Test/app.R

In RasmusJensen96/VolatilityModelling: Work in progress volatility models for my personal usage

#
# This is a Shiny web application. You can run the application by clicking
# the 'Run App' button above.
#
# Find out more about building applications with Shiny here:
#
#    http://shiny.rstudio.com/
#

library(shiny)

# Define UI for application that draws a histogram
ui <- shinyUI(pageWithSidebar(

    headerPanel("Stock Explorer"),

    sidebarPanel(

        helpText("Select a stock to examine.
      Information will be collected from yahoo finance."),

        textInput("symb", "Symbol", "GOOG"),

        dateRangeInput("dates",
                       "Compare to historic returns from",
                       start = "2013-01-01", end = "2013-09-05"),

        actionButton("get", "Get Stock"),

        br(),
        br(),

        uiOutput("newBox")

    ),

    # Show a tabset that includes a plot, summary, and table view
    # of the generated distribution
    mainPanel(
        tabsetPanel(
            tabPanel("Charts", plotOutput("chart")),
            tabPanel("Model", div(h3(textOutput("ks"))),
                     div(h3(textOutput("ksp"))),
                     plotOutput("hist")),
            tabPanel("VaR", h3(textOutput("text3"))),
            id = "tab"
        )
    )
))

# Define server logic required to draw a histogram

library(shiny)
library(quantmod)
library(VGAM)

# Define server logic for random distribution application
server <- shinyServer(function(input, output) {

    # acquiring data
    dataInput <- reactive({
        if (input$get == 0)
            return(NULL)

        return(isolate({
            getSymbols(input$symb,src="yahoo", auto.assign = FALSE)
        }))
    })

    datesInput <- reactive({
        if (input$get == 0)
            return(NULL)

        return(isolate({
            paste0(input$dates[1], "::",  input$dates[2])
        }))
    })

    returns <- reactive({
        if (input$get == 0)
            return(NULL)

        dailyReturn(dataInput())
    })

    xs <- reactive({
        if (input$get == 0)
            return(NULL)

        span <- range(returns())
        seq(span[1], span[2], by = diff(span) / 100)
    })

    # tab based controls
    output$newBox <- renderUI({
        switch(input$tab,
               "Charts" = chartControls,
               "Model" = modelControls,
               "VaR" = helpText("VaR")
        )
    })

    # Charts tab
    chartControls <- div(
        wellPanel(
            selectInput("chart_type",
                        label = "Chart type",
                        choices = c("Candlestick" = "candlesticks",
                                    "Matchstick" = "matchsticks",
                                    "Bar" = "bars",
                                    "Line" = "line"),
                        selected = "Line"
            ),
            checkboxInput(inputId = "log_y", label = "log y axis",
                          value = FALSE)
        ),

        wellPanel(
            p(strong("Technical Analysis")),
            checkboxInput("ta_vol", label = "Volume", value = FALSE),
            checkboxInput("ta_sma", label = "Simple Moving Average",
                          value = FALSE),
            checkboxInput("ta_ema", label = "Exponential Moving Average",
                          value = FALSE),
            checkboxInput("ta_wma", label = "Weighted Moving Average",
                          value = FALSE),
            checkboxInput("ta_bb", label = "Bolinger Bands",
                          value = FALSE),
            checkboxInput("ta_momentum", label = "Momentum",
                          value = FALSE),

            br(),

            actionButton("chart_act", "Add Technical Analysis")
        )
    )

    TAInput <- reactive({
        if (input$chart_act == 0)
            return("NULL")

        tas <- isolate({c(input$ta_vol, input$ta_sma, input$ta_ema,
                          input$ta_wma,input$ta_bb, input$ta_momentum)})
        funcs <- c(addVo(), addSMA(), addEMA(), addWMA(),
                   addBBands(), addMomentum())

        if (any(tas)) funcs[tas]
        else "NULL"
    })

    output$chart <- renderPlot({
        chartSeries(dataInput(),
                    name = input$symb,
                    type = input$chart_type,
                    subset = datesInput(),
                    log.scale = input$log_y,
                    theme = "white",
                    TA = TAInput())
    })

    # Model tab
    modelControls <- div(
        br(),

        sliderInput("n", "Number of bins in histogram",
                    min = 1, max = 250, value = 30
        ),

        br(),

        wellPanel(
            selectInput("family", "Model returns as",
                        choices = c("normal", "double exponential", "t"),
                        selected = "normal"
            ),

            sliderInput("mu", "Mean",
                        min = -1, max = 1, value = 0, step = 0.01
            ),

            sliderInput("sigma", "Standard Deviation",
                        min = 0, max = 0.1, value = 0.05, step = 0.001
            ),
            conditionalPanel(condition = "input.family == 't'",
                             sliderInput("df", "Degrees of freedom",
                                         min = 2, max = 1000, value = 10
                             )
            )

        )
    )

    ys <- reactive({
        if (input$get == 0)
            return(NULL)

        switch(input$family,
               "double exponential" = dlaplace(xs(),
                                               location = input$mu,
                                               scale = input$sigma
               ),
               "normal" = dnorm(xs(),
                                mean = input$mu,
                                sd = input$sigma
               ),
               "t" = dt((xs() - input$mu) / input$sigma,
                        df = input$df) * sqrt(2 * length(returns()))
        )
    })

    ks <- reactive({
        switch(input$family,
               "double exponential" = ks.test(returns(), "plaplace",
                                              input$mu, input$sigma),
               "normal" = ks.test(returns(), "pnorm",
                                  input$mu, input$sigma),
               "t" = ks.test((returns() - input$mu) / input$sigma, "pt",
                             input$df)
        )
    })

    output$hist <- renderPlot({
        hist(returns(), xlab = "returns", freq = FALSE,
             main = paste(input$symb, "Daily Returns:",
                          input$dates[1], "-", input$dates[2], sep = " "),
             breaks = input$n)
        lines(xs(), ys(), col = "red")
    })


    output$ks <- renderText({
        paste0("Kolmogorv-Smirnoff statistic: ", ks()$statistic)
    })
    output$ksp <- renderText({
        paste0("P-value for model: ", ks()$p.value)
    })

    # VaR tab
    output$text3 <- renderText({paste0(input$symb, " 3: ", input$tab)})

})

shinyApp(ui = ui, server = server)