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"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/shinseitaro/be1d1ea012b1dc2657569632eb1e9069/crypto-advent-calender-2021.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "dAVhEe7LnSW6"
},
"source": [
"# [仮想通貨botter Advent Calendar 2021 13日目](https://qiita.com/advent-calendar/2021/botter)\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "9QcysVugnckB"
},
"source": [
"## このノートでやること\n",
"\n",
"1. CCXT からデータをフェッチ\n",
"1. バックテスト用にデータ前処理\n",
"1. Backtesting.py を使ったバックテスト方法の解説\n",
"1. SuperTrend インディケータを backtesting.py でコーディング\n",
"1. Backtesting.py を使った最適化\n",
"1. 最適化したパラメータを使って out-of-sample テスト\n"
]
},
{
"cell_type": "markdown",
"source": [
"## 前提知識\n",
"\n",
"- Python の基本的な文法\n",
"- [Pandas](https://pandas.pydata.org/) の使い方\n",
"- Google Colab の使い方"
],
"metadata": {
"id": "hzhgBv9vfXND"
}
},
{
"cell_type": "markdown",
"metadata": {
"id": "HV4gZ7nRnczB"
},
"source": [
"## CCXTからデータを取得\n",
"- CCXT は、色々な暗号通貨取引所のAPIを共通のインターフェイスで使えるようにしてくれるライブラリです。\n",
"- レポジトリ：[ccxt/ccxt: A JavaScript / Python / PHP cryptocurrency trading API with support for more than 100 bitcoin/altcoin exchanges](https://github.com/ccxt/ccxt)\n",
"- 今回はCCXT経由で[FTX](https://ftx.com/markets)のデータを取得します。CCXTの詳細については公式レポジトリを参照してください。\n",
"- 実行時に `timeout: The read operation timed out` エラーが発生することがあります。この場合は10秒くらい待って再度実行してください。\n"
]
},
{
"cell_type": "code",
"metadata": {
"id": "EI7vFqkpCn2_"
},
"source": [
"# インストール\n",
"!pip install ccxt"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "QTnl8IEpCuJa"
},
"source": [
"import pandas as pd\n",
"import ccxt\n",
"\n",
"\n",
"def data_to_df(data):\n",
" \"\"\"CCXTから取得したデータをDataFrameに変換\"\"\"\n",
"\n",
" df = pd.DataFrame(\n",
" data, columns=[\"Date Time\", \"Open\", \"High\", \"Low\", \"Close\", \"Volume\"]\n",
" )\n",
" df[\"Date Time\"] = pd.to_datetime(df[\"Date Time\"] / 1000, unit=\"s\")\n",
" df.set_index(\"Date Time\", inplace=True)\n",
" return df\n",
"\n",
"\n",
"def get_data(ticker, timeframe=\"5m\"):\n",
" # 取引所のリミットレート(アクセス制限)を超えないように設定\n",
" exchange = ccxt.ftx({\"enableRateLimit\": True})\n",
" df = data_to_df(\n",
" exchange.fetch_ohlcv(\n",
" ticker, \n",
" timeframe=timeframe, \n",
" params={\"reverse\": False})\n",
" )\n",
" return df\n"
],
"execution_count": 2,
"outputs": []
},
{
"cell_type": "code",
"source": [
"# データが取得できることを確認 \n",
"get_data(\"BTC-PERP\")"
],
"metadata": {
"id": "ugUKsZXQzbf0",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 455
},
"outputId": "50bd6dbc-13e8-4190-abec-9a604c2de643"
},
"execution_count": 3,
"outputs": [
{
"output_type": "execute_result",
"data": {
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"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Open</th>\n",
" <th>High</th>\n",
" <th>Low</th>\n",
" <th>Close</th>\n",
" <th>Volume</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Date Time</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2021-12-08 15:15:00</th>\n",
" <td>50991.0</td>\n",
" <td>51036.0</td>\n",
" <td>50888.0</td>\n",
" <td>50944.0</td>\n",
" <td>1.464595e+07</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-12-08 15:20:00</th>\n",
" <td>50944.0</td>\n",
" <td>51300.0</td>\n",
" <td>50937.0</td>\n",
" <td>51105.0</td>\n",
" <td>4.496129e+07</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-12-08 15:25:00</th>\n",
" <td>51104.0</td>\n",
" <td>51149.0</td>\n",
" <td>50858.0</td>\n",
" <td>50858.0</td>\n",
" <td>1.830533e+07</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-12-08 15:30:00</th>\n",
" <td>50858.0</td>\n",
" <td>51005.0</td>\n",
" <td>50846.0</td>\n",
" <td>50935.0</td>\n",
" <td>1.888942e+07</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-12-08 15:35:00</th>\n",
" <td>50935.0</td>\n",
" <td>50956.0</td>\n",
" <td>50766.0</td>\n",
" <td>50791.0</td>\n",
" <td>2.739046e+07</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-12-13 19:55:00</th>\n",
" <td>46614.0</td>\n",
" <td>46879.0</td>\n",
" <td>46570.0</td>\n",
" <td>46749.0</td>\n",
" <td>6.924345e+07</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-12-13 20:00:00</th>\n",
" <td>46749.0</td>\n",
" <td>46825.0</td>\n",
" <td>46604.0</td>\n",
" <td>46671.0</td>\n",
" <td>3.639398e+07</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-12-13 20:05:00</th>\n",
" <td>46671.0</td>\n",
" <td>46953.0</td>\n",
" <td>46630.0</td>\n",
" <td>46946.0</td>\n",
" <td>3.129267e+07</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-12-13 20:10:00</th>\n",
" <td>46946.0</td>\n",
" <td>46979.0</td>\n",
" <td>46803.0</td>\n",
" <td>46922.0</td>\n",
" <td>2.020791e+07</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-12-13 20:15:00</th>\n",
" <td>46918.0</td>\n",
" <td>46951.0</td>\n",
" <td>46644.0</td>\n",
" <td>46655.0</td>\n",
" <td>2.138693e+07</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>1500 rows × 5 columns</p>\n",
"</div>"
],
"text/plain": [
" Open High Low Close Volume\n",
"Date Time \n",
"2021-12-08 15:15:00 50991.0 51036.0 50888.0 50944.0 1.464595e+07\n",
"2021-12-08 15:20:00 50944.0 51300.0 50937.0 51105.0 4.496129e+07\n",
"2021-12-08 15:25:00 51104.0 51149.0 50858.0 50858.0 1.830533e+07\n",
"2021-12-08 15:30:00 50858.0 51005.0 50846.0 50935.0 1.888942e+07\n",
"2021-12-08 15:35:00 50935.0 50956.0 50766.0 50791.0 2.739046e+07\n",
"... ... ... ... ... ...\n",
"2021-12-13 19:55:00 46614.0 46879.0 46570.0 46749.0 6.924345e+07\n",
"2021-12-13 20:00:00 46749.0 46825.0 46604.0 46671.0 3.639398e+07\n",
"2021-12-13 20:05:00 46671.0 46953.0 46630.0 46946.0 3.129267e+07\n",
"2021-12-13 20:10:00 46946.0 46979.0 46803.0 46922.0 2.020791e+07\n",
"2021-12-13 20:15:00 46918.0 46951.0 46644.0 46655.0 2.138693e+07\n",
"\n",
"[1500 rows x 5 columns]"
]
},
"metadata": {},
"execution_count": 3
}
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},
{
"cell_type": "markdown",
"metadata": {
"id": "_3SprhhundII"
},
"source": [
"## Backtesting.py について\n",
"- Backtesting.py は、取引ストラテジーのバックテストを行い、その有用性を評価するためのPythonフレームワークです(公式ドキュメント：[Backtesting.py - Backtest trading strategies in Python](https://kernc.github.io/backtesting.py/))。\n",
"- 今回、初めてBacktesting.pyを使ってみて、Pandasが得意な方にとってはとっつきやすいフレームワークという印象を受けました。そうでない方には難しく感じるかもしれません。\n",
"- ただ、 Pandas のことは知ってて損はないので、この機会に勉強してみたいという方には、このあたりがオススメです。\n",
" - [Pythonによるデータ分析入門 第2版 ―NumPy、pandasを使ったデータ処理](https://www.amazon.co.jp/dp/487311845X)\n",
" - [改訂版　Pythonユーザのための Jupyter［実践］入門 ](https://www.amazon.co.jp/dp/B08G1HYL9P)\n",
"\n"
]
},
{
"cell_type": "code",
"metadata": {
"id": "1gyLgvqpS9Am"
},
"source": [
"# インストール \n",
"!pip install backtesting"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "w4Jcn0mVL3Z8"
},
"source": [
"### backtesting.py の勘所\n",
"\n",
"- ストラテジーの作り方\n",
" - `backtesting.Strategy` クラスを継承したクラスを作成\n",
" - `init` メソッドと `next` メソッドを上書きしてストラテジーを作成\n",
" - `init` メソッドで、シグナルを作るためのインディケータ等を記述\n",
" - `next` メソッドで、各バーごとにシグナルが発生しているかどうかを確かめてアクションをするコードを記述\n",
"- ポイント\n",
" - `init` メソッド内では、`I` メソッドを用いて、ストラテジーで使うインディケータを定義する。`I` メソッドの呼び出し時に渡すパラメータは、`インディケータ計算用関数`、ならびに、`インディケータ計算用のデータ`、 `関数に渡すパラメータ`\n",
" - インディケータ計算用のデータは pandas.Series型で渡す（例 `self.data[\"Close\"]` もしくは`self.data.Close`)\n",
" - なお、 `I` メソッドに渡されたデータは、その時点で `backtesting._util._Array` に変換される。**したがって、インディケータの計算時に pandas のメソッドを使いたい場合は、下記の`インディケータ計算用関数`の例 `SMA(values, n)` にあるように、いったん受け取った引数を Series や DataFrame に変換して扱う必要**がある。`インディケータ計算用関数`の返り値は pandas.Series のままで構わない。\n",
"- 例： [Quick Start User Guide](https://kernc.github.io/backtesting.py/doc/examples/Quick%20Start%20User%20Guide.html)を引用\n",
" - 移動平均クロスオーバー戦略\n",
" - 遅い移動平均(長期)と速い移動平均（短期）の2つの移動平均を使用\n",
" - 速い移動平均が遅い移動平均をうわ抜いたタイミングでロング、その逆でショートポジションを持つ\n",
"- メモ： [Backtesting.py のチュートリアル](https://kernc.github.io/backtesting.py/doc/examples/Quick%20Start%20User%20Guide.html)では、Pandas の SeriesのindexやDataframe のColumnsにアクセスするコードを `.` で記述していますが、これだと属性への記述との区別がわかりにくいので本稿では`[\"コラム名\"]` を使います\n",
" - 例：`self.data.Close` - > `self.data[\"Close\"]`\n",
"\n"
]
},
{
"cell_type": "code",
"metadata": {
"id": "Kd4g5PJXO9I8"
},
"source": [
"import pandas as pd\n",
"from backtesting import Strategy\n",
"\n",
"\n",
"def SMA(values, n):\n",
" # I メソッド経由で渡ってくるデータはただの array なので、\n",
" # pandas.Series メソッドへ変換して移動平均を作る\n",
" return pd.Series(values).rolling(n).mean()\n",
"\n",
"\n",
"class SmaCross(Strategy):\n",
" n1 = 10\n",
" n2 = 20\n",
"\n",
" def init(self):\n",
" # まずは SMA を2本計算\n",
" self.sma1 = self.I(SMA, self.data[\"Close\"], self.n1) # 速い移動平均\n",
" self.sma2 = self.I(SMA, self.data[\"Close\"], self.n2) # 遅い移動平均\n",
"\n",
" def next(self):\n",
" # next メソッドは、バー毎に実行される\n",
" # 最新のバーは[-1]でアクセスできる。\n",
"\n",
" # 速い移動平均が遅い移動平均をうわ抜いたタイミングであれば、\n",
" if self.sma1[-2] < self.sma2[-2] and self.sma1[-1] > self.sma2[-1]:\n",
" # その時持っていたポジションをクローズして\n",
" self.position.close()\n",
" # ロングポジションを取る\n",
" self.buy()\n",
"\n",
" # その逆\n",
" elif self.sma1[-2] > self.sma2[-2] and self.sma1[-1] < self.sma2[-1]:\n",
" self.position.close()\n",
" self.sell()\n",
"\n"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
" なお、この crossover 戦略については、Backtesting.pyのライブラリのなかに、あらかじめ `crossover` 関数が用意されており以下のように書くこともできます\n",
"\n",
"\n",
"```python\n",
"from backtesting.lib import crossover\n",
"....\n",
"class SmaCross(Strategy):\n",
" ....\n",
" def next(self):\n",
" # 速い移動平均が遅い移動平均をうわ抜いたタイミングであれば、\n",
" if crossover(self.sma1, self.sma2):\n",
" self.position.close()\n",
" self.buy()\n",
"\n",
" # その逆\n",
" elif crossover(self.sma2, self.sma1):\n",
" self.position.close()\n",
" self.sell()\n",
"```"
],
"metadata": {
"id": "fzvM6qwXtiw8"
}
},
{
"cell_type": "markdown",
"metadata": {
"id": "kEYiHP3sVTuO"
},
"source": [
"### バックテストの実行\n",
"1. `Backtest` インスタンス（`bt`）を作成する\n",
"1. インスタンスの作成時に、データ、ストラテジー、初期投資額、手数料、シグナル発生時どのタイミングで取引をするか、などのオプションを渡す\n",
"1. `run` メソッドでバックテスト実行\n",
"1. 戻り値はバックテストの結果情報 (pandas.Series型)\n"
]
},
{
"cell_type": "code",
"metadata": {
"id": "IXwyEdwkVQ5g",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "95bd537a-b625-4880-94e9-7d89863b5d57"
},
"source": [
"from backtesting import Backtest\n",
"\n",
"df = get_data(\"ETH-PERP\")\n",
"bt = Backtest(\n",
" df, # データ\n",
" SmaCross, # ストラテジークラス\n",
" cash=10000, # 初期投資額\n",
" commission=0.002, # 取引手数料\n",
" trade_on_close = True, # False にするとシグナル発生後の次のバーのオープンで取引をする。default は False.\n",
")\n",
"# バックテスト実行\n",
"stats = bt.run() \n",
"# 結果を出力\n",
"print(stats)\n",
"\n"
],
"execution_count": 6,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Start 2021-12-08 15:15:00\n",
"End 2021-12-13 20:15:00\n",
"Duration 5 days 05:00:00\n",
"Exposure Time [%] 97.2\n",
"Equity Final [$] 8143.85\n",
"Equity Peak [$] 10005.4\n",
"Return [%] -18.5615\n",
"Buy & Hold Return [%] -15.0062\n",
"Return (Ann.) [%] -99.9976\n",
"Volatility (Ann.) [%] 0.00106253\n",
"Sharpe Ratio 0\n",
"Sortino Ratio 0\n",
"Calmar Ratio 0\n",
"Max. Drawdown [%] -20.6008\n",
"Avg. Drawdown [%] -10.5706\n",
"Max. Drawdown Duration 5 days 00:45:00\n",
"Avg. Drawdown Duration 2 days 12:48:00\n",
"# Trades 94\n",
"Win Rate [%] 24.4681\n",
"Best Trade [%] 3.86791\n",
"Worst Trade [%] -4.11474\n",
"Avg. Trade [%] -0.209365\n",
"Max. Trade Duration 0 days 04:35:00\n",
"Avg. Trade Duration 0 days 01:18:00\n",
"Profit Factor 0.529103\n",
"Expectancy [%] -0.204919\n",
"SQN -2.8345\n",
"_strategy SmaCross\n",
"_equity_curve ...\n",
"_trades Size EntryB...\n",
"dtype: object\n"
]
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "CDZGDu5TWUUK"
},
"source": [
"### バックテストの結果情報の確認\n",
"\n",
"- バックテストの評価結果は、`run` メソッドの返り値として得られます。この返り値は pandas.Seriesになっていて、項目名とその値の組み合わせが表の形で表されています。大部分の項目は、説明するまでもないかと思いますが、いくつか特徴的なものだけ以下に説明します。\n",
"\n",
" - `SQN `: シャープレシオから時間の概念を外して、代わりにトレードの回数の平方根を掛けたもの\n",
" - [ソースコード backtesting/_stats.py#L139](https://github.com/kernc/backtesting.py/blob/77f4c46b82169c2689e1c4ad5994765556179eb2/backtesting/_stats.py#L139)\n",
" ```\n",
" s.loc['SQN'] = np.sqrt(n_trades) * pl.mean() / (pl.std() or np.nan)\n",
" ```\n",
" - つまり\n",
" - トレード回数が多いほうが信用できるよね、でも10回トレードしたストラテジーと100回トレードしたストラテジーを比べたとき、10倍信用できるか、というと、うーん？って感じだよね。とりあえず平方根にしとくか。というくらいの意味かな？たぶん。\n",
" - 大きければ大きいほどよい。\n",
"\n",
" - `_strategy` はストラテジー実行時の情報を保持するインスタンス（pandas.Seriesの値にインスタンスが埋め込まれています。以下同様）\n",
" - `_equity_curve` は資金の増減を保持するインスタンス(pandas.DataFrame)\n",
" - `_trades` は取引履歴を保持するインスタンス(pandas.DataFrame)"
]
},
{
"cell_type": "code",
"source": [
"print(stats[\"_strategy\"])\n",
"print(dir(stats[\"_strategy\"]))\n"
],
"metadata": {
"id": "W3ZrvtNq54G2",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "cd4bf2d0-56bb-4db8-c4c1-66af7377a6e8"
},
"execution_count": 7,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"SmaCross\n",
"['I', '_FULL_EQUITY', '_Strategy__FULL_EQUITY', '__abstractmethods__', '__class__', '__delattr__', '__dict__', '__dir__', '__doc__', '__eq__', '__format__', '__ge__', '__getattribute__', '__gt__', '__hash__', '__init__', '__init_subclass__', '__le__', '__lt__', '__module__', '__ne__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__sizeof__', '__str__', '__subclasshook__', '__weakref__', '_abc_impl', '_broker', '_check_params', '_data', '_indicators', '_params', 'buy', 'closed_trades', 'data', 'equity', 'init', 'n1', 'n2', 'next', 'orders', 'position', 'sell', 'sma1', 'sma2', 'trades']\n"
]
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "uGzuJf8rWsR-",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 238
},
"outputId": "9d888b68-fafe-4454-efbd-7357bb448445"
},
"source": [
"# 資金の増減\n",
"stats[\"_equity_curve\"].tail()\n"
],
"execution_count": 8,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
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" vertical-align: middle;\n",
" }\n",
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" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Equity</th>\n",
" <th>DrawdownPct</th>\n",
" <th>DrawdownDuration</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Date Time</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
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" <tbody>\n",
" <tr>\n",
" <th>2021-12-13 19:55:00</th>\n",
" <td>8174.8548</td>\n",
" <td>0.182953</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-12-13 20:00:00</th>\n",
" <td>8180.6548</td>\n",
" <td>0.182373</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-12-13 20:05:00</th>\n",
" <td>8142.4548</td>\n",
" <td>0.186191</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-12-13 20:10:00</th>\n",
" <td>8143.8548</td>\n",
" <td>0.186051</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-12-13 20:15:00</th>\n",
" <td>8143.8548</td>\n",
" <td>0.186051</td>\n",
" <td>5 days 00:45:00</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Equity DrawdownPct DrawdownDuration\n",
"Date Time \n",
"2021-12-13 19:55:00 8174.8548 0.182953 NaT\n",
"2021-12-13 20:00:00 8180.6548 0.182373 NaT\n",
"2021-12-13 20:05:00 8142.4548 0.186191 NaT\n",
"2021-12-13 20:10:00 8143.8548 0.186051 NaT\n",
"2021-12-13 20:15:00 8143.8548 0.186051 5 days 00:45:00"
]
},
"metadata": {},
"execution_count": 8
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "is5WZ006WvcJ",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 206
},
"outputId": "28a6c4b6-a87c-4383-e918-0f72b828a9af"
},
"source": [
"# 取引履歴\n",
"stats[\"_trades\"].head()"
],
"execution_count": 9,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Size</th>\n",
" <th>EntryBar</th>\n",
" <th>ExitBar</th>\n",
" <th>EntryPrice</th>\n",
" <th>ExitPrice</th>\n",
" <th>PnL</th>\n",
" <th>ReturnPct</th>\n",
" <th>EntryTime</th>\n",
" <th>ExitTime</th>\n",
" <th>Duration</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2</td>\n",
" <td>41</td>\n",
" <td>54</td>\n",
" <td>4418.4192</td>\n",
" <td>4388.0</td>\n",
" <td>-60.8384</td>\n",
" <td>-0.006885</td>\n",
" <td>2021-12-08 18:40:00</td>\n",
" <td>2021-12-08 19:45:00</td>\n",
" <td>0 days 01:05:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>-2</td>\n",
" <td>54</td>\n",
" <td>65</td>\n",
" <td>4379.2240</td>\n",
" <td>4418.1</td>\n",
" <td>-77.7520</td>\n",
" <td>-0.008877</td>\n",
" <td>2021-12-08 19:45:00</td>\n",
" <td>2021-12-08 20:40:00</td>\n",
" <td>0 days 00:55:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2</td>\n",
" <td>65</td>\n",
" <td>80</td>\n",
" <td>4426.9362</td>\n",
" <td>4421.0</td>\n",
" <td>-11.8724</td>\n",
" <td>-0.001341</td>\n",
" <td>2021-12-08 20:40:00</td>\n",
" <td>2021-12-08 21:55:00</td>\n",
" <td>0 days 01:15:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>-2</td>\n",
" <td>80</td>\n",
" <td>85</td>\n",
" <td>4412.1580</td>\n",
" <td>4419.9</td>\n",
" <td>-15.4840</td>\n",
" <td>-0.001755</td>\n",
" <td>2021-12-08 21:55:00</td>\n",
" <td>2021-12-08 22:20:00</td>\n",
" <td>0 days 00:25:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2</td>\n",
" <td>85</td>\n",
" <td>95</td>\n",
" <td>4428.7398</td>\n",
" <td>4405.1</td>\n",
" <td>-47.2796</td>\n",
" <td>-0.005338</td>\n",
" <td>2021-12-08 22:20:00</td>\n",
" <td>2021-12-08 23:10:00</td>\n",
" <td>0 days 00:50:00</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Size EntryBar ... ExitTime Duration\n",
"0 2 41 ... 2021-12-08 19:45:00 0 days 01:05:00\n",
"1 -2 54 ... 2021-12-08 20:40:00 0 days 00:55:00\n",
"2 2 65 ... 2021-12-08 21:55:00 0 days 01:15:00\n",
"3 -2 80 ... 2021-12-08 22:20:00 0 days 00:25:00\n",
"4 2 85 ... 2021-12-08 23:10:00 0 days 00:50:00\n",
"\n",
"[5 rows x 10 columns]"
]
},
"metadata": {},
"execution_count": 9
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "mx3albqYSC-z"
},
"source": [
"### バックテスト結果の描画\n",
"\n",
"- `bt.run()` でバックテストを実行すると、 `bt._results.values` に結果が格納されており、その結果を `bt.plot()` で描画できる。\n",
"- `Strategy` クラスの `init` メソッドの中で `I`メソッドに渡したインディケータも描画される\n"
]
},
{
"cell_type": "code",
"metadata": {
"id": "bDPSaz7Eb4Is",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "8fb4b7ae-cc7d-474b-80fc-26e8afec140f"
},
"source": [
"# 結果は _results.values でアクセス可\n",
"bt._results.values"
],
"execution_count": 10,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"array([Timestamp('2021-12-08 15:15:00'), Timestamp('2021-12-13 20:15:00'),\n",
" Timedelta('5 days 05:00:00'), 97.2, 8143.854800000003, 10005.3616,\n",
" -18.561451999999974, -15.006202774331795, -99.9976120875548,\n",
" 0.0010625279622058104, 0.0, 0.0, 0.0, -20.600782684355945,\n",
" -10.570583342177981, Timedelta('5 days 00:45:00'),\n",
" Timedelta('2 days 12:48:00'), 94, 24.46808510638298,\n",
" 3.867912550425656, -4.1147377143003645, -0.20936523972133747,\n",
" Timedelta('0 days 04:35:00'), Timedelta('0 days 01:18:00'),\n",
" 0.5291032023607063, -0.2049194897217074, -2.8344963197526836,\n",
" <Strategy SmaCross>,\n",
" Equity DrawdownPct DrawdownDuration\n",
"Date Time \n",
"2021-12-08 15:15:00 10000.0000 0.000000 NaT\n",
"2021-12-08 15:20:00 10000.0000 0.000000 NaT\n",
"2021-12-08 15:25:00 10000.0000 0.000000 NaT\n",
"2021-12-08 15:30:00 10000.0000 0.000000 NaT\n",
"2021-12-08 15:35:00 10000.0000 0.000000 NaT\n",
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]
},
"metadata": {},
"execution_count": 10
}
]
},
{
"cell_type": "code",
"source": [
"# 結果を描画\n",
"# SmaCross の init メソッド内で定義した、sma 2つ描画されることを確認\n",
"bt.plot()"
],
"metadata": {
"id": "B3DI_3Cu8EtD",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 724
},
"outputId": "46695afd-8ae1-471f-ef44-048bd4e032b7"
},
"execution_count": 11,
"outputs": [
{
"output_type": "display_data",
"data": {
"application/javascript": [
"\n",
"(function(root) {\n",
" function now() {\n",
" return new Date();\n",
" }\n",
"\n",
" var force = true;\n",
"\n",
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" root._bokeh_onload_callbacks = [];\n",
" root._bokeh_is_loading = undefined;\n",
" }\n",
"\n",
" var JS_MIME_TYPE = 'application/javascript';\n",
" var HTML_MIME_TYPE = 'text/html';\n",
" var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
" var CLASS_NAME = 'output_bokeh rendered_html';\n",
"\n",
" /**\n",
" * Render data to the DOM node\n",
" */\n",
" function render(props, node) {\n",
" var script = document.createElement(\"script\");\n",
" node.appendChild(script);\n",
" }\n",
"\n",
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" var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
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" delete Bokeh.index[id];\n",
" }\n",
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" }\n",
" });\n",
" // Destroy server and session\n",
" var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
" cell.notebook.kernel.execute(cmd);\n",
" }\n",
" }\n",
"\n",
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" * Handle when a new output is added\n",
" */\n",
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" var output_area = handle.output_area;\n",
" var output = handle.output;\n",
"\n",
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" if ((output.output_type != \"display_data\") || (!Object.prototype.hasOwnProperty.call(output.data, EXEC_MIME_TYPE))) {\n",
" return\n",
" }\n",
"\n",
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"\n",
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" // store reference to embed id on output_area\n",
" output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
" }\n",
" if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
" var bk_div = document.createElement(\"div\");\n",
" bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
" var script_attrs = bk_div.children[0].attributes;\n",
" for (var i = 0; i < script_attrs.length; i++) {\n",
" toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
" toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n",
" }\n",
" // store reference to server id on output_area\n",
" output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
" }\n",
" }\n",
"\n",
" function register_renderer(events, OutputArea) {\n",
"\n",
" function append_mime(data, metadata, element) {\n",
" // create a DOM node to render to\n",
" var toinsert = this.create_output_subarea(\n",
" metadata,\n",
" CLASS_NAME,\n",
" EXEC_MIME_TYPE\n",
" );\n",
" this.keyboard_manager.register_events(toinsert);\n",
" // Render to node\n",
" var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
" render(props, toinsert[toinsert.length - 1]);\n",
" element.append(toinsert);\n",
" return toinsert\n",
" }\n",
"\n",
" /* Handle when an output is cleared or removed */\n",
" events.on('clear_output.CodeCell', handleClearOutput);\n",
" events.on('delete.Cell', handleClearOutput);\n",
"\n",
" /* Handle when a new output is added */\n",
" events.on('output_added.OutputArea', handleAddOutput);\n",
"\n",
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" /* Is output safe? */\n",
" safe: true,\n",
" /* Index of renderer in `output_area.display_order` */\n",
" index: 0\n",
" });\n",
" }\n",
"\n",
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" var events = require('base/js/events');\n",
" var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
"\n",
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" }\n",
"\n",
" var NB_LOAD_WARNING = {'data': {'text/html':\n",
" \"<div style='background-color: #fdd'>\\n\"+\n",
" \"<p>\\n\"+\n",
" \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
" \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
" \"</p>\\n\"+\n",
" \"<ul>\\n\"+\n",
" \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
" \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
" \"</ul>\\n\"+\n",
" \"<code>\\n\"+\n",
" \"from bokeh.resources import INLINE\\n\"+\n",
" \"output_notebook(resources=INLINE)\\n\"+\n",
" \"</code>\\n\"+\n",
" \"</div>\"}};\n",
"\n",
" function display_loaded() {\n",
" var el = document.getElementById(null);\n",
" if (el != null) {\n",
" el.textContent = \"BokehJS is loading...\";\n",
" }\n",
" if (root.Bokeh !== undefined) {\n",
" if (el != null) {\n",
" el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
" }\n",
" } else if (Date.now() < root._bokeh_timeout) {\n",
" setTimeout(display_loaded, 100)\n",
" }\n",
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"\n",
"\n",
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" try {\n",
" root._bokeh_onload_callbacks.forEach(function(callback) {\n",
" if (callback != null)\n",
" callback();\n",
" });\n",
" } finally {\n",
" delete root._bokeh_onload_callbacks\n",
" }\n",
" console.debug(\"Bokeh: all callbacks have finished\");\n",
" }\n",
"\n",
" function load_libs(css_urls, js_urls, callback) {\n",
" if (css_urls == null) css_urls = [];\n",
" if (js_urls == null) js_urls = [];\n",
"\n",
" root._bokeh_onload_callbacks.push(callback);\n",
" if (root._bokeh_is_loading > 0) {\n",
" console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
" return null;\n",
" }\n",
" if (js_urls == null || js_urls.length === 0) {\n",
" run_callbacks();\n",
" return null;\n",
" }\n",
" console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
" root._bokeh_is_loading = css_urls.length + js_urls.length;\n",
"\n",
" function on_load() {\n",
" root._bokeh_is_loading--;\n",
" if (root._bokeh_is_loading === 0) {\n",
" console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
" run_callbacks()\n",
" }\n",
" }\n",
"\n",
" function on_error(url) {\n",
" console.error(\"failed to load \" + url);\n",
" }\n",
"\n",
" for (let i = 0; i < css_urls.length; i++) {\n",
" const url = css_urls[i];\n",
" const element = document.createElement(\"link\");\n",
" element.onload = on_load;\n",
" element.onerror = on_error.bind(null, url);\n",
" element.rel = \"stylesheet\";\n",
" element.type = \"text/css\";\n",
" element.href = url;\n",
" console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
" document.body.appendChild(element);\n",
" }\n",
"\n",
" const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.3.3.min.js\": \"dM3QQsP+wXdHg42wTqW85BjZQdLNNIXqlPw/BgKoExPmTG7ZLML4EGqLMfqHT6ON\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.3.3.min.js\": \"8x57I4YuIfu8XyZfFo0XVr2WAT8EK4rh/uDe3wF7YuW2FNUSNEpJbsPaB1nJ2fz2\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.3.3.min.js\": \"3QTqdz9LyAm2i0sG5XTePsHec3UHWwVsrOL68SYRoAXsafvfAyqtQ+h440+qIBhS\"};\n",
"\n",
" for (let i = 0; i < js_urls.length; i++) {\n",
" const url = js_urls[i];\n",
" const element = document.createElement('script');\n",
" element.onload = on_load;\n",
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" if (url in hashes) {\n",
" element.crossOrigin = \"anonymous\";\n",
" element.integrity = \"sha384-\" + hashes[url];\n",
" }\n",
" console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
" document.head.appendChild(element);\n",
" }\n",
" };\n",
"\n",
" function inject_raw_css(css) {\n",
" const element = document.createElement(\"style\");\n",
" element.appendChild(document.createTextNode(css));\n",
" document.body.appendChild(element);\n",
" }\n",
"\n",
" \n",
" var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.3.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.3.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.3.3.min.js\"];\n",
" var css_urls = [];\n",
" \n",
"\n",
" var inline_js = [\n",
" function(Bokeh) {\n",
" Bokeh.set_log_level(\"info\");\n",
" },\n",
" function(Bokeh) {\n",
" \n",
" \n",
" }\n",
" ];\n",
"\n",
" function run_inline_js() {\n",
" \n",
" if (root.Bokeh !== undefined || force === true) {\n",
" \n",
" for (var i = 0; i < inline_js.length; i++) {\n",
" inline_js[i].call(root, root.Bokeh);\n",
" }\n",
" } else if (Date.now() < root._bokeh_timeout) {\n",
" setTimeout(run_inline_js, 100);\n",
" } else if (!root._bokeh_failed_load) {\n",
" console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
" root._bokeh_failed_load = true;\n",
" } else if (force !== true) {\n",
" var cell = $(document.getElementById(null)).parents('.cell').data().cell;\n",
" cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
" }\n",
"\n",
" }\n",
"\n",
" if (root._bokeh_is_loading === 0) {\n",
" console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
" run_inline_js();\n",
" } else {\n",
" load_libs(css_urls, js_urls, function() {\n",
" console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
" run_inline_js();\n",
" });\n",
" }\n",
"}(window));"
],
"application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n\n if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n \n\n \n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n var NB_LOAD_WARNING = {'data': {'text/html':\n \"<div style='background-color: #fdd'>\\n\"+\n \"<p>\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"</p>\\n\"+\n \"<ul>\\n\"+\n \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n \"<li>use INLINE resources instead, as so:</li>\\n\"+\n \"</ul>\\n\"+\n \"<code>\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"</code>\\n\"+\n \"</div>\"}};\n\n function display_loaded() {\n var el = document.getElementById(null);\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\n }\n\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls == null || js_urls.length === 0) {\n run_callbacks();\n return null;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n\n function on_error(url) {\n console.error(\"failed to load \" + url);\n }\n\n for (let i = 0; i < css_urls.length; i++) {\n const url = css_urls[i];\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error.bind(null, url);\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n }\n\n const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.3.3.min.js\": \"dM3QQsP+wXdHg42wTqW85BjZQdLNNIXqlPw/BgKoExPmTG7ZLML4EGqLMfqHT6ON\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.3.3.min.js\": \"8x57I4YuIfu8XyZfFo0XVr2WAT8EK4rh/uDe3wF7YuW2FNUSNEpJbsPaB1nJ2fz2\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.3.3.min.js\": \"3QTqdz9LyAm2i0sG5XTePsHec3UHWwVsrOL68SYRoAXsafvfAyqtQ+h440+qIBhS\"};\n\n for (let i = 0; i < js_urls.length; i++) {\n const url = js_urls[i];\n const element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error.bind(null, url);\n element.async = false;\n element.src = url;\n if (url in hashes) {\n element.crossOrigin = \"anonymous\";\n element.integrity = \"sha384-\" + hashes[url];\n }\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n \n var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.3.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.3.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.3.3.min.js\"];\n var css_urls = [];\n \n\n var inline_js = [\n function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\n function(Bokeh) {\n \n \n }\n ];\n\n function run_inline_js() {\n \n if (root.Bokeh !== undefined || force === true) {\n \n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n } else if (force !== true) {\n var cell = $(document.getElementById(null)).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\n }\n\n }\n\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(css_urls, js_urls, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));"
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(max - min) * .03 : 0;\\n range.start = min - pad;\\n range.end = max + pad;\\n } else console.error('backtesting: scale range error:', min, max, range);\\n };\\n}\\n\\nclearTimeout(window._bt_autoscale_timeout);\\n\\nwindow._bt_autoscale_timeout = setTimeout(function () {\\n /**\\n * @variable cb_obj `fig_ohlc.x_range`.\\n * @variable source `ColumnDataSource`\\n * @variable ohlc_range `fig_ohlc.y_range`.\\n * @variable volume_range `fig_volume.y_range`.\\n */\\n \\\"use strict\\\";\\n\\n let i = Math.max(Math.floor(cb_obj.start), 0),\\n j = Math.min(Math.ceil(cb_obj.end), source.data['ohlc_high'].length);\\n\\n let max = Math.max.apply(null, source.data['ohlc_high'].slice(i, j)),\\n min = Math.min.apply(null, source.data['ohlc_low'].slice(i, j));\\n _bt_scale_range(ohlc_range, min, max, true);\\n\\n if (volume_range) {\\n max = Math.max.apply(null, source.data['Volume'].slice(i, j));\\n _bt_scale_range(volume_range, 0, max * 1.03, false);\\n }\\n\\n}, 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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1500]},\"Volume\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1500]},\"datetime\":{\"__ndarray__\":\"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\"type\":\"Patch\"},{\"attributes\":{\"axis\":{\"id\":\"1191\"},\"ticker\":null},\"id\":\"1194\",\"type\":\"Grid\"},{\"attributes\":{\"factors\":[\"0\",\"1\"],\"palette\":[\"rgb(254, 220, 214)\",\"rgb(214, 254, 214)\"]},\"id\":\"1280\",\"type\":\"CategoricalColorMapper\"},{\"attributes\":{\"fill_color\":{\"field\":\"returns_positive\",\"transform\":{\"id\":\"1038\"}},\"marker\":{\"value\":\"triangle\"},\"size\":{\"field\":\"marker_size\"},\"x\":{\"field\":\"index\"},\"y\":{\"field\":\"returns_long\"}},\"id\":\"1217\",\"type\":\"Scatter\"},{\"attributes\":{},\"id\":\"1009\",\"type\":\"LinearScale\"},{\"attributes\":{\"bottom\":{\"field\":\"Close\"},\"fill_color\":{\"field\":\"inc\",\"transform\":{\"id\":\"1280\"}},\"line_color\":{\"value\":null},\"top\":{\"field\":\"Open\"},\"width\":{\"field\":\"_width\"},\"x\":{\"field\":\"index\"}},\"id\":\"1282\",\"type\":\"VBar\"},{\"attributes\":{\"line_color\":{\"field\":\"returns_positive\",\"transform\":{\"id\":\"1039\"}},\"line_dash\":{\"value\":\"dotted\"},\"line_width\":{\"value\":8},\"xs\":{\"field\":\"position_lines_xs\"},\"ys\":{\"field\":\"position_lines_ys\"}},\"id\":\"1297\",\"type\":\"MultiLine\"},{\"attributes\":{},\"id\":\"1196\",\"type\":\"BasicTicker\"},{\"attributes\":{\"factors\":[\"0\",\"1\"],\"palette\":[\"tomato\",\"lime\"]},\"id\":\"1038\",\"type\":\"CategoricalColorMapper\"},{\"attributes\":{\"line_color\":\"#666666\",\"line_dash\":[6],\"location\":0},\"id\":\"1215\",\"type\":\"Span\"},{\"attributes\":{\"dimensions\":\"width\",\"maintain_focus\":false},\"id\":\"1020\",\"type\":\"WheelZoomTool\"}],\"root_ids\":[\"1433\"]},\"title\":\"Bokeh Application\",\"version\":\"2.3.3\"}};\n",
" var render_items = [{\"docid\":\"372e82a4-82d6-4674-9c1b-2543db04ae10\",\"root_ids\":[\"1433\"],\"roots\":{\"1433\":\"ded7347e-a5a0-4029-9899-651be2e93c4d\"}}];\n",
" root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
"\n",
" }\n",
" if (root.Bokeh !== undefined) {\n",
" embed_document(root);\n",
" } else {\n",
" var attempts = 0;\n",
" var timer = setInterval(function(root) {\n",
" if (root.Bokeh !== undefined) {\n",
" clearInterval(timer);\n",
" embed_document(root);\n",
" } else {\n",
" attempts++;\n",
" if (attempts > 100) {\n",
" clearInterval(timer);\n",
" console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
" }\n",
" }\n",
" }, 10, root)\n",
" }\n",
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"Row(id='1433', ...)"
]
},
"metadata": {},
"execution_count": 11
}
]
},
{
"cell_type": "markdown",
"source": [
"### チャートの操作\n",
"\n",
"- ズームイン/アウトが可能\n",
"- 各チャートの左上にある指標名のクリックでプロットのON/OFF"
],
"metadata": {
"id": "d0he7MrjJtmv"
}
},
{
"cell_type": "markdown",
"metadata": {
"id": "ClD3k6VuX4uI"
},
"source": [
"\n",
"\n",
"---\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "TnCXAOZkFXNH"
},
"source": [
"## SuperTrendインディケータを用いた検討例\n",
"\n",
"- ここまで、簡単にBacktesting.py の使い方を説明しました。ここからは、もう少し踏み込んで、SuperTrendというインディケータを使ったストラテジーを書いてみます。今回このインディケータを選んだ理由は、[Quant Zone Rule Building Competition](https://help.ftx.com/hc/en-us/articles/360041935611-Quant-Zone-Rules-Examples)というFTX の大会で一番人気があったストラテジーがSuperTrendを使っていたからです。計算式は色々あるようですが、代表的なものは以下のような感じです。\n",
"\n",
"```\n",
"TrueRange(TR) = MAX(\n",
" (高値-安値), \n",
" abs(前日終値-高値),\n",
" abs(前日終値-安値)\n",
" )\n",
"ATR = EMA(TR, term)\n",
"HL = average(高値, 安値)\n",
"\n",
"BASIC_UPPERBAND = HL + ATR * multiplier\n",
"BASIC_LOWERBAND = HL - ATR * multiplier \n",
"\n",
"FINAL_UPPERBAND = \n",
" if (BASIC_UPPERBAND < PREV_FINAL_UPPERBAND) OR (PREV_FINAL_UPPERBAND < 前日終値): \n",
" BASIC_UPPERBAND \n",
" else: \n",
" PREV_FINAL_UPPERBAND\n",
"\n",
"FINAL_LOWERBAND = \n",
" if (前日終値 < PREV_FINAL_LOWERBAND ) OR (PREV_FINAL_LOWERBAND < BASIC_LOWERBAND): \n",
" BASIC_LOWERBAND \n",
" else: \n",
" PREV_FINAL_LOWERBAND\n",
"\n",
"SUPERTREND =\n",
" if PREV_SUPERTREND == PREV_FINAL_UPPERBAND: \n",
" if 終値 <= FINAL_UPPERBAND: \n",
" FINAL_UPPERBAND \n",
" else: \n",
" FINAL_LOWERBAND\n",
" elif PREV_SUPERTREND == PREV_FINAL_LOWERBAND: \n",
" if 終値 >= FINAL_LOWERBAND: \n",
" FINAL_LOWERBAND\n",
" else: \n",
" FINAL_UPPERBAND \n",
"\n",
"```\n",
"なんか、イライラしますね。ザックリ説明すると、\n",
"1. TrueRangeの指数平滑移動平均を作成(= ATR)\n",
"1. 高値安値の平均に、`1`を m倍した数値を上下に足してバンドを作る（= BASIC UPPERBANDとLOWERBAND）\n",
"1. `2`を前日の終値および前日のバンドと比べて最終的なバンドを決定（= FINAL UPPERBANDとLOWERBAND）\n",
"1. 最終的なバンドと、当日の終値および前日の最終バンドとの位置関係で、最終的なバンドの上下のうちの一つをSUPERTREND インディケータとする\n"
]
},
{
"cell_type": "markdown",
"source": [
"### SuperTrend テスト戦略\n",
"\n",
"- 以下のような前提で、バックテストをすることを考えます。\n",
" - ATRの term は 15 \n",
" - バンド幅 multiplier は 3\n",
" - 終値のEMAの term は 200\n",
" - シグナルは、SUPERTREND が 終値のEMA200より上だった場合ロングポジション、下だった場合はショートポジションをとってホールド\n"
],
"metadata": {
"id": "Gbyr8l3GCNJI"
}
},
{
"cell_type": "markdown",
"source": [
"### SuperTrendコード作成\n",
"\n",
"- 実際に Backtesting.py に SuperTrend を実装するときの、コーディング時のポイントを説明します。"
],
"metadata": {
"id": "DSW6eThw8eAD"
}
},
{
"cell_type": "markdown",
"source": [
"#### 【ポイント1】: インディケータで使うパラメータ等の計算は、あらかじめDataFrameで計算する\n",
"- Backtesting.py でインディケータの関数を書くよりも、pandas の DataFrame での操作のほうが1000倍クリアでラク\n",
"- 今回の場合は、`前日終値`、`High Lowの平均`、`TrueRange(TR) ` は、DataFrameの操作で用意\n"
],
"metadata": {
"id": "GRfr5VRh-uG0"
}
},
{
"cell_type": "code",
"metadata": {
"id": "6IBpA7-aSaAT"
},
"source": [
"def add_features(df):\n",
" df[\"Prev_Close\"] = df[\"Close\"].shift()\n",
" df[\"HL\"] = (df[\"High\"] + df[\"Low\"]) / 2\n",
" df[\"TR\"] = df.apply(\n",
" lambda row: max(\n",
" row[\"High\"] - row[\"Low\"],\n",
" abs(row[\"Prev_Close\"] - row[\"Low\"]),\n",
" abs(row[\"Prev_Close\"] - row[\"High\"]),\n",
" ),\n",
" axis=1,\n",
" )\n",
" return df\n"
],
"execution_count": 12,
"outputs": []
},
{
"cell_type": "code",
"source": [
"# test\n",
"df = get_data(\"SOL-PERP\")\n",
"add_features(df).head()"
],
"metadata": {
"id": "vxArw5y3-kg-",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 238
},
"outputId": "e35a68f7-2cc3-4dad-fa6f-d34b47fced10"
},
"execution_count": 13,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Open</th>\n",
" <th>High</th>\n",
" <th>Low</th>\n",
" <th>Close</th>\n",
" <th>Volume</th>\n",
" <th>Prev_Close</th>\n",
" <th>HL</th>\n",
" <th>TR</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Date Time</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2021-12-08 15:15:00</th>\n",
" <td>195.0325</td>\n",
" <td>195.5175</td>\n",
" <td>194.2875</td>\n",
" <td>195.2650</td>\n",
" <td>4.310541e+06</td>\n",
" <td>NaN</td>\n",
" <td>194.90250</td>\n",
" <td>1.2300</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-12-08 15:20:00</th>\n",
" <td>195.2650</td>\n",
" <td>196.7700</td>\n",
" <td>195.1275</td>\n",
" <td>195.9500</td>\n",
" <td>6.182965e+06</td>\n",
" <td>195.2650</td>\n",
" <td>195.94875</td>\n",
" <td>1.6425</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-12-08 15:25:00</th>\n",
" <td>195.9500</td>\n",
" <td>196.2750</td>\n",
" <td>194.7525</td>\n",
" <td>194.7525</td>\n",
" <td>3.002578e+06</td>\n",
" <td>195.9500</td>\n",
" <td>195.51375</td>\n",
" <td>1.5225</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-12-08 15:30:00</th>\n",
" <td>194.7525</td>\n",
" <td>195.3625</td>\n",
" <td>194.4000</td>\n",
" <td>194.9200</td>\n",
" <td>3.732641e+06</td>\n",
" <td>194.7525</td>\n",
" <td>194.88125</td>\n",
" <td>0.9625</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-12-08 15:35:00</th>\n",
" <td>194.9200</td>\n",
" <td>194.9200</td>\n",
" <td>193.4825</td>\n",
" <td>193.4825</td>\n",
" <td>3.272395e+06</td>\n",
" <td>194.9200</td>\n",
" <td>194.20125</td>\n",
" <td>1.4375</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Open High ... HL TR\n",
"Date Time ... \n",
"2021-12-08 15:15:00 195.0325 195.5175 ... 194.90250 1.2300\n",
"2021-12-08 15:20:00 195.2650 196.7700 ... 195.94875 1.6425\n",
"2021-12-08 15:25:00 195.9500 196.2750 ... 195.51375 1.5225\n",
"2021-12-08 15:30:00 194.7525 195.3625 ... 194.88125 0.9625\n",
"2021-12-08 15:35:00 194.9200 194.9200 ... 194.20125 1.4375\n",
"\n",
"[5 rows x 8 columns]"
]
},
"metadata": {},
"execution_count": 13
}
]
},
{
"cell_type": "markdown",
"source": [
"#### 【ポイント2】: バックテスト結果のチャートに載せたいインディケータは、関数化してIメソッドで渡す\n",
"- `FINAL_UPPER_BAND`, `FINAL_LOWER_BAND`, `SUPERTREND_BAND` はバックテストの結果と一緒に描画してほしいので、`init`メソッドのなかで`I`メソッドを使って定義しておく\n"
],
"metadata": {
"id": "PeonOuse_TpP"
}
},
{
"cell_type": "code",
"source": [
"# SuperTrendを算出するための関数群\n",
"\n",
"def ATR(value_tr, period):\n",
" s = pd.Series(value_tr)\n",
" return s.ewm(alpha=1 / period, min_periods=period).mean()\n",
"\n",
"\n",
"def EMA(value, period):\n",
" s = pd.Series(value)\n",
" return s.ewm(alpha=1 / period, min_periods=period).mean()\n",
"\n",
"\n",
"def BASIC_BANDS(value_hl, value_atr, multiplier):\n",
" s_hl = pd.Series(value_hl)\n",
" s_atr = pd.Series(value_atr)\n",
"\n",
" basic_upper_band = s_hl + s_atr * multiplier\n",
" basic_lower_band = s_hl - s_atr * multiplier\n",
"\n",
" return basic_upper_band, basic_lower_band\n",
"\n",
"\n",
"def get_final_ub(basic_ub, prev_close, prev_final_ub):\n",
" if basic_ub < prev_final_ub or prev_final_ub < prev_close:\n",
" return basic_ub\n",
" else:\n",
" return prev_final_ub\n",
"\n",
"\n",
"def get_final_lb(basic_lb, prev_close, prev_final_lb):\n",
" if prev_close < prev_final_lb or prev_final_lb < basic_lb:\n",
" return basic_lb\n",
" else:\n",
" return prev_final_lb\n",
"\n",
"\n",
"def FINAL_UPPER_BAND(basic_ub, prev_close, period):\n",
" s_basic_ub = pd.Series(basic_ub)\n",
" s_prev_close = pd.Series(prev_close)\n",
" s_prev_final_ub = s_basic_ub.copy()\n",
"\n",
" for i in range(len(s_basic_ub)):\n",
" if i <= period:\n",
" continue # s_prev_final_ub.iloc[i] = s_basic_ub.iloc[i]\n",
" else:\n",
" s_prev_final_ub.iloc[i] = get_final_ub(\n",
" s_basic_ub.iloc[i], s_prev_close.iloc[i], s_prev_final_ub.iloc[i - 1]\n",
" )\n",
" return s_prev_final_ub\n",
"\n",
"\n",
"def FINAL_LOWER_BAND(basic_lb, prev_close, period):\n",
" s_basic_lb = pd.Series(basic_lb)\n",
" s_prev_close = pd.Series(prev_close)\n",
" s_prev_final_lb = s_basic_lb.copy()\n",
"\n",
" for i in range(len(s_basic_lb)):\n",
" if i <= period:\n",
" continue\n",
" s_prev_final_lb.iloc[i] = get_final_lb(\n",
" s_basic_lb.iloc[i], s_prev_close.iloc[i], s_prev_final_lb.iloc[i - 1]\n",
" )\n",
"\n",
" return s_prev_final_lb\n",
"\n",
"\n",
"def get_supertrend(close, prev_st, final_ub, prev_final_ub, final_lb, prev_final_lb):\n",
"\n",
" if prev_st == prev_final_ub:\n",
" if close <= final_ub:\n",
" st = final_ub\n",
" else:\n",
" return final_lb\n",
" elif prev_st == prev_final_lb:\n",
" if close >= final_lb:\n",
" st = final_lb\n",
" else:\n",
" st = final_ub\n",
" else:\n",
" st = None\n",
" return st\n",
"\n",
"\n",
"def SUPERTREND_BAND(close, final_ub, final_lb, period):\n",
" s_close = pd.Series(close)\n",
" s_final_ub = pd.Series(final_ub)\n",
" s_final_lb = pd.Series(final_lb)\n",
" s_supertrend = s_final_ub.copy() # 初期値としてUpperを渡すのがいいかどうかは悩ましいけど\n",
"\n",
" for i in range(len(s_close)):\n",
" if i <= period:\n",
" continue\n",
" close = s_close.iloc[i]\n",
" prev_st = s_supertrend.iloc[i - 1]\n",
" final_ub = s_final_ub.iloc[i]\n",
" prev_final_ub = s_final_ub.iloc[i - 1]\n",
" final_lb = s_final_lb.iloc[i]\n",
" prev_final_lb = s_final_lb.iloc[i - 1]\n",
"\n",
" s_supertrend.iloc[i] = get_supertrend(\n",
" close, prev_st, final_ub, prev_final_ub, final_lb, prev_final_lb\n",
" )\n",
" return s_supertrend\n"
],
"metadata": {
"id": "wFOecNX2Bnlp"
},
"execution_count": 14,
"outputs": []
},
{
"cell_type": "code",
"source": [
"# SuperTrendストラテジーを作成\n",
"class SuperTrend(Strategy):\n",
" period = 15\n",
" ema_period = 200\n",
" multiplier = 3\n",
"\n",
" switch_position = 0\n",
"\n",
" def init(self):\n",
" self.atr = self.I(ATR, self.data.TR, self.period)\n",
" self.basic_ub, self.basic_lb = self.I(\n",
" BASIC_BANDS, self.data.HL, self.atr, self.multiplier\n",
" )\n",
" self.close_ema = self.I(EMA, self.data.Close, self.ema_period)\n",
"\n",
" self.final_ub = self.I(\n",
" FINAL_UPPER_BAND,\n",
" self.basic_ub,\n",
" self.data.Prev_Close,\n",
" self.period,\n",
" )\n",
"\n",
" self.final_lb = self.I(\n",
" FINAL_LOWER_BAND,\n",
" self.basic_lb,\n",
" self.data.Prev_Close,\n",
" self.period,\n",
" )\n",
"\n",
" self.supertrend = self.I(\n",
" SUPERTREND_BAND,\n",
" self.data.Close,\n",
" self.final_ub,\n",
" self.final_lb,\n",
" self.period,\n",
" )\n",
"\n",
" # シグナル確認 check_box\n",
" self.check_box = self.close_ema.copy()\n",
"\n",
" def next(self):\n",
" self.check_box[-1] = 0\n",
"\n",
" if self.switch_position:\n",
" self.switch_position = 0\n",
"\n",
" # simulation\n",
" if not self.position:\n",
" if self.supertrend[-1] > self.close_ema[-1]:\n",
" self.buy()\n",
" self.check_box[-1] = 1\n",
" self.switch_position = 1\n",
"\n",
" elif self.supertrend[-1] < self.close_ema[-1]:\n",
" self.sell()\n",
" self.check_box[-1] = 2\n",
" self.switch_position = 2\n",
" if (\n",
" self.supertrend[-2] > self.close_ema[-2]\n",
" and self.supertrend[-1] < self.close_ema[-1]\n",
" ):\n",
" self.position.close()\n",
" self.buy()\n",
" self.check_box[-1] = 3\n",
" self.switch_position = 3\n",
"\n",
" elif (\n",
" self.supertrend[-2] < self.close_ema[-2]\n",
" and self.supertrend[-1] > self.close_ema[-1]\n",
" ):\n",
" self.position.close()\n",
" self.sell()\n",
" self.check_box[-1] = 4\n",
" self.switch_position = 4\n"
],
"metadata": {
"id": "IkHkMRTzB586"
},
"execution_count": 15,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"### テスト戦略の実行"
],
"metadata": {
"id": "6n9lrB4SkQHz"
}
},
{
"cell_type": "code",
"source": [
"def supertrend_test(df):\n",
" bt = Backtest(df, SuperTrend, trade_on_close = True, cash=100000, commission=0.001)\n",
" stats = bt.run()\n",
"\n",
" return (bt, stats)"
],
"metadata": {
"id": "j9KhbBoZFUok"
},
"execution_count": 16,
"outputs": []
},
{
"cell_type": "code",
"source": [
"df = get_data(\"SOL-PERP\")\n",
"df = add_features(df)\n",
"bt, stats = supertrend_test(df)"
],
"metadata": {
"id": "nGXDld0fFqzV"
},
"execution_count": 17,
"outputs": []
},
{
"cell_type": "code",
"source": [
"stats"
],
"metadata": {
"id": "dQVH1J66Zc0s",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "b1267755-9730-4ce9-ee36-6a838db0c15c"
},
"execution_count": 18,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"Start 2021-12-08 15:15:00\n",
"End 2021-12-13 20:15:00\n",
"Duration 5 days 05:00:00\n",
"Exposure Time [%] 86.6\n",
"Equity Final [$] 96375.6\n",
"Equity Peak [$] 108163\n",
"Return [%] -3.62445\n",
"Buy & Hold Return [%] -21.5003\n",
"Return (Ann.) [%] -89.4159\n",
"Volatility (Ann.) [%] 12.9533\n",
"Sharpe Ratio 0\n",
"Sortino Ratio 0\n",
"Calmar Ratio 0\n",
"Max. Drawdown [%] -13.2457\n",
"Avg. Drawdown [%] -1.34702\n",
"Max. Drawdown Duration 3 days 05:10:00\n",
"Avg. Drawdown Duration 0 days 04:51:00\n",
"# Trades 11\n",
"Win Rate [%] 63.6364\n",
"Best Trade [%] 7.02633\n",
"Worst Trade [%] -8.92633\n",
"Avg. Trade [%] -0.334801\n",
"Max. Trade Duration 1 days 06:50:00\n",
"Avg. Trade Duration 0 days 09:51:00\n",
"Profit Factor 0.780053\n",
"Expectancy [%] -0.268112\n",
"SQN -0.277633\n",
"_strategy SuperTrend\n",
"_equity_curve ...\n",
"_trades Size EntryB...\n",
"dtype: object"
]
},
"metadata": {},
"execution_count": 18
}
]
},
{
"cell_type": "markdown",
"source": [
"### テスト戦略の描画\n",
"\n"
],
"metadata": {
"id": "LE9-GbwLkaOf"
}
},
{
"cell_type": "code",
"source": [
"bt.plot()"
],
"metadata": {
"id": "_Dp32E6oF7Dc",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 814
},
"outputId": "2ce252d8-fb98-4258-eddc-fd804b53a017"
},
"execution_count": 19,
"outputs": [
{
"output_type": "display_data",
"data": {
"application/javascript": [
"\n",
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" return new Date();\n",
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" root._bokeh_onload_callbacks = [];\n",
" root._bokeh_is_loading = undefined;\n",
" }\n",
"\n",
" var JS_MIME_TYPE = 'application/javascript';\n",
" var HTML_MIME_TYPE = 'text/html';\n",
" var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
" var CLASS_NAME = 'output_bokeh rendered_html';\n",
"\n",
" /**\n",
" * Render data to the DOM node\n",
" */\n",
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" var script = document.createElement(\"script\");\n",
" node.appendChild(script);\n",
" }\n",
"\n",
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" * Handle when an output is cleared or removed\n",
" */\n",
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" var cell = handle.cell;\n",
"\n",
" var id = cell.output_area._bokeh_element_id;\n",
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"\n",
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" var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
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" if (id in Bokeh.index) {\n",
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" return\n",
" }\n",
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" }\n",
" if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
" var bk_div = document.createElement(\"div\");\n",
" bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
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" toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n",
" }\n",
" // store reference to server id on output_area\n",
" output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
" }\n",
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"\n",
" function register_renderer(events, OutputArea) {\n",
"\n",
" function append_mime(data, metadata, element) {\n",
" // create a DOM node to render to\n",
" var toinsert = this.create_output_subarea(\n",
" metadata,\n",
" CLASS_NAME,\n",
" EXEC_MIME_TYPE\n",
" );\n",
" this.keyboard_manager.register_events(toinsert);\n",
" // Render to node\n",
" var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
" render(props, toinsert[toinsert.length - 1]);\n",
" element.append(toinsert);\n",
" return toinsert\n",
" }\n",
"\n",
" /* Handle when an output is cleared or removed */\n",
" events.on('clear_output.CodeCell', handleClearOutput);\n",
" events.on('delete.Cell', handleClearOutput);\n",
"\n",
" /* Handle when a new output is added */\n",
" events.on('output_added.OutputArea', handleAddOutput);\n",
"\n",
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" OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
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" safe: true,\n",
" /* Index of renderer in `output_area.display_order` */\n",
" index: 0\n",
" });\n",
" }\n",
"\n",
" // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
" if (root.Jupyter !== undefined) {\n",
" var events = require('base/js/events');\n",
" var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
"\n",
" if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
" register_renderer(events, OutputArea);\n",
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"\n",
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" root._bokeh_timeout = Date.now() + 5000;\n",
" root._bokeh_failed_load = false;\n",
" }\n",
"\n",
" var NB_LOAD_WARNING = {'data': {'text/html':\n",
" \"<div style='background-color: #fdd'>\\n\"+\n",
" \"<p>\\n\"+\n",
" \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
" \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
" \"</p>\\n\"+\n",
" \"<ul>\\n\"+\n",
" \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
" \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
" \"</ul>\\n\"+\n",
" \"<code>\\n\"+\n",
" \"from bokeh.resources import INLINE\\n\"+\n",
" \"output_notebook(resources=INLINE)\\n\"+\n",
" \"</code>\\n\"+\n",
" \"</div>\"}};\n",
"\n",
" function display_loaded() {\n",
" var el = document.getElementById(null);\n",
" if (el != null) {\n",
" el.textContent = \"BokehJS is loading...\";\n",
" }\n",
" if (root.Bokeh !== undefined) {\n",
" if (el != null) {\n",
" el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
" }\n",
" } else if (Date.now() < root._bokeh_timeout) {\n",
" setTimeout(display_loaded, 100)\n",
" }\n",
" }\n",
"\n",
"\n",
" function run_callbacks() {\n",
" try {\n",
" root._bokeh_onload_callbacks.forEach(function(callback) {\n",
" if (callback != null)\n",
" callback();\n",
" });\n",
" } finally {\n",
" delete root._bokeh_onload_callbacks\n",
" }\n",
" console.debug(\"Bokeh: all callbacks have finished\");\n",
" }\n",
"\n",
" function load_libs(css_urls, js_urls, callback) {\n",
" if (css_urls == null) css_urls = [];\n",
" if (js_urls == null) js_urls = [];\n",
"\n",
" root._bokeh_onload_callbacks.push(callback);\n",
" if (root._bokeh_is_loading > 0) {\n",
" console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
" return null;\n",
" }\n",
" if (js_urls == null || js_urls.length === 0) {\n",
" run_callbacks();\n",
" return null;\n",
" }\n",
" console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
" root._bokeh_is_loading = css_urls.length + js_urls.length;\n",
"\n",
" function on_load() {\n",
" root._bokeh_is_loading--;\n",
" if (root._bokeh_is_loading === 0) {\n",
" console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
" run_callbacks()\n",
" }\n",
" }\n",
"\n",
" function on_error(url) {\n",
" console.error(\"failed to load \" + url);\n",
" }\n",
"\n",
" for (let i = 0; i < css_urls.length; i++) {\n",
" const url = css_urls[i];\n",
" const element = document.createElement(\"link\");\n",
" element.onload = on_load;\n",
" element.onerror = on_error.bind(null, url);\n",
" element.rel = \"stylesheet\";\n",
" element.type = \"text/css\";\n",
" element.href = url;\n",
" console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
" document.body.appendChild(element);\n",
" }\n",
"\n",
" const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.3.3.min.js\": \"dM3QQsP+wXdHg42wTqW85BjZQdLNNIXqlPw/BgKoExPmTG7ZLML4EGqLMfqHT6ON\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.3.3.min.js\": \"8x57I4YuIfu8XyZfFo0XVr2WAT8EK4rh/uDe3wF7YuW2FNUSNEpJbsPaB1nJ2fz2\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.3.3.min.js\": \"3QTqdz9LyAm2i0sG5XTePsHec3UHWwVsrOL68SYRoAXsafvfAyqtQ+h440+qIBhS\"};\n",
"\n",
" for (let i = 0; i < js_urls.length; i++) {\n",
" const url = js_urls[i];\n",
" const element = document.createElement('script');\n",
" element.onload = on_load;\n",
" element.onerror = on_error.bind(null, url);\n",
" element.async = false;\n",
" element.src = url;\n",
" if (url in hashes) {\n",
" element.crossOrigin = \"anonymous\";\n",
" element.integrity = \"sha384-\" + hashes[url];\n",
" }\n",
" console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
" document.head.appendChild(element);\n",
" }\n",
" };\n",
"\n",
" function inject_raw_css(css) {\n",
" const element = document.createElement(\"style\");\n",
" element.appendChild(document.createTextNode(css));\n",
" document.body.appendChild(element);\n",
" }\n",
"\n",
" \n",
" var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.3.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.3.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.3.3.min.js\"];\n",
" var css_urls = [];\n",
" \n",
"\n",
" var inline_js = [\n",
" function(Bokeh) {\n",
" Bokeh.set_log_level(\"info\");\n",
" },\n",
" function(Bokeh) {\n",
" \n",
" \n",
" }\n",
" ];\n",
"\n",
" function run_inline_js() {\n",
" \n",
" if (root.Bokeh !== undefined || force === true) {\n",
" \n",
" for (var i = 0; i < inline_js.length; i++) {\n",
" inline_js[i].call(root, root.Bokeh);\n",
" }\n",
" } else if (Date.now() < root._bokeh_timeout) {\n",
" setTimeout(run_inline_js, 100);\n",
" } else if (!root._bokeh_failed_load) {\n",
" console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
" root._bokeh_failed_load = true;\n",
" } else if (force !== true) {\n",
" var cell = $(document.getElementById(null)).parents('.cell').data().cell;\n",
" cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
" }\n",
"\n",
" }\n",
"\n",
" if (root._bokeh_is_loading === 0) {\n",
" console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
" run_inline_js();\n",
" } else {\n",
" load_libs(css_urls, js_urls, function() {\n",
" console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
" run_inline_js();\n",
" });\n",
" }\n",
"}(window));"
],
"application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n\n if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n \n\n \n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n var NB_LOAD_WARNING = {'data': {'text/html':\n \"<div style='background-color: #fdd'>\\n\"+\n \"<p>\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"</p>\\n\"+\n \"<ul>\\n\"+\n \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n \"<li>use INLINE resources instead, as so:</li>\\n\"+\n \"</ul>\\n\"+\n \"<code>\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"</code>\\n\"+\n \"</div>\"}};\n\n function display_loaded() {\n var el = document.getElementById(null);\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\n }\n\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls == null || js_urls.length === 0) {\n run_callbacks();\n return null;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n\n function on_error(url) {\n console.error(\"failed to load \" + url);\n }\n\n for (let i = 0; i < css_urls.length; i++) {\n const url = css_urls[i];\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error.bind(null, url);\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n }\n\n const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.3.3.min.js\": \"dM3QQsP+wXdHg42wTqW85BjZQdLNNIXqlPw/BgKoExPmTG7ZLML4EGqLMfqHT6ON\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.3.3.min.js\": \"8x57I4YuIfu8XyZfFo0XVr2WAT8EK4rh/uDe3wF7YuW2FNUSNEpJbsPaB1nJ2fz2\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.3.3.min.js\": \"3QTqdz9LyAm2i0sG5XTePsHec3UHWwVsrOL68SYRoAXsafvfAyqtQ+h440+qIBhS\"};\n\n for (let i = 0; i < js_urls.length; i++) {\n const url = js_urls[i];\n const element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error.bind(null, url);\n element.async = false;\n element.src = url;\n if (url in hashes) {\n element.crossOrigin = \"anonymous\";\n element.integrity = \"sha384-\" + hashes[url];\n }\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n \n var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.3.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.3.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.3.3.min.js\"];\n var css_urls = [];\n \n\n var inline_js = [\n function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\n function(Bokeh) {\n \n \n }\n ];\n\n function run_inline_js() {\n \n if (root.Bokeh !== undefined || force === true) {\n \n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n } else if (force !== true) {\n var cell = $(document.getElementById(null)).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\n }\n\n }\n\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(css_urls, js_urls, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
" <div class=\"bk-root\" id=\"ccfa1f3f-1567-4c19-91a6-ab69e50326ff\" data-root-id=\"2294\"></div>\n"
]
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"metadata": {}
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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1500]},\"Close\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1500]},\"FINAL_UPP\\u2026(BASIC_BAN\\u2026,Prev_Close,15)_3_1\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1500]},\"High\":{\"__ndarray__\":\"w/UoXI9waEBxPQrXo5hoQM3MzMzMiGhAmpmZmZlraEA9CtejcF1oQHsUrkfhOGhA9ihcj8IjaEDNzMzMzB5oQB+F61G4JGhAzczMzMxGaEDNzMzMzD5oQClcj8L1OmhApHA9CtcxaEAK16NwPRZoQKRwPQrXB2hAmpmZmZn5Z0AK16NwPeJnQOF6FK5H8WdAPQrXo3D3Z0CkcD0K1wVoQOF6FK5HBWhAUrgehesJaEC4HoXrUShoQBSuR+F6JmhAj8L1KFwdaEBSuB6F6xFoQHE9CtejHmhAcT0K16MgaEC4HoXrURRoQLgehetREGhAKVyPwvUOaEDD9ShcjxxoQMP1KFyPMGhAKVyPwvU0aEBSuB6F6yVoQLgehetRNGhAj8L1KFw1aEDD9Shcjz5oQLgehetRRGhAPQrXo3BXaED2KFyPwkloQIXrUbgeR2hAuB6F61FCaEAUrkfhelBoQGZmZmZmUGhACtejcD1WaEAzMzMzM1NoQOF6FK5HTWhAKVyPwvVOaEBxPQrXo05oQI/C9ShcS2hAMzMzMzNdaEBmZmZmZl5oQFyPwvUoUGhAZmZmZmY0aEAzMzMzMxloQOxRuB6FJ2hArkfhehQ2aEDsUbgehTdoQK5H4XoUOGhArkfhehQ8aEB7FK5H4SZoQJqZmZmZN2hAZmZmZmZGaEDXo3A9CkloQJqZmZmZPWhAH4XrUbg2aEBmZmZmZkRoQOF6FK5HO2hApHA9CtczaEAzMzMzMzVoQI/C9ShcN2hA16NwPQodaECkcD0K1xVoQNejcD0KD2hAAAAAAAD8Z0DNzMzMzAJoQGZmZmZmDmhAMzMzMzMLaECuR+F6FARoQClcj8L1AGhAUrgehesNaEApXI/C9RJoQOF6FK5H/WdAhetRuB4FaEAfhetRuApoQGZmZmZmDmhAcT0K16MWaEBmZmZmZhpoQHsUrkfhImhAMzMzMzMraEDhehSuRx9oQMP1KFyPLmhAKVyPwvU8aEDhehSuRz1oQI/C9ShcQWhAZmZmZmZcaEDNzMzMzFxoQIXrUbgeQ2hAuB6F61FEaEAK16NwPURoQHsUrkfhRGhAMzMzMzNTaED2KFyPwlVoQK5H4XoUXGhAexSuR+FoaEA9CtejcJVoQM3MzMzMoGhApHA9CteZaEApXI/C9ZZoQAAAAAAAbmhAexSuR+F6aEBI4XoUroFoQJqZmZmZfWhAUrgeheuHaEDXo3A9Cn1oQIXrUbgedWhAMzMzMzNbaEBxPQrXo1poQK5H4XoURGhAmpmZmZlDaEDD9Shcj1JoQOF6FK5HT2hAuB6F61FGaEAzMzMzM0loQBSuR+F6TGhAPQrXo3BLaECF61G4HkdoQNejcD0KMWhApHA9CtcxaECkcD0K1zFoQFK4HoXrJ2hAmpmZmZkvaEDNzMzMzBZoQI/C9Shc72dAmpmZmZnnZ0DNzMzMzPRnQBSuR+F69mdA7FG4HoX3Z0CamZmZmfdnQPYoXI/C72dApHA9CtflZ0AfhetRuOpnQB+F61G44mdAzczMzMzaZ0AK16NwPdZnQD0K16NwyWdA7FG4HoXJZ0CF61G4HsFnQHsUrkfhsmdAzczMzMysZ0AfhetRuL5nQB+F61G4vGdAj8L1KFzRZ0AAAAAAANpnQBSuR+F64mdAcT0K16PWZ0BxPQrXo+ZnQGZmZmZm5mdA7FG4HoXjZ0CkcD0K1+VnQJqZmZmZ42dACtejcD3uZ0DNzMzMzPBnQOxRuB6F9WdArkfhehQIaEAfhetRuPxnQJqZmZmZ92dA9ihcj8LtZ0AfhetRuOxnQB+F61G49mdAZmZmZmbsZ0D2KFyPwvtnQB+F61G48mdAH4XrUbjwZ0DNzMzMzOhnQFyPwvUo7GdA16NwPQrZZ0ApXI/C9eRnQEjhehSu+2dA9ihcj8LxZ0BI4XoUru9nQLgehetR5GdAUrgehevZZ0C4HoXrUcZnQDMzMzMzzWdAcT0K16PmZ0BSuB6F6+VnQOxRuB6F4WdAzczMzMzeZ0Bcj8L1KMxnQB+F61G4tmdAFK5H4XrGZ0C4HoXrUcpnQDMzMzMzzWdApHA9Ctf5Z0CF61G4HulnQDMzMzMz7WdAhetRuB7pZ0AAAAAAAPJnQBSuR+F66mdAexSuR+HiZ0DXo3A9CtFnQOxRuB6FxWdA7FG4HoXRZ0DXo3A9CsFnQI/C9ShcxWdApHA9CtfRZ0DNzMzMzMRnQB+F61G4qmdASOF6FK61Z0BI4XoUrqVnQNejcD0KsWdAFK5H4XqmZ0BSuB6F66FnQNejcD0KnWdAUrgeheuXZ0DhehSuR6NnQClcj8L1lGdAj8L1KFyBZ0DXo3A9CntnQM3MzMzMjGdASOF6FK6NZ0CkcD0K15FnQEjhehSugWdAMzMzMzOLZ0AK16NwPXZnQDMzMzMzd2dAAAAAAACAZ0AAAAAAAIBnQClcj8L1fmdAuB6F61F4Z0C4HoXrUXxnQEjhehSuhWdAPQrXo3CJZ0BSuB6F649nQAAAAAAAoGdAUrgeheufZ0BmZmZmZppnQIXrUbgem2dA7FG4HoWXZ0BmZmZmZppnQJqZmZmZiWdAzczMzMyIZ0AfhetRuHxnQBSuR+F6iGdAKVyPwvWSZ0A9CtejcJNnQAAAAAAAimdAH4XrUbh6Z0AAAAAAAIRnQK5H4XoUhmdAj8L1KFybZ0ApXI/C9ZRnQAAAAAAAkGdAH4XrUbh8Z0AfhetRuH5nQDMzMzMzj2dAMzMzMzOVZ0D2KFyPwpFnQM3MzMzMmmdArkfhehSUZ0CF61G4Ho1nQJqZmZmZiWdAFK5H4XqQZ0AK16NwPZBnQBSuR+F6jmdAexSuR+GQZ0AfhetRuK5nQFyPwvUouGdAMzMzMzOxZ0BxPQrXo6hnQLgehetRpmdAMzMzMzO3Z0DhehSuR7NnQD0K16Nwq2dAUrgeheu1Z0DhehSuR5lnQFK4HoXrd2dAmpmZmZlzZ0CkcD0K10lnQFK4HoXrR2dA16NwPQpDZ0BxPQrXozhnQLgehetRJmdArkfhehQ8Z0AK16NwPVpnQHE9CtejVmdA9ihcj8JVZ0DD9ShcjzxnQHE9CtejMGdAFK5H4XoCZ0CamZmZmQFnQOxRuB6FAWdAKVyPwvUeZ0AzMzMzMyNnQFK4HoXrJWdAexSuR+FSZ0BmZmZmZkhnQDMzMzMzP2dAXI/C9SggZ0DNzMzMzBxnQKRwPQrXKWdAmpmZmZkzZ0AzMzMzM0NnQIXrUbgeS2dAZmZmZmYeZ0AAAAAAACBnQAAAAAAAIGdAH4XrUbgcZ0CamZmZmR1nQK5H4XoUGmdAexSuR+EYZ0CuR+F6FBRnQKRwPQrXE2dACtejcD0GZ0DNzMzMzAxnQAAAAAAABmdAH4XrUbj0ZkCamZmZmQFnQNejcD0K8WZAcT0K16PiZkDsUbgeheFmQLgehetR4mZAXI/C9SjcZkAfhetRuNJmQFyPwvUoxmZACtejcD22ZkBmZmZmZqZmQOF6FK5Ho2ZAUrgeheubZkBcj8L1KHpmQM3MzMzMmGZA9ihcj8KtZkAAAAAAAMBmQKRwPQrXs2ZAmpmZmZm/ZkAAAAAAAL5mQMP1KFyPvGZAhetRuB7FZkAzMzMzM9NmQClcj8L12GZASOF6FK7bZkAAAAAAAOBmQIXrUbgeyWZAhetRuB6/ZkDhehSuR6FmQLgehetRlGZAw/UoXI+gZkDNzMzMzKJmQOxRuB6Fm2ZAAAAAAACgZkAUrkfhepBmQIXrUbgec2ZAzczMzMyGZkDNzMzMzIRmQK5H4XoUnmZAFK5H4XqsZkAzMzMzM8FmQGZmZmZmxmZA9ihcj8K9ZkA9CtejcMVmQEjhehSu0WZACtejcD3KZkBmZmZmZsJmQDMzMzMz12ZAXI/C9SjgZkDhehSuR+tmQLgehetR5mZArkfhehT6ZkBI4XoUrv9mQLgehetR/mZAAAAAAAAAZ0BmZmZmZgBnQNejcD0KBWdAXI/C9SgCZ0BmZmZmZu5mQJqZmZmZ22ZAexSuR+HYZkCkcD0K1+NmQNejcD0K72ZAzczMzMzyZkBmZmZmZvpmQOxRuB6FAWdAcT0K16MAZ0DD9Shcj/RmQLgehetR9mZAMzMzMzP5ZkDsUbgehelmQGZmZmZm4GZAAAAAAADcZkBI4XoUrttmQArXo3A9ymZAuB6F61HIZkBSuB6F69tmQEjhehSu52ZAH4XrUbjyZkCPwvUoXOVmQK5H4XoU5GZAuB6F61EUZ0CF61G4HhFnQDMzMzMz7WZAKVyPwvXmZkA9CtejcN1mQLgehetRymZAuB6F61HAZkDXo3A9Cq9mQM3MzMzMyGZAMzMzMzPfZkC4HoXrUeZmQMP1KFyP6mZA4XoUrkfnZkCF61G4HuNmQFyPwvUo7mZAcT0K16PoZkDhehSuR/FmQK5H4XoU7GZA7FG4HoXZZkAAAAAAAMBmQFyPwvUosmZAMzMzMzPJZkDhehSuR8NmQKRwPQrXxWZAw/UoXI/EZkAK16NwPcpmQB+F61G4zGZAAAAAAADMZkDsUbgehblmQAAAAAAAwGZA7FG4HoXNZkDXo3A9Cr1mQJqZmZmZs2ZAzczMzMymZkAzMzMzM51mQLgehetRomZAUrgeheudZkAUrkfhepxmQFK4HoXrk2ZAZmZmZmaMZkBSuB6F64dmQOF6FK5Hg2ZAZmZmZmaKZkCkcD0K13lmQJqZmZmZb2ZA9ihcj8J3ZkAUrkfheoxmQFyPwvUohGZAZmZmZmaGZkBSuB6F639mQM3MzMzMaGZAMzMzMzN7ZkCPwvUoXHtmQKRwPQrXdWZAFK5H4XpkZkDhehSuR2VmQPYoXI/CcWZAZmZmZmZ2ZkDD9Shcj3RmQJqZmZmZR2ZAAAAAAABIZkAAAAAAADpmQAAAAAAAQGZAKVyPwvVIZkA9CtejcEdmQEjhehSuU2ZAXI/C9ShcZkDNzMzMzF5mQEjhehSuW2ZAH4XrUbhsZkBmZmZmZmpmQAAAAAAAXGZAFK5H4XpOZkBSuB6F609mQGZmZmZmTmZAXI/C9ShUZkCuR+F6FEhmQEjhehSuOWZA7FG4HoUpZkC4HoXrUSZmQLgehetRFGZAKVyPwvUOZkA9CtejcAVmQD0K16NwE2ZArkfhehQiZkBSuB6F6x1mQClcj8L1AGZAhetRuB4JZkBmZmZmZvplQKRwPQrXC2ZApHA9CtcHZkCkcD0K1xdmQClcj8L1FGZAuB6F61EKZkC4HoXrURBmQB+F61G4FGZA7FG4HoUTZkAAAAAAACBmQMP1KFyPGmZAhetRuB4ZZkAzMzMzMylmQGZmZmZmJGZAZmZmZmYmZkAAAAAAACRmQD0K16NwKWZAzczMzMwWZkC4HoXrUQ5mQHsUrkfhCGZAmpmZmZkDZkCF61G4HgtmQAAAAAAAEGZAAAAAAAAQZkAAAAAAABxmQM3MzMzMJGZAcT0K16MqZkApXI/C9R5mQGZmZmZmKmZAw/UoXI8mZkDhehSuR0NmQNejcD0KNWZAj8L1KFw5ZkBxPQrXozhmQAAAAAAAQmZA9ihcj8JBZkAzMzMzMzNmQBSuR+F6MmZAmpmZmZk9ZkCF61G4Hk1mQFK4HoXrP2ZA9ihcj8I3ZkAzMzMzMyNmQPYoXI/CKWZApHA9CtchZkAzMzMzMydmQM3MzMzMMGZAUrgehetVZkD2KFyPwltmQK5H4XoUVmZAUrgeheuVZkDsUbgehZtmQLgehetRpmZACtejcD2uZkDXo3A9CodmQFK4HoXrj2ZAFK5H4XqMZkAfhetRuIBmQPYoXI/CgWZAhetRuB51ZkCF61G4HoNmQOxRuB6FkWZA16NwPQqPZkBcj8L1KIJmQLgehetRhGZAH4XrUbh6ZkDD9Shcj2pmQJqZmZmZW2ZAAAAAAACgZkAfhetRuNZmQGZmZmZmzmZAH4XrUbjOZkBSuB6F68dmQDMzMzMz42ZAzczMzMzsZkAzMzMzM/NmQMP1KFyP6GZA9ihcj8LTZkDsUbgehctmQB+F61G4yGZAexSuR+G+ZkBcj8L1KNBmQHE9CtejzmZArkfhehS2ZkBI4XoUrlNmQFK4HoXrHWZAmpmZmZkVZkCF61G4Hj1mQFK4HoXrOWZAH4XrUbguZkDXo3A9CiVmQDMzMzMzM2ZAexSuR+EuZkCkcD0K1xFmQIXrUbgeF2ZAUrgehesLZkDNzMzMzN5lQIXrUbge12VAFK5H4Xq2ZUD2KFyPwpVlQEjhehSuiWVA7FG4HoV3ZUCuR+F6FGxlQOF6FK5HYWVAZmZmZmaGZUAAAAAAAJBlQPYoXI/CgWVAMzMzMzObZUCuR+F6FJZlQLgehetRhmVASOF6FK5/ZUDD9Shcj4JlQHsUrkfhhmVAPQrXo3CPZUCF61G4HoVlQD0K16NwhWVAZmZmZmZoZUCamZmZmVllQOxRuB6FVWVA16NwPQpdZUA9CtejcGtlQD0K16Nwf2VACtejcD2aZUCuR+F6FKhlQOF6FK5HzWVA16NwPQrfZUBcj8L1KLxlQAAAAAAAvmVAj8L1KFy1ZUD2KFyPwqllQJqZmZmZt2VAj8L1KFyjZUCPwvUoXJ1lQI/C9ShcgWVAzczMzMx8ZUAUrkfhenRlQOxRuB6Fg2VAAAAAAACQZUBI4XoUrqVlQClcj8L1qGVAexSuR+GyZUDsUbgehb1lQD0K16NwvWVAPQrXo3C7ZUCamZmZmcFlQLgehetRxGVAw/UoXI/OZUBSuB6F689lQClcj8L12GVA16NwPQrfZUAAAAAAAOBlQK5H4XoU3mVAcT0K16PeZUBxPQrXo9ZlQB+F61G4xGVA7FG4HoXJZUDXo3A9Cu9lQFyPwvUo9GVAhetRuB7tZUB7FK5H4eZlQOF6FK5H6WVAKVyPwvXkZUC4HoXrUeZlQNejcD0K12VAmpmZmZnnZUDD9Shcj+ZlQFyPwvUo2GVA16NwPQrTZUDXo3A9Cs9lQEjhehSu22VAAAAAAAC6ZUAAAAAAAKZlQAAAAAAApmVAFK5H4Xq0ZUDD9Shcj6RlQLgehetRnmVAZmZmZmaKZUA9CtejcH1lQNejcD0Kj2VAAAAAAACQZUBxPQrXo4ZlQKRwPQrXe2VA4XoUrkd5ZUCamZmZmX9lQAAAAAAAiGVAhetRuB6RZUDsUbgehZ1lQMP1KFyPoGVAuB6F61GOZUAfhetRuHZlQJqZmZmZaWVAmpmZmZllZUA9CtejcFtlQArXo3A9KmVAw/UoXI8EZUDXo3A9CutkQAAAAAAAsGRAhetRuB5vZECuR+F6FJ5kQEjhehSuCWVA16NwPQoHZUCuR+F6FDRlQGZmZmZmHmVAPQrXo3AHZUAAAAAAAOJkQFyPwvUovmRAw/UoXI/UZEBmZmZmZupkQLgehetR1GRAUrgehevjZEDD9Shcj+JkQB+F61G45GRAcT0K16P8ZEAzMzMzM2dlQAAAAAAAUGVAAAAAAAAsZUApXI/C9RJlQKRwPQrXK2VApHA9CtcjZUD2KFyPwjFlQOxRuB6FKWVA16NwPQojZUDNzMzMzBZlQDMzMzMzE2VAzczMzMwMZUD2KFyPwv1kQB+F61G4BGVACtejcD0KZUBmZmZmZgZlQJqZmZmZ/WRA7FG4HoUdZUBxPQrXozRlQEjhehSuU2VAzczMzMxeZUCamZmZmWdlQArXo3A9emVA16NwPQphZUAfhetRuGBlQB+F61G4ZmVA7FG4HoVRZUApXI/C9VJlQDMzMzMzVWVAzczMzMxiZUBSuB6F63NlQK5H4XoUTmVA9ihcj8JFZUDNzMzMzDxlQClcj8L1QGVAhetRuB5RZUAK16NwPUZlQMP1KFyPSGVAPQrXo3BTZUCF61G4Hl1lQM3MzMzMZGVAH4XrUbhaZUCuR+F6FFJlQIXrUbgeU2VAPQrXo3BbZUAAAAAAAGBlQFK4HoXrb2VAPQrXo3BxZUApXI/C9WxlQNejcD0KeWVAFK5H4Xp2ZUAAAAAAAEplQAAAAAAASmVACtejcD1oZUBxPQrXo4plQMP1KFyPhmVAMzMzMzNzZUB7FK5H4V5lQClcj8L1UGVA7FG4HoVHZUDD9Shcj1ZlQHsUrkfhRGVACtejcD0qZUBI4XoUriFlQIXrUbgeHWVA7FG4HoUhZUBmZmZmZi5lQMP1KFyPOGVAKVyPwvUmZUC4HoXrUSZlQOxRuB6FG2VAPQrXo3AdZUAfhetRuChlQIXrUbgeMWVA7FG4HoUvZUBmZmZmZjJlQAAAAAAAQGVAcT0K16MkZUDD9ShcjzRlQLgehetRPmVAXI/C9ShWZUBxPQrXo3plQM3MzMzMimVAexSuR+GOZUCF61G4Hn9lQNejcD0KfWVA7FG4HoVpZUBmZmZmZl5lQGZmZmZmaGVA4XoUrkddZUBI4XoUrldlQAAAAAAAaGVAMzMzMzNvZUAzMzMzM29lQArXo3A9emVA16NwPQp9ZUDsUbgehXllQAAAAAAAeGVAmpmZmZlpZUAfhetRuH5lQDMzMzMzf2VAzczMzMyAZUBI4XoUrndlQBSuR+F6mGVAw/UoXI98ZUB7FK5H4XplQB+F61G4emVA4XoUrkd3ZUAAAAAAAHRlQBSuR+F6fGVAKVyPwvWOZUAUrkfheoxlQM3MzMzMiGVAUrgeheuJZUCamZmZmYtlQB+F61G4hGVAMzMzMzN3ZUAAAAAAAFplQClcj8L1VGVA16NwPQpRZUBcj8L1KF5lQFyPwvUoXmVAuB6F61FSZUCF61G4Hk9lQFyPwvUoVGVAj8L1KFxZZUDsUbgehV9lQD0K16NwU2VAw/UoXI9oZUCamZmZmWdlQLgehetRVmVAFK5H4XpeZUAAAAAAAGhlQKRwPQrXW2VAUrgehetXZUAUrkfhelplQFK4HoXrW2VAhetRuB49ZUDsUbgehVNlQI/C9ShcKWVArkfhehQ6ZUAAAAAAADplQArXo3A9MGVAMzMzMzMvZUD2KFyPwillQFK4HoXrF2VAPQrXo3AXZUCamZmZmRllQMP1KFyPGmVAzczMzMwMZUApXI/C9RJlQClcj8L1EmVAmpmZmZkhZUC4HoXrURZlQPYoXI/CI2VAPQrXo3AbZUCamZmZmR9lQB+F61G4LmVAAAAAAAAwZUBcj8L1KC5lQClcj8L1QGVA7FG4HoU3ZUAzMzMzMzVlQFyPwvUoNmVAMzMzMzM5ZUBcj8L1KD5lQD0K16NwTWVAPQrXo3BVZUAfhetRuFJlQIXrUbgeT2VA7FG4HoVXZUApXI/C9WRlQKRwPQrXZWVAUrgehetvZUApXI/C9XZlQM3MzMzMimVAAAAAAACoZUDNzMzMzLhlQOF6FK5HtWVAmpmZmZmxZUApXI/C9bJlQI/C9Shcp2VAMzMzMzOZZUB7FK5H4ZZlQArXo3A9lGVAMzMzMzOFZUDsUbgehYdlQD0K16NwgWVArkfhehSEZUAAAAAAAH5lQI/C9Shcg2VA9ihcj8JxZUAUrkfhemRlQArXo3A9XmVAmpmZmZlJZUC4HoXrUU5lQIXrUbgeU2VAUrgehetXZUAAAAAAAExlQPYoXI/CP2VArkfhehQ8ZUC4HoXrUTplQK5H4XoUPGVAexSuR+E8ZUAzMzMzMzdlQKRwPQrXMWVA4XoUrkcvZUCuR+F6FBhlQHsUrkfhFGVAKVyPwvUQZUAfhetRuAxlQOxRuB6FC2VASOF6FK4XZUAAAAAAABZlQOxRuB6FE2VAUrgehesJZUCuR+F6FA5lQM3MzMzMEGVAH4XrUbgQZUDD9ShcjwhlQOxRuB6FCWVArkfhehQOZUC4HoXrUSJlQClcj8L1JGVAXI/C9SgkZUCF61G4HillQI/C9ShcN2VAFK5H4Xo6ZUCF61G4HjtlQD0K16NwOWVApHA9CtcxZUBxPQrXozhlQJqZmZmZN2VA7FG4HoUdZUDNzMzMzBJlQLgehetRJGVArkfhehQmZUAK16NwPSZlQB+F61G4HGVA9ihcj8IHZUCamZmZmQdlQB+F61G4IGVAj8L1KFwnZUCkcD0K1zFlQOxRuB6FO2VAFK5H4Xo6ZUDNzMzMzDplQAAAAAAAOmVA7FG4HoUzZUBI4XoUritlQBSuR+F6NmVAMzMzMzNJZUAAAAAAAGBlQClcj8L1WGVAXI/C9ShiZUCkcD0K111lQOF6FK5HY2VAAAAAAABwZUAUrkfhenhlQPYoXI/CdWVA4XoUrkd/ZUAUrkfheoJlQMP1KFyPimVAAAAAAACSZUDXo3A9CndlQOF6FK5He2VAexSuR+GCZUDhehSuR4llQPYoXI/CiWVA4XoUrkeLZUBxPQrXo4BlQD0K16Nwk2VAKVyPwvWWZUCkcD0K149lQM3MzMzMdmVA9ihcj8JTZUBSuB6F61llQIXrUbgeVWVAH4XrUbhMZUApXI/C9VxlQArXo3A9XmVAH4XrUbhsZUCF61G4HmVlQArXo3A9aGVAMzMzMzNhZUA9CtejcDtlQClcj8L1OmVApHA9Ctc5ZUA9CtejcDVlQFK4HoXrP2VAZmZmZmY8ZUBSuB6F6zdlQPYoXI/CM2VAZmZmZmYyZUCamZmZmS1lQGZmZmZmLGVApHA9CtcrZUC4HoXrUS5lQB+F61G4MGVAH4XrUbgwZUCkcD0K1zllQIXrUbgeO2VAFK5H4XoyZUB7FK5H4SJlQM3MzMzMImVAUrgehesjZUBmZmZmZiZlQMP1KFyPKmVAcT0K16MwZUApXI/C9ThlQI/C9ShcO2VAMzMzMzNBZUBSuB6F60tlQGZmZmZmRmVAXI/C9ShEZUAzMzMzM0FlQJqZmZmZQ2VAzczMzMwiZUDNzMzMzBplQFyPwvUoImVAw/UoXI8oZUAfhetRuDBlQDMzMzMzNWVArkfhehQwZUAzMzMzMzFlQLgehetRKGVAUrgehesTZUAzMzMzMxdlQM3MzMzMKmVAhetRuB4rZUCuR+F6FChlQMP1KF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zMzMzM5tmQOF6FK5HsWZAZmZmZmasZkC4HoXrUbpmQB+F61G4sGZAzczMzMzEZkCuR+F6FLxmQPYoXI/Cv2ZApHA9CtfVZkAK16NwPdRmQLgehetR5mZAZmZmZmbSZkAzMzMzM/dmQEjhehSu+2ZAFK5H4XruZkDNzMzMzPpmQFyPwvUoAGdAPQrXo3ABZ0CPwvUoXOdmQJqZmZmZ22ZASOF6FK63ZkBxPQrXo9hmQHE9Ctej4GZAKVyPwvXuZkCamZmZme1mQOxRuB6F+WZA7FG4HoX5ZkCamZmZme1mQEjhehSu8WZAj8L1KFzrZkBmZmZmZuhmQB+F61G42mZAXI/C9SjWZkA9CtejcNlmQNejcD0Ku2ZAFK5H4XqmZkApXI/C9a5mQPYoXI/C2WZAw/UoXI/iZkAUrkfhetJmQAAAAAAA4GZAPQrXo3DhZkBSuB6F6wFnQDMzMzMz7WZA7FG4HoXdZkAK16NwPc5mQM3MzMzMxGZAmpmZmZm3ZkBxPQrXo4xmQAAAAAAArmZAzczMzMzIZkA9CtejcN1mQD0K16Nw2WZAMzMzMzPnZkCamZmZmdFmQMP1KFyP1mZASOF6FK7nZkBSuB6F6+NmQMP1KFyP6GZA7FG4HoXHZkAAAAAAAMBmQD0K16NwqWZA9ihcj8KtZkAfhetRuMBmQPYoXI/CuWZAKVyPwvW4ZkCamZmZmb9mQKRwPQrXyWZACtejcD3IZkAK16NwPbZmQNejcD0KsWZAuB6F61G+ZkCkcD0K17NmQK5H4XoUrGZAexSuR+GcZkCPwvUoXJtmQNejcD0Km2ZAMzMzMzObZkAUrkfhepJmQDMzMzMzjWZAuB6F61GAZkAAAAAAAIBmQEjhehSue2ZAj8L1KFx7ZkCkcD0K13lmQIXrUbgeXWZAAAAAAABuZkCamZmZmW1mQOxRuB6Ff2ZAUrgehet/ZkAK16NwPW5mQLgehetRaGZAw/UoXI9kZkCamZmZmXlmQI/C9Shca2ZA4XoUrkddZkBcj8L1KFpmQNejcD0KXWZAw/UoXI9eZkDsUbgehXFmQGZmZmZmQGZACtejcD08ZkAzMzMzMy1mQArXo3A9LGZA7FG4HoU5ZkDNzMzMzEJmQBSuR+F6OGZAH4XrUbhOZkDNzMzMzExmQAAAAAAAWmZASOF6FK5NZkCkcD0K12FmQMP1KFyPVGZAexSuR+E6ZkBSuB6F601mQB+F61G4PGZApHA9CtdJZkCF61G4HkNmQLgehetRNGZAexSuR+EcZkCPwvUoXB9mQI/C9ShcBWZAKVyPwvUMZkB7FK5H4f5lQOxRuB6FBWZAPQrXo3ATZkBI4XoUrhlmQMP1KFyP+mVApHA9Ctf9ZUAK16NwPfJlQPYoXI/C72VAhetRuB4HZkAK16NwPfplQFyPwvUoFGZApHA9Ctf9ZUCPwvUoXAVmQPYoXI/CBWZAj8L1KFwHZkBmZmZmZhJmQOF6FK5HFWZAw/UoXI8IZkDNzMzMzBhmQHE9CtejImZArkfhehQQZkDNzMzMzCJmQLgehetRHGZAmpmZmZkTZkDsUbgehQVmQFyPwvUoBmZAAAAAAAD0ZUCPwvUoXPdlQAAAAAAACGZAj8L1KFwPZkAzMzMzMw9mQPYoXI/CG2ZAmpmZmZkhZkC4HoXrURJmQJqZmZmZFWZA9ihcj8IjZkDD9ShcjxhmQFK4HoXrL2ZAFK5H4XomZkDsUbgehTVmQArXo3A9LGZAH4XrUbg6ZkAAAAAAADJmQDMzMzMzK2ZAH4XrUbguZkCamZmZmTlmQFyPwvUoOmZAexSuR+E0ZkBxPQrXoxZmQB+F61G4GmZAH4XrUbgKZkCkcD0K1yFmQFK4HoXrHWZA9ihcj8IpZkDNzMzMzFRmQD0K16NwS2ZArkfhehRWZkBcj8L1KJRmQFK4HoXriWZAuB6F61GmZkCPwvUoXINmQDMzMzMzeWZAH4XrUbiGZkCuR+F6FGxmQB+F61G4gGZAw/UoXI9yZkCkcD0K12tmQMP1KFyPfGZAPQrXo3CNZkDXo3A9Cn1mQFyPwvUofGZAUrgehet5ZkAK16NwPWpmQD0K16NwV2ZAKVyPwvVQZkCamZmZmYNmQLgehetRzmZAexSuR+HIZkDNzMzMzMBmQI/C9ShcxWZAH4XrUbjIZkAAAAAAAORmQHE9Ctej2mZAzczMzMzOZkA9CtejcL1mQB+F61G4yGZAcT0K16O2ZkBI4XoUrrNmQOF6FK5HzWZAhetRuB6zZkAUrkfhejJmQGZmZmZmDmZAXI/C9Sj0ZUCkcD0K181lQPYoXI/CNWZA16NwPQoFZkDXo3A9ChlmQPYoXI/CHWZAXI/C9SguZkBxPQrXowZmQFK4HoXrDWZA9ihcj8ILZkBmZmZmZtplQFK4HoXr0WVAUrgeheuzZUDsUbgehYVlQPYoXI/ChWVAUrgehetvZUAAAAAAAExlQHE9CtejRGVAcT0K16NgZUAAAAAAAIRlQKRwPQrXWWVAH4XrUbiAZUAfhetRuI5lQK5H4XoUeGVAw/UoXI9mZUDD9Shcj3xlQClcj8L1cGVAZmZmZmaAZUCkcD0K14FlQPYoXI/Cf2VAw/UoXI9WZUBmZmZmZkplQOF6FK5HQWVA9ihcj8JPZUDsUbgehUVlQJqZmZmZZWVA16NwPQp7ZUB7FK5H4ZBlQM3MzMzMomVAw/UoXI/CZUCkcD0K17dlQFK4HoXroWVAMzMzMzO1ZUAK16NwPZxlQGZmZmZmqGVArkfhehSiZUDsUbgehZNlQI/C9ShcgWVA7FG4HoVzZUCamZmZmWdlQK5H4XoUamVAw/UoXI9yZUDsUbgehY1lQOxRuB6Fl2VAH4XrUbicZUD2KFyPwqdlQJqZmZmZu2VApHA9CtelZUDsUbgehbVlQD0K16Nws2VAZmZmZmayZUD2KFyPwsVlQPYoXI/Cx2VAmpmZmZnLZUDhehSuR9dlQJqZmZmZ02VAH4XrUbjOZUCF61G4Hs1lQArXo3A9wmVAXI/C9Si6ZUCkcD0K18NlQB+F61G40mVAUrgehevrZUA9CtejcONlQB+F61G40GVAexSuR+HKZUDD9Shcj95lQOxRuB6F02VAuB6F61HSZUDhehSuR99lQOxRuB6F0WVAzczMzMzKZUCkcD0K17VlQHsUrkfhwmVAFK5H4XquZUAzMzMzM5tlQI/C9ShcpWVAAAAAAACgZUA9CtejcKNlQArXo3A9lmVAmpmZmZmJZUCkcD0K129lQI/C9ShcfWVAKVyPwvWOZUBxPQrXo4ZlQNejcD0Kb2VAFK5H4XpmZUBI4XoUrm1lQOxRuB6Ff2VApHA9CtdnZUDhehSuR4tlQArXo3A9mGVApHA9CteBZUB7FK5H4XJlQFyPwvUoWmVA4XoUrkdfZUBI4XoUrk9lQHsUrkfhEmVA7FG4HoXpZEDD9Shcj+pkQHE9CtejnmRA7FG4HoVZZEDD9Shcj0JkQPYoXI/Cl2RApHA9Ctf9ZEAzMzMzM+1kQI/C9ShcGWVApHA9CtfrZECuR+F6FNxkQI/C9ShcuWRA16NwPQqnZECuR+F6FNJkQArXo3A9wmRA16NwPQrTZEDD9Shcj+JkQEjhehSuy2RArkfhehTiZEBcj8L1KPRkQPYoXI/CQ2VAuB6F61EWZUDhehSuRw9lQKRwPQrXA2VAFK5H4XoEZUDsUbgehR1lQBSuR+F6JmVApHA9CtcdZUA9CtejcAllQNejcD0K+2RAmpmZmZkHZUA9CtejcN9kQNejcD0K+2RAKVyPwvX+ZEB7FK5H4fpkQAAAAAAA+GRAXI/C9Sj6ZEBI4XoUriNlQK5H4XoUNGVAmpmZmZlPZUDNzMzMzFRlQEjhehSuW2VACtejcD1cZUAK16NwPUZlQGZmZmZmUGVA7FG4HoVJZUAAAAAAAEJlQMP1KFyPRGVAj8L1KFxBZUDXo3A9ClllQDMzMzMzSWVA9ihcj8JFZUDhehSuRzFlQEjhehSuNWVAUrgehes/ZUCPwvUoXD9lQK5H4XoUNGVAMzMzMzM5ZUAUrkfhelJlQOF6FK5HXWVAXI/C9ShaZUDhehSuR0tlQK5H4XoUTmVAKVyPwvU8ZUAUrkfhek5lQHsUrkfhXmVAuB6F61FuZUC4HoXrUWplQIXrUbgeZ2VAAAAAAAByZUD2KFyPwjtlQFK4HoXrRWVAcT0K16M8ZUCPwvUoXGFlQIXrUbgeeWVAZmZmZmZoZUDNzMzMzExlQHsUrkfhUGVAmpmZmZk5ZUA9CtejcEdlQArXo3A9QmVAAAAAAAAaZUDXo3A9ChtlQD0K16NwB2VAKVyPwvUcZUCuR+F6FBRlQIXrUbgeIWVAKVyPwvUmZUCF61G4HiFlQK5H4XoUGmVA4XoUrkcLZUApXI/C9RxlQHsUrkfhJmVAH4XrUbgoZUDXo3A9Ci1lQFyPwvUoJmVAmpmZmZkhZUB7FK5H4QxlQOxRuB6FL2VAUrgehes7ZUDhehSuR01lQHE9CtejemVA9ihcj8KHZUApXI/C9W5lQB+F61G4cGVAFK5H4XpgZUApXI/C9UhlQEjhehSuXWVAcT0K16NOZUAzMzMzM1VlQDMzMzMzU2VAKVyPwvVmZUAUrkfhemplQLgehetRXGVASOF6FK51ZUCuR+F6FGxlQBSuR+F6dGVAMzMzMzNjZUAUrkfhemJlQHsUrkfhcGVArkfhehR2ZUDsUbgehXNlQMP1KFyPYmVA9ihcj8J5ZUCF61G4Hm9lQOxRuB6FdWVApHA9CtdxZUCF61G4HmVlQEjhehSub2VAzczMzMx2ZUBI4XoUrotlQOF6FK5He2VArkfhehSIZUB7FK5H4YRlQK5H4XoUgmVAFK5H4XpwZUBSuB6F60tlQDMzMzMzUWVAKVyPwvVEZUDNzMzMzFBlQBSuR+F6VGVAcT0K16NOZUBxPQrXo0ZlQHsUrkfhQmVASOF6FK5RZUAUrkfhelhlQMP1KFyPTmVA4XoUrkdPZUAzMzMzM1tlQIXrUbgeTWVA9ihcj8JTZUB7FK5H4VplQKRwPQrXW2VASOF6FK5LZUCkcD0K109lQB+F61G4VmVA7FG4HoU3ZUAK16NwPSxlQK5H4XoUFmVAuB6F61EkZUDsUbgehTllQAAAAAAAIGVApHA9CtcrZUDD9ShcjyRlQDMzMzMzD2VArkfhehQGZUCPwvUoXBFlQFK4HoXrE2VAPQrXo3AFZUD2KFyPwgtlQIXrUbgeD2VAMzMzMzMPZUCkcD0K1xNlQDMzMzMzE2VAH4XrUbgKZUApXI/C9RZlQJqZmZmZH2VAPQrXo3AtZUDD9ShcjyRlQM3MzMzMJmVA4XoUrkcxZUDhehSuRy9lQMP1KFyPKGVAMzMzMzMzZUA9CtejcDdlQDMzMzMzOWVApHA9CtdLZUBSuB6F61FlQD0K16NwTWVAKVyPwvVKZUDhehSuR0llQM3MzMzMYGVAuB6F61FYZUBSuB6F61llQClcj8L1dGVAcT0K16OCZUDD9Shcj6ZlQDMzMzMzrWVArkfhehSgZUCamZmZmZ9lQI/C9Shcp2VAexSuR+GUZUAAAAAAAJZlQFK4HoXrjWVAZmZmZmZ4ZUDsUbgehX1lQBSuR+F6eGVAexSuR+F8ZUAAAAAAAHRlQBSuR+F6fGVAZmZmZmZsZUBxPQrXo15lQGZmZmZmXGVACtejcD1GZUAK16NwPTxlQClcj8L1SGVAw/UoXI9OZUDhehSuR0dlQNejcD0KOWVACtejcD02ZUDD9Shcjy5lQPYoXI/CL2VAH4XrUbguZUAfhetRuDRlQEjhehSuJWVApHA9CtctZUCPwvUoXBFlQOxRuB6FEWVAPQrXo3ANZUCuR+F6FAZlQOF6FK5HAWVAzczMzMwIZUCPwvUoXBNlQArXo3A9DGVAcT0K16MIZUDXo3A9CgVlQGZmZmZmAmVArkfhehQGZUAK16NwPQBlQLgehetRAmVAmpmZmZn9ZECkcD0K1wdlQK5H4XoUGmVAH4XrUbggZUDD9ShcjyJlQOF6FK5HI2VAPQrXo3AtZUDhehSuRzVlQAAAAAAAOGVA4XoUrkcrZUBSuB6F6y9lQK5H4XoUNmVASOF6FK4bZUDD9Shcjw5lQLgehetRDGVAAAAAAAAgZUCPwvUoXCVlQEjhehSuE2VAXI/C9SgAZUDXo3A9CgVlQEjhehSuB2VAMzMzMzMZZUApXI/C9SZlQOF6FK5HL2VAUrgehes1ZUC4HoXrUThlQAAAAAAAOmVA7FG4HoUzZUCF61G4HitlQEjhehSuK2VAFK5H4Xo2ZUBxPQrXo0hlQKRwPQrXTWVAKVyPwvVYZUDhehSuR11lQD0K16NwT2VAAAAAAABiZUDD9Shcj2hlQDMzMzMzZWVApHA9CtdtZUAfhetRuH5lQHsUrkfhfmVAZmZmZmaIZUBmZmZmZm5lQOxRuB6FdWVAuB6F61F0ZUBI4XoUroFlQGZmZmZmhmVA7FG4HoVvZUDsUbgehXllQIXrUbgee2VAzczMzMyMZUD2KFyPwo1lQClcj8L1dGVASOF6FK5FZUD2KFyPwkVlQIXrUbgeVWVAUrgehes7ZUAK16NwPUxlQClcj8L1WGVA9ihcj8JXZUBcj8L1KGJlQOxRuB6FVWVA7FG4HoVdZUApXI/C9TZlQBSuR+F6OmVAuB6F61E4ZUBxPQrXoy5lQD0K16NwNWVAexSuR+E6ZUDXo3A9CjNlQB+F61G4LGVAZmZmZmYsZUCamZmZmS1lQI/C9ShcHWVAUrgeheshZUCPwvUoXCVlQB+F61G4KGVAw/UoXI8qZUAfhetRuCxlQEjhehSuOWVAMzMzMzMxZUCF61G4Hh9lQArXo3A9GmVAH4XrUbgeZUD2KFyPwiFlQK5H4XoUImVAXI/C9SgmZUDsUbgehSFlQPYoXI/CMWVA4XoUrkczZUBxPQrXozxlQHE9CtejQGVAXI/C9ShEZUAK16NwPThlQI/C9ShcO2VAAAAAAAAeZUDNzMzMzBRlQJqZmZmZD2VAexSuR+EeZUBSuB6F6yFlQFK4HoXrK2VAmpmZmZktZUDXo3A9CillQLgehetRIGVA7FG4HoUPZUA9CtejcAtlQKRwPQrXDWVAMzMzMzMpZUCF61G4HiVlQB+F61G4HGVAzczMzMwiZUCF61G4HillQI/C9ShcGWVApHA9CtcbZUCF61G4Hh1lQPYoXI/CG2VAKVyPwvUWZUDhehSuRw9lQPYoXI/CD2VACtejcD0OZUAAAAAAABZlQHE9CtejHmVAcT0K16MqZUCPwvUoXDFlQJqZmZmZJWVAUrgehesxZUBmZmZmZjhlQDMzMzMzO2VAUrgehesxZUA9CtejcEVlQOF6FK5HO2VAPQrXo3A3ZUAK16NwPUBlQHsUrkfhPGVAH4XrUbhQZUB7FK5H4VBlQEjhehSuT2VAXI/C9ShMZUBI4XoUrl1lQHE9CtejUGVAhetRuB5NZUA9CtejcEdlQPYoXI/CSWVAexSuR+E+ZUD2KFyPwkVlQM3MzMzMSGVArkfhehREZUA9CtejcEFlQGZmZmZmOmVA4XoUrkcvZUAAAAAAACZlQLgehetRIGVAKVyPwvUcZUDNzMzMzBplQAAAAAAAGGVA16NwPQonZUBxPQrXoyplQNejcD0KHWVAj8L1KFwpZUBcj8L1KDJlQBSuR+F6LmVAZmZmZmYmZUD2KFyPwh1lQAAAAAAAFmVAKVyPwvUQZUC4HoXrUQhlQK5H4XoUCGVACtejcD0KZUApXI/C9fxkQPYoXI/CBWVAH4XrUbgSZUB7FK5H4RRlQClcj8L1FGVAPQrXo3ALZUBmZmZmZgBlQK5H4XoUCGVA9ihcj8IHZUDXo3A9Cv9kQI/C9ShcCWVACtejcD3+ZEBI4XoUrgFlQPYoXI/CCWVAzczMzMwQZUBI4XoUrhllQIXrUbgeK2VAmpmZmZkzZUA9CtejcDFlQAAAAAAAOmVAj8L1KFw3ZUCF61G4HiNlQFK4HoXrJWVAUrgehespZUCF61G4Hh9lQD0K16NwP2VAcT0K16NCZUBmZmZmZkxlQOF6FK5HSWVAPQrXo3BHZUB7FK5H4TRlQB+F61G4PmVAUrgeheszZUDhehSuRy1lQArXo3A9MmVASOF6FK4tZUDNzMzMzERlQOxRuB6FRWVArkfhehRGZUCPwvUoXDtlQK5H4XoUOmVAFK5H4XpKZUBcj8L1KFZlQD0K16NwX2VA9ihcj8JVZUApXI/C9WRlQLgehetRbGVAKVyPwvVoZUCPwvUoXHdlQMP1KFyPdmVAhetRuB5zZUDXo3A9CmNlQIXrUbgeW2VAUrgehetBZUDD9Shcj0RlQOF6FK5HSWVAexSuR+FWZUBSuB6F61dlQHsUrkfhXmVAFK5H4XpcZUCPwvUoXFdlQEjhehSuV2VA4XoUrkdLZUAAAAAAAGJlQIXrUbgeYWVACtejcD1OZUDD9Shcj1JlQIXrUbgeUWVAH4XrUbhOZUCamZmZmVdlQKRwPQrXUWVAj8L1KFxfZUA9CtejcE1lQJqZmZmZRWVAw/UoXI9QZUA9CtejcFNlQI/C9ShcZWVACtejcD14ZUCuR+F6FHplQBSuR+F6fGVAMzMzMzN9ZUAK16NwPXZlQClcj8L1eGVAj8L1KFyPZUAfhetRuJZlQJqZmZmZv2VAFK5H4XrWZUCamZmZmcNlQNejcD0KsWVAKVyPwvWmZUCF61G4HrllQEjhehSurWVAzczMzMzMZUAAAAAAAOBlQOF6FK5H92VAXI/C9SgEZkAUrkfhegZmQMP1KFyPDmZAFK5H4Xr2ZUA9CtejcANmQKRwPQrXCWZAXI/C9Sj8ZUCamZmZmfllQClcj8L1AGZAPQrXo3DtZUAAAAAAAPRlQFyPwvUo7GVAKVyPwvX+ZUDD9ShcjwRmQMP1KFyP+mVAuB6F61HuZUBI4XoUru1lQNejcD0K5WVArkfhehTgZUA9CtejcO9lQGZmZmZm3mVAAAAAAADQZUA9CtejcNNlQD0K16Nw0WVASOF6FK7VZUC4HoXrUeRlQNejcD0K62VApHA9CtflZUAfhetRuO5lQMP1KFyP4mVAhetRuB7pZUC4HoXrUeRlQM3MzMzM2mVAcT0K16POZUDNzMzMzNRlQBSuR+F60mVAuB6F61HKZUCkcD0K181lQB+F61G43mVACtejcD3qZUDNzMzMzOJlQM3MzMzM5mVAmpmZmZnhZUC4HoXrUchlQAAAAAAAvmVAUrgeheu5ZUBcj8L1KKplQAAAAAAArmVAPQrXo3CxZUApXI/C9bJlQAAAAAAAuGVAH4XrUbi8ZUAK16NwPbhlQNejcD0Kt2VAw/UoXI+wZUCamZmZmatlQOxRuB6FuWVAmpmZmZnBZUBmZmZmZsBlQEjhehSux2VAMzMzMzPLZUCamZmZmddlQJqZmZmZ02VAhetRuB7PZUBcj8L1KMZlQOxRuB6F12VAFK5H4Xq8ZUB7FK5H4aplQHsUrkfhuGVAhetRuB63ZUCuR+F6FL5lQFK4HoXrm2VAZmZmZmaUZUBSuB6F65FlQFyPwvUolGVAhetRuB6LZUAzMzMzM39lQKRwPQrXe2VAH4XrUbh2ZUA9CtejcGVlQEjhehSubWVAhetRuB5TZUDNzMzMzE5lQMP1KFyPVmVAhetRuB5VZUBSuB6F60llQAAAAAAAQmVAH4XrUbhYZUBxPQrXo1JlQAAAAAAAQmVApHA9Ctc/ZUApXI/C9ThlQGZmZmZmKGVAZmZmZmYWZUBSuB6F6/9kQLgehetR/mRAhetRuB4TZUBcj8L1KBplQK5H4XoUHGVArkfhehQWZUDsUbgehRllQLgehetRDmVACtejcD3+ZEDNzMzMzP5kQB+F61G4+GRA4XoUrkf9ZEB7FK5H4QZlQB+F61G49mRA4XoUrkfzZEAK16NwPf5kQArXo3A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ugrFnQF2zRO6CsWdAXbNE7oKxZ0Bds0TugrFnQF2zRO6CsWdAXbNE7oKxZ0Bds0TugrFnQF2zRO6CsWdAXbNE7oKxZ0Bds0TugrFnQF2zRO6CsWdAXbNE7oKxZ0Bds0TugrFnQF2zRO6CsWdAXbNE7oKxZ0Bds0TugrFnQF2zRO6CsWdAXbNE7oKxZ0Bds0TugrFnQF2zRO6CsWdAXbNE7oKxZ0Bds0TugrFnQF2zRO6CsWdAXbNE7oKxZ0Bds0TugrFnQF2zRO6CsWdAXbNE7oKxZ0Bds0TugrFnQF2zRO6CsWdAaceUbnaiZ0CiHkPbJpVnQOWWXDJak2dAqZu9o+eHZ0ASDrf3sYNnQEeuX+A4cWdAR65f4DhxZ0BHrl/gOHFnQEeuX+A4cWdAR65f4DhxZ0BHrl/gOHFnQEeuX+A4cWdA6z5vt0tOZ0DrPm+3S05nQOs+b7dLTmdA6z5vt0tOZ0DrPm+3S05nQOs+b7dLTmdA6z5vt0tOZ0DrPm+3S05nQOs+b7dLTmdA6z5vt0tOZ0DrPm+3S05nQOs+b7dLTmdA6z5vt0tOZ0DrPm+3S05nQOs+b7dLTmdA6z5vt0tOZ0DrPm+3S05nQOs+b7dLTmdA6z5vt0tOZ0DrPm+3S05nQOs+b7dLTmdA6z5vt0tOZ0DrPm+3S05nQOs+b7dLTmdA6z5vt0tOZ0DrPm+3S05nQOs+b7dLTmdAU4OI9exAZ0BTg4j17EBnQFxIbM50NGdAWM92Rs0sZ0CxicOIkipnQLGJw4iSKmdAfNTQ4homZ0DaYMisoxNnQJBA/TGrBmdAcvLZ74n8ZkCNeIbRdfRmQHUYM+1P9GZAdKz1PLvkZkCVygjN99FmQJXKCM330WZAlcoIzffRZkCVygjN99FmQJXKCM330WZAlcoIzffRZkCVygjN99FmQJXKCM330WZAlcoIzffRZkCVygjN99FmQJXKCM330WZAV1bYDJdpZkDFp7n7/G5mQMWnufv8bmZAxae5+/xuZkDFp7n7/G5mQMWnufv8bmZAxae5+/xuZkDFp7n7/G5mQMWnufv8bmZAxae5+/xuZkAT+yZMT9dmQDJz7kAN0WZAMnPuQA3RZkAyc+5ADdFmQDJz7kAN0WZAMnPuQA3RZkAyc+5ADdFmQDJz7kAN0WZAMnPuQA3RZkAyc+5ADdFmQDJz7kAN0WZAMnPuQA3RZkAyc+5ADdFmQJu0xVTlZGZAcsu1BFVxZkB3U/7ku39mQHdT/uS7f2ZA49u0fqOBZkBN+C/ztZNmQE34L/O1k2ZATfgv87WTZkCQBf9GWZlmQO28U5p7pmZA7bxTmnumZkDtvFOae6ZmQO28U5p7pmZA7bxTmnumZkDtvFOae6ZmQO28U5p7pmZA7bxTmnumZkDtvFOae6ZmQO28U5p7pmZA7bxTmnumZkDtvFOae6ZmQO28U5p7pmZA7bxTmnumZkDtvFOae6ZmQO28U5p7pmZA7bxTmnumZkDtvFOae6ZmQMpUm/JYBmdAylSb8lgGZ0DKVJvyWAZnQMpUm/JYBmdAylSb8lgGZ0DKVJvyWAZnQMpUm/JYBmdAylSb8lgGZ0DKVJvyWAZnQMpUm/JYBmdAylSb8lgGZ0DKVJvyWAZnQMpUm/JYBmdAylSb8lgGZ0D3SLTADwRnQPdItMAPBGdA90i0wA8EZ0D3SLTADwRnQPdItMAPBGdA90i0wA8EZ0D3SLTADwRnQPdItMAPBGdA90i0wA8EZ0D3SLTADwRnQPdItMAPBGdA90i0wA8EZ0D3SLTADwRnQPSNBFnwAGdA9I0EWfAAZ0D0jQRZ8ABnQPSNBFnwAGdA9I0EWfAAZ0D0jQRZ8ABnQPSNBFnwAGdA9I0EWfAAZ0Dh/RZpxABnQOH9FmnEAGdA4f0WacQAZ0CCxVHOwP1mQLnIChxX8WZAbGn8gyHnZkC9VEQpmttmQL1URCma22ZASJxclUzaZkBc/DQR/dRmQFa4dXYwy2ZAdmivrCPGZkCYrMx0fcFmQG+T5Ofeu2ZAb5Pk5967ZkB3eHdis6pmQIaQVW4ZoWZAhpBVbhmhZkCGkFVuGaFmQIaQVW4ZoWZAhpBVbhmhZkCGkFVuGaFmQIaQVW4ZoWZAhpBVbhmhZkCGkFVuGaFmQIaQVW4ZoWZAJz52euiZZkAnPnZ66JlmQCc+dnromWZAJz52euiZZkAnPnZ66JlmQJi3VRASimZA4cHTmfeIZkA0MV0xpH1mQDQxXTGkfWZANDFdMaR9ZkA0MV0xpH1mQDQxXTGkfWZANDFdMaR9ZkA0MV0xpH1mQDQxXTGkfWZANDFdMaR9ZkA0MV0xpH1mQDQxXTGkfWZANDFdMaR9ZkA0MV0xpH1mQDQxXTGkfWZANDFdMaR9ZkA0MV0xpH1mQKCnZxhWdWZAQpSScSlqZkDsaNtjYWVmQHlA/UVAW2ZACqj43ERUZkAdxRO5YU1mQB3FE7lhTWZAHcUTuWFNZkAdxRO5YU1mQE9zOM62R2ZAT3M4zrZHZkBPQEqZczlmQE9ASplzOWZAT0BKmXM5ZkBPQEqZczlmQE9ASplzOWZAT0BKmXM5ZkBPQEqZczlmQE9ASplzOWZAT0BKmXM5ZkBPQEqZczlmQE9ASplzOWZAT0BKmXM5ZkBPQEqZczlmQE9ASplzOWZAT0BKmXM5ZkBPQEqZczlmQE9ASplzOWZAT0BKmXM5ZkBPQEqZczlmQE9ASplzOWZAT0BKmXM5ZkBPQEqZczlmQE9ASplzOWZAT0BKmXM5ZkBPQEqZczlmQE9ASplzOWZAT0BKmXM5ZkBPQEqZczlmQE9ASplzOWZAT0BKmXM5ZkBPQEqZczlmQE9ASplzOWZAT0BKmXM5ZkBPQEqZczlmQG6j36iE+GVA2wmlkI37ZUDbCaWQjftlQNsJpZCN+2VA2wmlkI37ZUCTSyISUARmQJNLIhJQBGZAk0siElAEZkCTSyISUARmQJNLIhJQBGZAk0siElAEZkCTSyISUARmQJNLIhJQBGZAk0siElAEZkAvv2gSgQpmQC+/aBKBCmZA45REymgiZkCeURT02UNmQMgQiS1PRmZAyBCJLU9GZkDIEIktT0ZmQMgQiS1PRmZAyBCJLU9GZkDIEIktT0ZmQMgQiS1PRmZAyBCJLU9GZkDIEIktT0ZmQMgQiS1PRmZAyBCJLU9GZkDIEIktT0ZmQMgQiS1PRmZAyBCJLU9GZkDIEIktT0ZmQMgQiS1PRmZAyBCJLU9GZkDfup0uK0xmQBohc0V8amZAGiFzRXxqZkAaIXNFfGpmQGLLE/mjeWZAhltGbht+ZkAM4sr9m4lmQAziyv2biWZADOLK/ZuJZkAM4sr9m4lmQAziyv2biWZADOLK/ZuJZkAM4sr9m4lmQAziyv2biWZAxaLVAFLVZkCjtn8fSadmQLdR/BmFemZAZUNTmxp0ZkBlQ1ObGnRmQGVDU5sadGZAZUNTmxp0ZkBlQ1ObGnRmQGVDU5sadGZAZUNTmxp0ZkBlQ1ObGnRmQGVDU5sadGZAZUNTmxp0ZkBbgZQWj1JmQIj+DJR4OmZAG6Ho03wiZkDUVPBocAhmQLi7x0x5/WVANPYmQI/eZUD8XwjfxdxlQLTee4j51mVAtN57iPnWZUC03nuI+dZlQLTee4j51mVAtN57iPnWZUC03nuI+dZlQLTee4j51mVAtN57iPnWZUC03nuI+dZlQLTee4j51mVAtN57iPnWZUC03nuI+dZlQLTee4j51mVApSled0TKZUBTAd1JCb5lQL5Ppcbwt2VAvk+lxvC3ZUC+T6XG8LdlQL5Ppcbwt2VAvk+lxvC3ZUC+T6XG8LdlQNIYfVU1R2VAIiSFUp5SZUAiJIVSnlJlQCIkhVKeUmVAIiSFUp5SZUAiJIVSnlJlQCIkhVKeUmVAIiSFUp5SZUAiJIVSnlJlQCIkhVKeUmVAIiSFUp5SZUAiJIVSnlJlQCIkhVKeUmVAIiSFUp5SZUAiJIVSnlJlQCIkhVKeUmVAIiSFUp5SZUCFiprLElRlQOdwfFFdV2VA2Qu3hIVXZUBFaZjFZmJlQANY2VgAZGVAI+CS7sRqZUDcCUBpfHdlQFbkeSVnf2VAVuR5JWd/ZUAhMN09SoVlQCEw3T1KhWVAITDdPUqFZUAhMN09SoVlQCEw3T1KhWVAITDdPUqFZUB3Kxi+eIplQHayqi33kWVAAisn+g6TZUACKyf6DpNlQAIrJ/oOk2VAAisn+g6TZUACKyf6DpNlQAIrJ/oOk2VAAisn+g6TZUACKyf6DpNlQAIrJ/oOk2VAAisn+g6TZUACKyf6DpNlQAIrJ/oOk2VAAisn+g6TZUACKyf6DpNlQAIrJ/oOk2VAAisn+g6TZUACKyf6DpNlQIsMAdwu22VACH0IayzIZUA3pwpqmbxlQDenCmqZvGVAN6cKapm8ZUACGv09/7plQAIa/T3/umVAuCKjgBS2ZUC4IqOAFLZlQLgio4AUtmVAuCKjgBS2ZUC4IqOAFLZlQLgio4AUtmVAuCKjgBS2ZUC4IqOAFLZlQLgio4AUtmVA9uBqPOyyZUBMJ8qe/pdlQG19JiACc2VAxD0jh25fZUA3J/MSRzhlQEklz0/B/GRAWnPUym7WZEBac9TKbtZkQJM6EdNAImRAFYH30TtHZEBdZSKSZWVkQF1lIpJlZWRAXWUikmVlZEBdZSKSZWVkQF1lIpJlZWRAXWUikmVlZEBdZSKSZWVkQF1lIpJlZWRAXWUikmVlZEBdZSKSZWVkQF1lIpJlZWRAXWUikmVlZEDwPmxR44JkQMjKE7MVimRAyMoTsxWKZEDIyhOzFYpkQMjKE7MVimRAyMoTsxWKZEBv/BA5UpNkQG/8EDlSk2RAb/wQOVKTZEBv/BA5UpNkQG/8EDlSk2RAb/wQOVKTZEBv/BA5UpNkQG/8EDlSk2RAb/wQOVKTZEBv/BA5UpNkQG/8EDlSk2RAJXXLsseTZEBIskMpBrVkQMqabQZ10GRAS94MwTznZEBB1OdEbfJkQBX+gEhW/mRAFf6ASFb+ZEAV/oBIVv5kQBX+gEhW/mRAFf6ASFb+ZEAV/oBIVv5kQBX+gEhW/mRAFf6ASFb+ZEAV/oBIVv5kQBX+gEhW/mRAFf6ASFb+ZEAV/oBIVv5kQBX+gEhW/mRAFf6ASFb+ZEAV/oBIVv5kQBX+gEhW/mRAFf6ASFb+ZEDie3+d+AFlQOnGGFCeBmVA6cYYUJ4GZUDpxhhQngZlQOnGGFCeBmVA6cYYUJ4GZUDpxhhQngZlQHXni76XFmVA/iuqRikeZUD+K6pGKR5lQOFOFeU7JWVA4U4V5TslZUDhThXlOyVlQOFOFeU7JWVA4U4V5TslZUDhThXlOyVlQOFOFeU7JWVA4U4V5TslZUDhThXlOyVlQOFOFeU7JWVA4U4V5TslZUDhThXlOyVlQLBIN6HCiGVABPZ77LJ5ZUCP/xzRO2xlQOF9u4UcamVA4X27hRxqZUDhfbuFHGplQOF9u4UcamVA4X27hRxqZUDhfbuFHGplQLQpl6JRWmVAtCmXolFaZUC0KZeiUVplQLQpl6JRWmVAtCmXolFaZUC0KZeiUVplQLQpl6JRWmVAtCmXolFaZUC0KZeiUVplQLQpl6JRWmVAtCmXolFaZUAcWj35Fg1lQMVwpPdyJWVAxXCk93IlZUDFcKT3ciVlQMVwpPdyJWVAxXCk93IlZUDFcKT3ciVlQMVwpPdyJWVAxXCk93IlZUDFcKT3ciVlQMVwpPdyJWVAxXCk93IlZUDFcKT3ciVlQMVwpPdyJWVAxXCk93IlZUDFcKT3ciVlQMVwpPdyJWVAxXCk93IlZUDFcKT3ciVlQCXkiNwuJmVACwRurv4vZUALBG6u/i9lQAsEbq7+L2VACwRurv4vZUALBG6u/i9lQAsEbq7+L2VACwRurv4vZUALBG6u/i9lQAsEbq7+L2VA44Mb5Wc6ZUBhzhC1jjplQGHOELWOOmVAYc4QtY46ZUBhzhC1jjplQGHOELWOOmVAYc4QtY46ZUBhzhC1jjplQGHOELWOOmVAYc4QtY46ZUBhzhC1jjplQGHOELWOOmVAYc4QtY46ZUBhzhC1jjplQGHOELWOOmVAYc4QtY46ZUBhzhC1jjplQGHOELWOOmVAYc4QtY46ZUBhzhC1jjplQGHOELWOOmVAYc4QtY46ZUBhzhC1jjplQGHOELWOOmVAYc4QtY46ZUBhzhC1jjplQM5Cglt7iGVAd5iITEFtZUB3mIhMQW1lQPa0bhZwaGVA9rRuFnBoZUD2tG4WcGhlQPa0bhZwaGVA9rRuFnBoZUD2tG4WcGhlQPdUNVbDXGVAMWcFE6xXZUAxZwUTrFdlQDFnBROsV2VA1KVSmJtQZUDUpVKYm1BlQNSlUpibUGVA1KVSmJtQZUDUpVKYm1BlQNSlUpibUGVA1KVSmJtQZUDUpVKYm1BlQNSlUpibUGVA1KVSmJtQZUDUpVKYm1BlQNSlUpibUGVA1KVSmJtQZUDUpVKYm1BlQNSlUpibUGVA1KVSmJtQZUDUpVKYm1BlQNSlUpibUGVApb7SmXYOZUCFPHjSHhBlQIU8eNIeEGVAqp1OdnUXZUByn36q0htlQHKffqrSG2VARgjeGUckZUBGCN4ZRyRlQGiCDd0COmVALMbayFxPZUDlYBvljWhlQOVgG+WNaGVA5WAb5Y1oZUDlYBvljWhlQOVgG+WNaGVA5WAb5Y1oZUDlYBvljWhlQOVgG+WNaGVA5WAb5Y1oZUDlYBvljWhlQOVgG+WNaGVA5WAb5Y1oZUDlYBvljWhlQOVgG+WNaGVAO6XQ7OKnZUDVQiCaEp5lQKWChDrvkWVAo4nnQtCBZUCjiedC0IFlQKOJ50LQgWVAo4nnQtCBZUBygYO0BH5lQKNU6brLd2VAWt4kk15zZUABua/t13FlQByjMImCcGVAHKMwiYJwZUBMfrM3UmllQI4EoOspZ2VAfzme64FdZUAV8pCiXk5lQPqNPVhnR2VAHde7Nw9EZUD2XiO5+T5lQNa2MKE5PGVA1rYwoTk8ZUDWtjChOTxlQNa2MKE5PGVAEHtQJmc5ZUAQe1AmZzllQBB7UCZnOWVAEHtQJmc5ZUBf06E3vjRlQBGuwPNtNGVAEa7A8200ZUARrsDzbTRlQBGuwPNtNGVAEa7A8200ZUARrsDzbTRlQBGuwPNtNGVAKt0QBGb+ZECGttXazwFlQIa21drPAWVAhrbV2s8BZUCGttXazwFlQIa21drPAWVAhrbV2s8BZUCGttXazwFlQIa21drPAWVAhrbV2s8BZUCGttXazwFlQCSOrX1sRGVAwqR4Fig6ZUDCpHgWKDplQMKkeBYoOmVAwqR4Fig6ZUDCpHgWKDplQMKkeBYoOmVAwqR4Fig6ZUDCpHgWKDplQMKkeBYoOmVAwqR4Fig6ZUDCpHgWKDplQMKkeBYoOmVAaeK5m5oJZUCDlIa1IRxlQIOUhrUhHGVA6jSotJ0mZUDqNKi0nSZlQOo0qLSdJmVAgj3efoQtZUCCPd5+hC1lQII93n6ELWVAdDSmunkzZUCg21bQpDxlQESuh3DQRWVARK6HcNBFZUBErodw0EVlQESuh3DQRWVARK6HcNBFZUBErodw0EVlQESuh3DQRWVARK6HcNBFZUBErodw0EVlQESuh3DQRWVA/AdXmAFJZUD8B1eYAUllQCBd1b6PqWVAhPCTKYaUZUCE8JMphpRlQN0xYKIkkmVAve9DRF6LZUC970NEXotlQL3vQ0Rei2VAve9DRF6LZUC970NEXotlQL3vQ0Rei2VAve9DRF6LZUD8B8C+8nxlQIvgTiHQe2VAzIVF/MR3ZUD91j6NDnVlQP3WPo0OdWVA/dY+jQ51ZUDAnQCMZnBlQDcSa5T2aGVANxJrlPZoZUCq2Qq7e19lQKrZCrt7X2VAr2cIO69eZUCvZwg7r15lQK9nCDuvXmVAr2cIO69eZUCvZwg7r15lQK9nCDuvXmVAGHe+rWdcZUDmDncET1JlQNWKnWwfUWVA1YqdbB9RZUDVip1sH1FlQNWKnWwfUWVA1YqdbB9RZUDVip1sH1FlQNWKnWwfUWVA1YqdbB9RZUDVip1sH1FlQNWKnWwfUWVA1YqdbB9RZUDVip1sH1FlQNWKnWwfUWVAWvWF60xPZUB8a7hlU0hlQHxruGVTSGVAfGu4ZVNIZUB8a7hlU0hlQHxruGVTSGVAfGu4ZVNIZUB8a7hlU0hlQHxruGVTSGVARpZIC/xAZUBGlkgL/EBlQEaWSAv8QGVARpZIC/xAZUBGlkgL/EBlQEaWSAv8QGVARpZIC/xAZUBGlkgL/EBlQEaWSAv8QGVARpZIC/xAZUBGlkgL/EBlQEaWSAv8QGVARpZIC/xAZUBGlkgL/EBlQEaWSAv8QGVARpZIC/xAZUBGlkgL/EBlQEaWSAv8QGVARpZIC/xAZUBGlkgL/EBlQEaWSAv8QGVARpZIC/xAZUBGlkgL/EBlQEaWSAv8QGVAdf6+IqIMZUBMjfUv8A5lQEyN9S/wDmVATI31L/AOZUB4g2QYlA9lQHGoc9D4F2VANCtnkWgfZUB4Lr+lHCBlQHguv6UcIGVA/ClTPB8lZUCHYIqJLSVlQIdgioktJWVAh2CKiS0lZUCHYIqJLSVlQIdgioktJWVAh2CKiS0lZUCHYIqJLSVlQIdgioktJWVAh2CKiS0lZUCHYIqJLSVlQIdgioktJWVAh2CKiS0lZUB9vta5HEplQN/RA+KdSWVA39ED4p1JZUD+zmEMukhlQP7OYQy6SGVA/s5hDLpIZUD+zmEMukhlQP7OYQy6SGVA/s5hDLpIZUD+zmEMukhlQP7OYQy6SGVA/s5hDLpIZUD4duRqPEhlQA0MP3jmPWVADQw/eOY9ZUDVPRQqwTllQNU9FCrBOWVAT5k/Jkk1ZUDOZssneDBlQM5myyd4MGVAzmbLJ3gwZUDOZssneDBlQM5myyd4MGVAzmbLJ3gwZUDOZssneDBlQM5myyd4MGVA5c6xdJUuZUDlzrF0lS5lQOXOsXSVLmVAXkTDz04tZUBeRMPPTi1lQF5Ew89OLWVAXkTDz04tZUBeRMPPTi1lQKPxCtab+mRAIu39CQAAZUBaXmDEAgZlQJ6oBp5nCGVAnqgGnmcIZUCeqAaeZwhlQJ6oBp5nCGVAnqgGnmcIZUCeqAaeZwhlQJ6oBp5nCGVAr0PJVXsRZUCZUaUhghZlQJlRpSGCFmVAmVGlIYIWZUCZUaUhghZlQJlRpSGCFmVAmVGlIYIWZUCZUaUhghZlQJlRpSGCFmVAmVGlIYIWZUCZUaUhghZlQGPvWWPfFmVAY+9ZY98WZUBj71lj3xZlQGPvWWPfFmVAmZ8TXoYhZUCnMkaIuyplQKcyRoi7KmVAYpBl6FotZUBJnfPafzhlQEmd89p/OGVAB29fnns9ZUB909yV0UNlQLML6PCmRmVAswvo8KZGZUCzC+jwpkZlQI0OgyA/hGVAo/O/9oN7ZUBX/eQNIXplQFf95A0hemVAV/3kDSF6ZUBX/eQNIXplQFf95A0hemVAV/3kDSF6ZUBX/eQNIXplQFf95A0hemVAV/3kDSF6ZUBX/eQNIXplQFf95A0hemVAV/3kDSF6ZUBX/eQNIXplQFf95A0hemVAV/3kDSF6ZUBX/eQNIXplQFf95A0hemVAV/3kDSF6ZUBX/eQNIXplQFf95A0hemVAV/3kDSF6ZUBX/eQNIXplQFf95A0hemVAV/3kDSF6ZUCRejw9AkZlQMgrmNohRmVAycGQODpHZUDJwZA4OkdlQMM6wv+nSmVAeFHTutJYZUBhzLKRanRlQDmoq0EFg2VAyC9mJQ+LZUDIL2YlD4tlQMgvZiUPi2VAyC9mJQ+LZUDIL2YlD4tlQMgvZiUPi2VAyC9mJQ+LZUDA65qsaJplQJUBlLX+s2VAz1a97SC6ZUB1Y80EcsJlQHVjzQRywmVAdWPNBHLCZUB1Y80EcsJlQHVjzQRywmVAdWPNBHLCZUB1Y80EcsJlQHVjzQRywmVAdWPNBHLCZUB1Y80EcsJlQHVjzQRywmVAdWPNBHLCZUB1Y80EcsJlQHVjzQRywmVAdWPNBHLCZUB1Y80EcsJlQHVjzQRywmVAdWPNBHLCZUB1Y80EcsJlQHVjzQRywmVAdWPNBHLCZUB1Y80EcsJlQHVjzQRywmVAdWPNBHLCZUB1Y80EcsJlQHVjzQRywmVAdWPNBHLCZUB1Y80EcsJlQHVjzQRywmVAdWPNBHLCZUB1Y80EcsJlQHVjzQRywmVAdWPNBHLCZUB1Y80EcsJlQHVjzQRywmVAdWPNBHLCZUB1Y80EcsJlQHVjzQRywmVAdWPNBHLCZUB1Y80EcsJlQHVjzQRywmVAdWPNBHLCZUASM2B2sPVlQBIzYHaw9WVARhLA9RLvZUDpCv9xI+plQOkK/3Ej6mVAlY7w0FvnZUCVjvDQW+dlQJWO8NBb52VAlY7w0FvnZUCVjvDQW+dlQJWO8NBb52VAR/RMmWrbZUBH9EyZattlQEf0TJlq22VAR/RMmWrbZUBH9EyZattlQEf0TJlq22VAR/RMmWrbZUBH9EyZattlQEf0TJlq22VAR/RMmWrbZUBH9EyZattlQEf0TJlq22VAR/RMmWrbZUBH9EyZattlQEf0TJlq22VAR/RMmWrbZUBH9EyZattlQFLuchetzWVAqUulC1PLZUCpS6ULU8tlQKlLpQtTy2VArOW2E2HCZUAX2bDXq7RlQBfZsNertGVAUtn0OYusZUBS2fQ5i6xlQLtWjrM4p2VA0xI5X1aXZUBY64lK35NlQBHfP42PkmVAEGckWM6PZUBRnktFwYZlQFGeS0XBhmVAUZ5LRcGGZUBRnktFwYZlQKI7eUr0gmVAojt5SvSCZUAz10myNGllQDPXSbI0aWVASnwwhKxZZUBo2sbhflRlQGjaxuF+VGVAaNrG4X5UZUBo2sbhflRlQGjaxuF+VGVAaNrG4X5UZUBo2sbhflRlQPI3H4N3SWVAOe0FpHM6ZUA57QWkczplQDntBaRzOmVAOe0FpHM6ZUA57QWkczplQMjjR4e5M2VAyONHh7kzZUDI40eHuTNlQMjjR4e5M2VAUQdRcncxZUB8FCZFnzBlQHwUJkWfMGVA1HGz1mowZUDUcbPWajBlQNRxs9ZqMGVAuJ/07N0qZUAm0cAEdSllQE9kDfThE2VAT2QN9OETZUBPZA304RNlQE9kDfThE2VAT2QN9OETZUBPZA304RNlQE9kDfThE2VAT2QN9OETZUBPZA304RNlQE9kDfThE2VAT2QN9OETZUBPZA304RNlQE9kDfThE2VAT2QN9OETZUBPZA304RNlQE9kDfThE2VAT2QN9OETZUBPZA304RNlQFuxJUqlDGVAW7ElSqUMZUBbsSVKpQxlQFuxJUqlDGVAW7ElSqUMZUBbsSVKpQxlQFuxJUqlDGVAW7ElSqUMZUBbsSVKpQxlQFuxJUqlDGVAz5r1hvYKZUDb2NQUAgBlQL1KxfbJ9GRAvUrF9sn0ZEC9SsX2yfRkQNzNhqq972RAduo6IgviZEAJgPcurNNkQCjM+jGZ0WRADFTYqB3QZEBmBd0M1sZkQGYF3QzWxmRAZgXdDNbGZEBmBd0M1sZkQGYF3QzWxmRAZgXdDNbGZEBmBd0M1sZkQGYF3QzWxmRAqrJs6E3EZEDHblZqWMJkQMduVmpYwmRAE+bpY8DAZEAT5uljwMBkQBPm6WPAwGRAE+bpY8DAZEAT5uljwMBkQBPm6WPAwGRAE+bpY8DAZEAT5uljwMBkQBPm6WPAwGRAQZCmqOKCZEBBkKao4oJkQEGQpqjigmRAQZCmqOKCZEBBkKao4oJkQEGQpqjigmRAQZCmqOKCZEBBkKao4oJkQEGQpqjigmRAQZCmqOKCZEBBkKao4oJkQEGQpqjigmRAQZCmqOKCZEBBkKao4oJkQEGQpqjigmRAQZCmqOKCZECljiuQvo5kQKWOK5C+jmRApY4rkL6OZECljiuQvo5kQKWOK5C+jmRApY4rkL6OZECljiuQvo5kQKWOK5C+jmRApY4rkL6OZECljiuQvo5kQM856nqcj2RAX6vAHhWbZEDh1Zd77Z1kQLFKX4KQoGRAevSuMvinZEB69K4y+KdkQA9sgUnzsGRABMGhfoOzZEAEwaF+g7NkQATBoX6Ds2RABMGhfoOzZEA5Trs0YrhkQPKpxMhSvGRASrsihma/ZECC6YookMZkQARddc6fzGRA1h74L/rUZEDWHvgv+tRkQNYe+C/61GRAr+xdrW4ZZUCv7F2tbhllQPiOdkDnEGVA+I52QOcQZUBXksFAdw1lQFeSwUB3DWVAV5LBQHcNZUBXksFAdw1lQCuiyZ8TAWVABYn14rjpZEAFifXiuOlkQAWJ9eK46WRABYn14rjpZEAFifXiuOlkQAWJ9eK46WRABYn14rjpZEBibjxmo+hkQCZe0zeMy2RAK0g3jjzAZEArSDeOPMBkQDVOg72+o2RAP6kb19ScZECR8Ffh7JRkQJHwV+HslGRAkfBX4eyUZECR8Ffh7JRkQJHwV+HslGRAkfBX4eyUZECR8Ffh7JRkQJHwV+HslGRA2pAWCo6AZEDutPegamVkQIrFuBzSPGRAisW4HNI8ZEA1xjLN2SlkQDXGMs3ZKWRANcYyzdkpZEA1xjLN2SlkQDXGMs3ZKWRA8/T4kLsoZEBxeftcWB9kQHF5+1xYH2RAcXn7XFgfZEBxeftcWB9kQHF5+1xYH2RAcXn7XFgfZEBxeftcWB9kQHF5+1xYH2RAcXn7XFgfZEBxeftcWB9kQHF5+1xYH2RAcXn7XFgfZEAJcSn7mR1kQPRDIwlICWRA9EMjCUgJZED0QyMJSAlkQPRDIwlICWRA9EMjCUgJZED0QyMJSAlkQPRDIwlICWRA9EMjCUgJZED0QyMJSAlkQOzw1eTcBmRA7PDV5NwGZEDs8NXk3AZkQOzw1eTcBmRA7PDV5NwGZEDs8NXk3AZkQOzw1eTcBmRA7PDV5NwGZEA2Ua2eVQRkQIaVNqc27WNAty6EvTXsY0C3LoS9NexjQKQAAKZg52NApAAApmDnY0CkAACmYOdjQKGoPqMB4mNAIvZOJDjOY0Ai9k4kOM5jQA2SBl+nsmNASCN4Xc2ZY0B9Ko5WsXBjQDS/apYoTGNAAR9cmYtHY0AxNjUShyxjQDE2NRKHLGNAMTY1EocsY0AxNjUShyxjQDE2NRKHLGNADXzts6iZYkCw4QMP8LtiQLDhAw/wu2JA\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1500]},\"Volume\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1500]},\"datetime\":{\"__ndarray__\":\"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55VCy8D/LWUXe/q7wPzh4ceaIo/A/0LO101Gm8D9hurYW8qLwPyuX2IA5ufA/d/8PIBm+8D8jpdphM83wP3kYAAlPyvA/oEFVUIK98D/dWPaDRsLwPyvu5Z3PwvA/HsoHrV2+8D8vhnPHgrfwP8ywUvuUuPA/N1DhwqHE8D+3mnbrHMjwP5xSugk5v/A/IxCwED3G8D+fa6rybsvwP3WAct+b1fA/i4KGXaDW8D+rJLM019bwP5vTHMm71vA/dRWdMJLc8D98iP0OG+DwP+8FwmO66PA/DqjuOvHo8D+3NMmT1evwP9fW9WoM7PA/7dgJ6RDt8D92r+/YSgDxP3lHfQL+9PA/avbmluL08D89m7F9Q+nwP3zfCiyx6fA/4c0b4dT08D8ohdVty/jwPxn2Ic5P+/A/hFJrCjrt8D/9gK1xwvbwP2ZeWW0vAPE/GYtMH0YC8T/thiQjPQDxP+fVphBU//A/HlCSw6Ly8D+W/zbqrRPxP81lWguJF/E/X4VLN18g8T+9a9G8AyHxP6MjFdsfGPE/E8YGe+kR8T+KMmYW0hjxP/4uyKvuCfE/u/vTtjcL8T8o3OKKYQLxP+Q9GeegCvE/JVgd8yH98D8/oNnUBQbxP51yl8g2F/E/TMS3xXcK8T9ozlZz+xXxP17XMP0yDfE/E8YGe+kR8T8jbqoDmxvxP6TRLxVMK/E/MemVEaMp8T+uXYDcCjvxP0JTHGb0NfE/qzDIYWE/8T8nNbUm/TrxP0WA1OCdMfE/d6BPnpkt8T9UvaK6RULxP5I/GZ0TQPE/Z5L+vaBH8T/7HMWYgEnxPwHiCj3dOfE//IeaR4pC8T9/E7B8IjHxP5I/GZ0TQPE/rl2A3Ao78T+eDOpw7zrxP2poqRu0OfE/LI8lHFAy8T8Bi/0fRzDxP3MIwnTmOPE/tuSoTAcu8T8G5W0VmifxP5AmKbTdM/E/Xhp2iFUn8T+FLwM+FSvxPzUvPnWCMfE/ngzqcO868T9gyJDCgTrxP9q4tfWpRvE/jxJhImpE8T+yTBsjVDnxP1eTTRhZNPE/ZuTjg3Q08T8TCUwGDCzxP1R6XS8jKPE/s7fw0V0y8T94YjJqOTDxPwA08AKxJvE/TV4KbjAu8T9TI1ASjR7xP/XR9N3eJPE/LA7DXM0a8T+9a9G8AyHxP63DLTRSF/E/hwWumygd8T+keiL4tSHxP0mDN7laH/E/G/tJJRIY8T9l37ssshfxP2tSHAs7G/E/crG0V1Av8T/5F51BvizxP+I/3mWmOfE/vQD8Dfon8T++wt7ZmSrxPzFUa8CsIvE/qCZ4s9wF8T/BrFHJIAzxPyqexVYBBfE/UMLyRnLb8D/wcJcSxOHwP9XRzRNKz/A/xAGaZ7Hm8D8GyritXuzwP3lbRZRx5PA/NhSJDUf28D9IO8rWdejwPzhBQYjw8fA/zo3qLnD28D/gdg7EPuvwP+UOnO3x3/A/soNLgezq8D+JQQZRg+vwP2SwPjMD7fA/a7jJYoL38D8l7UdEGATxP2Tzg74lB/E/PdnOsaPm8D93qAIDg7TwPyXmWm5QuPA/Mgo5X8K88D+PLtwYx7rwP529j7hCuPA/osDykP+l8D/qOY/plazwP0e1P8AwtPA/6uepI8K/8D/sUn/Sy7jwP4+F6TVdxPA/UwNzU4/G8D98WYAVbLXwP4H2NZbhxvA/wlpsA00f8T8BHGV/DDTxPyAjbWOrG/E/kK92OYn98D955aI1WU7xPwbVLoGuKPE/LkpCRw848T/QZe0lOzzxP1UeFo/vR/E/557ndL0p8T+J19PYZy/xP+mW6oK5LfE/9ffVi08H8T9SAWkkpgDxPwaohzJd6fA/k7RUAzHF8D802PzTYMXwP4vUSMtAtfA/PWYjRn2Y8D86Ud+yApPwPwVen16NqPA/89IrLwLE8D+ibAOcQqPwP/L3aaaEwfA/l+bZGyrM8D9u9cROy7rwP8jM0s4orfA/cI4H20e+8D+L1EjLQLXwP3HIieVEwfA/Mp56yWPC8D9yacljxcDwP8GFCSO1oPA/vHjCgT6X8D8YZRSVFo/wP141rd7qmvA/W6RnRHKT8D9IPjKMaazwP++gphYJvfA/uFajMhjO8D+/uq1jCtzwP+w8CMvh9PA/5+1BLWrs8D8fOEURW9vwPwZmCDZc6vA/QkFRtMXg8D8B+gATZuDwP99PtfF62/A/mt7cKSbQ8D/xViooBMLwP01ourJet/A/KGerAfit8D+IYES2Rq/wPwzCqY9/tvA/92NxyXrL8D9bMM8UQ9PwPz00ChNP1/A/AZtAkebf8D8KHIxHV+/wPwB+/wto3vA/h5Xo9pvq8D/FYDeR/ejwPybezj5O6PA/jX3xIJD28D9upmqWHvjwPxBjVfPK+/A/1ChM8+EE8T+TBjrJBALxPzEy34s4/vA/sER+x/n88D+s9bcpgvTwP+gKg7Lo7fA/LOMY7sD18D/zg9F2VQHxP5wgyAvyFPE/2DWTlFgO8T8SW1gBx//wPy/4XIE7+/A/d2E4V4wK8T+z+gHZ9AHxP5FIucUFAfE/V8wwyRsL8T/S0YhjZgDxP0/sJJEr+/A/BsXIt9vq8D+sVHirAfXwP4OApGMh5fA/PHaJD1DW8D/BlW/sh97wPx4bBIzc2fA/vxlu5Ync8D9ack4RRNLwPxYet85tyPA/Sy44qGG08D8wBTg9577wP7c5Yq2ZzPA/lXLVBjDG8D+LtwdGwrPwP+fAmt4YrfA/y0DX4yKz8D/SRSGTlcDwPwjSo3OHrvA/dhdQg7zJ8D87m8eG0tPwPzKeesljwvA/jPGJUL+28D+iDUMaw6LwP0Wl7//sqPA/X5RtYGqb8D8GrfkWOmvwPzaT8sk4TPA/V+Z6W6hM8D8YaoZ58xDwP3vbnDmRtu8/K/F1rc+X7z9XGJSO1g3wPz4UPoCpW/A/d5jDbpdN8D8pFcY7JHHwP3eYw26XTfA/kaSCVJNB8D8iX9ZEXibwP7y/s2IcGPA/rEmExgs58D8GnZNNZy3wP81ajVt6OvA/1EKWhW5G8D9Kt6iFQDTwP5P7ReQORvA/WnfA9SBU8D96mC9UYpPwPwdGPKO2bvA/BTH4Dzxp8D/gjqngVGDwP4EREjMEYfA/y3LwFlF08D/PAzaxyXvwP0ui0NeQdPA/Is78j7Bk8D+ddJSoe1nwPwO98/pBY/A/snMM7QBE8D+ddJSoe1nwP1/GhpOYXPA/3VwkyFtZ8D9csUIAHlfwP/3xK1bMWPA/oj9cTfFj8D+Th62034XwP598/X9Km/A/wWjInTaf8D9Drezx8KTwPwQkHVSQpfA/Ow9gtgGU8D9e8y3i6ZvwPxz2WS+PlvA/2ZnF+rSQ8D/5CY8Ro5LwP5lSdVlVkPA/4vXSOaOi8D9cParQ7pbwP/vHDxWik/A/8ucD3bGD8D8UdQ55HofwPxhlFJUWj/A/mNZzUleO8D+Th62034XwP5V/sMLbifA/4D9PKKid8D+EU/0U0KXwPyKc41yCo/A/XPsq1O2X8D/9mtSrG5rwP7et+tzIjPA/XdbsXGua8D/FWM65LqfwP6pMD9Qys/A/6Poc6RWw8D/oH1tgmK3wP+xuIf4PtvA/l/uxydmL8D+733/1wZPwPxeKUgyZjPA/5ciX0Byp8D/Pj52BmrvwP+jd22OXrvA/Xbmr1+yY8D+fOn6DSZzwPzYCGRWLivA/PM3guQCV8D95vW3L5JDwP2lcFt2DcfA/qgInAGNy8D8isbsKMmPwP6ofaIXhc/A/h/kaXfhs8D8sicpQHnfwPw7sxdCpe/A/LInKUB538D8JPj+xsnLwP0PfBSUfZvA/6gf4pMFz8D+PvOUPanvwP1DxlnUIffA/kXJpIWWA8D/NpHUvSnvwP23QGvJ9d/A/xMxm6V1n8D+y4jI4U4LwP1a0YSh6i/A/PSSkSXyZ8D9wccZVybzwPxW/9kzux/A/Kb5ukXOy8D/ssKD6ELXwP8V1Dz+tqPA/+6LRnR+W8D+kpoWmP6bwPx7uXD2LmvA/4LtQL6af8D//kte5F57wPycI6394rfA/qBKNyTWw8D/D3MyyMKXwPy2RMyjtuPA/SvS1nWSx8D8M3+oU/rfwPwbaoGWLqvA/JW+o8/up8D+syBDbMLXwP43MS9k8ufA/jVBK0j638D8Ge+DjC6rwP8/uXQMavPA/a8M/NtKz8D9uecNHzbjwPyxXsR3wtfA/J+up+vmr8D+LFsjHQbTwP243REvMufA/1lJoNAzK8D/vQeaUibzwP3Q8jvo+x/A/dGHMccHE8D/SwSKak8LwP0uN+CnhtPA/XVrrVW2Y8D8fal5EiZzwP/poT5Mik/A/vy5Gkzmc8D8AUVi9Fp/wPx7uXD2LmvA/m0p4Z1GU8D96HC5NZJHwP1+xruXonPA/waJKqDOi8D8+4iRNe5rwPx5NHb8Km/A/gza8j1Gk8D9+DDRpXJnwPyDmX0uHnvA/AwfczhGk8D+DlXwR0aTwP702Q4U9mPA/PqClUHqb8D/B5MmkNKHwP9Qtvte+hvA/0Ps4v8V/8D9nIpTShm7wPy1kjNmbefA/Fq+QgxuK8D8qT0hGIXTwP3DAIA52f/A/rpNsmtt58D8lJcAfLGnwP2HbyiYTYvA/pXHhZepq8D8nvgKsqGzwPwFB8vNDYfA/hCZWxn5m8D9ly9BCC2rwPyUlwB8safA/59VyjMhs8D/Ggur6WGzwP4Jo1cJ/ZfA/CKX8JDZv8D+Mp6F873XwP/CtgdK0gPA/7Xv8ubt58D9O1FXwiXvwP5NqbC9hhPA/Eb+KZyOC8D+P2SaV6HzwP/MERWIwhfA/VHrfHX2I8D+Vf7DC24nwP31Os2VdmPA/4D9PKKid8D/9OxQqnJnwP9zLShOul/A/fNKxXl+W8D9Fpe//7KjwPwGL2scTovA/gng7jFKj8D9NJju2XbjwP/MUqysDw/A/AZtAkebf8D+DwiNgIuTwPx4bBIzc2fA/vt/r2ozZ8D+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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1500]},\"ohlc_low\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1500]}},\"selected\":{\"id\":\"1820\"},\"selection_policy\":{\"id\":\"1821\"}},\"id\":\"1751\",\"type\":\"ColumnDataSource\"}],\"root_ids\":[\"2294\"]},\"title\":\"Bokeh Application\",\"version\":\"2.3.3\"}};\n",
" var render_items = [{\"docid\":\"b845e20f-cae0-40db-a31c-27fc942e13e8\",\"root_ids\":[\"2294\"],\"roots\":{\"2294\":\"ccfa1f3f-1567-4c19-91a6-ab69e50326ff\"}}];\n",
" root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
"\n",
" }\n",
" if (root.Bokeh !== undefined) {\n",
" embed_document(root);\n",
" } else {\n",
" var attempts = 0;\n",
" var timer = setInterval(function(root) {\n",
" if (root.Bokeh !== undefined) {\n",
" clearInterval(timer);\n",
" embed_document(root);\n",
" } else {\n",
" attempts++;\n",
" if (attempts > 100) {\n",
" clearInterval(timer);\n",
" console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
" }\n",
" }\n",
" }, 10, root)\n",
" }\n",
"})(window);"
],
"application/vnd.bokehjs_exec.v0+json": ""
},
"metadata": {
"application/vnd.bokehjs_exec.v0+json": {
"id": "2294"
}
}
},
{
"output_type": "execute_result",
"data": {
"text/html": [
"<div style=\"display: table;\"><div style=\"display: table-row;\"><div style=\"display: table-cell;\"><b title=\"bokeh.models.layouts.Row\">Row</b>(</div><div style=\"display: table-cell;\">id&nbsp;=&nbsp;'2294', <span id=\"2632\" style=\"cursor: pointer;\">&hellip;)</span></div></div><div class=\"2631\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">align&nbsp;=&nbsp;'start',</div></div><div class=\"2631\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">aspect_ratio&nbsp;=&nbsp;None,</div></div><div class=\"2631\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">background&nbsp;=&nbsp;None,</div></div><div class=\"2631\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">children&nbsp;=&nbsp;[GridBox(id='2291', ...), ToolbarBox(id='2293', ...)],</div></div><div class=\"2631\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">cols&nbsp;=&nbsp;'auto',</div></div><div class=\"2631\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">css_classes&nbsp;=&nbsp;[],</div></div><div class=\"2631\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">disabled&nbsp;=&nbsp;False,</div></div><div class=\"2631\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">height&nbsp;=&nbsp;None,</div></div><div class=\"2631\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">height_policy&nbsp;=&nbsp;'auto',</div></div><div class=\"2631\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">js_event_callbacks&nbsp;=&nbsp;{},</div></div><div class=\"2631\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">js_property_callbacks&nbsp;=&nbsp;{},</div></div><div class=\"2631\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">margin&nbsp;=&nbsp;(0, 0, 0, 0),</div></div><div class=\"2631\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">max_height&nbsp;=&nbsp;None,</div></div><div class=\"2631\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">max_width&nbsp;=&nbsp;None,</div></div><div class=\"2631\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">min_height&nbsp;=&nbsp;None,</div></div><div class=\"2631\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">min_width&nbsp;=&nbsp;None,</div></div><div class=\"2631\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">name&nbsp;=&nbsp;None,</div></div><div class=\"2631\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">sizing_mode&nbsp;=&nbsp;'stretch_width',</div></div><div class=\"2631\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">spacing&nbsp;=&nbsp;0,</div></div><div class=\"2631\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">subscribed_events&nbsp;=&nbsp;[],</div></div><div class=\"2631\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">syncable&nbsp;=&nbsp;True,</div></div><div class=\"2631\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">tags&nbsp;=&nbsp;[],</div></div><div class=\"2631\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">visible&nbsp;=&nbsp;True,</div></div><div class=\"2631\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">width&nbsp;=&nbsp;None,</div></div><div class=\"2631\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">width_policy&nbsp;=&nbsp;'auto')</div></div></div>\n",
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"text/plain": [
"Row(id='2294', ...)"
]
},
"metadata": {},
"execution_count": 19
}
]
},
{
"cell_type": "markdown",
"source": [
"#### 【ポイント3】想定通り動作したかの確認\n",
"\n",
"- `Backtest`インスタンスには、バックテストの過程で使った値が保管されている。この例では、`bt._results[\"_strategy\"].変数名` でバックテストの実行時に使った値にアクセスできる。この値と、価格データを比較するなどして、適切な処理がされているか確認できる（下記の例のように、pandas.DataFrameのマージなどで比較すると便利）。\n",
"> **注意**： `Backtest` のインスタンスを作るとき、 defalut 設定である `trade_on_close = False` のままにすると、取引時刻がインディケータよりも「一つ後のバーの時刻」になる。この場合は、下記の `merge_results` 関数はそのままでは使えない。`df.shift()` メソッド等で合わせるなど修正が必要。\n",
"- この例では、ポジションを保持した時にフラグが残るように `init`メソッドのなかで`check_box`という変数を仕込ませたのでそれを使って確認できる。このあたりは色々工夫の余地があると思う。"
],
"metadata": {
"id": "okCGLdU6GE0b"
}
},
{
"cell_type": "code",
"source": [
"def merge_results(df, bt):\n",
" _df = df.copy()\n",
"\n",
" _df = _df.merge(\n",
" bt._results[\"_trades\"], right_on=\"EntryTime\", left_index=True, how=\"outer\"\n",
" )\n",
" _df = _df.set_index(\"EntryTime\")\n",
"\n",
" _df[\"BASIC_UPPERBAND\"] = bt._results[\"_strategy\"].basic_ub\n",
" _df[\"BASIC_LOWERBAND\"] = bt._results[\"_strategy\"].basic_lb\n",
" _df[\"FINAL_UPPERBAND\"] = bt._results[\"_strategy\"].final_ub\n",
" _df[\"FINAL_LOWERBAND\"] = bt._results[\"_strategy\"].final_lb\n",
" _df[\"SUPERTREND\"] = bt._results[\"_strategy\"].supertrend\n",
" _df[\"EMA\"] = bt._results[\"_strategy\"].close_ema\n",
" _df[\"CHECKBOX\"] = bt._results[\"_strategy\"].check_box\n",
"\n",
" return _df\n"
],
"metadata": {
"id": "ACmCEYrURLwr"
},
"execution_count": 20,
"outputs": []
},
{
"cell_type": "code",
"source": [
"# マージしたデータを確認\n",
"df_merged = merge_results(df, bt)\n",
"df_merged.info()"
],
"metadata": {
"id": "OIBLeJTiRTkN",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "ee2dc739-b8ec-40b5-fdd2-a67bcc2ef394"
},
"execution_count": 21,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"DatetimeIndex: 1500 entries, 2021-12-08 15:15:00 to 2021-12-13 20:15:00\n",
"Data columns (total 24 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 Open 1500 non-null float64 \n",
" 1 High 1500 non-null float64 \n",
" 2 Low 1500 non-null float64 \n",
" 3 Close 1500 non-null float64 \n",
" 4 Volume 1500 non-null float64 \n",
" 5 Prev_Close 1499 non-null float64 \n",
" 6 HL 1500 non-null float64 \n",
" 7 TR 1500 non-null float64 \n",
" 8 Size 11 non-null float64 \n",
" 9 EntryBar 11 non-null float64 \n",
" 10 ExitBar 11 non-null float64 \n",
" 11 EntryPrice 11 non-null float64 \n",
" 12 ExitPrice 11 non-null float64 \n",
" 13 PnL 11 non-null float64 \n",
" 14 ReturnPct 11 non-null float64 \n",
" 15 ExitTime 11 non-null datetime64[ns] \n",
" 16 Duration 11 non-null timedelta64[ns]\n",
" 17 BASIC_UPPERBAND 1486 non-null float64 \n",
" 18 BASIC_LOWERBAND 1486 non-null float64 \n",
" 19 FINAL_UPPERBAND 1486 non-null float64 \n",
" 20 FINAL_LOWERBAND 1486 non-null float64 \n",
" 21 SUPERTREND 1486 non-null float64 \n",
" 22 EMA 1301 non-null float64 \n",
" 23 CHECKBOX 1301 non-null float64 \n",
"dtypes: datetime64[ns](1), float64(22), timedelta64[ns](1)\n",
"memory usage: 293.0 KB\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"# ポジションの確認\n",
"# flag 3 は Supertrend が Close より小さくなるタイミングでロングポジションを持つ時のフラグ\n",
"df_merged[df_merged[\"CHECKBOX\"]==3].index"
],
"metadata": {
"id": "3ymuGKR5Sjgu",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "fc9517a7-d9f2-470a-c49e-ee6006d577ef"
},
"execution_count": 22,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"DatetimeIndex(['2021-12-10 14:50:00', '2021-12-11 17:45:00',\n",
" '2021-12-12 01:40:00', '2021-12-12 16:40:00',\n",
" '2021-12-13 01:40:00'],\n",
" dtype='datetime64[ns]', name='EntryTime', freq=None)"
]
},
"metadata": {},
"execution_count": 22
}
]
},
{
"cell_type": "code",
"source": [
"# 個別データの確認\n",
"# インディケータを描画してコード通りのタイミングであることを確認\n",
"i = df_merged[df_merged[\"CHECKBOX\"]==3].index[1]\n",
"df_merged.loc[i- pd.DateOffset(minutes=10) : i + pd.DateOffset(minutes=10)][[\"SUPERTREND\",\"EMA\", \"CHECKBOX\"]].plot(secondary_y=\"CHECKBOX\")"
],
"metadata": {
"id": "BINS9n-4U5Uh",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 296
},
"outputId": "1f880389-08b8-4135-c04d-6a6d34ebe702"
},
"execution_count": 23,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7fd5fbd61810>"
]
},
"metadata": {},
"execution_count": 23
},
{
"output_type": "display_data",
"data": {
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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"source": [
"# 同タイミングのストラテジーデータを確認。\n",
"df_merged.loc[i]"
],
"metadata": {
"id": "-J8jl4bqWwKw",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "f235aa80-3eca-4b59-f438-eef1b0e8dd91"
},
"execution_count": 24,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"Open 170.887\n",
"High 170.945\n",
"Low 170.05\n",
"Close 170.175\n",
"Volume 1.51842e+06\n",
"Prev_Close 170.887\n",
"HL 170.498\n",
"TR 0.895\n",
"Size 613\n",
"EntryBar 893\n",
"ExitBar 974\n",
"EntryPrice 170.345\n",
"ExitPrice 170.178\n",
"PnL -102.785\n",
"ReturnPct -0.000984325\n",
"ExitTime 2021-12-12 00:30:00\n",
"Duration 0 days 06:45:00\n",
"BASIC_UPPERBAND 172.56\n",
"BASIC_LOWERBAND 168.435\n",
"FINAL_UPPERBAND 172.56\n",
"FINAL_LOWERBAND 168.903\n",
"SUPERTREND 172.56\n",
"EMA 172.782\n",
"CHECKBOX 3\n",
"Name: 2021-12-11 17:45:00, dtype: object"
]
},
"metadata": {},
"execution_count": 24
}
]
},
{
"cell_type": "markdown",
"source": [
"## 最適化\n",
"\n",
"- Backtesting.py では、パラメータの値に選択肢として渡された値を総当りで試し、最もよい組み合わせを探してくれます。\n",
"- [Backtest.optimize](https://kernc.github.io/backtesting.py/doc/backtesting/backtesting.html#backtesting.backtesting.Backtest.optimize)\n",
"- 制約条件なども追加できます。詳しくはこちら：[Backtest.optimize](https://kernc.github.io/backtesting.py/doc/backtesting/backtesting.html#backtesting.backtesting.Backtest.optimize)\n"
],
"metadata": {
"id": "Sh5YVkb8dxFa"
}
},
{
"cell_type": "markdown",
"source": [
"### パラメータ\n",
"\n",
"- Supertrend の例では、その定義で以下の3つのパラメータを使用しています。\n",
" ```python\n",
" class SuperTrend(Strategy):\n",
" period = 15\n",
" ema_period = 200\n",
" multiplier = 3\n",
" :\n",
" :\n",
"\n",
" ``` \n",
"- 最適化の機能では、これらのパラメータに様々な値を渡して、全ての組み合わせを横断的に実行し、最も成績のよいパラメータの組み合わせを得ることができます。\n"
],
"metadata": {
"id": "VoNhU4W1d2tf"
}
},
{
"cell_type": "markdown",
"source": [
"### 最適化の実行\n",
"\n",
"- `Backtest` インスタンスを作成し、`optimize` メソッドを呼び出す\n",
"- その際、`Strategy`クラスで使ったパラメータと同じ名前の変数に、最適化の候補として試したい値をリストで渡す\n",
"- `maximize=` オプションで、最大の値にしたい評価指標の名前を渡す\n",
"- `return_heatmap=True,` とすると、全ての組み合わせによる評価結果を返す\n"
],
"metadata": {
"id": "MXegRld5ml6J"
}
},
{
"cell_type": "code",
"source": [
"periods = [5,15,20]\n",
"multipliers = [3,5,7]\n",
"ema_periods = [100,200,300]\n",
"\n",
"df = get_data(\"ETH-PERP\")\n",
"df = add_features(df)\n",
"\n",
"# インスタンス作成\n",
"bt = Backtest(\n",
" df,\n",
" SuperTrend,\n",
" cash=10000,\n",
" commission=0.001,\n",
" trade_on_close=True,\n",
" )\n",
"\n",
"# optimize メソッド呼び出し\n",
"stats, heatmap = bt.optimize(\n",
" period=periods,\n",
" multiplier=multipliers,\n",
" ema_period=ema_periods,\n",
" maximize=\"SQN\",\n",
" return_heatmap=True, # False にした場合は返り値は stats のみ\n",
" )"
],
"metadata": {
"id": "m0-E0wJ2nD-s",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 17,
"referenced_widgets": [
"ff4c6d67258648fea0e51e773cd9c7cf",
"dde1a57859ad4fa7b30c5e034a429c26",
"c325a174e01847eda117b17dd26aaa2a",
"f7a166f26574476fa87ed01153c3bdd3",
"4e8699667dfa4ce984c21c3d5fdd4355",
"91d8968352214a9095f51ca440b9ccc0",
"77b62d3b012944ad8139ba7e49fbeb54",
"0035f39553ce48b5bce708e804627614",
"e25b1fd7e3df464bb245e41b77f1fdb3",
"f3591392b04b47918cc410e5c4367a34",
"fcc340d2926b408ab29d935338c1f410"
]
},
"outputId": "e8abbc7b-7f73-4dd3-bf78-0b427711bdf0"
},
"execution_count": 25,
"outputs": [
{
"output_type": "display_data",
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "ff4c6d67258648fea0e51e773cd9c7cf",
"version_minor": 0,
"version_major": 2
},
"text/plain": [
"Backtest.optimize: 0%| | 0/3 [00:00<?, ?it/s]"
]
},
"metadata": {}
}
]
},
{
"cell_type": "markdown",
"source": [
"### 結果を確認\n",
"\n",
"- `stats` は、`maximize=` オプションで指定した評価指標が最大になった時のパラメータの組み合わせで得られた結果\n",
"- `heatmap` は、全ての組み合わせで得られた結果\n"
],
"metadata": {
"id": "UM6z_zOGIBZO"
}
},
{
"cell_type": "code",
"source": [
"stats"
],
"metadata": {
"id": "EyWvkroEvJ_c",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "2fa0a143-21dc-4e27-f74c-57b6c017720d"
},
"execution_count": 26,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"Start 2021-12-08 15:15:00\n",
"End 2021-12-13 20:15:00\n",
"Duration 5 days 05:00:00\n",
"Exposure Time [%] 93.2667\n",
"Equity Final [$] 10833.3\n",
"Equity Peak [$] 11355.7\n",
"Return [%] 8.33308\n",
"Buy & Hold Return [%] -14.9949\n",
"Return (Ann.) [%] 10576.2\n",
"Volatility (Ann.) [%] 12105.5\n",
"Sharpe Ratio 0.873674\n",
"Sortino Ratio 382.332\n",
"Calmar Ratio 1429.68\n",
"Max. Drawdown [%] -7.39765\n",
"Avg. Drawdown [%] -0.866275\n",
"Max. Drawdown Duration 1 days 08:10:00\n",
"Avg. Drawdown Duration 0 days 03:22:00\n",
"# Trades 22\n",
"Win Rate [%] 72.7273\n",
"Best Trade [%] 4.50419\n",
"Worst Trade [%] -6.05808\n",
"Avg. Trade [%] 0.434495\n",
"Max. Trade Duration 1 days 06:25:00\n",
"Avg. Trade Duration 0 days 05:18:00\n",
"Profit Factor 1.89455\n",
"Expectancy [%] 0.455885\n",
"SQN 1.02382\n",
"_strategy SuperTrend(perio...\n",
"_equity_curve ...\n",
"_trades Size EntryB...\n",
"dtype: object"
]
},
"metadata": {},
"execution_count": 26
}
]
},
{
"cell_type": "code",
"source": [
"# この結果を得た時のパラメータの組み合わせ\n",
"stats[\"_strategy\"]"
],
"metadata": {
"id": "RKTHrrA0v2Ey",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "53b90d55-a59f-48d9-d234-8fa762254897"
},
"execution_count": 27,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<Strategy SuperTrend(period=15,multiplier=3,ema_period=100)>"
]
},
"metadata": {},
"execution_count": 27
}
]
},
{
"cell_type": "code",
"source": [
"# 全組み合わせの結果を確認\n",
"heatmap.sort_values(ascending=False)"
],
"metadata": {
"id": "o4ruxNjLvoNI",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "49b8107c-53a3-474a-f1a4-0e5abe0f57ad"
},
"execution_count": 28,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"period multiplier ema_period\n",
"15 3 100 1.023822\n",
" 5 300 0.866060\n",
"20 7 300 0.827568\n",
" 3 100 0.824220\n",
"15 7 300 0.803267\n",
"20 5 300 0.752613\n",
" 7 100 0.730872\n",
"5 7 100 0.608776\n",
" 5 300 0.473080\n",
"20 3 300 0.440610\n",
"15 3 200 0.437680\n",
" 300 0.412526\n",
"5 3 300 0.403365\n",
" 200 0.371488\n",
"15 5 100 0.336720\n",
"20 5 100 0.078990\n",
"5 7 300 0.044706\n",
" 3 100 -0.097544\n",
"20 7 200 -0.140871\n",
"5 5 100 -0.235726\n",
"15 7 200 -0.578098\n",
" 100 -0.648745\n",
" 5 200 -0.870168\n",
"5 7 200 -0.908744\n",
"20 5 200 -0.935830\n",
" 3 200 -1.043078\n",
"5 5 200 -1.106144\n",
"Name: SQN, dtype: float64"
]
},
"metadata": {},
"execution_count": 28
}
]
},
{
"cell_type": "code",
"source": [
"# bt は最も良かったパラメータのストラテジーを保持しているので\n",
"# plot すると、その結果を描画する\n",
"print(bt._results[\"_strategy\"])\n",
"bt.plot()"
],
"metadata": {
"id": "dBkhJlxbGncm",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 832
},
"outputId": "eaaaf55d-d524-47d8-ea03-c436e6d6ad4f"
},
"execution_count": 29,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"SuperTrend(period=15,multiplier=3,ema_period=100)\n"
]
},
{
"output_type": "display_data",
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"}(window));"
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