app.R

# 必要パッケージ
library(shiny)
library(ggplot2)
library(dplyr)
library(readr)
library(writexl)
library(tidyr)

# UI定義
ui <- fluidPage(
  titlePanel("Gibson-Schwartzモデルによる銅価格シミュレーション"),
  sidebarLayout(
    sidebarPanel(
      numericInput("kappa", "κ（平均回帰速度）", 3.77),
      numericInput("alpha", "α（便利性利得の平均）", -0.003),
      numericInput("sigma_delta", "σδ（便利性利得のボラティリティ）", 0.015),
      numericInput("sigma_S", "σS（価格のボラティリティ）", 0.02),
      numericInput("rho", "相関係数ρ", 0.3),
      numericInput("n_path", "シミュレーションパス数", 20, min = 1, max = 100),
      actionButton("run", "シミュレーション実行"),
      downloadButton("download", "CSVでダウンロード")
    ),
    mainPanel(
      plotOutput("simPlot")
    )
  )
)

# サーバー定義
server <- function(input, output) {
  sim_data <- reactiveVal(NULL)
  
  observeEvent(input$run, {
    df <- read_csv("copper_futures_cleaned.csv")
    df <- df %>% drop_na()
    S0 <- exp(mean(df$log_price, na.rm = TRUE))
    T_days <- 252
    dt <- 1 / T_days
    n <- input$n_path
    
    logS <- matrix(0, nrow = T_days + 1, ncol = n)
    delta <- matrix(0, nrow = T_days + 1, ncol = n)
    logS[1, ] <- log(S0)
    delta[1, ] <- input$alpha
    
    set.seed(123)
    for (i in 2:(T_days + 1)) {
      Z1 <- rnorm(n)
      Z2 <- rnorm(n)
      W_delta <- Z1
      W_S <- input$rho * Z1 + sqrt(1 - input$rho^2) * Z2
      delta[i, ] <- delta[i - 1, ] + input$kappa * (input$alpha - delta[i - 1, ]) * dt + input$sigma_delta * sqrt(dt) * W_delta
      logS[i, ] <- logS[i - 1, ] + (- delta[i - 1, ] - 0.5 * input$sigma_S^2) * dt + input$sigma_S * sqrt(dt) * W_S
    }
    
    # ワイド形式のデータフレーム作成
    df_sim <- as.data.frame(exp(logS))
    colnames(df_sim) <- paste0("path_", 1:n)
    df_sim$day <- 0:T_days
    df_sim <- df_sim %>% relocate(day)
    sim_data(df_sim)
    
    # ロング形式でプロット用データも作成
    df_long <- df_sim %>% pivot_longer(-day, names_to = "path", values_to = "price")
    
    output$simPlot <- renderPlot({
      ggplot(df_long, aes(x = day, y = price, group = path, color = path)) +
        geom_line(alpha = 0.8) +
        scale_color_viridis_d(option = "D") +
        labs(title = "Copper Price Simulation using the Gibson-Schwartz Model",
             x = "Days", y = "Copper Price (USD/t)", color = "Path") +
        theme_minimal(base_size = 14) +
        theme(legend.position = "none")
    })
  })
  
  output$download <- downloadHandler(
    filename = function() {
      paste0("copper_simulation_", Sys.Date(), ".csv")
    },
    content = function(file) {
      write.csv(sim_data(), file, row.names = FALSE)
    }
  )
}

# アプリ起動
shinyApp(ui = ui, server = server)