library(shiny)
library(rsconnect)
library(shinyjs)
ui <- shinyUI(fluidPage(
    titlePanel("index predictive plot and predictive table"),
    mainPanel(
        textInput("index1", label = "code") ,
        textOutput("yahooop"),
        actionButton("goButton", "Go!"),

        tabsetPanel(
            tabPanel(
                "op.index",
                plotOutput("open.predict.plot1"),
                tableOutput("open.value1"),
                textOutput("open.table1"),
                tableOutput("open.predict.table1"),
                textOutput("open.table2")
            ),
            tabPanel(
                "close.index",
                plotOutput("close.predict.plot1"),
                tableOutput("close.value1"),
                textOutput("close.table1"),
                tableOutput("close.predict.table1"),
                textOutput("close.table2"),
                textOutput("income")
            )
        )
        ,
        width = 15,
        height = 15
    )
))

server <- shinyServer(function(input, output, session) {
    library(rsconnect)
    library(tseries)
    library(quantmod)
    library(forecast)
    library(car)
    library(haven)
    library(ggplot2)


    yahoo1 <- reactive({
        paste("Please enter the code for YAHOO finance")
    })
    output$yahooop <- renderText({
        yahoo1()
    })

    observeEvent(input$goButton, {
        library(tseries)
        library(quantmod)
        library(forecast)
        library(car)
        library(haven)

        index3 <-
            getSymbols(input$index1, auto.assign = FALSE)
        index2 <- input$index1
        index.open <- na.omit(data.frame(index3[, 1]))
        index.close <- na.omit(data.frame(index3[, 4]))
        index.open.test <-
            data.frame(index.open[1:(nrow(index.open) - 365), ])
        index.close.test <-
            data.frame(index.close[1:(nrow(index.open) - 365), ])
        index.open.train <-
            data.frame(index.open[1:(nrow(index.open)), ])
        index.close.train <-
            data.frame(index.close[1:(nrow(index.open)), ])
        index.open.year <- data.frame(tail(index.open, 365))
        index.close.year <-
            data.frame(tail(index.close, 365))
        colnames(index.open.year) = "OP.value"
        colnames(index.open.train) = "OP.value"
        colnames(index.close.year) = "close.value"
        colnames(index.close.train) = "close.value"
        mod1 <-
            auto.arima(
                index.open.train,
                seasonal = TRUE,
                ic = "aic",
                test = "adf",
                seasonal.test = "seas",
                allowdrift = TRUE,
                allowmean = TRUE,
                stepwise = FALSE,
                approximation = FALSE
            )
        mod2 <-
            auto.arima(
                index.close.train,
                seasonal = TRUE,
                ic = "aic",
                test = "adf",
                seasonal.test = "seas",
                allowdrift = TRUE,
                allowmean = TRUE,
                stepwise = FALSE,
                approximation = FALSE
            )
        predict.open <-
            forecast(
                index.open.test[[1]],
                model = mod1,
                h = 365,
                include.mean = TRUE
            )
        predict.close <-
            forecast(
                index.close.test[[1]],
                model = mod2,
                h = 365,
                include.mean = TRUE
            )
        t1 <- data.frame(index.open.year$OP.value)
        t2 <- data.frame(index.close.year$close.value)
        p2 <- data.frame(predict.close$mean)
        p1 <- data.frame(predict.open$mean)
        d1 = 0
        for (x in 1:2) {
            d1 <-
                ((t2[x,]) - (t1[x,]) - ((p2[x,]) - (p1[x,])))
        }
        output$open.predict.plot1 <-
            renderPlot(plot(
                forecast(index.open.year[[1]] , model = mod1, h = 5),
                main = paste(c(index2), ".open", "ARIMA predicton plot")
            ))

        output$open.value1 <-
            renderTable(tail(index.open.year, 5), rownames = TRUE)
        open.formulaText1 <- reactive({
            paste("it is the index opening index in the past five days")
        })
        output$open.table1 <-
            renderText({
                open.formulaText1()
            })
        output$open.predict.table1 <-
            renderTable(data.frame(forecast(
                index.open.year[[1]],
                model = mod2,
                h = 5
            )))

        open.formulaText2 <- reactive({
            paste(
                "The expected value of the opening index  in the next five days and its 80%, 95% confidence interval"
            )
        })
        output$open.table2 <-
            renderText({
                open.formulaText2()
            })

        output$close.predict.plot1 <-
            renderPlot(plot(
                forecast(index.close.year[[1]], 30 , model = mod2, h = 5),
                main = paste(c(index2), ".close", " ARIMA predicton plot")
            ))
        output$close.value1 <-
            renderTable(tail(index.close.year, 5), rownames = TRUE)
        close.formulaText1 <- reactive({
            paste("it is the index closeing index in the past five days")
        })
        output$close.table1 <-
            renderText({
                close.formulaText1()
            })
        output$close.predict.table1 <-
            renderTable(data.frame(forecast(
                tail(index.close.year, 30)[[1]] ,
                model = mod2,
                h = 5
            )))

        close.formulaText2 <- reactive({
            paste(
                "The expected value of the closeing index  in the next five days and its 80%, 95% confidence interval"
            )
        })
        output$close.table2 <-
            renderText({
                close.formulaText2()
            })
        income <- reactive({
            paste("the net income is", d1)
        })
    })
})
shinyApp(ui = ui, server = server)