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| import gradio as gr | |
| import pandas as pd | |
| from datetime import datetime | |
| # 從 bond.py 導入重構後的函數和數據 | |
| from bond import create_bond_database, run_simulation | |
| # 1. 數據準備 | |
| BOND_DATABASE = create_bond_database() | |
| BOND_CHOICES = list(BOND_DATABASE.keys()) | |
| # --- Gradio 介面輔助函數 --- | |
| def get_bond_info_html(bond_name): | |
| """ | |
| 根據下拉選單選擇的債券名稱，生成用於顯示其詳細資訊的 HTML 字串。 | |
| :param bond_name: str, 使用者從下拉選單選擇的債券名稱。 | |
| :return: str, 一個 HTML 格式的字串，用於在 Gradio 介面中顯示。 | |
| """ | |
| if not bond_name: | |
| return "<p>請從上方選擇一個債券</p>" | |
| bond = BOND_DATABASE[bond_name] | |
| issue_date_str = bond['issueDate'].strftime('%Y-%m-%d') | |
| maturity_date_str = bond['maturity'].strftime('%Y-%m-%d') | |
| # **重要**: 根據資料庫中的百分比格式，調整顯示方式 | |
| html = f""" | |
| <div style="border: 1px solid #e0e0e0; padding: 15px; border-radius: 5px;"> | |
| <h4 style="margin-top:0;">債券: {bond_name}</h4> | |
| <table style="width:100%;"> | |
| <tr><td style="width:50%;"><strong>平均殖利率 (avgYld):</strong> {bond['avgYld']:.3f}%</td><td style="width:50%;"><strong>票面利率 (coupon):</strong> {bond['coupon']:.3f}%</td></tr> | |
| <tr><td><strong>發行日 (issueDate):</strong> {issue_date_str}</td><td><strong>到期日 (maturity):</strong> {maturity_date_str}</td></tr> | |
| <tr><td><strong>每年付息 (payPerYr):</strong> {bond['payPerYr']} 次</td><td><strong>每年複利 (compPerYr):</strong> {bond['compPerYr']} 次</td></tr> | |
| <tr><td><strong>存續期間 (durT):</strong> {bond['durT']}</td><td><strong>修正存續期間 (mdurT):</strong> {bond['mdurT']}</td></tr> | |
| <tr><td><strong>價格曲度 (convT):</strong> {bond['convT']}</td><td></td></tr> | |
| </table> | |
| </div> | |
| """ | |
| return html | |
| def run_monte_carlo( | |
| bond_name, n_simulations, dt, | |
| kappa_rf, theta_rf, sigma_rf, | |
| initial_spread, sigma_spread, correlation, | |
| mu_r, sigma_r, | |
| kappa_cir, theta_cir, sigma_cir | |
| ): | |
| """ | |
| Gradio 的主要執行函數。 | |
| 它負責收集所有來自介面的輸入參數，將百分比單位轉換為小數， | |
| 調用後端的 `run_simulation` 核心函式，並將計算結果回傳給介面的各個輸出元件。 | |
| :param bond_name: str, 選擇的債券名稱。 (e.g., 'CGB10Y') | |
| :param n_simulations: int, 模擬次數。 (e.g., 100) | |
| :param dt: float, 時間步長。 (e.g., 1/252) | |
| :param kappa_rf: float, 均值回歸速度。 (e.g., 0.3) | |
| :param theta_rf: float, 長期平均利率 (%)。 (e.g., 2.2) | |
| :param sigma_rf: float, 波動率 (%)。 (e.g., 0.5) | |
| :param initial_spread: float, 初始信用利差 (%)。 (e.g., 0.8) | |
| :param sigma_spread: float, 利差波動率 (%)。 (e.g., 0.3) | |
| :param correlation: float, drf與利差的相關係數。 (e.g., 0.6) | |
| :param mu_r: float, 長期漂移趨勢 (%)。 (e.g., 0.05) | |
| :param sigma_r: float, 年化波動率 (%)。 (e.g., 0.6) | |
| :param kappa_cir: float, CIR 均值回歸速度。 | |
| :param theta_cir: float, CIR 長期平均利率 (%)。 | |
| :param sigma_cir: float, CIR 波動率 (%)。 | |
| :return: tuple, 包含所有結果的元組，用於更新 Gradio 介面的各個輸出元件。 | |
| """ | |
| if not bond_name: | |
| raise gr.Error("請先選擇一個債券！") | |
| bond_data = BOND_DATABASE[bond_name] | |
| # **重要**: 將來自UI的百分比參數轉換為小數以進行計算 | |
| params = { | |
| 'kappa_rf': kappa_rf, | |
| 'theta_rf': theta_rf / 100.0, | |
| 'sigma_rf': sigma_rf / 100.0, | |
| 'initial_spread': initial_spread / 100.0, | |
| 'sigma_spread': sigma_spread / 100.0, | |
| 'correlation': correlation, | |
| 'mu_r': mu_r / 100.0, | |
| 'sigma_r': sigma_r / 100.0, | |
| 'kappa_cir': kappa_cir, | |
| 'theta_cir': theta_cir / 100.0, | |
| 'sigma_cir': sigma_cir / 100.0, | |
| "n_simulations":int(n_simulations), | |
| } | |
| rate_stats_df, price_stats_df, fig_rate_paths, fig_rate_dist, fig_price_paths, fig_price_dist, report_filepath = run_simulation( | |
| bond_data=bond_data, n_simulations=int(n_simulations), dt=dt, params=params | |
| ) | |
| return ( | |
| rate_stats_df, price_stats_df, | |
| fig_rate_paths, fig_rate_dist, | |
| fig_price_paths, fig_price_dist, | |
| gr.update(value=report_filepath, visible=True) | |
| ) | |
| # --- 建立 Gradio 介面 --- | |
| with gr.Blocks(theme=gr.themes.Soft(), title="債券利率蒙地卡羅模擬") as app: | |
| gr.Markdown("# 債券利率與價格蒙地卡羅模擬") | |
| # --- 步驟 1 & 2: 參數設定 --- | |
| with gr.Row(): | |
| with gr.Column(scale=2): | |
| gr.Markdown("## 步驟 1: 選擇債券") | |
| bond_selector = gr.Dropdown(BOND_CHOICES, label="選擇債券", info="從模擬的資料庫中選擇一個債券以載入其初始參數。", value=BOND_CHOICES[0]) | |
| bond_info_display = gr.HTML(get_bond_info_html(BOND_CHOICES[0])) | |
| with gr.Column(scale=3): | |
| gr.Markdown("## 步驟 2: 設定模擬參數") | |
| with gr.Tabs(): | |
| with gr.Tab("債券風險利率 (drf)"): | |
| kappa_rf = gr.Slider(0.01, 1.0, value=0.3, step=0.01, label="均值回歸速度 (kappa_rf)") | |
| theta_rf = gr.Slider(1.0, 5.0, value=2.2, step=0.1, label="長期平均利率 (%)") | |
| sigma_rf = gr.Slider(0.1, 2.0, value=0.5, step=0.1, label="波動率 (%)") | |
| with gr.Tab("有風險利率 (drs)"): | |
| initial_spread = gr.Slider(0.1, 3.0, value=0.8, step=0.1, label="初始信用利差 (%)") | |
| sigma_spread = gr.Slider(0.1, 1.0, value=0.3, step=0.05, label="利差波動率 (%)") | |
| correlation = gr.Slider(-1.0, 1.0, value=0.6, step=0.05, label="drf與利差的相關係數") | |
| with gr.Tab("綜合利率 (dr)"): | |
| mu_r = gr.Slider(0.0, 0.2, value=0.05, step=0.01, label="長期漂移趨勢 (%)") | |
| sigma_r = gr.Slider(0.1, 2.0, value=0.6, step=0.1, label="年化波動率 (%)") | |
| with gr.Tab("CIR 利率 (dr_cir)"): | |
| gr.Markdown("#### Cox-Ingersoll-Ross (CIR) 模型\n此模型 `dr = k(θ - r)dt + σ√r dW` 確保利率為正。") | |
| kappa_cir = gr.Slider(0.01, 1.0, value=0.2, step=0.01, label="均值回歸速度 (kappa_cir)") | |
| theta_cir = gr.Slider(1.0, 5.0, value=2.5, step=0.1, label="長期平均利率 (%)") | |
| sigma_cir = gr.Slider(0.1, 2.0, value=0.4, step=0.1, label="波動率 (%)") | |
| n_simulations = gr.Slider(50, 100000, value=50, step=50, label="模擬次數 (n_simulations)") | |
| dt = gr.Number(value=1/252, label="時間步長 (dt)", info="以年為單位，預設為一個交易日(1/252年)。") | |
| # --- 步驟 3: 執行 --- | |
| run_button = gr.Button("開始模擬", variant="primary") | |
| # --- 步驟 4: 結果呈現 --- | |
| with gr.Tabs(): | |
| with gr.Tab("利率分析"): | |
| gr.Markdown("## 利率模擬結果") | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| gr.Markdown("#### 利率統計數據") | |
| rate_results_table = gr.DataFrame(headers=["指標", "數值"], datatype=["str", "str"]) | |
| with gr.Column(scale=2): | |
| gr.Markdown("#### 利率路徑與相關性圖") | |
| plot_rate_paths = gr.Plot() | |
| gr.Markdown("#### 利率變化分佈圖") | |
| plot_rate_distribution = gr.Plot() | |
| with gr.Tab("債券價格分析"): | |
| gr.Markdown("## 債券價格模擬結果") | |
| gr.Markdown("使用修正存續期間與曲度來估算價格變化。初始價格假設為 100。") | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| gr.Markdown("#### 價格統計數據 (含 VaR)") | |
| price_results_table = gr.DataFrame() | |
| with gr.Column(scale=2): | |
| gr.Markdown("#### 價格模擬路徑") | |
| plot_price_paths = gr.Plot() | |
| gr.Markdown("#### 最終價格分佈") | |
| plot_price_distribution = gr.Plot() | |
| # --- 步驟 5: 下載資料 --- | |
| with gr.Column(): | |
| gr.Markdown("--- \n ## 下載完整報告，(若模擬次數超過1000，則不會包含模擬路徑與價格資料，以避免檔案過大)") | |
| report_file = gr.File(label="下載完整報告 (Excel)", visible=False) | |
| # --- 事件監聽 --- | |
| bond_selector.change(fn=get_bond_info_html, inputs=bond_selector, outputs=bond_info_display) | |
| all_inputs = [ | |
| bond_selector, n_simulations, dt, | |
| kappa_rf, theta_rf, sigma_rf, | |
| initial_spread, sigma_spread, correlation, | |
| mu_r, sigma_r, | |
| kappa_cir, theta_cir, sigma_cir | |
| ] | |
| run_button.click( | |
| fn=run_monte_carlo, | |
| inputs=all_inputs, | |
| outputs=[ | |
| rate_results_table, price_results_table, | |
| plot_rate_paths, plot_rate_distribution, | |
| plot_price_paths, plot_price_distribution, | |
| report_file | |
| ] | |
| ) | |
| if __name__ == "__main__": | |
| app.launch() | |