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Add portfolio-dashboard to Connect Gallery (#52)
* Add portfolio-dashboard to gallery * Add extension object in manifest * Add version constraint to manifest * Use >=4.3 for environment.r.requires * Include returns.rds file * Update manifest generated from IDE * Update README with R version requirement --------- Co-authored-by: Jordan Jensen <[email protected]>
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.github/workflows/extensions.yml

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filters: |
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reaper: extensions/reaper/**
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integration-session-manager: extensions/integration-session-manager/**
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portfolio-dashboard: extensions/portfolio-dashboard/**
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# Runs for each extension that has changed from `simple-extension-changes`
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# Lints and packages in preparation for tests and and release.
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# Portfolio Dashboard
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## About this example
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A shiny application makes it easy to transform your analysis into an interactive dashboard using R so users can ask and answer questions in real-time, without having to touch any code.
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## Learn more
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* [Shiny Documentation](https://shiny.posit.co/)
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* [Gallery of example Shiny apps](https://shiny.posit.co/r/gallery/)
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* [Articles on Shiny](https://shiny.posit.co/r/articles/)
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## Requirements
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* R version 4.4 or higher
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library(dplyr)
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library(dygraphs)
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library(plotly)
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library(PerformanceAnalytics)
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library(shiny)
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library(shinydashboard)
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library(xts)
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library(zoo)
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returns <- readRDS("returns.rds")
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portfolio_choices <- c(
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"Conservative" = "conservative_portfolio_returns",
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"Balanced" = "balanced_portfolio_returns",
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"Aggressive" = "aggressive_portfolio_returns"
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)
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ui <- dashboardPage(
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dashboardHeader(title = "Portfolio Dashboard"),
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dashboardSidebar(
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selectInput(
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"portfolio",
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"Choose a portfolio",
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choices = portfolio_choices,
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selected = "balanced_portfolio_returns"
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),
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dateInput(
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inputId = "date",
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label = "Starting Date",
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value = "2010-01-01",
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format = "yyyy-mm-dd"
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),
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sliderInput("mar", "Min Acceptable Rate", min = 0, max = 0.1, value = 0.008, step = 0.001),
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numericInput("window", "Rolling Window", min = 6, max = 36, value = 12)
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),
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dashboardBody(
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fluidRow(
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box(title = "Rolling Sortino", width = 12,
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plotlyOutput("time_series")
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)
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),
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fluidRow(
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box(title = "Scatterplot", width = 4,
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plotlyOutput("scatterplot", height = 250)
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),
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box(title = "Histogram", width = 4,
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plotlyOutput("histogram", height = 250)
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),
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box(title = "Density", width = 4,
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plotlyOutput("density", height = 250)
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)
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)
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)
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)
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server <- function(input, output) {
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rate_limit_sec <- 2
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portfolio_selected <- throttle(reactive({
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req(input$portfolio, input$date)
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returns[[input$portfolio]] %>%
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as_tibble() %>%
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#collect() %>%
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mutate(date = as.Date(date)) %>%
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filter(date >= input$date)
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}), rate_limit_sec * 1000)
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rolling_sortino <- reactive({
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req(input$mar)
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req(input$window)
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portfolio_selected()$returns %>%
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xts::xts(order.by = portfolio_selected()$date) %>%
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rollapply(input$window, function(x) SortinoRatio(x, MAR = input$mar)) %>%
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`colnames<-`("24-rolling")
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})
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sortino_byhand <- reactive({
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portfolio_selected() %>%
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mutate(ratio = mean(returns - input$mar) / sqrt(sum(pmin(returns - input$mar, 0)^2) / nrow(.))) %>%
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# Add two new columns to help with ggplot.
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mutate(status = ifelse(returns < input$mar, "down", "up"))
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})
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output$time_series <- renderPlotly({
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plot_ly() %>%
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add_lines(x = index(rolling_sortino()), y = as.numeric(rolling_sortino())) %>%
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layout(
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hovermode = "x",
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xaxis = list(
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rangeslider = list(visible = TRUE),
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rangeselector = list(
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x = 0, y = 1, xanchor = 'left', yanchor = "top", font = list(size = 9),
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buttons = list(
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list(count = 1, label = 'RESET', step = 'all'),
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list(count = 1, label = '1 YR', step = 'year', stepmode = 'backward'),
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list(count = 3, label = '3 MO', step = 'month', stepmode = 'backward'),
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list(count = 1, label = '1 MO', step = 'month', stepmode = 'backward')
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)
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)
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)
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)
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})
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output$scatterplot <- renderPlotly({
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portfolio_scatter <- ggplot(sortino_byhand(), aes(x = date, y = returns, color = status) )+
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geom_point() +
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geom_vline(xintercept = as.numeric(as.Date("2016-11-30")), color = "blue") +
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geom_hline(yintercept = input$mar, color = "purple", linetype = "dotted") +
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scale_color_manual(values = c("tomato", "chartreuse3")) +
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theme(legend.position = "none") + ylab("percent monthly returns")
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ggplotly(portfolio_scatter) %>%
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add_annotations(
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text = "Trump", x = as.numeric(as.Date("2016-11-30")),
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y = -.05, xshift = -10, textangle = -90, showarrow = FALSE
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)
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})
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output$histogram <- renderPlotly({
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p <- ggplot(sortino_byhand(), aes(x = returns)) +
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geom_histogram(alpha = 0.25, binwidth = .01, fill = "cornflowerblue") +
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geom_vline(xintercept = input$mar, color = "green")
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ggplotly(p) %>%
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add_annotations(text = "MAR", x = input$mar, y = 10, xshift = 10, showarrow = FALSE, textangle = -90)
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})
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output$density <- renderPlotly({
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sortino_density_plot <- ggplot(sortino_byhand(), aes(x = returns)) +
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stat_density(geom = "line", size = 1, color = "cornflowerblue")
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shaded_area_data <- ggplot_build(sortino_density_plot)$data[[1]] %>%
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filter(x < input$mar)
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sortino_density_plot <-
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sortino_density_plot +
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geom_area(data = shaded_area_data, aes(x = x, y = y), fill = "pink", alpha = 0.5) +
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geom_segment(
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data = shaded_area_data, aes(x = input$mar, y = 0, xend = input$mar, yend = y),
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color = "red", linetype = "dotted"
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)
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ggplotly(sortino_density_plot) %>%
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add_annotations(
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x = input$mar, y = 5, text = paste("MAR =", input$mar, sep = ""), textangle = -90
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) %>%
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add_annotations(
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x = (input$mar - .02), y = .1, text = "Downside",
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xshift = -20, yshift = 10, showarrow = FALSE
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)
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})
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}
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shinyApp(ui = ui, server = server)

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