Fix 最優造市參數計算器

Research/最優造市參數計算器_ccxt.ipynb

@@ -0,0 +1,361 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "be3eb8aa",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "正在從 bybit 獲取 BTC/USDT 的 1h K線數據...\n",
+      "📊 BTC/USDT 日化波動率估計值: 2.74%\n",
+      "\n",
+      "--- 🔬 最優造市參數計算結果 ---\n",
+      "asset                         : BTC/USDT\n",
+      "current_mid_price             : 89029.4000 USDT\n",
+      "order_refresh_time_sec        : 30.0000 秒\n",
+      "bid_spread                    : 0.0528 %\n",
+      "ask_spread                    : 0.0528 %\n",
+      "long_profit_taking_spread     : 0.0528 %\n",
+      "short_profit_taking_spread    : 0.0528 %\n",
+      "stop_loss_spread              : 3.5057 %\n"
+     ]
+    }
+   ],
+   "source": [
+    "import ccxt\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "from scipy.stats import norm\n",
+    "from datetime import datetime, timedelta, timezone\n",
+    "\n",
+    "# --- 常數定義 ---\n",
+    "DAYS_PER_YEAR = 365.25\n",
+    "SECONDS_PER_DAY = 24 * 3600\n",
+    "\n",
+    "# --- CCXT K 線資料抓取 ---\n",
+    "def get_kline_data(exchange_id: str, symbol: str, timeframe: str = \"1h\", limit: int = 720) -> pd.DataFrame:\n",
+    "    \"\"\"\n",
+    "    使用 CCXT 從指定交易所取得歷史 K 線資料\n",
+    "    \"\"\"\n",
+    "    try:\n",
+    "        exchange_class = getattr(ccxt, exchange_id)\n",
+    "        exchange = exchange_class({\n",
+    "            'enableRateLimit': True,\n",
+    "            'options': {'defaultType': 'spot'} # 預設使用現貨，可根據需要調整\n",
+    "        })\n",
+    "        \n",
+    "        # 檢查並載入市場數據以確保符號正確\n",
+    "        exchange.load_markets()\n",
+    "        \n",
+    "        if symbol not in exchange.markets:\n",
+    "            # 嘗試自動修正常見格式差異 (例如 gate 的 BTC_USDT -> BTC/USDT)\n",
+    "            if '_' in symbol and '/' not in symbol:\n",
+    "                symbol = symbol.replace('_', '/')\n",
+    "            \n",
+    "            if symbol not in exchange.markets:\n",
+    "                raise ValueError(f\"交易所 {exchange_id} 不支持交易對 {symbol}\")\n",
+    "\n",
+    "        # 獲取 K 線數據: [timestamp, open, high, low, close, volume]\n",
+    "        ohlcv = exchange.fetch_ohlcv(symbol, timeframe, limit=limit)\n",
+    "        \n",
+    "        df = pd.DataFrame(ohlcv, columns=[\"timestamp\", \"open\", \"high\", \"low\", \"close\", \"volume\"])\n",
+    "        df[\"timestamp\"] = pd.to_datetime(df[\"timestamp\"], unit=\"ms\", utc=True)\n",
+    "        \n",
+    "        # 依時間排序\n",
+    "        df = df.sort_values(\"timestamp\").reset_index(drop=True)\n",
+    "        \n",
+    "        return df[[\"timestamp\", \"open\", \"high\", \"low\", \"close\"]]\n",
+    "        \n",
+    "    except Exception as e:\n",
+    "        print(f\"獲取 K 線數據失敗: {e}\")\n",
+    "        return pd.DataFrame()\n",
+    "\n",
+    "\n",
+    "# --- 核心策略計算 ---\n",
+    "def calculate_optimal_market_making_params(\n",
+    "    asset: str,\n",
+    "    mid_price: float,\n",
+    "    daily_volatility_pct: float,\n",
+    "    target_order_fill_prob: float,\n",
+    "    order_refresh_time_sec: int,\n",
+    "    stop_loss_risk_prob: float,\n",
+    "    max_holding_time_days: float = 30.0,\n",
+    "    profit_factor: float = 2.0\n",
+    ") -> dict:\n",
+    "    \"\"\"\n",
+    "    根據 GBM 波動率模型，計算最優造市參數\n",
+    "    \"\"\"\n",
+    "    daily_volatility = daily_volatility_pct / 100.0\n",
+    "    annual_volatility = daily_volatility * np.sqrt(DAYS_PER_YEAR)\n",
+    "    dt_order = order_refresh_time_sec / (DAYS_PER_YEAR * SECONDS_PER_DAY)\n",
+    "    dt_loss = max_holding_time_days / DAYS_PER_YEAR\n",
+    "\n",
+    "    # 基礎掛單價差\n",
+    "    p_half_order = target_order_fill_prob / 2.0\n",
+    "    Z_order = norm.ppf(p_half_order)\n",
+    "    base_spread_pct = (annual_volatility * np.sqrt(dt_order) * np.abs(Z_order)) * 100\n",
+    "\n",
+    "    # 止盈與止損\n",
+    "    profit_taking_spread_pct = base_spread_pct * profit_factor\n",
+    "    p_half_loss = stop_loss_risk_prob / 2.0\n",
+    "    Z_loss = norm.ppf(p_half_loss)\n",
+    "    stop_loss_spread_pct = (annual_volatility * np.sqrt(dt_loss) * np.abs(Z_loss)) * 100\n",
+    "\n",
+    "    return {\n",
+    "        \"asset\": asset,\n",
+    "        \"current_mid_price\": mid_price,\n",
+    "        \"order_refresh_time_sec\": order_refresh_time_sec,\n",
+    "        \"bid_spread\": round(base_spread_pct, 4),\n",
+    "        \"ask_spread\": round(base_spread_pct, 4),\n",
+    "        \"long_profit_taking_spread\": round(profit_taking_spread_pct, 4),\n",
+    "        \"short_profit_taking_spread\": round(profit_taking_spread_pct, 4),\n",
+    "        \"stop_loss_spread\": round(stop_loss_spread_pct, 4),\n",
+    "        \"Z_score_order\": round(np.abs(Z_order), 4),\n",
+    "        \"Z_score_stop_loss\": round(np.abs(Z_loss), 4)\n",
+    "    }\n",
+    "\n",
+    "\n",
+    "# --- 主流程：自動從交易所取得波動率並計算策略 ---\n",
+    "def calculate_strategy(exchange_id: str, symbol: str, timeframe: str):\n",
+    "    \"\"\"\n",
+    "    從指定交易所取得歷史資料，自動估算波動率並計算造市策略參數\n",
+    "    \"\"\"\n",
+    "    print(f\"正在從 {exchange_id} 獲取 {symbol} 的 {timeframe} K線數據...\")\n",
+    "    df = get_kline_data(exchange_id, symbol, timeframe=timeframe, limit=720)\n",
+    "\n",
+    "    if df.empty:\n",
+    "        print(\"無法獲取數據，程序終止。\")\n",
+    "        return\n",
+    "\n",
+    "    # 計算對數報酬率\n",
+    "    df[\"log_return\"] = np.log(df[\"close\"] / df[\"close\"].shift(1))\n",
+    "    \n",
+    "    # 計算標準差 (波動率)\n",
+    "    period_vol = df[\"log_return\"].std()\n",
+    "\n",
+    "    # 根據 timeframe 換算成日化波動率\n",
+    "    # 假設 timeframe 格式為 '1m', '5m', '1h', '1d' 等\n",
+    "    intervals_per_day = 24 # Default 1h\n",
+    "    if timeframe == '1m':\n",
+    "        intervals_per_day = 1440\n",
+    "    elif timeframe == '5m':\n",
+    "        intervals_per_day = 288\n",
+    "    elif timeframe == '15m':\n",
+    "        intervals_per_day = 96\n",
+    "    elif timeframe == '30m':\n",
+    "        intervals_per_day = 48\n",
+    "    elif timeframe == '1h':\n",
+    "        intervals_per_day = 24\n",
+    "    elif timeframe == '4h':\n",
+    "        intervals_per_day = 6\n",
+    "    elif timeframe == '1d':\n",
+    "        intervals_per_day = 1\n",
+    "    \n",
+    "    daily_vol = period_vol * np.sqrt(intervals_per_day)\n",
+    "    print(f\"📊 {symbol} 日化波動率估計值: {daily_vol*100:.2f}%\")\n",
+    "\n",
+    "    params = {\n",
+    "        \"asset\": symbol,\n",
+    "        \"mid_price\": df[\"close\"].iloc[-1],\n",
+    "        \"daily_volatility_pct\": daily_vol * 100,\n",
+    "        \"target_order_fill_prob\": 0.3,\n",
+    "        \"order_refresh_time_sec\": 30,\n",
+    "        \"stop_loss_risk_prob\": 0.2,\n",
+    "        \"max_holding_time_days\": 1,\n",
+    "        \"profit_factor\": 1\n",
+    "    }\n",
+    "\n",
+    "    result = calculate_optimal_market_making_params(**params)\n",
+    "\n",
+    "    print(\"\\n--- 🔬 最優造市參數計算結果 ---\")\n",
+    "    for key, value in result.items():\n",
+    "        if \"_spread\" in key or \"time_sec\" in key:\n",
+    "            unit = \"%\" if \"spread\" in key else \"秒\"\n",
+    "            print(f\"{key:<30}: {value:>.4f} {unit}\")\n",
+    "        elif key == \"current_mid_price\":\n",
+    "            print(f\"{key:<30}: {value:>.4f} USDT\")\n",
+    "        elif key == \"asset\":\n",
+    "            print(f\"{key:<30}: {value}\")\n",
+    "\n",
+    "    return result\n",
+    "\n",
+    "\n",
+    "# --- 主執行 ---\n",
+    "if __name__ == \"__main__\":\n",
+    "    # 傳入參數\n",
+    "    exchange_id = 'bybit' # 支援主流交易所 可參照以下輸出\n",
+    "    symbol = 'BTC/USDT' # 需加上/USDT或/USDC等\n",
+    "    timeframe = '1h' # 格式為 '1m', '5m', '1h', '1d' 等\n",
+    "    calculate_strategy(exchange_id, symbol, timeframe)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f4f9b29f",
+   "metadata": {},
+   "source": [
+    "### ccxt支援的交易所列表"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "f8773aea",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CCXT Version: 4.5.2\n",
+      "alpaca\n",
+      "apex\n",
+      "ascendex\n",
+      "bequant\n",
+      "bigone\n",
+      "binance\n",
+      "binancecoinm\n",
+      "binanceus\n",
+      "binanceusdm\n",
+      "bingx\n",
+      "bit2c\n",
+      "bitbank\n",
+      "bitbns\n",
+      "bitfinex\n",
+      "bitflyer\n",
+      "bitget\n",
+      "bithumb\n",
+      "bitmart\n",
+      "bitmex\n",
+      "bitopro\n",
+      "bitrue\n",
+      "bitso\n",
+      "bitstamp\n",
+      "bitteam\n",
+      "bittrade\n",
+      "bitvavo\n",
+      "blockchaincom\n",
+      "blofin\n",
+      "btcalpha\n",
+      "btcbox\n",
+      "btcmarkets\n",
+      "btcturk\n",
+      "bybit\n",
+      "cex\n",
+      "coinbase\n",
+      "coinbaseadvanced\n",
+      "coinbaseexchange\n",
+      "coinbaseinternational\n",
+      "coincatch\n",
+      "coincheck\n",
+      "coinex\n",
+      "coinmate\n",
+      "coinmetro\n",
+      "coinone\n",
+      "coinsph\n",
+      "coinspot\n",
+      "cryptocom\n",
+      "cryptomus\n",
+      "defx\n",
+      "delta\n",
+      "deribit\n",
+      "derive\n",
+      "digifinex\n",
+      "exmo\n",
+      "fmfwio\n",
+      "foxbit\n",
+      "gate\n",
+      "gateio\n",
+      "gemini\n",
+      "hashkey\n",
+      "hibachi\n",
+      "hitbtc\n",
+      "hollaex\n",
+      "htx\n",
+      "huobi\n",
+      "hyperliquid\n",
+      "independentreserve\n",
+      "indodax\n",
+      "kraken\n",
+      "krakenfutures\n",
+      "kucoin\n",
+      "kucoinfutures\n",
+      "latoken\n",
+      "lbank\n",
+      "luno\n",
+      "mercado\n",
+      "mexc\n",
+      "modetrade\n",
+      "myokx\n",
+      "ndax\n",
+      "novadax\n",
+      "oceanex\n",
+      "okcoin\n",
+      "okx\n",
+      "okxus\n",
+      "onetrading\n",
+      "oxfun\n",
+      "p2b\n",
+      "paradex\n",
+      "paymium\n",
+      "phemex\n",
+      "poloniex\n",
+      "probit\n",
+      "timex\n",
+      "tokocrypto\n",
+      "tradeogre\n",
+      "upbit\n",
+      "wavesexchange\n",
+      "whitebit\n",
+      "woo\n",
+      "woofipro\n",
+      "xt\n",
+      "yobit\n",
+      "zaif\n",
+      "zonda\n"
+     ]
+    }
+   ],
+   "source": [
+    "from pprint import pprint\n",
+    "import ccxt  # noqa: E402\n",
+    "\n",
+    "print('CCXT Version:', ccxt.__version__)\n",
+    "\n",
+    "for exchange_id in ccxt.exchanges:\n",
+    "    try:\n",
+    "        exchange = getattr(ccxt, exchange_id)()\n",
+    "        print(exchange_id)\n",
+    "        # do what you want with this exchange\n",
+    "        # pprint(dir(exchange))\n",
+    "    except Exception as e:\n",
+    "        print(e)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "vedanta",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.0"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}