docker-compose up lab\r\n<\/code><\/pre>\n\u3082\u3057\u304f\u306f<\/p>\n
docker run -p 8888:8888 smartradev\/quantx-lab\r\n<\/code><\/pre>\n\u3092\u5165\u529b\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n
\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9\u5f8c\u3001\u300c\u3053\u306eURL\u3092\u30d6\u30e9\u30a6\u30b6\u4e0a\u306b\u30b3\u30d4\u30da\u3057\u3066\u306d\uff01\u300d\u3068\u3044\u3046\u30e1\u30c3\u30bb\u30fc\u30b8\u304c\u51fa\u3066\u304f\u308b\u3068\u601d\u3046\u306e\u3067\u3001\u8a18\u8f09\u3055\u308c\u3066\u3044\u308bURL\u3092\u30b3\u30d4\u30da\u3057\u307e\u3057\u3087\u3046\u3002
\n\u304a\u305d\u3089\u304f\u3001http:\/\/(********* or 127.0.0.1):8888?token=**************\u307f\u305f\u3044\u306a\u611f\u3058\u306b\u306a\u308b\u3068\u601d\u3046\u306e\u3067\u3001()\u5185\u3092\u76f4\u3057\u3066\u30b3\u30d4\u30da\u3057\u307e\u3057\u3087\u3046\u3002<\/p>\n
\u30ed\u30b0\u30a4\u30f3<\/h1>\n
\u30ed\u30b0\u30a4\u30f3\u753b\u9762\u304c\u51fa\u3066\u304f\u308b\u3068\u601d\u3046\u306e\u3067\u3001\u5148\u307b\u3069\u306etoken=*************\u306e\u5024\u90e8\u5206\u3060\u3051\u3092\u30b3\u30d4\u30da\u3057\u3066\u30ed\u30b0\u30a4\u30f3\u3057\u307e\u3057\u3087\u3046\u3002
\n\u4e0a\u624b\u304f\u884c\u304f\u3068\u3001jupyter\u304c\u7acb\u3061\u4e0a\u304c\u308b\u3068\u601d\u3044\u307e\u3059\u3002<\/p>\n
\u3059\u3067\u306b\u30c8\u30fc\u30af\u30f3\u3092\u4f5c\u6210\u3057\u3066\u3044\u308b\u4eba\u306f\u30a8\u30e9\u30fc\u304c\u51fa\u308b\u307f\u305f\u3044\u3067\u3059\u3002\u30bf\u30fc\u30df\u30ca\u30eb\u3067jupyter notebook\u3092\u7acb\u3061\u4e0a\u3052\u305f\u6642\u306b\u8868\u793a\u3055\u308c\u308btoken\u3092\u53c2\u7167\u3057\u307e\u3057\u3087\u3046\u3002<\/p>\n
\u65e9\u901f\u52d5\u304b\u3057\u3066\u307f\u308b<\/h1>\n
\u65e9\u901fQuantX SDK\u3092\u4f7f\u3063\u3066\u307f\u307e\u3059\u3002<\/p>\n
\u30a2\u30af\u30bb\u30b9\u30ad\u30fc\u306e\u53d6\u5f97<\/h3>\n
SDK\u3092\u4f7f\u3046\u305f\u3081\u306b\u306f\u3001\u30a2\u30af\u30bb\u30b9\u30ad\u30fc\u3068\u30b7\u30fc\u30af\u30ec\u30c3\u30c8\u30ad\u30fc\u304c\u5fc5\u8981\u3067\u3059\u3002QuantX\u306b\u30ed\u30b0\u30a4\u30f3\u3057\u3066\u3001https:\/\/factory.quantx.io\/settings\/token\u304b\u3089\u53d6\u5f97\u3057\u3066\u304f\u3060\u3055\u3044\u3002\u30c8\u30fc\u30af\u30f3\u540d\u306f\u306a\u3093\u3067\u3082\u3044\u3044\u3067\u3059\u3002\u4e00\u5ea6\u3057\u304b\u767a\u884c\u3055\u308c\u306a\u3044\u306e\u3067\u3001\u5fd8\u308c\u305a\u306b\u4fdd\u7ba1\u3057\u307e\u3057\u3087\u3046\u3002<\/p>\n
\u65b0\u898f\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u3092\u4f5c\u6210<\/h3>\n# public_key\u3068secret_key\u306f\u5404\u81ea\u3054\u81ea\u8eab\u306e\u30ad\u30fc\u3067\u7f6e\u304d\u63db\u3048\u3066\u304f\u3060\u3055\u3044\r\n<\/span>access_key<\/span> =<\/span> \"************************************\"<\/span>\r\nsecret_key<\/span> =<\/span> \"************************************\"<\/span>\r\n\r\n# sdk \u3092\u30a4\u30f3\u30dd\u30fc\u30c8\r\n<\/span>from<\/span> quantx_sdk<\/span> import<\/span> QX<\/span>\r\n\r\n# \u65b0\u898f\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u4f5c\u6210\r\n<\/span>qx<\/span> =<\/span> QX<\/span>(<\/span>access_key<\/span>,<\/span> secret_key<\/span>)<\/span>\r\n\r\n# \u65b0\u898f\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u540d\u3002\uff15\u6587\u5b57\u4ee5\u4e0a\u306e\u9069\u5f53\u306a\u6587\u5b57\u5217\r\n<\/span>new_name<\/span> =<\/span> \"New Project\"<\/span>\r\n\r\n# \u65b0\u898f\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u3092\u4f5c\u6210\u3002\r\n<\/span>prj<\/span> =<\/span> qx<\/span>.<\/span>new_project<\/span>(<\/span>new_name<\/span>)<\/span>\r\n<\/code><\/pre>\n\u5148\u307b\u3069\u53d6\u5f97\u3057\u305f\u30a2\u30af\u30bb\u30b9\u30ad\u30fc\u3068\u30b7\u30fc\u30af\u30ec\u30c3\u30c8\u30ad\u30fc\u3092\u5909\u6570\u5185\u306b\u683c\u7d0d\u3057\u3066\u3001\u65b0\u898f\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u3092\u4f5c\u6210\u3057\u3066\u304f\u3060\u3055\u3044\u3002\u4eca\u56de\u306fNew Project\u3068\u3044\u3046\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u540d\u306b\u3057\u307e\u3057\u305f\u3002\u5b9f\u884c\u5f8c\u3001\u30d6\u30e9\u30a6\u30b6\u3067\u65b0\u898f\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u304c\u4f5c\u6210\u3055\u308c\u3066\u3044\u308b\u3053\u3068\u304c\u78ba\u8a8d\u3067\u304d\u308b\u3068\u601d\u3044\u307e\u3059\u3002<\/p>\n
\u30cf\u30c3\u30b7\u30e5\u756a\u53f7\u3092\u53d6\u5f97<\/h3>\n# \u30cf\u30c3\u30b7\u30e5\u756a\u53f7\u3092\u683c\u7d0d\uff0c\u78ba\u8a8d\uff0e\r\n<\/span>prjct_hash<\/span> =<\/span> prj<\/span>.<\/span>project_hash<\/span>\r\n<\/code><\/pre>\nQuantX\u3067\u306f\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u306f\u540d\u524d\u3067\u306f\u306a\u304f\u30cf\u30c3\u30b7\u30e5\u756a\u53f7\u3067\u7ba1\u7406\u3057\u3066\u3044\u308b\u3088\u3046\u3067\u3059\u3002\u30b3\u30fc\u30c9\u3092\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u306b\u30d7\u30c3\u30b7\u30e5\u3059\u308b\u4e0a\u3067\u3001\u30d7\u30c3\u30b7\u30e5\u5148\u306e\u30cf\u30c3\u30b7\u30e5\u756a\u53f7\u3092\u9593\u9055\u3048\u306a\u3044\u3088\u3046\u306b\u6c17\u3092\u3064\u3051\u307e\u3057\u3087\u3046\u3002<\/p>\n
\u30b3\u30fc\u30c9\u53d6\u5f97<\/h3>\n
\u65b0\u898f\u4f5c\u6210\u3057\u305f\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u306b\u306f\u3001\u30b5\u30f3\u30d7\u30eb\u30b3\u30fc\u30c9\u304c\u4e0e\u3048\u3089\u308c\u3066\u3044\u307e\u3059\u3002<\/p>\n
prj<\/span>.<\/span>source<\/span>()<\/span>\r\n<\/code><\/pre>\n\u3067\u53d6\u5f97\u3067\u304d\u307e\u3059\u3002<\/p>\n
\u81ea\u5206\u306e\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u3092\u30a2\u30c3\u30d7\u30ed\u30fc\u30c9\u3057\u3066\u5b9f\u884c\u3059\u308b\u3002<\/h1>\n
\u3067\u306f\u3001\u81ea\u5206\u3067\u66f8\u3044\u305f\u30a2\u30eb\u30b4\u30eb\u30ba\u30e0\u3092QuantX\u306b\u30a2\u30c3\u30d7\u30ed\u30fc\u30c9\u3057\u3066\u30d0\u30c3\u30af\u30c6\u30b9\u30c8\u3092\u884c\u3063\u3066\u307f\u307e\u3059\u3002<\/p>\n
\u30bd\u30fc\u30b9\u30b3\u30fc\u30c9\u3092\u30a2\u30c3\u30d7\u30ed\u30fc\u30c9\u3059\u308b<\/h3>\n
\u4eca\u56de\u306f\u3001\u524d\u56de\u50d5\u304c\u66f8\u3044\u305fMACD\u306e\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u3092\u4f7f\u3063\u3066\u307f\u307e\u3059\u3002
\n\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306f\u6587\u5b57\u5217\u3067\u6e21\u3057\u307e\u3059\u3002<\/p>\n
source<\/span> =<\/span> \"\"\"import pandas as pd\r\nimport numpy as np \r\nimport talib as ta \r\n\r\ndef initialize(ctx):\r\n # \u8a2d\u5b9a\r\n ctx.logger.debug(\"initialize() called\")\r\n ctx.configure(\r\n channels=\r\n {\r\n \"jp.stock\": {\r\n \"columns\": [\r\n \"close_price_adj\"\r\n ],\r\n \"symbols\": [\r\n \"jp.stock.1414\", \"jp.stock.2269\",\r\n \"jp.stock.2292\", \"jp.stock.2371\",\r\n \"jp.stock.2379\", \"jp.stock.2413\",\r\n \"jp.stock.2427\", \"jp.stock.2702\",\r\n \"jp.stock.2782\", \"jp.stock.2809\",\r\n \"jp.stock.3003\",\r\n \"jp.stock.3053\", \r\n \"jp.stock.3092\", \"jp.stock.3141\",\r\n \"jp.stock.3382\", \"jp.stock.3407\",\r\n \"jp.stock.3665\", \"jp.stock.3676\",\r\n \"jp.stock.4063\", \"jp.stock.4343\",\r\n \"jp.stock.4452\", \"jp.stock.4519\",\r\n \"jp.stock.4543\", \"jp.stock.4704\",\r\n \"jp.stock.4751\", \"jp.stock.4911\",\r\n \"jp.stock.4974\", \"jp.stock.5108\",\r\n \"jp.stock.6028\", \"jp.stock.6098\",\r\n \"jp.stock.6194\", \"jp.stock.6503\",\r\n \"jp.stock.6645\", \"jp.stock.6758\",\r\n \"jp.stock.6866\", \"jp.stock.7269\",\r\n \"jp.stock.7272\", \"jp.stock.7606\",\r\n \"jp.stock.7936\", \"jp.stock.8020\",\r\n \"jp.stock.8252\", \"jp.stock.8591\",\r\n \"jp.stock.8929\", \"jp.stock.9007\",\r\n \"jp.stock.9086\", \"jp.stock.9433\",\r\n \"jp.stock.9613\"\r\n ]\r\n }\r\n }\r\n )\r\n\r\n def _my_signal(data):\r\n cp=data[\"close_price_adj\"].fillna(method='ffill')\r\n macd=pd.DataFrame(data=0,columns=cp.columns,index=cp.index)\r\n macdsignal=pd.DataFrame(data=0,columns=cp.columns,index=cp.index)\r\n macdhist=pd.DataFrame(data=0,columns=cp.columns,index=cp.index)\r\n dmacd = pd.DataFrame(data=0,columns=cp.columns,index=cp.index)\r\n dmacdsignal = pd.DataFrame(data=0,columns=cp.columns, index=cp.index)\r\n for (sym,val) in cp.items():\r\n macd[sym], macdsignal[sym], macdhist[sym] = ta.MACD(cp[sym].values.astype(np.double), fastperiod=9, slowperiod=26, signalperiod=9)\r\n dmacd[sym] = np.gradient(macd[sym])\r\n dmacdsignal[sym] = np.gradient(macdsignal[sym])\r\n\r\n #\u901a\u5e38\u306eMACD\r\n #buy_sig = ((macd > macdsignal) & (macd.shift(1) < macdsignal.shift(1)))\r\n #sell_sig= ((macd < macdsignal) & (macd.shift(1) > macdsignal.shift(1)))\r\n\r\n #\u6539\u826f\u7248\r\n buy_sig = ((macd > macdsignal) & (macd.shift(1) < macdsignal.shift(1)) & (dmacd\/dmacdsignal>5.0) & (abs(dmacdsignal) > 1.0))\r\n sell_sig = ((macd < macdsignal) & (macd.shift(1) > macdsignal.shift(1)) & (dmacd\/dmacdsignal>5.0) & (abs(dmacdsignal) > 1.0))\r\n\r\n return {\r\n \"macd\": macd,\r\n \"macdsignal\": macdsignal,\r\n \"hist\":macdhist,\r\n \"dmacd\":dmacd,\r\n \"dmacdsignal\":dmacdsignal,\r\n \"buy:sig\": buy_sig,\r\n \"sell:sig\": sell_sig,\r\n }\r\n\r\n # \u30b7\u30b0\u30ca\u30eb\u767b\u9332\r\n ctx.regist_signal(\"my_signal\", _my_signal)\r\n\r\ndef handle_signals(ctx, date, current):\r\n '''\r\n current: pd.DataFrame\r\n '''\r\n\r\n df = current.copy()\r\n\r\n # \u8cb7\u3044\u30b7\u30b0\u30ca\u30eb\r\n df_long = df[df[\"buy:sig\"]]\r\n if not df_long.empty:\r\n for (sym, val) in df_long.iterrows(): \r\n #ctx.logger.info(val)\r\n sec = ctx.getSecurity(sym)\r\n msg = \"\u8cb7\u3044\u30b7\u30b0\u30ca\u30eb\"\r\n sec.order_target_percent(0.10, comment= msg)\r\n\r\n # \u58f2\u308a\u30b7\u30b0\u30ca\u30eb\r\n df_sell = df[df[\"sell:sig\"]]\r\n if not df_sell.empty:\r\n for (sym, val) in df_sell.iterrows(): \r\n sec = ctx.getSecurity(sym)\r\n msg = \"\u58f2\u308a\u30b7\u30b0\u30ca\u30eb\"\r\n sec.order_target_percent(0, comment= msg)\r\n\"\"\"<\/span>\r\n\r\n<\/code><\/pre>\n\u6b21\u306b\u3001\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u3092\u6307\u5b9a\u3057\u3066\u30bd\u30fc\u30b9\u30b3\u30fc\u30c9\u3092\u30a2\u30c3\u30d7\u30ed\u30fc\u30c9\u3057\u307e\u3059\u3002\u5148\u307b\u3069\u4f5c\u3063\u305fprjct_hash\u3092\u4f7f\u3063\u3066\u3001\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u4f5c\u308a\u3001\u305d\u306e\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306b\u5bfe\u3057\u3066upload_source()\u30e1\u30bd\u30c3\u30c9\u3067\u30b3\u30fc\u30c9\u3092Upload\u3057\u307e\u3059\u3002<\/p>\n
# hash\u756a\u53f7\u3092\u4e0e\u3048\u3066\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u4f5c\u308a\u307e\u3059\r\n<\/span>prj<\/span> =<\/span> qx<\/span>.<\/span>project<\/span>(<\/span>prjct_hash<\/span>)<\/span>\r\n\r\n# \u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u306b\u30b3\u30fc\u30c9\u3092Upload\r\n<\/span>prj<\/span>.<\/span>upload_source<\/span>(<\/span>source<\/span>)<\/span>\r\n<\/code><\/pre>\n‘code’: 200\u304c\u8fd4\u3063\u3066\u304f\u308c\u3070\u6210\u529f\u3067\u3059\u3002<\/p>\n
\u30d0\u30c3\u30af\u30c6\u30b9\u30c8\u3092\u5b9f\u884c\u3059\u308b\u3002<\/h3>\n# \u30d0\u30c3\u30af\u30c6\u30b9\u30c8\u30d1\u30e9\u30e1\u30fc\u30bf\r\n<\/span>bt_parameter<\/span> =<\/span> {<\/span>\r\n 'engine'<\/span>:<\/span> 'maron-0.0.1b'<\/span>,<\/span>\r\n 'from_date'<\/span>:<\/span> '2015-12-01'<\/span>,<\/span>\r\n 'to_date'<\/span>:<\/span> '2018-12-01'<\/span>,<\/span>\r\n 'capital_base'<\/span>:<\/span> 10000000<\/span>}<\/span>\r\n\r\n# backtest \u306e\u5b9f\u884c. \r\n<\/span>bt<\/span> =<\/span> prj<\/span>.<\/span>backtest<\/span>(<\/span>bt_parameter<\/span>)<\/span>\r\n\r\n## backtest result \u30a4\u30f3\u30b9\u30bf\u30f3\u30b9\u3092\u4f5c\u6210\r\n<\/span>join<\/span> =<\/span> bt<\/span>.<\/span>join<\/span>()<\/span>\r\n\r\n## \u7d50\u679c\u306e\u30b5\u30de\u30ea\u30fc\u3092\u53d6\u5f97\r\n<\/span>summary<\/span> =<\/span> join<\/span>.<\/span>summary<\/span>()<\/span>\r\n<\/code><\/pre>\n\u4f7f\u7528\u3059\u308b\u30a8\u30f3\u30b8\u30f3\u3001\u671f\u9593\u3001\u8cc7\u91d1\u984d\u306a\u3069\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u3092\u6307\u5b9a\u3057\u3066\u3042\u3052\u3066\u3001\u30d0\u30c3\u30af\u30c6\u30b9\u30c8\u3092\u5b9f\u884c\u3057\u3066\u304f\u3060\u3055\u3044\u3002
\nsummary\u5185\u306b\u7d50\u679c\u304c\u51fa\u529b\u3055\u308c\u3066\u3044\u308b\u306f\u305a\u3067\u3059\u3002<\/p>\n
![\"\u30b9\u30af\u30ea\u30fc\u30f3\u30b7\u30e7\u30c3\u30c8](\"https:\/\/cdn.silicloud.com\/blog-img\/blog\/img\/657d643737434c4406d03d96\/41-0.png\" "\\"\\"")
<\/div>\n\u304a\u308f\u308a\u306b<\/h1>\n
Jupyter\u3067QuantX\u3092\u5b9f\u884c\u3057\u3066\u307f\u307e\u3057\u305f\u3002\u30ed\u30fc\u30ab\u30eb\u3067\u958b\u767a\u3067\u304d\u308b\u3088\u3046\u306b\u306a\u308a\u3001\u304b\u306a\u308a\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u304c\u66f8\u304d\u3084\u3059\u304f\u306a\u3063\u305f\u306e\u3067\u306f\u306a\u3044\u3067\u3057\u3087\u3046\u304b\u3002pyfolio\u306a\u3069\u306e\u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u4f7f\u3048\u3070\u3001\u3082\u3063\u3068\u7cbe\u7dfb\u306a\u30d0\u30c3\u30af\u30c6\u30b9\u30c8\u306e\u5206\u6790\u304c\u3067\u304d\u308b\u307f\u305f\u3044\u3067\u3059\u3002<\/p>\n
\u5f15\u7528\u5143<\/h1>\n
https:\/\/github.com\/smartradev\/quantx-lab<\/p>\n","protected":false},"excerpt":{"rendered":"
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