_portfolio_frontier <- function(data, riskFree, estimator="kendallEstimator",
                          optimizeParam, frontierPoints, riskFreeRate,
                          targetReturn, targetRisk, constraints="none") {
  data = timeSeries(data)
  
  riskFree = (riskFree/100)/12
  targetReturn = targetReturn/100
  targetRisk = targetRisk/100
  
  Spec1 = portfolioSpec(
    model=list(
      type="MV",
      optimize=optimizeParam,
      estimator=estimator,
      tailRisk=list(),
      params=list(alpha=0.05,a=2)),
    portfolio = list(
      weights=NULL,
      targetReturn=targetReturn,
      targetRisk=targetRisk,
      riskFreeRate = riskFree,
      nFrontierPoints = frontierPoints),
    optim = list(
      solver = "solveRquadprog",
      objective=NULL,
      control=list(meq=2)))
  
  
  if (constraints != "none") {
    setSolver(Spec1) = "solveRshortExact"
    portfFrontier = portfolioFrontier(data=data, spec=Spec1, constraints=constraints)
  } else {
    portfFrontier = portfolioFrontier(data=data, spec=Spec1)  
  }
  return(portfFrontier)
}

getColor <- function(numberOfEntries) {
  return(divPalette(numberOfEntries, "RdBu"))
}

shinyServer(function(input, output) {
  
  datasetInput <- reactive({
    switch(input$dataset,
           "EDHEC" = edhec,
           "Indices" = indexes)
  })
  
  constraints <- reactive({
    switch(input$constraints,
          "None" = "none",
          "Long Only" = "LongOnly")
  })
  
  portfolio_estimator <- reactive({
    switch(input$estimator,
           "MVE" = "mveEstimator",
           "Kendall" = "kendallEstimator",
           "Covariance MCD" = "covMcdEstimator",
           "Covariance OGK" = "covOGKEstimator",
           "NNVE" = "nnveEstimator")
  })
  
  optimize_parameters <- reactive({
    switch(input$optimize,
           "Minimum Risk" = "minRisk",
           "Maximum Return" = "maxReturn")
  })
  
  riskfree_rate <- reactive({input$riskfree})
  frontier_points <- reactive({input$frontier_points})
  target_return <- reactive({input$target_return})
  target_risk <- reactive({input$target_risk})
  
  
  
   output$frontierPlot <- renderPlot({
    # Take a dependency on input$goButton
    input$goButton

    if (input$goButton == 0) {
    return()
    } else {
      portfolio <- datasetInput()
      pfrontier = get_portfolio_frontier(portfolio, riskFree=riskfree_rate(),
                  estimator=portfolio_estimator(), optimizeParam=optimize_parameters(),
                  frontierPoints = frontier_points(), riskFreeRate=riskfree_rate(),
                  targetReturn=target_return(), targetRisk=target_risk(), 
                  constraints = constraints())
      
      tailoredFrontierPlot(pfrontier, risk="Sigma")
    }
  })

  output$weightsPlot <- renderPlot({
		input$goButton
		if (input$goButton == 0) {
    	return()
    } else {
      portfolio <- datasetInput()
      pfrontier = get_portfolio_frontier(portfolio, riskFree=riskfree_rate(),
                                         estimator=portfolio_estimator(), optimizeParam=optimize_parameters(),
                                         frontierPoints = frontier_points(), riskFreeRate=riskfree_rate(),
                                         targetReturn=target_return(), targetRisk=target_risk(), 
                                         constraints = constraints())
      weightsPlot(pfrontier, mtext=FALSE, col=getColor(length(colnames(portfolio))))
		}
  })
  
  output$weightedReturnsPlot <- renderPlot({
    input$goButton

		if (input$goButton == 0) {
      return()
    } else {
      portfolio <- datasetInput()
      pfrontier = get_portfolio_frontier(portfolio, riskFree=riskfree_rate(),
                                         estimator=portfolio_estimator(), optimizeParam=optimize_parameters(),
                                         frontierPoints = frontier_points(), riskFreeRate=riskfree_rate(),
                                         targetReturn=target_return(), targetRisk=target_risk(), 
                                         constraints = constraints())
      weightedReturnsPlot(pfrontier, mtext=FALSE, col=getColor(length(colnames(portfolio))))
    }
  })
  
	output$summaryTable <- renderPrint({
		input$goButton

		if (input$goButton == 0) {
    	return()
    } else {
      portfolio <- datasetInput()
      pfrontier = get_portfolio_frontier(portfolio, riskFree=riskfree_rate(),
                                         estimator=portfolio_estimator(), optimizeParam=optimize_parameters(),
                                         frontierPoints = frontier_points(), riskFreeRate=riskfree_rate(),
                                         targetReturn=target_return(), targetRisk=target_risk(), 
                                         constraints = constraints())
      print(pfrontier)
		}
	})


})

timer.js

<script type="text/javascript">
  var wasBusy = false;
var elapsedTimer = null;
var startTime = null;
function updateBusy() {
  var isBusy = $('html').hasClass('shiny-busy');
  if (isBusy && !wasBusy) {
    startTime = new Date().getTime();
    elapsedTimer = setInterval(function() {
      var millisElapsed = new Date().getTime() - startTime;
      $('#progress').text(Math.round(millisElapsed/1000) + ' seconds have elapsed');
    }, 1000);
  }
  else if (!isBusy && wasBusy) {
    clearInterval(elapsedTimer);
  }
  wasBusy = isBusy;
}
</script>

ui.R

library(shinyIncubator)

shinyUI(pageWithSidebar(
  headerPanel("Portfolio Analytics"),
  sidebarPanel(
    selectInput("dataset", "Choose A Dataset:",
      choices=c("EDHEC", "Indices")),
    p(br()),
    numericInput("riskfree", "Risk free Rate: ", 0),
    sliderInput("frontier_points", "Number Of Frontier Points :", value=10, 
                min=5, max=100, step=1),
    numericInput("target_return", "Target Return %: ", 10),
    numericInput("target_risk", "Target Risk %", 2),
    selectInput("constraints", "Constraints: ",
      choices=c("None","Long Only")),
    selectInput("estimator", "Portfolio Estimator",
      choices=c("MVE", "Kendall","Covariance OGK", "Covariance MCD",
                "NNVE")),
    selectInput("optimize", "Optimize For: ",
      choices=c("Minimum Risk","Maximum Return")),
    p(br()),
    actionButton("goButton", "Start"),
    
    helpText("This is the ATYS experimental risk charting app. More details will be 
             filled in as the app becomes more developed."),
    
    p(br(), a("ATYS Bonds Home", href="http://atysbonds.com/blog")),
    p(br(), a("ATYS Support", href="mailto:[email protected]"))
    
  ),
  mainPanel(
    conditionalPanel("updateBusy() || $('html').hasClass('shiny-busy')",
                     id='progressIndicator',
                     "Processing Request",
                     div(id='progress',includeHTML("timer.js"))
    ),
    tags$head(tags$style(type="text/css",
                         '#progressIndicator {',
                         '  position: float; top: 8px; right: 8px; width: 200px; height: 50px;',
                         '  padding: 8px; border: 1px solid #CCC; border-radius: 8px;',
                         '}')),
    
    tabsetPanel(

  		tabPanel("Charts",				
               h4("Tailored Frontier Plot"),
               plotOutput("frontierPlot"),
               h4("Portfolio Weights"),
               plotOutput("weightsPlot"),
			         h4("Weighted Returns Plot"),
			         plotOutput("weightedReturnsPlot")),

			tabPanel("Summary",
				verbatimTextOutput("summaryTable"))
		)
  )
))