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firmai/finml-global.ipynb

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FinML Global.ipynb
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finml-global.ipynb
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "FinML Global.ipynb",
"provenance": [],
"include_colab_link": true
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
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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/firmai/571c895fe1ac5180bc249ede54cb1ade/finml-global.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "code",
"metadata": {
"id": "x7YsNWuZZSYO",
"outputId": "0b449d98-0a70-44f6-f4a8-51540c8d971e",
"colab": {
"base_uri": "https://localhost:8080/"
}
},
"source": [
"!pip install scipy==1.2.2"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Collecting scipy==1.2.2\n",
" Downloading scipy-1.2.2-cp37-cp37m-manylinux1_x86_64.whl (24.8 MB)\n",
"\u001b[K |████████████████████████████████| 24.8 MB 1.3 MB/s \n",
"\u001b[?25hRequirement already satisfied: numpy>=1.8.2 in /usr/local/lib/python3.7/dist-packages (from scipy==1.2.2) (1.19.5)\n",
"Installing collected packages: scipy\n",
" Attempting uninstall: scipy\n",
" Found existing installation: scipy 1.4.1\n",
" Uninstalling scipy-1.4.1:\n",
" Successfully uninstalled scipy-1.4.1\n",
"\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
"albumentations 0.1.12 requires imgaug<0.2.7,>=0.2.5, but you have imgaug 0.2.9 which is incompatible.\u001b[0m\n",
"Successfully installed scipy-1.2.2\n"
]
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "JeQs2e0DHBhO",
"outputId": "77dfebdc-b00b-459e-bea0-d729b108a7b9",
"colab": {
"base_uri": "https://localhost:8080/"
}
},
"source": [
"import matplotlib.pyplot as plt\n",
"import statsmodels.api as sm\n",
"import pandas as pd\n",
"import numpy as np\n",
"import seaborn as sns\n",
"from sklearn.linear_model import ElasticNetCV as en\n",
"from statsmodels.tsa.stattools import adfuller as adf\n",
"import os\n",
"\n",
"## Save future files to your drive\n",
"import numpy as np\n",
"# from google.colab import drive\n",
"# drive.mount('/content/drive',force_remount=True)\n",
"# %cd \"/content/drive/My Drive/FirmAI/FinML/Data/Commodity\"\n",
"\n"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"/usr/local/lib/python3.7/dist-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n",
" import pandas.util.testing as tm\n"
]
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "4DTi0fVBZNy1"
},
"source": [
"import pandas as pd\n",
"\n",
"df=pd.read_csv(\"https://storage.googleapis.com/public-quant/course//content/brent%20crude%20nokjpy.csv\")\n",
"df.set_index(pd.to_datetime(df[list(df.columns)[0]]),inplace=True)\n",
"del df[list(df.columns)[0]]"
],
"execution_count": 1,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "p9a_U0YjaDpX",
"outputId": "ad23a9af-cbd2-4b50-d3e9-89161620c151",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 237
}
},
"source": [
"df.head()"
],
"execution_count": 2,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" nok usd eur gbp brent \\\n",
"date \n",
"2013-04-25 16.901885 99.255002 129.165590 153.186274 10263.95955 \n",
"2013-04-26 16.760666 98.050001 127.746551 151.768098 10114.83800 \n",
"2013-04-29 16.818312 97.765004 128.073770 151.538112 10148.98465 \n",
"2013-04-30 16.882766 97.424999 128.287364 151.331719 9973.39725 \n",
"2013-05-01 16.883051 97.389997 128.353228 151.492198 9734.13050 \n",
"\n",
" gdp yoy interest rate \n",
"date \n",
"2013-04-25 NaN NaN \n",
"2013-04-26 NaN NaN \n",
"2013-04-29 NaN NaN \n",
"2013-04-30 NaN 1.5 \n",
"2013-05-01 NaN 1.5 "
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" <th>2013-04-25</th>\n",
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"metadata": {},
"execution_count": 2
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "ovMtE4iJrI-D"
},
"source": [
"## List of features that don't make sense but works\n",
"## Shift the target, never the features.\n",
"## Correlation catcher\n",
"## A hand engineered feature that weights N rolling averages of two variables and find\n",
"## .. the rolling correlations of the rolling averages\n",
"## If the bb correlation with response is bigger than the cc coefficient, probably causal\n",
"import numpy as np\n",
"\n",
"\n",
"for fact in [40]:\n",
" b=2\n",
" g=0\n",
" keep = []\n",
" for r in range(fact):\n",
" b = b**(1+((10/fact)/np.log(fact)))\n",
" keep.append(b)\n",
" g = g + b\n",
" df['brent_'+str(r)] = df['brent'].rolling(window=fact).mean().bfill()\n",
" df['nok'+str(r)] = df['nok'].rolling(window=fact).mean().bfill()\n",
" df['cc_'+str(r)] = df['brent_'+str(r)].rolling(fact).corr(df['nok'+str(r)]).bfill()\n",
"\n",
" del df['nok'+str(r)], df['brent_'+str(r)]\n",
"\n",
"\n",
" arr = np.log(np.array(keep))\n",
" arr = arr/arr.sum()\n",
" arr = arr[::-1]\n",
"\n",
" for it,ar in enumerate(arr):\n",
" df['cc_'+str(it)] = df['cc_'+str(it)]*ar\n",
" if it==0:\n",
" df['cc_weighted_'+str(fact)] = 0\n",
" df['cc_weighted_'+str(fact)] = df['cc_weighted_'+str(fact)] + df['cc_'+str(it)]\n",
" del df['cc_'+str(it)]\n",
" df['cc_weighted_'+str(fact)] = df['cc_weighted_'+str(fact)].replace(np.inf,np.nan).replace(-np.inf,np.nan)\n",
" df['cc_weighted_'+str(fact)] = df['cc_weighted_'+str(fact)].bfill()\n"
],
"execution_count": 4,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "TLjuX1teft03"
},
"source": [
"## Shift the target, never the features.\n",
"## Correlation catcher\n",
"## A hand engineered feature that weights N rolling averages of two variables and find\n",
"## .. the rolling correlations of the rolling averages\n",
"## If the cc correlation with response is bigger than the bb coefficient, probably causal\n",
"## If bb is larger there is lagged causality\n",
"## the best techniques to confirm causality would in fact be to look at prediction success.\n",
"\n",
"\n",
"for fact in [2,3,5,10,20,40,60,80,120,150,200]:\n",
" b=2\n",
" g=0\n",
" keep = []\n",
" for r in range(fact):\n",
" b = b**(1+((10/fact)/np.log(fact)))\n",
" keep.append(b)\n",
" g = g + b\n",
" df['brent_'+str(r)] = df['brent'].rolling(window=2+r).mean().bfill()\n",
" df['nok'+str(r)] = df['nok'].rolling(window=2+r).mean().bfill()\n",
" df['cc_'+str(r)] = df['brent_'+str(r)].rolling(2+r).corr(df['nok'+str(r)]).bfill()\n",
" df['bb_'+str(r)] = df['brent_'+str(r)].rolling(2+r).corr(df['nok'+str(r)]).bfill()\n",
"\n",
" del df['nok'+str(r)], df['brent_'+str(r)]\n",
"\n",
"\n",
" arr = np.log(np.array(keep))\n",
" arr = arr/arr.sum()\n",
"\n",
" for it,ar in enumerate(arr):\n",
" df['cc_'+str(it)] = df['cc_'+str(it)]*ar\n",
" if it==0:\n",
" df['cc_weighted_'+str(fact)] = 0\n",
" df['cc_weighted_'+str(fact)] = df['cc_weighted_'+str(fact)] + df['cc_'+str(it)]\n",
" del df['cc_'+str(it)]\n",
" df['cc_weighted_'+str(fact)] = df['cc_weighted_'+str(fact)].replace(np.inf,np.nan).replace(-np.inf,np.nan)\n",
" df['cc_weighted_'+str(fact)] = df['cc_weighted_'+str(fact)].bfill()\n",
"\n",
" dar = arr[::-1].copy()\n",
" for it,ar in enumerate(dar):\n",
" df['bb_'+str(it)] = df['bb_'+str(it)]*ar\n",
" if it==0:\n",
" df['bb_weighted_'+str(fact)] = 0\n",
" df['bb_weighted_'+str(fact)] = df['bb_weighted_'+str(fact)] + df['bb_'+str(it)]\n",
" del df['bb_'+str(it)]\n",
" df['bb_weighted_'+str(fact)] = df['bb_weighted_'+str(fact)].replace(np.inf,np.nan).replace(-np.inf,np.nan)\n",
" df['bb_weighted_'+str(fact)] = df['bb_weighted_'+str(fact)].bfill()\n",
" df['causal_size_step'+str(fact)] = df['bb_weighted_'+str(fact)] - df['cc_weighted_'+str(fact)]\n",
"\n",
"\n",
""
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "qgiTME0VudGa",
"outputId": "31533556-39a7-4792-9fcf-3fc99f5e6e85",
"colab": {
"base_uri": "https://localhost:8080/"
}
},
"source": [
"df.sum()"
],
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"nok 1.911090e+04\n",
"usd 1.417756e+05\n",
"eur 1.687475e+05\n",
"gbp 2.078402e+05\n",
"brent 9.708692e+06\n",
"gdp yoy 3.372000e+01\n",
"interest rate 1.235250e+03\n",
"cc_weighted_40 4.692687e+02\n",
"cc_weighted_2 4.166537e+02\n",
"bb_weighted_2 3.554804e+02\n",
"causal_size_step2 -6.117328e+01\n",
"cc_weighted_3 4.121278e+02\n",
"bb_weighted_3 3.648854e+02\n",
"causal_size_step3 -4.724238e+01\n",
"cc_weighted_5 4.331537e+02\n",
"bb_weighted_5 3.801708e+02\n",
"causal_size_step5 -5.298283e+01\n",
"cc_weighted_10 4.217326e+02\n",
"bb_weighted_10 3.985647e+02\n",
"causal_size_step10 -2.316794e+01\n",
"cc_weighted_20 4.603348e+02\n",
"bb_weighted_20 4.207841e+02\n",
"causal_size_step20 -3.955065e+01\n",
"bb_weighted_40 4.398241e+02\n",
"causal_size_step40 -2.944460e+01\n",
"cc_weighted_60 3.607571e+02\n",
"bb_weighted_60 4.126314e+02\n",
"causal_size_step60 5.187432e+01\n",
"cc_weighted_80 3.517289e+02\n",
"bb_weighted_80 4.066224e+02\n",
"causal_size_step80 5.489353e+01\n",
"cc_weighted_120 4.033036e+02\n",
"bb_weighted_120 4.147532e+02\n",
"causal_size_step120 1.144967e+01\n",
"cc_weighted_150 4.375767e+02\n",
"bb_weighted_150 4.432083e+02\n",
"causal_size_step150 5.631628e+00\n",
"cc_weighted_200 5.503299e+02\n",
"bb_weighted_200 5.629468e+02\n",
"causal_size_step200 1.261697e+01\n",
"dtype: float64"
]
},
"metadata": {},
"execution_count": 32
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "_7NQE1tTs0Lj",
"outputId": "6b68a006-9b18-4e2f-d71d-06f08a17f6b0",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
}
},
"source": [
"### This to me shows that in the short run the NOKs exchange rate change in expectation of a change\n",
"### of the oil price, oil is a lagging indicator, but oil becomes a leading indicator from 60 time steps\n",
"### onwards. Can be seen in the middle chart a few code blocks below.\n",
"df.corr()"
],
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/html": [
"\n",
" <div id=\"df-852460f5-d289-4781-a2e8-a37e3a8fac30\">\n",
" <div class=\"colab-df-container\">\n",
" <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>nok</th>\n",
" <th>usd</th>\n",
" <th>eur</th>\n",
" <th>gbp</th>\n",
" <th>brent</th>\n",
" <th>gdp yoy</th>\n",
" <th>interest rate</th>\n",
" <th>cc_weighted_40</th>\n",
" <th>cc_weighted_2</th>\n",
" <th>bb_weighted_2</th>\n",
" <th>causal_size_step2</th>\n",
" <th>cc_weighted_3</th>\n",
" <th>bb_weighted_3</th>\n",
" <th>causal_size_step3</th>\n",
" <th>cc_weighted_5</th>\n",
" <th>bb_weighted_5</th>\n",
" <th>causal_size_step5</th>\n",
" <th>cc_weighted_10</th>\n",
" <th>bb_weighted_10</th>\n",
" <th>causal_size_step10</th>\n",
" <th>cc_weighted_20</th>\n",
" <th>bb_weighted_20</th>\n",
" <th>causal_size_step20</th>\n",
" <th>bb_weighted_40</th>\n",
" <th>causal_size_step40</th>\n",
" <th>cc_weighted_60</th>\n",
" <th>bb_weighted_60</th>\n",
" <th>causal_size_step60</th>\n",
" <th>cc_weighted_80</th>\n",
" <th>bb_weighted_80</th>\n",
" <th>causal_size_step80</th>\n",
" <th>cc_weighted_120</th>\n",
" <th>bb_weighted_120</th>\n",
" <th>causal_size_step120</th>\n",
" <th>cc_weighted_150</th>\n",
" <th>bb_weighted_150</th>\n",
" <th>causal_size_step150</th>\n",
" <th>cc_weighted_200</th>\n",
" <th>bb_weighted_200</th>\n",
" <th>causal_size_step200</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>nok</th>\n",
" <td>1.000000</td>\n",
" <td>-0.259508</td>\n",
" <td>0.803596</td>\n",
" <td>0.582291</td>\n",
" <td>0.896812</td>\n",
" <td>0.258060</td>\n",
" <td>0.948522</td>\n",
" <td>-0.141402</td>\n",
" <td>-0.056319</td>\n",
" <td>-0.064972</td>\n",
" <td>-0.020026</td>\n",
" <td>-0.021618</td>\n",
" <td>-0.067087</td>\n",
" <td>-0.047840</td>\n",
" <td>0.005980</td>\n",
" <td>-0.065978</td>\n",
" <td>-0.065444</td>\n",
" <td>-0.041579</td>\n",
" <td>-0.060965</td>\n",
" <td>-0.009961</td>\n",
" <td>-0.064844</td>\n",
" <td>-0.053142</td>\n",
" <td>0.023753</td>\n",
" <td>-0.097234</td>\n",
" <td>0.089757</td>\n",
" <td>-0.350755</td>\n",
" <td>-0.246233</td>\n",
" <td>0.261053</td>\n",
" <td>-0.334209</td>\n",
" <td>-0.290207</td>\n",
" <td>0.216959</td>\n",
" <td>-0.271450</td>\n",
" <td>-0.320824</td>\n",
" <td>0.074887</td>\n",
" <td>-0.302172</td>\n",
" <td>-0.313927</td>\n",
" <td>0.142523</td>\n",
" <td>-0.422151</td>\n",
" <td>-0.141308</td>\n",
" <td>0.372049</td>\n",
" </tr>\n",
" <tr>\n",
" <th>usd</th>\n",
" <td>-0.259508</td>\n",
" <td>1.000000</td>\n",
" <td>0.122163</td>\n",
" <td>0.502560</td>\n",
" <td>-0.550984</td>\n",
" <td>0.330808</td>\n",
" <td>-0.284277</td>\n",
" <td>0.237304</td>\n",
" <td>0.026735</td>\n",
" <td>0.021255</td>\n",
" <td>-0.000384</td>\n",
" <td>0.014072</td>\n",
" <td>0.023031</td>\n",
" <td>0.011031</td>\n",
" <td>-0.005367</td>\n",
" <td>0.024029</td>\n",
" <td>0.026596</td>\n",
" <td>0.023814</td>\n",
" <td>0.025707</td>\n",
" <td>-0.002068</td>\n",
" <td>0.193440</td>\n",
" <td>0.053981</td>\n",
" <td>-0.161100</td>\n",
" <td>0.167541</td>\n",
" <td>-0.146911</td>\n",
" <td>0.503233</td>\n",
" <td>0.365989</td>\n",
" <td>-0.363736</td>\n",
" <td>0.619542</td>\n",
" <td>0.468312</td>\n",
" <td>-0.466680</td>\n",
" <td>0.745436</td>\n",
" <td>0.644580</td>\n",
" <td>-0.420112</td>\n",
" <td>0.719586</td>\n",
" <td>0.711037</td>\n",
" <td>-0.369146</td>\n",
" <td>0.705825</td>\n",
" <td>0.602888</td>\n",
" <td>-0.390721</td>\n",
" </tr>\n",
" <tr>\n",
" <th>eur</th>\n",
" <td>0.803596</td>\n",
" <td>0.122163</td>\n",
" <td>1.000000</td>\n",
" <td>0.758971</td>\n",
" <td>0.633535</td>\n",
" <td>0.550526</td>\n",
" <td>0.695060</td>\n",
" <td>-0.138216</td>\n",
" <td>-0.059551</td>\n",
" <td>-0.057299</td>\n",
" <td>-0.009414</td>\n",
" <td>-0.060483</td>\n",
" <td>-0.062147</td>\n",
" <td>-0.011515</td>\n",
" <td>-0.052460</td>\n",
" <td>-0.070466</td>\n",
" <td>-0.018944</td>\n",
" <td>-0.079864</td>\n",
" <td>-0.084028</td>\n",
" <td>0.008779</td>\n",
" <td>-0.045029</td>\n",
" <td>-0.092966</td>\n",
" <td>-0.031896</td>\n",
" <td>-0.109861</td>\n",
" <td>0.075088</td>\n",
" <td>-0.176562</td>\n",
" <td>-0.143334</td>\n",
" <td>0.114942</td>\n",
" <td>-0.140039</td>\n",
" <td>-0.160778</td>\n",
" <td>0.054639</td>\n",
" <td>0.040982</td>\n",
" <td>-0.123307</td>\n",
" <td>-0.167086</td>\n",
" <td>0.044275</td>\n",
" <td>-0.098405</td>\n",
" <td>-0.138423</td>\n",
" <td>-0.068797</td>\n",
" <td>-0.063644</td>\n",
" <td>0.035004</td>\n",
" </tr>\n",
" <tr>\n",
" <th>gbp</th>\n",
" <td>0.582291</td>\n",
" <td>0.502560</td>\n",
" <td>0.758971</td>\n",
" <td>1.000000</td>\n",
" <td>0.275338</td>\n",
" <td>0.378526</td>\n",
" <td>0.591654</td>\n",
" <td>0.011280</td>\n",
" <td>-0.005235</td>\n",
" <td>-0.010576</td>\n",
" <td>-0.006541</td>\n",
" <td>0.009679</td>\n",
" <td>-0.009902</td>\n",
" <td>-0.017496</td>\n",
" <td>-0.015093</td>\n",
" <td>-0.008871</td>\n",
" <td>0.004966</td>\n",
" <td>-0.042187</td>\n",
" <td>-0.014716</td>\n",
" <td>0.029678</td>\n",
" <td>0.068271</td>\n",
" <td>-0.011837</td>\n",
" <td>-0.083518</td>\n",
" <td>0.020098</td>\n",
" <td>0.003373</td>\n",
" <td>0.092282</td>\n",
" <td>0.066808</td>\n",
" <td>-0.066962</td>\n",
" <td>0.178726</td>\n",
" <td>0.099995</td>\n",
" <td>-0.167128</td>\n",
" <td>0.371613</td>\n",
" <td>0.211026</td>\n",
" <td>-0.309489</td>\n",
" <td>0.413040</td>\n",
" <td>0.288933</td>\n",
" <td>-0.308915</td>\n",
" <td>0.352685</td>\n",
" <td>0.356759</td>\n",
" <td>-0.160210</td>\n",
" </tr>\n",
" <tr>\n",
" <th>brent</th>\n",
" <td>0.896812</td>\n",
" <td>-0.550984</td>\n",
" <td>0.633535</td>\n",
" <td>0.275338</td>\n",
" <td>1.000000</td>\n",
" <td>0.157756</td>\n",
" <td>0.837671</td>\n",
" <td>-0.247128</td>\n",
" <td>-0.091345</td>\n",
" <td>-0.087462</td>\n",
" <td>-0.013998</td>\n",
" <td>-0.075629</td>\n",
" <td>-0.094047</td>\n",
" <td>-0.030317</td>\n",
" <td>-0.041948</td>\n",
" <td>-0.102366</td>\n",
" <td>-0.057185</td>\n",
" <td>-0.110637</td>\n",
" <td>-0.114513</td>\n",
" <td>0.013759</td>\n",
" <td>-0.196904</td>\n",
" <td>-0.144189</td>\n",
" <td>0.086957</td>\n",
" <td>-0.228803</td>\n",
" <td>0.106623</td>\n",
" <td>-0.452798</td>\n",
" <td>-0.386232</td>\n",
" <td>0.278934</td>\n",
" <td>-0.474177</td>\n",
" <td>-0.442606</td>\n",
" <td>0.279251</td>\n",
" <td>-0.472386</td>\n",
" <td>-0.509751</td>\n",
" <td>0.174362</td>\n",
" <td>-0.516936</td>\n",
" <td>-0.537918</td>\n",
" <td>0.243109</td>\n",
" <td>-0.641033</td>\n",
" <td>-0.404657</td>\n",
" <td>0.445014</td>\n",
" </tr>\n",
" <tr>\n",
" <th>gdp yoy</th>\n",
" <td>0.258060</td>\n",
" <td>0.330808</td>\n",
" <td>0.550526</td>\n",
" <td>0.378526</td>\n",
" <td>0.157756</td>\n",
" <td>1.000000</td>\n",
" <td>0.100783</td>\n",
" <td>-0.152517</td>\n",
" <td>0.114226</td>\n",
" <td>0.107809</td>\n",
" <td>-0.001082</td>\n",
" <td>-0.095895</td>\n",
" <td>0.100718</td>\n",
" <td>0.213975</td>\n",
" <td>-0.141884</td>\n",
" <td>0.072137</td>\n",
" <td>0.209196</td>\n",
" <td>-0.293206</td>\n",
" <td>-0.030928</td>\n",
" <td>0.208870</td>\n",
" <td>0.048541</td>\n",
" <td>-0.162178</td>\n",
" <td>-0.139372</td>\n",
" <td>-0.174560</td>\n",
" <td>0.085000</td>\n",
" <td>0.014738</td>\n",
" <td>-0.039319</td>\n",
" <td>-0.061609</td>\n",
" <td>-0.035928</td>\n",
" <td>-0.046444</td>\n",
" <td>0.004799</td>\n",
" <td>0.124796</td>\n",
" <td>0.009955</td>\n",
" <td>-0.143363</td>\n",
" <td>0.117644</td>\n",
" <td>0.029261</td>\n",
" <td>-0.120829</td>\n",
" <td>0.060222</td>\n",
" <td>0.000712</td>\n",
" <td>-0.063900</td>\n",
" </tr>\n",
" <tr>\n",
" <th>interest rate</th>\n",
" <td>0.948522</td>\n",
" <td>-0.284277</td>\n",
" <td>0.695060</td>\n",
" <td>0.591654</td>\n",
" <td>0.837671</td>\n",
" <td>0.100783</td>\n",
" <td>1.000000</td>\n",
" <td>-0.140215</td>\n",
" <td>-0.023259</td>\n",
" <td>-0.035662</td>\n",
" <td>-0.017370</td>\n",
" <td>0.019710</td>\n",
" <td>-0.034545</td>\n",
" <td>-0.049587</td>\n",
" <td>0.032019</td>\n",
" <td>-0.027943</td>\n",
" <td>-0.053177</td>\n",
" <td>-0.007743</td>\n",
" <td>-0.012240</td>\n",
" <td>-0.002616</td>\n",
" <td>-0.036317</td>\n",
" <td>-0.004077</td>\n",
" <td>0.035419</td>\n",
" <td>-0.052167</td>\n",
" <td>0.126652</td>\n",
" <td>-0.317493</td>\n",
" <td>-0.195803</td>\n",
" <td>0.259093</td>\n",
" <td>-0.311229</td>\n",
" <td>-0.244178</td>\n",
" <td>0.225678</td>\n",
" <td>-0.276848</td>\n",
" <td>-0.285256</td>\n",
" <td>0.113570</td>\n",
" <td>-0.278183</td>\n",
" <td>-0.270781</td>\n",
" <td>0.145253</td>\n",
" <td>-0.379649</td>\n",
" <td>-0.066175</td>\n",
" <td>0.372963</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cc_weighted_40</th>\n",
" <td>-0.141402</td>\n",
" <td>0.237304</td>\n",
" <td>-0.138216</td>\n",
" <td>0.011280</td>\n",
" <td>-0.247128</td>\n",
" <td>-0.152517</td>\n",
" <td>-0.140215</td>\n",
" <td>1.000000</td>\n",
" <td>0.019477</td>\n",
" <td>0.004681</td>\n",
" <td>-0.011425</td>\n",
" <td>0.031125</td>\n",
" <td>0.007694</td>\n",
" <td>-0.017739</td>\n",
" <td>0.072217</td>\n",
" <td>0.016940</td>\n",
" <td>-0.047054</td>\n",
" <td>0.180516</td>\n",
" <td>0.053522</td>\n",
" <td>-0.134962</td>\n",
" <td>0.495968</td>\n",
" <td>0.195253</td>\n",
" <td>-0.363982</td>\n",
" <td>0.585515</td>\n",
" <td>-0.721943</td>\n",
" <td>0.664622</td>\n",
" <td>0.759728</td>\n",
" <td>-0.245657</td>\n",
" <td>0.435070</td>\n",
" <td>0.774564</td>\n",
" <td>0.084900</td>\n",
" <td>0.067352</td>\n",
" <td>0.652547</td>\n",
" <td>0.501109</td>\n",
" <td>-0.010402</td>\n",
" <td>0.576002</td>\n",
" <td>0.482557</td>\n",
" <td>0.004544</td>\n",
" <td>0.546441</td>\n",
" <td>0.339829</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cc_weighted_2</th>\n",
" <td>-0.056319</td>\n",
" <td>0.026735</td>\n",
" <td>-0.059551</td>\n",
" <td>-0.005235</td>\n",
" <td>-0.091345</td>\n",
" <td>0.114226</td>\n",
" <td>-0.023259</td>\n",
" <td>0.019477</td>\n",
" <td>1.000000</td>\n",
" <td>0.441720</td>\n",
" <td>-0.378815</td>\n",
" <td>0.681645</td>\n",
" <td>0.537411</td>\n",
" <td>-0.029027</td>\n",
" <td>0.346351</td>\n",
" <td>0.670538</td>\n",
" <td>0.312608</td>\n",
" <td>0.116856</td>\n",
" <td>0.718559</td>\n",
" <td>0.489816</td>\n",
" <td>0.062246</td>\n",
" <td>0.545786</td>\n",
" <td>0.404263</td>\n",
" <td>0.329986</td>\n",
" <td>0.257869</td>\n",
" <td>0.016281</td>\n",
" <td>0.217205</td>\n",
" <td>0.162657</td>\n",
" <td>0.019825</td>\n",
" <td>0.159568</td>\n",
" <td>0.118920</td>\n",
" <td>0.000581</td>\n",
" <td>0.094481</td>\n",
" <td>0.084916</td>\n",
" <td>0.001302</td>\n",
" <td>0.083766</td>\n",
" <td>0.066469</td>\n",
" <td>-0.001095</td>\n",
" <td>0.100864</td>\n",
" <td>0.064839</td>\n",
" </tr>\n",
" <tr>\n",
" <th>bb_weighted_2</th>\n",
" <td>-0.064972</td>\n",
" <td>0.021255</td>\n",
" <td>-0.057299</td>\n",
" <td>-0.010576</td>\n",
" <td>-0.087462</td>\n",
" <td>0.107809</td>\n",
" <td>-0.035662</td>\n",
" <td>0.004681</td>\n",
" <td>0.441720</td>\n",
" <td>1.000000</td>\n",
" <td>0.662961</td>\n",
" <td>0.290797</td>\n",
" <td>0.993228</td>\n",
" <td>0.731994</td>\n",
" <td>0.167121</td>\n",
" <td>0.945600</td>\n",
" <td>0.719044</td>\n",
" <td>0.092802</td>\n",
" <td>0.761850</td>\n",
" <td>0.550353</td>\n",
" <td>0.061562</td>\n",
" <td>0.500361</td>\n",
" <td>0.365789</td>\n",
" <td>0.286184</td>\n",
" <td>0.238558</td>\n",
" <td>0.019176</td>\n",
" <td>0.192245</td>\n",
" <td>0.137577</td>\n",
" <td>0.017496</td>\n",
" <td>0.141574</td>\n",
" <td>0.105645</td>\n",
" <td>0.008441</td>\n",
" <td>0.088304</td>\n",
" <td>0.068719</td>\n",
" <td>0.016434</td>\n",
" <td>0.078391</td>\n",
" <td>0.042160</td>\n",
" <td>0.020298</td>\n",
" <td>0.088914</td>\n",
" <td>0.033928</td>\n",
" </tr>\n",
" <tr>\n",
" <th>causal_size_step2</th>\n",
" <td>-0.020026</td>\n",
" <td>-0.000384</td>\n",
" <td>-0.009414</td>\n",
" <td>-0.006541</td>\n",
" <td>-0.013998</td>\n",
" <td>-0.001082</td>\n",
" <td>-0.017370</td>\n",
" <td>-0.011425</td>\n",
" <td>-0.378815</td>\n",
" <td>0.662961</td>\n",
" <td>1.000000</td>\n",
" <td>-0.268841</td>\n",
" <td>0.576123</td>\n",
" <td>0.779323</td>\n",
" <td>-0.116626</td>\n",
" <td>0.415900</td>\n",
" <td>0.480877</td>\n",
" <td>-0.001782</td>\n",
" <td>0.186277</td>\n",
" <td>0.158985</td>\n",
" <td>0.011563</td>\n",
" <td>0.060710</td>\n",
" <td>0.039987</td>\n",
" <td>0.019851</td>\n",
" <td>0.030902</td>\n",
" <td>0.006195</td>\n",
" <td>0.017061</td>\n",
" <td>0.006186</td>\n",
" <td>0.001505</td>\n",
" <td>0.012887</td>\n",
" <td>0.009744</td>\n",
" <td>0.008223</td>\n",
" <td>0.012249</td>\n",
" <td>0.000027</td>\n",
" <td>0.015866</td>\n",
" <td>0.010965</td>\n",
" <td>-0.011976</td>\n",
" <td>0.021852</td>\n",
" <td>0.007552</td>\n",
" <td>-0.019108</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cc_weighted_3</th>\n",
" <td>-0.021618</td>\n",
" <td>0.014072</td>\n",
" <td>-0.060483</td>\n",
" <td>0.009679</td>\n",
" <td>-0.075629</td>\n",
" <td>-0.095895</td>\n",
" <td>0.019710</td>\n",
" <td>0.031125</td>\n",
" <td>0.681645</td>\n",
" <td>0.290797</td>\n",
" <td>-0.268841</td>\n",
" <td>1.000000</td>\n",
" <td>0.384019</td>\n",
" <td>-0.436602</td>\n",
" <td>0.640177</td>\n",
" <td>0.560061</td>\n",
" <td>-0.042713</td>\n",
" <td>0.235220</td>\n",
" <td>0.748908</td>\n",
" <td>0.397316</td>\n",
" <td>0.109206</td>\n",
" <td>0.670883</td>\n",
" <td>0.461821</td>\n",
" <td>0.441560</td>\n",
" <td>0.338874</td>\n",
" <td>0.000491</td>\n",
" <td>0.282819</td>\n",
" <td>0.239554</td>\n",
" <td>0.016462</td>\n",
" <td>0.205261</td>\n",
" <td>0.166109</td>\n",
" <td>-0.018795</td>\n",
" <td>0.116565</td>\n",
" <td>0.131064</td>\n",
" <td>-0.022937</td>\n",
" <td>0.099332</td>\n",
" <td>0.111069</td>\n",
" <td>-0.022974</td>\n",
" <td>0.127136</td>\n",
" <td>0.105320</td>\n",
" </tr>\n",
" <tr>\n",
" <th>bb_weighted_3</th>\n",
" <td>-0.067087</td>\n",
" <td>0.023031</td>\n",
" <td>-0.062147</td>\n",
" <td>-0.009902</td>\n",
" <td>-0.094047</td>\n",
" <td>0.100718</td>\n",
" <td>-0.034545</td>\n",
" <td>0.007694</td>\n",
" <td>0.537411</td>\n",
" <td>0.993228</td>\n",
" <td>0.576123</td>\n",
" <td>0.384019</td>\n",
" <td>1.000000</td>\n",
" <td>0.663011</td>\n",
" <td>0.220073</td>\n",
" <td>0.975888</td>\n",
" <td>0.700861</td>\n",
" <td>0.109456</td>\n",
" <td>0.817069</td>\n",
" <td>0.580337</td>\n",
" <td>0.068879</td>\n",
" <td>0.552241</td>\n",
" <td>0.402713</td>\n",
" <td>0.320373</td>\n",
" <td>0.264060</td>\n",
" <td>0.019470</td>\n",
" <td>0.214115</td>\n",
" <td>0.155759</td>\n",
" <td>0.019018</td>\n",
" <td>0.157492</td>\n",
" <td>0.118172</td>\n",
" <td>0.007022</td>\n",
" <td>0.097205</td>\n",
" <td>0.078705</td>\n",
" <td>0.014384</td>\n",
" <td>0.086072</td>\n",
" <td>0.051112</td>\n",
" <td>0.017804</td>\n",
" <td>0.098878</td>\n",
" <td>0.042939</td>\n",
" </tr>\n",
" <tr>\n",
" <th>causal_size_step3</th>\n",
" <td>-0.047840</td>\n",
" <td>0.011031</td>\n",
" <td>-0.011515</td>\n",
" <td>-0.017496</td>\n",
" <td>-0.030317</td>\n",
" <td>0.213975</td>\n",
" <td>-0.049587</td>\n",
" <td>-0.017739</td>\n",
" <td>-0.029027</td>\n",
" <td>0.731994</td>\n",
" <td>0.779323</td>\n",
" <td>-0.436602</td>\n",
" <td>0.663011</td>\n",
" <td>1.000000</td>\n",
" <td>-0.304609</td>\n",
" <td>0.496786</td>\n",
" <td>0.717524</td>\n",
" <td>-0.084061</td>\n",
" <td>0.188926</td>\n",
" <td>0.243324</td>\n",
" <td>-0.021428</td>\n",
" <td>-0.005853</td>\n",
" <td>0.017955</td>\n",
" <td>-0.045846</td>\n",
" <td>-0.017461</td>\n",
" <td>0.018573</td>\n",
" <td>-0.020677</td>\n",
" <td>-0.042458</td>\n",
" <td>0.005183</td>\n",
" <td>-0.012966</td>\n",
" <td>-0.019534</td>\n",
" <td>0.022080</td>\n",
" <td>0.000205</td>\n",
" <td>-0.029576</td>\n",
" <td>0.032612</td>\n",
" <td>0.003329</td>\n",
" <td>-0.040251</td>\n",
" <td>0.035974</td>\n",
" <td>-0.006736</td>\n",
" <td>-0.043553</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cc_weighted_5</th>\n",
" <td>0.005980</td>\n",
" <td>-0.005367</td>\n",
" <td>-0.052460</td>\n",
" <td>-0.015093</td>\n",
" <td>-0.041948</td>\n",
" <td>-0.141884</td>\n",
" <td>0.032019</td>\n",
" <td>0.072217</td>\n",
" <td>0.346351</td>\n",
" <td>0.167121</td>\n",
" <td>-0.116626</td>\n",
" <td>0.640177</td>\n",
" <td>0.220073</td>\n",
" <td>-0.304609</td>\n",
" <td>1.000000</td>\n",
" <td>0.369233</td>\n",
" <td>-0.528572</td>\n",
" <td>0.520399</td>\n",
" <td>0.678629</td>\n",
" <td>0.053434</td>\n",
" <td>0.181165</td>\n",
" <td>0.778577</td>\n",
" <td>0.477515</td>\n",
" <td>0.582389</td>\n",
" <td>0.408879</td>\n",
" <td>-0.013380</td>\n",
" <td>0.384120</td>\n",
" <td>0.344189</td>\n",
" <td>0.005003</td>\n",
" <td>0.277689</td>\n",
" <td>0.249813</td>\n",
" <td>-0.042570</td>\n",
" <td>0.149458</td>\n",
" <td>0.192946</td>\n",
" <td>-0.050180</td>\n",
" <td>0.117863</td>\n",
" <td>0.162041</td>\n",
" <td>-0.049278</td>\n",
" <td>0.132915</td>\n",
" <td>0.137705</td>\n",
" </tr>\n",
" <tr>\n",
" <th>bb_weighted_5</th>\n",
" <td>-0.065978</td>\n",
" <td>0.024029</td>\n",
" <td>-0.070466</td>\n",
" <td>-0.008871</td>\n",
" <td>-0.102366</td>\n",
" <td>0.072137</td>\n",
" <td>-0.027943</td>\n",
" <td>0.016940</td>\n",
" <td>0.670538</td>\n",
" <td>0.945600</td>\n",
" <td>0.415900</td>\n",
" <td>0.560061</td>\n",
" <td>0.975888</td>\n",
" <td>0.496786</td>\n",
" <td>0.369233</td>\n",
" <td>1.000000</td>\n",
" <td>0.593738</td>\n",
" <td>0.166683</td>\n",
" <td>0.911254</td>\n",
" <td>0.602718</td>\n",
" <td>0.090068</td>\n",
" <td>0.662268</td>\n",
" <td>0.474932</td>\n",
" <td>0.399994</td>\n",
" <td>0.320725</td>\n",
" <td>0.017768</td>\n",
" <td>0.265142</td>\n",
" <td>0.201380</td>\n",
" <td>0.020603</td>\n",
" <td>0.194306</td>\n",
" <td>0.149951</td>\n",
" <td>0.001137</td>\n",
" <td>0.116842</td>\n",
" <td>0.104449</td>\n",
" <td>0.006648</td>\n",
" <td>0.102113</td>\n",
" <td>0.074360</td>\n",
" <td>0.009466</td>\n",
" <td>0.119070</td>\n",
" <td>0.064790</td>\n",
" </tr>\n",
" <tr>\n",
" <th>causal_size_step5</th>\n",
" <td>-0.065444</td>\n",
" <td>0.026596</td>\n",
" <td>-0.018944</td>\n",
" <td>0.004966</td>\n",
" <td>-0.057185</td>\n",
" <td>0.209196</td>\n",
" <td>-0.053177</td>\n",
" <td>-0.047054</td>\n",
" <td>0.312608</td>\n",
" <td>0.719044</td>\n",
" <td>0.480877</td>\n",
" <td>-0.042713</td>\n",
" <td>0.700861</td>\n",
" <td>0.717524</td>\n",
" <td>-0.528572</td>\n",
" <td>0.593738</td>\n",
" <td>1.000000</td>\n",
" <td>-0.298328</td>\n",
" <td>0.244786</td>\n",
" <td>0.504278</td>\n",
" <td>-0.074589</td>\n",
" <td>-0.069186</td>\n",
" <td>0.020367</td>\n",
" <td>-0.138888</td>\n",
" <td>-0.061063</td>\n",
" <td>0.027815</td>\n",
" <td>-0.090398</td>\n",
" <td>-0.114066</td>\n",
" <td>0.014487</td>\n",
" <td>-0.062948</td>\n",
" <td>-0.079328</td>\n",
" <td>0.037898</td>\n",
" <td>-0.022679</td>\n",
" <td>-0.071654</td>\n",
" <td>0.049521</td>\n",
" <td>-0.008777</td>\n",
" <td>-0.072378</td>\n",
" <td>0.051313</td>\n",
" <td>-0.006321</td>\n",
" <td>-0.060049</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cc_weighted_10</th>\n",
" <td>-0.041579</td>\n",
" <td>0.023814</td>\n",
" <td>-0.079864</td>\n",
" <td>-0.042187</td>\n",
" <td>-0.110637</td>\n",
" <td>-0.293206</td>\n",
" <td>-0.007743</td>\n",
" <td>0.180516</td>\n",
" <td>0.116856</td>\n",
" <td>0.092802</td>\n",
" <td>-0.001782</td>\n",
" <td>0.235220</td>\n",
" <td>0.109456</td>\n",
" <td>-0.084061</td>\n",
" <td>0.520399</td>\n",
" <td>0.166683</td>\n",
" <td>-0.298328</td>\n",
" <td>1.000000</td>\n",
" <td>0.420344</td>\n",
" <td>-0.643122</td>\n",
" <td>0.447415</td>\n",
" <td>0.752490</td>\n",
" <td>0.169130</td>\n",
" <td>0.738283</td>\n",
" <td>0.409633</td>\n",
" <td>0.048179</td>\n",
" <td>0.554164</td>\n",
" <td>0.406094</td>\n",
" <td>0.073476</td>\n",
" <td>0.439312</td>\n",
" <td>0.299948</td>\n",
" <td>-0.019067</td>\n",
" <td>0.278811</td>\n",
" <td>0.278595</td>\n",
" <td>-0.033317</td>\n",
" <td>0.230196</td>\n",
" <td>0.231264</td>\n",
" <td>-0.020847</td>\n",
" <td>0.244359</td>\n",
" <td>0.176962</td>\n",
" </tr>\n",
" <tr>\n",
" <th>bb_weighted_10</th>\n",
" <td>-0.060965</td>\n",
" <td>0.025707</td>\n",
" <td>-0.084028</td>\n",
" <td>-0.014716</td>\n",
" <td>-0.114513</td>\n",
" <td>-0.030928</td>\n",
" <td>-0.012240</td>\n",
" <td>0.053522</td>\n",
" <td>0.718559</td>\n",
" <td>0.761850</td>\n",
" <td>0.186277</td>\n",
" <td>0.748908</td>\n",
" <td>0.817069</td>\n",
" <td>0.188926</td>\n",
" <td>0.678629</td>\n",
" <td>0.911254</td>\n",
" <td>0.244786</td>\n",
" <td>0.420344</td>\n",
" <td>1.000000</td>\n",
" <td>0.424494</td>\n",
" <td>0.174448</td>\n",
" <td>0.873496</td>\n",
" <td>0.566657</td>\n",
" <td>0.594824</td>\n",
" <td>0.442332</td>\n",
" <td>0.020665</td>\n",
" <td>0.404154</td>\n",
" <td>0.315566</td>\n",
" <td>0.033773</td>\n",
" <td>0.300505</td>\n",
" <td>0.229132</td>\n",
" <td>-0.008549</td>\n",
" <td>0.179856</td>\n",
" <td>0.174662</td>\n",
" <td>-0.009261</td>\n",
" <td>0.152257</td>\n",
" <td>0.136134</td>\n",
" <td>-0.006681</td>\n",
" <td>0.170120</td>\n",
" <td>0.114642</td>\n",
" </tr>\n",
" <tr>\n",
" <th>causal_size_step10</th>\n",
" <td>-0.009961</td>\n",
" <td>-0.002068</td>\n",
" <td>0.008779</td>\n",
" <td>0.029678</td>\n",
" <td>0.013759</td>\n",
" <td>0.208870</td>\n",
" <td>-0.002616</td>\n",
" <td>-0.134962</td>\n",
" <td>0.489816</td>\n",
" <td>0.550353</td>\n",
" <td>0.158985</td>\n",
" <td>0.397316</td>\n",
" <td>0.580337</td>\n",
" <td>0.243324</td>\n",
" <td>0.053434</td>\n",
" <td>0.602718</td>\n",
" <td>0.504278</td>\n",
" <td>-0.643122</td>\n",
" <td>0.424494</td>\n",
" <td>1.000000</td>\n",
" <td>-0.299237</td>\n",
" <td>-0.013706</td>\n",
" <td>0.309457</td>\n",
" <td>-0.234712</td>\n",
" <td>-0.035457</td>\n",
" <td>-0.030637</td>\n",
" <td>-0.211900</td>\n",
" <td>-0.138908</td>\n",
" <td>-0.044817</td>\n",
" <td>-0.184767</td>\n",
" <td>-0.105935</td>\n",
" <td>0.011811</td>\n",
" <td>-0.126428</td>\n",
" <td>-0.130597</td>\n",
" <td>0.025430</td>\n",
" <td>-0.101210</td>\n",
" <td>-0.115882</td>\n",
" <td>0.015164</td>\n",
" <td>-0.100267</td>\n",
" <td>-0.079834</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cc_weighted_20</th>\n",
" <td>-0.064844</td>\n",
" <td>0.193440</td>\n",
" <td>-0.045029</td>\n",
" <td>0.068271</td>\n",
" <td>-0.196904</td>\n",
" <td>0.048541</td>\n",
" <td>-0.036317</td>\n",
" <td>0.495968</td>\n",
" <td>0.062246</td>\n",
" <td>0.061562</td>\n",
" <td>0.011563</td>\n",
" <td>0.109206</td>\n",
" <td>0.068879</td>\n",
" <td>-0.021428</td>\n",
" <td>0.181165</td>\n",
" <td>0.090068</td>\n",
" <td>-0.074589</td>\n",
" <td>0.447415</td>\n",
" <td>0.174448</td>\n",
" <td>-0.299237</td>\n",
" <td>1.000000</td>\n",
" <td>0.484398</td>\n",
" <td>-0.655579</td>\n",
" <td>0.792579</td>\n",
" <td>0.070585</td>\n",
" <td>0.196739</td>\n",
" <td>0.722794</td>\n",
" <td>0.350174</td>\n",
" <td>0.141216</td>\n",
" <td>0.626304</td>\n",
" <td>0.374634</td>\n",
" <td>0.000366</td>\n",
" <td>0.445147</td>\n",
" <td>0.403276</td>\n",
" <td>0.020733</td>\n",
" <td>0.395378</td>\n",
" <td>0.294518</td>\n",
" <td>0.081155</td>\n",
" <td>0.421935</td>\n",
" <td>0.177568</td>\n",
" </tr>\n",
" <tr>\n",
" <th>bb_weighted_20</th>\n",
" <td>-0.053142</td>\n",
" <td>0.053981</td>\n",
" <td>-0.092966</td>\n",
" <td>-0.011837</td>\n",
" <td>-0.144189</td>\n",
" <td>-0.162178</td>\n",
" <td>-0.004077</td>\n",
" <td>0.195253</td>\n",
" <td>0.545786</td>\n",
" <td>0.500361</td>\n",
" <td>0.060710</td>\n",
" <td>0.670883</td>\n",
" <td>0.552241</td>\n",
" <td>-0.005853</td>\n",
" <td>0.778577</td>\n",
" <td>0.662268</td>\n",
" <td>-0.069186</td>\n",
" <td>0.752490</td>\n",
" <td>0.873496</td>\n",
" <td>-0.013706</td>\n",
" <td>0.484398</td>\n",
" <td>1.000000</td>\n",
" <td>0.343060</td>\n",
" <td>0.853246</td>\n",
" <td>0.489757</td>\n",
" <td>0.052487</td>\n",
" <td>0.621518</td>\n",
" <td>0.457526</td>\n",
" <td>0.064464</td>\n",
" <td>0.484415</td>\n",
" <td>0.354799</td>\n",
" <td>-0.026651</td>\n",
" <td>0.301223</td>\n",
" <td>0.309148</td>\n",
" <td>-0.029847</td>\n",
" <td>0.254321</td>\n",
" <td>0.246330</td>\n",
" <td>-0.011477</td>\n",
" <td>0.285359</td>\n",
" <td>0.192596</td>\n",
" </tr>\n",
" <tr>\n",
" <th>causal_size_step20</th>\n",
" <td>0.023753</td>\n",
" <td>-0.161100</td>\n",
" <td>-0.031896</td>\n",
" <td>-0.083518</td>\n",
" <td>0.086957</td>\n",
" <td>-0.139372</td>\n",
" <td>0.035419</td>\n",
" <td>-0.363982</td>\n",
" <td>0.404263</td>\n",
" <td>0.365789</td>\n",
" <td>0.039987</td>\n",
" <td>0.461821</td>\n",
" <td>0.402713</td>\n",
" <td>0.017955</td>\n",
" <td>0.477515</td>\n",
" <td>0.474932</td>\n",
" <td>0.020367</td>\n",
" <td>0.169130</td>\n",
" <td>0.566657</td>\n",
" <td>0.309457</td>\n",
" <td>-0.655579</td>\n",
" <td>0.343060</td>\n",
" <td>1.000000</td>\n",
" <td>-0.114502</td>\n",
" <td>0.346948</td>\n",
" <td>-0.165931</td>\n",
" <td>-0.239591</td>\n",
" <td>0.018936</td>\n",
" <td>-0.095979</td>\n",
" <td>-0.254331</td>\n",
" <td>-0.095994</td>\n",
" <td>-0.023397</td>\n",
" <td>-0.217947</td>\n",
" <td>-0.166151</td>\n",
" <td>-0.048023</td>\n",
" <td>-0.204995</td>\n",
" <td>-0.103600</td>\n",
" <td>-0.097042</td>\n",
" <td>-0.206717</td>\n",
" <td>-0.024414</td>\n",
" </tr>\n",
" <tr>\n",
" <th>bb_weighted_40</th>\n",
" <td>-0.097234</td>\n",
" <td>0.167541</td>\n",
" <td>-0.109861</td>\n",
" <td>0.020098</td>\n",
" <td>-0.228803</td>\n",
" <td>-0.174560</td>\n",
" <td>-0.052167</td>\n",
" <td>0.585515</td>\n",
" <td>0.329986</td>\n",
" <td>0.286184</td>\n",
" <td>0.019851</td>\n",
" <td>0.441560</td>\n",
" <td>0.320373</td>\n",
" <td>-0.045846</td>\n",
" <td>0.582389</td>\n",
" <td>0.399994</td>\n",
" <td>-0.138888</td>\n",
" <td>0.738283</td>\n",
" <td>0.594824</td>\n",
" <td>-0.234712</td>\n",
" <td>0.792579</td>\n",
" <td>0.853246</td>\n",
" <td>-0.114502</td>\n",
" <td>1.000000</td>\n",
" <td>0.138231</td>\n",
" <td>0.291836</td>\n",
" <td>0.884895</td>\n",
" <td>0.360375</td>\n",
" <td>0.217046</td>\n",
" <td>0.764009</td>\n",
" <td>0.391932</td>\n",
" <td>0.004981</td>\n",
" <td>0.545377</td>\n",
" <td>0.487971</td>\n",
" <td>-0.011948</td>\n",
" <td>0.473341</td>\n",
" <td>0.401030</td>\n",
" <td>0.026161</td>\n",
" <td>0.488449</td>\n",
" <td>0.279621</td>\n",
" </tr>\n",
" <tr>\n",
" <th>causal_size_step40</th>\n",
" <td>0.089757</td>\n",
" <td>-0.146911</td>\n",
" <td>0.075088</td>\n",
" <td>0.003373</td>\n",
" <td>0.106623</td>\n",
" <td>0.085000</td>\n",
" <td>0.126652</td>\n",
" <td>-0.721943</td>\n",
" <td>0.257869</td>\n",
" <td>0.238558</td>\n",
" <td>0.030902</td>\n",
" <td>0.338874</td>\n",
" <td>0.264060</td>\n",
" <td>-0.017461</td>\n",
" <td>0.408879</td>\n",
" <td>0.320725</td>\n",
" <td>-0.061063</td>\n",
" <td>0.409633</td>\n",
" <td>0.442332</td>\n",
" <td>-0.035457</td>\n",
" <td>0.070585</td>\n",
" <td>0.489757</td>\n",
" <td>0.346948</td>\n",
" <td>0.138231</td>\n",
" <td>1.000000</td>\n",
" <td>-0.562879</td>\n",
" <td>-0.172858</td>\n",
" <td>0.607728</td>\n",
" <td>-0.346270</td>\n",
" <td>-0.294168</td>\n",
" <td>0.230816</td>\n",
" <td>-0.078034</td>\n",
" <td>-0.331714</td>\n",
" <td>-0.195699</td>\n",
" <td>0.002510</td>\n",
" <td>-0.299684</td>\n",
" <td>-0.247244</td>\n",
" <td>0.016778</td>\n",
" <td>-0.250673</td>\n",
" <td>-0.176501</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cc_weighted_60</th>\n",
" <td>-0.350755</td>\n",
" <td>0.503233</td>\n",
" <td>-0.176562</td>\n",
" <td>0.092282</td>\n",
" <td>-0.452798</td>\n",
" <td>0.014738</td>\n",
" <td>-0.317493</td>\n",
" <td>0.664622</td>\n",
" <td>0.016281</td>\n",
" <td>0.019176</td>\n",
" <td>0.006195</td>\n",
" <td>0.000491</td>\n",
" <td>0.019470</td>\n",
" <td>0.018573</td>\n",
" <td>-0.013380</td>\n",
" <td>0.017768</td>\n",
" <td>0.027815</td>\n",
" <td>0.048179</td>\n",
" <td>0.020665</td>\n",
" <td>-0.030637</td>\n",
" <td>0.196739</td>\n",
" <td>0.052487</td>\n",
" <td>-0.165931</td>\n",
" <td>0.291836</td>\n",
" <td>-0.562879</td>\n",
" <td>1.000000</td>\n",
" <td>0.666789</td>\n",
" <td>-0.774173</td>\n",
" <td>0.884327</td>\n",
" <td>0.815443</td>\n",
" <td>-0.530059</td>\n",
" <td>0.505247</td>\n",
" <td>0.870720</td>\n",
" <td>0.108761</td>\n",
" <td>0.348621</td>\n",
" <td>0.827250</td>\n",
" <td>0.214124</td>\n",
" <td>0.282330</td>\n",
" <td>0.648181</td>\n",
" <td>0.100537</td>\n",
" </tr>\n",
" <tr>\n",
" <th>bb_weighted_60</th>\n",
" <td>-0.246233</td>\n",
" <td>0.365989</td>\n",
" <td>-0.143334</td>\n",
" <td>0.066808</td>\n",
" <td>-0.386232</td>\n",
" <td>-0.039319</td>\n",
" <td>-0.195803</td>\n",
" <td>0.759728</td>\n",
" <td>0.217205</td>\n",
" <td>0.192245</td>\n",
" <td>0.017061</td>\n",
" <td>0.282819</td>\n",
" <td>0.214115</td>\n",
" <td>-0.020677</td>\n",
" <td>0.384120</td>\n",
" <td>0.265142</td>\n",
" <td>-0.090398</td>\n",
" <td>0.554164</td>\n",
" <td>0.404154</td>\n",
" <td>-0.211900</td>\n",
" <td>0.722794</td>\n",
" <td>0.621518</td>\n",
" <td>-0.239591</td>\n",
" <td>0.884895</td>\n",
" <td>-0.172858</td>\n",
" <td>0.666789</td>\n",
" <td>1.000000</td>\n",
" <td>-0.044489</td>\n",
" <td>0.542292</td>\n",
" <td>0.965239</td>\n",
" <td>0.105624</td>\n",
" <td>0.229367</td>\n",
" <td>0.817847</td>\n",
" <td>0.432662</td>\n",
" <td>0.164580</td>\n",
" <td>0.739078</td>\n",
" <td>0.384792</td>\n",
" <td>0.172784</td>\n",
" <td>0.648589</td>\n",
" <td>0.220476</td>\n",
" </tr>\n",
" <tr>\n",
" <th>causal_size_step60</th>\n",
" <td>0.261053</td>\n",
" <td>-0.363736</td>\n",
" <td>0.114942</td>\n",
" <td>-0.066962</td>\n",
" <td>0.278934</td>\n",
" <td>-0.061609</td>\n",
" <td>0.259093</td>\n",
" <td>-0.245657</td>\n",
" <td>0.162657</td>\n",
" <td>0.137577</td>\n",
" <td>0.006186</td>\n",
" <td>0.239554</td>\n",
" <td>0.155759</td>\n",
" <td>-0.042458</td>\n",
" <td>0.344189</td>\n",
" <td>0.201380</td>\n",
" <td>-0.114066</td>\n",
" <td>0.406094</td>\n",
" <td>0.315566</td>\n",
" <td>-0.138908</td>\n",
" <td>0.350174</td>\n",
" <td>0.457526</td>\n",
" <td>0.018936</td>\n",
" <td>0.360375</td>\n",
" <td>0.607728</td>\n",
" <td>-0.774173</td>\n",
" <td>-0.044489</td>\n",
" <td>1.000000</td>\n",
" <td>-0.724853</td>\n",
" <td>-0.273284</td>\n",
" <td>0.800261</td>\n",
" <td>-0.482476</td>\n",
" <td>-0.472572</td>\n",
" <td>0.221686</td>\n",
" <td>-0.327544</td>\n",
" <td>-0.481202</td>\n",
" <td>0.039787</td>\n",
" <td>-0.231712</td>\n",
" <td>-0.318015</td>\n",
" <td>0.052490</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cc_weighted_80</th>\n",
" <td>-0.334209</td>\n",
" <td>0.619542</td>\n",
" <td>-0.140039</td>\n",
" <td>0.178726</td>\n",
" <td>-0.474177</td>\n",
" <td>-0.035928</td>\n",
" <td>-0.311229</td>\n",
" <td>0.435070</td>\n",
" <td>0.019825</td>\n",
" <td>0.017496</td>\n",
" <td>0.001505</td>\n",
" <td>0.016462</td>\n",
" <td>0.019018</td>\n",
" <td>0.005183</td>\n",
" <td>0.005003</td>\n",
" <td>0.020603</td>\n",
" <td>0.014487</td>\n",
" <td>0.073476</td>\n",
" <td>0.033773</td>\n",
" <td>-0.044817</td>\n",
" <td>0.141216</td>\n",
" <td>0.064464</td>\n",
" <td>-0.095979</td>\n",
" <td>0.217046</td>\n",
" <td>-0.346270</td>\n",
" <td>0.884327</td>\n",
" <td>0.542292</td>\n",
" <td>-0.724853</td>\n",
" <td>1.000000</td>\n",
" <td>0.731658</td>\n",
" <td>-0.775709</td>\n",
" <td>0.758256</td>\n",
" <td>0.894891</td>\n",
" <td>-0.210347</td>\n",
" <td>0.550649</td>\n",
" <td>0.889318</td>\n",
" <td>-0.001488</td>\n",
" <td>0.410744</td>\n",
" <td>0.674832</td>\n",
" <td>-0.022942</td>\n",
" </tr>\n",
" <tr>\n",
" <th>bb_weighted_80</th>\n",
" <td>-0.290207</td>\n",
" <td>0.468312</td>\n",
" <td>-0.160778</td>\n",
" <td>0.099995</td>\n",
" <td>-0.442606</td>\n",
" <td>-0.046444</td>\n",
" <td>-0.244178</td>\n",
" <td>0.774564</td>\n",
" <td>0.159568</td>\n",
" <td>0.141574</td>\n",
" <td>0.012887</td>\n",
" <td>0.205261</td>\n",
" <td>0.157492</td>\n",
" <td>-0.012966</td>\n",
" <td>0.277689</td>\n",
" <td>0.194306</td>\n",
" <td>-0.062948</td>\n",
" <td>0.439312</td>\n",
" <td>0.300505</td>\n",
" <td>-0.184767</td>\n",
" <td>0.626304</td>\n",
" <td>0.484415</td>\n",
" <td>-0.254331</td>\n",
" <td>0.764009</td>\n",
" <td>-0.294168</td>\n",
" <td>0.815443</td>\n",
" <td>0.965239</td>\n",
" <td>-0.273284</td>\n",
" <td>0.731658</td>\n",
" <td>1.000000</td>\n",
" <td>-0.137357</td>\n",
" <td>0.387513</td>\n",
" <td>0.924109</td>\n",
" <td>0.315882</td>\n",
" <td>0.271615</td>\n",
" <td>0.856583</td>\n",
" <td>0.339440</td>\n",
" <td>0.240999</td>\n",
" <td>0.730133</td>\n",
" <td>0.197403</td>\n",
" </tr>\n",
" <tr>\n",
" <th>causal_size_step80</th>\n",
" <td>0.216959</td>\n",
" <td>-0.466680</td>\n",
" <td>0.054639</td>\n",
" <td>-0.167128</td>\n",
" <td>0.279251</td>\n",
" <td>0.004799</td>\n",
" <td>0.225678</td>\n",
" <td>0.084900</td>\n",
" <td>0.118920</td>\n",
" <td>0.105645</td>\n",
" <td>0.009744</td>\n",
" <td>0.166109</td>\n",
" <td>0.118172</td>\n",
" <td>-0.019534</td>\n",
" <td>0.249813</td>\n",
" <td>0.149951</td>\n",
" <td>-0.079328</td>\n",
" <td>0.299948</td>\n",
" <td>0.229132</td>\n",
" <td>-0.105935</td>\n",
" <td>0.374634</td>\n",
" <td>0.354799</td>\n",
" <td>-0.095994</td>\n",
" <td>0.391932</td>\n",
" <td>0.230816</td>\n",
" <td>-0.530059</td>\n",
" <td>0.105624</td>\n",
" <td>0.800261</td>\n",
" <td>-0.775709</td>\n",
" <td>-0.137357</td>\n",
" <td>1.000000</td>\n",
" <td>-0.743046</td>\n",
" <td>-0.444807</td>\n",
" <td>0.598094</td>\n",
" <td>-0.548675</td>\n",
" <td>-0.499224</td>\n",
" <td>0.316415</td>\n",
" <td>-0.373726</td>\n",
" <td>-0.304626</td>\n",
" <td>0.216092</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cc_weighted_120</th>\n",
" <td>-0.271450</td>\n",
" <td>0.745436</td>\n",
" <td>0.040982</td>\n",
" <td>0.371613</td>\n",
" <td>-0.472386</td>\n",
" <td>0.124796</td>\n",
" <td>-0.276848</td>\n",
" <td>0.067352</td>\n",
" <td>0.000581</td>\n",
" <td>0.008441</td>\n",
" <td>0.008223</td>\n",
" <td>-0.018795</td>\n",
" <td>0.007022</td>\n",
" <td>0.022080</td>\n",
" <td>-0.042570</td>\n",
" <td>0.001137</td>\n",
" <td>0.037898</td>\n",
" <td>-0.019067</td>\n",
" <td>-0.008549</td>\n",
" <td>0.011811</td>\n",
" <td>0.000366</td>\n",
" <td>-0.026651</td>\n",
" <td>-0.023397</td>\n",
" <td>0.004981</td>\n",
" <td>-0.078034</td>\n",
" <td>0.505247</td>\n",
" <td>0.229367</td>\n",
" <td>-0.482476</td>\n",
" <td>0.758256</td>\n",
" <td>0.387513</td>\n",
" <td>-0.743046</td>\n",
" <td>1.000000</td>\n",
" <td>0.670525</td>\n",
" <td>-0.739708</td>\n",
" <td>0.920013</td>\n",
" <td>0.765258</td>\n",
" <td>-0.589035</td>\n",
" <td>0.718785</td>\n",
" <td>0.529450</td>\n",
" <td>-0.451219</td>\n",
" </tr>\n",
" <tr>\n",
" <th>bb_weighted_120</th>\n",
" <td>-0.320824</td>\n",
" <td>0.644580</td>\n",
" <td>-0.123307</td>\n",
" <td>0.211026</td>\n",
" <td>-0.509751</td>\n",
" <td>0.009955</td>\n",
" <td>-0.285256</td>\n",
" <td>0.652547</td>\n",
" <td>0.094481</td>\n",
" <td>0.088304</td>\n",
" <td>0.012249</td>\n",
" <td>0.116565</td>\n",
" <td>0.097205</td>\n",
" <td>0.000205</td>\n",
" <td>0.149458</td>\n",
" <td>0.116842</td>\n",
" <td>-0.022679</td>\n",
" <td>0.278811</td>\n",
" <td>0.179856</td>\n",
" <td>-0.126428</td>\n",
" <td>0.445147</td>\n",
" <td>0.301223</td>\n",
" <td>-0.217947</td>\n",
" <td>0.545377</td>\n",
" <td>-0.331714</td>\n",
" <td>0.870720</td>\n",
" <td>0.817847</td>\n",
" <td>-0.472572</td>\n",
" <td>0.894891</td>\n",
" <td>0.924109</td>\n",
" <td>-0.444807</td>\n",
" <td>0.670525</td>\n",
" <td>1.000000</td>\n",
" <td>0.003245</td>\n",
" <td>0.522245</td>\n",
" <td>0.979178</td>\n",
" <td>0.109074</td>\n",
" <td>0.416676</td>\n",
" <td>0.809457</td>\n",
" <td>0.055523</td>\n",
" </tr>\n",
" <tr>\n",
" <th>causal_size_step120</th>\n",
" <td>0.074887</td>\n",
" <td>-0.420112</td>\n",
" <td>-0.167086</td>\n",
" <td>-0.309489</td>\n",
" <td>0.174362</td>\n",
" <td>-0.143363</td>\n",
" <td>0.113570</td>\n",
" <td>0.501109</td>\n",
" <td>0.084916</td>\n",
" <td>0.068719</td>\n",
" <td>0.000027</td>\n",
" <td>0.131064</td>\n",
" <td>0.078705</td>\n",
" <td>-0.029576</td>\n",
" <td>0.192946</td>\n",
" <td>0.104449</td>\n",
" <td>-0.071654</td>\n",
" <td>0.278595</td>\n",
" <td>0.174662</td>\n",
" <td>-0.130597</td>\n",
" <td>0.403276</td>\n",
" <td>0.309148</td>\n",
" <td>-0.166151</td>\n",
" <td>0.487971</td>\n",
" <td>-0.195699</td>\n",
" <td>0.108761</td>\n",
" <td>0.432662</td>\n",
" <td>0.221686</td>\n",
" <td>-0.210347</td>\n",
" <td>0.315882</td>\n",
" <td>0.598094</td>\n",
" <td>-0.739708</td>\n",
" <td>0.003245</td>\n",
" <td>1.000000</td>\n",
" <td>-0.766389</td>\n",
" <td>-0.143333</td>\n",
" <td>0.892899</td>\n",
" <td>-0.590910</td>\n",
" <td>0.020568</td>\n",
" <td>0.658564</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cc_weighted_150</th>\n",
" <td>-0.302172</td>\n",
" <td>0.719586</td>\n",
" <td>0.044275</td>\n",
" <td>0.413040</td>\n",
" <td>-0.516936</td>\n",
" <td>0.117644</td>\n",
" <td>-0.278183</td>\n",
" <td>-0.010402</td>\n",
" <td>0.001302</td>\n",
" <td>0.016434</td>\n",
" <td>0.015866</td>\n",
" <td>-0.022937</td>\n",
" <td>0.014384</td>\n",
" <td>0.032612</td>\n",
" <td>-0.050180</td>\n",
" <td>0.006648</td>\n",
" <td>0.049521</td>\n",
" <td>-0.033317</td>\n",
" <td>-0.009261</td>\n",
" <td>0.025430</td>\n",
" <td>0.020733</td>\n",
" <td>-0.029847</td>\n",
" <td>-0.048023</td>\n",
" <td>-0.011948</td>\n",
" <td>0.002510</td>\n",
" <td>0.348621</td>\n",
" <td>0.164580</td>\n",
" <td>-0.327544</td>\n",
" <td>0.550649</td>\n",
" <td>0.271615</td>\n",
" <td>-0.548675</td>\n",
" <td>0.920013</td>\n",
" <td>0.522245</td>\n",
" <td>-0.766389</td>\n",
" <td>1.000000</td>\n",
" <td>0.651829</td>\n",
" <td>-0.786732</td>\n",
" <td>0.890199</td>\n",
" <td>0.459665</td>\n",
" <td>-0.682527</td>\n",
" </tr>\n",
" <tr>\n",
" <th>bb_weighted_150</th>\n",
" <td>-0.313927</td>\n",
" <td>0.711037</td>\n",
" <td>-0.098405</td>\n",
" <td>0.288933</td>\n",
" <td>-0.537918</td>\n",
" <td>0.029261</td>\n",
" <td>-0.270781</td>\n",
" <td>0.576002</td>\n",
" <td>0.083766</td>\n",
" <td>0.078391</td>\n",
" <td>0.010965</td>\n",
" <td>0.099332</td>\n",
" <td>0.086072</td>\n",
" <td>0.003329</td>\n",
" <td>0.117863</td>\n",
" <td>0.102113</td>\n",
" <td>-0.008777</td>\n",
" <td>0.230196</td>\n",
" <td>0.152257</td>\n",
" <td>-0.101210</td>\n",
" <td>0.395378</td>\n",
" <td>0.254321</td>\n",
" <td>-0.204995</td>\n",
" <td>0.473341</td>\n",
" <td>-0.299684</td>\n",
" <td>0.827250</td>\n",
" <td>0.739078</td>\n",
" <td>-0.481202</td>\n",
" <td>0.889318</td>\n",
" <td>0.856583</td>\n",
" <td>-0.499224</td>\n",
" <td>0.765258</td>\n",
" <td>0.979178</td>\n",
" <td>-0.143333</td>\n",
" <td>0.651829</td>\n",
" <td>1.000000</td>\n",
" <td>-0.044679</td>\n",
" <td>0.535718</td>\n",
" <td>0.860410</td>\n",
" <td>-0.042384</td>\n",
" </tr>\n",
" <tr>\n",
" <th>causal_size_step150</th>\n",
" <td>0.142523</td>\n",
" <td>-0.369146</td>\n",
" <td>-0.138423</td>\n",
" <td>-0.308915</td>\n",
" <td>0.243109</td>\n",
" <td>-0.120829</td>\n",
" <td>0.145253</td>\n",
" <td>0.482557</td>\n",
" <td>0.066469</td>\n",
" <td>0.042160</td>\n",
" <td>-0.011976</td>\n",
" <td>0.111069</td>\n",
" <td>0.051112</td>\n",
" <td>-0.040251</td>\n",
" <td>0.162041</td>\n",
" <td>0.074360</td>\n",
" <td>-0.072378</td>\n",
" <td>0.231264</td>\n",
" <td>0.136134</td>\n",
" <td>-0.115882</td>\n",
" <td>0.294518</td>\n",
" <td>0.246330</td>\n",
" <td>-0.103600</td>\n",
" <td>0.401030</td>\n",
" <td>-0.247244</td>\n",
" <td>0.214124</td>\n",
" <td>0.384792</td>\n",
" <td>0.039787</td>\n",
" <td>-0.001488</td>\n",
" <td>0.339440</td>\n",
" <td>0.316415</td>\n",
" <td>-0.589035</td>\n",
" <td>0.109074</td>\n",
" <td>0.892899</td>\n",
" <td>-0.786732</td>\n",
" <td>-0.044679</td>\n",
" <td>1.000000</td>\n",
" <td>-0.736602</td>\n",
" <td>0.094836</td>\n",
" <td>0.864597</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cc_weighted_200</th>\n",
" <td>-0.422151</td>\n",
" <td>0.705825</td>\n",
" <td>-0.068797</td>\n",
" <td>0.352685</td>\n",
" <td>-0.641033</td>\n",
" <td>0.060222</td>\n",
" <td>-0.379649</td>\n",
" <td>0.004544</td>\n",
" <td>-0.001095</td>\n",
" <td>0.020298</td>\n",
" <td>0.021852</td>\n",
" <td>-0.022974</td>\n",
" <td>0.017804</td>\n",
" <td>0.035974</td>\n",
" <td>-0.049278</td>\n",
" <td>0.009466</td>\n",
" <td>0.051313</td>\n",
" <td>-0.020847</td>\n",
" <td>-0.006681</td>\n",
" <td>0.015164</td>\n",
" <td>0.081155</td>\n",
" <td>-0.011477</td>\n",
" <td>-0.097042</td>\n",
" <td>0.026161</td>\n",
" <td>0.016778</td>\n",
" <td>0.282330</td>\n",
" <td>0.172784</td>\n",
" <td>-0.231712</td>\n",
" <td>0.410744</td>\n",
" <td>0.240999</td>\n",
" <td>-0.373726</td>\n",
" <td>0.718785</td>\n",
" <td>0.416676</td>\n",
" <td>-0.590910</td>\n",
" <td>0.890199</td>\n",
" <td>0.535718</td>\n",
" <td>-0.736602</td>\n",
" <td>1.000000</td>\n",
" <td>0.429202</td>\n",
" <td>-0.821709</td>\n",
" </tr>\n",
" <tr>\n",
" <th>bb_weighted_200</th>\n",
" <td>-0.141308</td>\n",
" <td>0.602888</td>\n",
" <td>-0.063644</td>\n",
" <td>0.356759</td>\n",
" <td>-0.404657</td>\n",
" <td>0.000712</td>\n",
" <td>-0.066175</td>\n",
" <td>0.546441</td>\n",
" <td>0.100864</td>\n",
" <td>0.088914</td>\n",
" <td>0.007552</td>\n",
" <td>0.127136</td>\n",
" <td>0.098878</td>\n",
" <td>-0.006736</td>\n",
" <td>0.132915</td>\n",
" <td>0.119070</td>\n",
" <td>-0.006321</td>\n",
" <td>0.244359</td>\n",
" <td>0.170120</td>\n",
" <td>-0.100267</td>\n",
" <td>0.421935</td>\n",
" <td>0.285359</td>\n",
" <td>-0.206717</td>\n",
" <td>0.488449</td>\n",
" <td>-0.250673</td>\n",
" <td>0.648181</td>\n",
" <td>0.648589</td>\n",
" <td>-0.318015</td>\n",
" <td>0.674832</td>\n",
" <td>0.730133</td>\n",
" <td>-0.304626</td>\n",
" <td>0.529450</td>\n",
" <td>0.809457</td>\n",
" <td>0.020568</td>\n",
" <td>0.459665</td>\n",
" <td>0.860410</td>\n",
" <td>0.094836</td>\n",
" <td>0.429202</td>\n",
" <td>1.000000</td>\n",
" <td>0.162067</td>\n",
" </tr>\n",
" <tr>\n",
" <th>causal_size_step200</th>\n",
" <td>0.372049</td>\n",
" <td>-0.390721</td>\n",
" <td>0.035004</td>\n",
" <td>-0.160210</td>\n",
" <td>0.445014</td>\n",
" <td>-0.063900</td>\n",
" <td>0.372963</td>\n",
" <td>0.339829</td>\n",
" <td>0.064839</td>\n",
" <td>0.033928</td>\n",
" <td>-0.019108</td>\n",
" <td>0.105320</td>\n",
" <td>0.042939</td>\n",
" <td>-0.043553</td>\n",
" <td>0.137705</td>\n",
" <td>0.064790</td>\n",
" <td>-0.060049</td>\n",
" <td>0.176962</td>\n",
" <td>0.114642</td>\n",
" <td>-0.079834</td>\n",
" <td>0.177568</td>\n",
" <td>0.192596</td>\n",
" <td>-0.024414</td>\n",
" <td>0.279621</td>\n",
" <td>-0.176501</td>\n",
" <td>0.100537</td>\n",
" <td>0.220476</td>\n",
" <td>0.052490</td>\n",
" <td>-0.022942</td>\n",
" <td>0.197403</td>\n",
" <td>0.216092</td>\n",
" <td>-0.451219</td>\n",
" <td>0.055523</td>\n",
" <td>0.658564</td>\n",
" <td>-0.682527</td>\n",
" <td>-0.042384</td>\n",
" <td>0.864597</td>\n",
" <td>-0.821709</td>\n",
" <td>0.162067</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>\n",
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" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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" const element = document.querySelector('#df-852460f5-d289-4781-a2e8-a37e3a8fac30');\n",
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" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
" [key], {});\n",
" if (!dataTable) return;\n",
"\n",
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
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" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
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],
"text/plain": [
" nok usd ... bb_weighted_200 causal_size_step200\n",
"nok 1.000000 -0.259508 ... -0.141308 0.372049\n",
"usd -0.259508 1.000000 ... 0.602888 -0.390721\n",
"eur 0.803596 0.122163 ... -0.063644 0.035004\n",
"gbp 0.582291 0.502560 ... 0.356759 -0.160210\n",
"brent 0.896812 -0.550984 ... -0.404657 0.445014\n",
"gdp yoy 0.258060 0.330808 ... 0.000712 -0.063900\n",
"interest rate 0.948522 -0.284277 ... -0.066175 0.372963\n",
"cc_weighted_40 -0.141402 0.237304 ... 0.546441 0.339829\n",
"cc_weighted_2 -0.056319 0.026735 ... 0.100864 0.064839\n",
"bb_weighted_2 -0.064972 0.021255 ... 0.088914 0.033928\n",
"causal_size_step2 -0.020026 -0.000384 ... 0.007552 -0.019108\n",
"cc_weighted_3 -0.021618 0.014072 ... 0.127136 0.105320\n",
"bb_weighted_3 -0.067087 0.023031 ... 0.098878 0.042939\n",
"causal_size_step3 -0.047840 0.011031 ... -0.006736 -0.043553\n",
"cc_weighted_5 0.005980 -0.005367 ... 0.132915 0.137705\n",
"bb_weighted_5 -0.065978 0.024029 ... 0.119070 0.064790\n",
"causal_size_step5 -0.065444 0.026596 ... -0.006321 -0.060049\n",
"cc_weighted_10 -0.041579 0.023814 ... 0.244359 0.176962\n",
"bb_weighted_10 -0.060965 0.025707 ... 0.170120 0.114642\n",
"causal_size_step10 -0.009961 -0.002068 ... -0.100267 -0.079834\n",
"cc_weighted_20 -0.064844 0.193440 ... 0.421935 0.177568\n",
"bb_weighted_20 -0.053142 0.053981 ... 0.285359 0.192596\n",
"causal_size_step20 0.023753 -0.161100 ... -0.206717 -0.024414\n",
"bb_weighted_40 -0.097234 0.167541 ... 0.488449 0.279621\n",
"causal_size_step40 0.089757 -0.146911 ... -0.250673 -0.176501\n",
"cc_weighted_60 -0.350755 0.503233 ... 0.648181 0.100537\n",
"bb_weighted_60 -0.246233 0.365989 ... 0.648589 0.220476\n",
"causal_size_step60 0.261053 -0.363736 ... -0.318015 0.052490\n",
"cc_weighted_80 -0.334209 0.619542 ... 0.674832 -0.022942\n",
"bb_weighted_80 -0.290207 0.468312 ... 0.730133 0.197403\n",
"causal_size_step80 0.216959 -0.466680 ... -0.304626 0.216092\n",
"cc_weighted_120 -0.271450 0.745436 ... 0.529450 -0.451219\n",
"bb_weighted_120 -0.320824 0.644580 ... 0.809457 0.055523\n",
"causal_size_step120 0.074887 -0.420112 ... 0.020568 0.658564\n",
"cc_weighted_150 -0.302172 0.719586 ... 0.459665 -0.682527\n",
"bb_weighted_150 -0.313927 0.711037 ... 0.860410 -0.042384\n",
"causal_size_step150 0.142523 -0.369146 ... 0.094836 0.864597\n",
"cc_weighted_200 -0.422151 0.705825 ... 0.429202 -0.821709\n",
"bb_weighted_200 -0.141308 0.602888 ... 1.000000 0.162067\n",
"causal_size_step200 0.372049 -0.390721 ... 0.162067 1.000000\n",
"\n",
"[40 rows x 40 columns]"
]
},
"metadata": {},
"execution_count": 33
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "ZfnPH5Jysx2z",
"outputId": "fdaaabb9-9494-47f5-f1fb-06c04d16f910",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 350
}
},
"source": [
"#identification\n",
"#first of first, using scatter plot to visualize the correlation\n",
"#lets denote data from 2013-4-25 to 2017-4-25 as estimation horizon/training set\n",
"#lets denote data from 2017-4-25 to 2018-4-25 as validation horizon/testing set\n",
"ax=plt.figure(figsize=(10,5)).add_subplot(111)\n",
"ax.spines['top'].set_visible(False)\n",
"ax.spines['right'].set_visible(False)\n",
"ax.scatter(df['brent'][df.index<'2017-04-25'],df['nok'][df.index<'2017-04-25'],s=1,c='#5f0f4e')\n",
"\n",
"plt.title('NOK Brent Correlation')\n",
"plt.xlabel('Brent in JPY')\n",
"plt.ylabel('NOKJPY')\n",
"plt.show()"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "RNwMlDYcjGuo",
"outputId": "b7ca45e3-678b-4227-8edb-b87e584c13aa",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
}
},
"source": [
"df.tail()#dual axis plot\n",
"def dual_axis_plot(xaxis,data1,data2,fst_color='r',\n",
" sec_color='b',fig_size=(10,5),\n",
" x_label='',y_label1='',y_label2='',\n",
" legend1='',legend2='',grid=False,title=''):\n",
"\n",
" fig=plt.figure(figsize=fig_size)\n",
" ax=fig.add_subplot(111)\n",
"\n",
"\n",
" ax.set_xlabel(x_label)\n",
" ax.set_ylabel(y_label1, color=fst_color)\n",
" ax.plot(xaxis, data1, color=fst_color,label=legend1)\n",
" ax.tick_params(axis='y',labelcolor=fst_color)\n",
" ax.yaxis.labelpad=15\n",
"\n",
" plt.legend(loc=3)\n",
" ax2 = ax.twinx()\n",
"\n",
" ax2.set_ylabel(y_label2, color=sec_color,rotation=270)\n",
" ax2.plot(xaxis, data2, color=sec_color,label=legend2)\n",
" ax2.tick_params(axis='y',labelcolor=sec_color)\n",
" ax2.yaxis.labelpad=15\n",
"\n",
" fig.tight_layout()\n",
" plt.legend(loc=4)\n",
" plt.grid(grid)\n",
" plt.title(title)\n",
" plt.show()\n",
"\n",
"#nok vs ir\n",
"dual_axis_plot(df.index,df['nok'],df['interest rate'],\n",
" fst_color='#34262b',sec_color='#cb2800',\n",
" fig_size=(10,5),x_label='Date',\n",
" y_label1='NOKJPY',y_label2='Norges Bank Interest Rate %',\n",
" legend1='NOKJPY',legend2='Interest Rate',\n",
" grid=False,title='NOK vs Interest Rate')\n",
"\n",
"#nok vs brent\n",
"dual_axis_plot(df.index,df['nok'],df['brent'],\n",
" fst_color='#4f2d20',sec_color='#3feee6',\n",
" fig_size=(10,5),x_label='Date',\n",
" y_label1='NOKJPY',y_label2='Brent in JPY',\n",
" legend1='NOKJPY',legend2='Brent',\n",
" grid=False,title='NOK vs Brent')\n",
"\n",
"#nok vs gdp\n",
"#cuz gdp is released quarterly\n",
"#we need to convert nok into quarterly data as well\n",
"ind=df['gdp yoy'].dropna().index\n",
"dual_axis_plot(df.loc[ind].index,\n",
" df['nok'].loc[ind],\n",
" df['gdp yoy'].dropna(),\n",
" fst_color='#116466',sec_color='#ff652f',\n",
" fig_size=(10,5),x_label='Date',\n",
" y_label1='NOKJPY',y_label2='Norway GDP YoY %',\n",
" legend1='NOKJPY',legend2='GDP',\n",
" grid=False,title='NOK vs GDP')\n"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x360 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
}
},
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x360 with 2 Axes>"
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x360 with 2 Axes>"
]
},
"metadata": {}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "jKCh1BYgye0T"
},
"source": [
"df = df.ffill().fillna(df.mean()) ## this filling operations can be vastly improved (stay tuned)"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "EOH5eMgo3G8J"
},
"source": [
"# You don't have to shift, you are not predicting next day return, just establishing fundamental relationship\n",
"# df['nok'][df.index<'2017-04-25'].shift(1).head()"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"y"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "YoEulrJt5Yze",
"outputId": "79d056d8-de51-4734-b058-e542a1ead8d4"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"date\n",
"2013-04-25 NaN\n",
"2013-04-26 16.901885\n",
"2013-04-29 16.760666\n",
"2013-04-30 16.818312\n",
"2013-05-01 16.882766\n",
" ... \n",
"2017-04-18 12.726046\n",
"2017-04-19 12.739178\n",
"2017-04-20 12.687538\n",
"2017-04-21 12.680378\n",
"2017-04-24 12.580594\n",
"Name: nok, Length: 1031, dtype: float64"
]
},
"metadata": {},
"execution_count": 53
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "mrTEkT0naNxI",
"outputId": "686d7140-cfde-45d7-f5a3-5444641ecb7a",
"colab": {
"base_uri": "https://localhost:8080/"
}
},
"source": [
"#Now we do our linear regression\n",
"x0=pd.concat([df['usd'],df['gbp'],df['eur'],df['brent'],df['causal_size_step200'],df['causal_size_step60'],df['causal_size_step20'],df['causal_size_step10']],axis=1)\n",
"x1=sm.add_constant(x0)\n",
"x=x1[x1.index<'2017-04-25']\n",
"y=df['nok'][df.index<'2017-04-25'].shift(1).bfill()\n",
"\n",
"model=sm.OLS(y,x).fit()\n",
"print(model.summary(),'\\n')"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
" OLS Regression Results \n",
"==============================================================================\n",
"Dep. Variable: nok R-squared: 0.958\n",
"Model: OLS Adj. R-squared: 0.957\n",
"Method: Least Squares F-statistic: 2882.\n",
"Date: Mon, 31 Jan 2022 Prob (F-statistic): 0.00\n",
"Time: 16:09:20 Log-Likelihood: -360.78\n",
"No. Observations: 1031 AIC: 739.6\n",
"Df Residuals: 1022 BIC: 784.0\n",
"Df Model: 8 \n",
"Covariance Type: nonrobust \n",
"=======================================================================================\n",
" coef std err t P>|t| [0.025 0.975]\n",
"---------------------------------------------------------------------------------------\n",
"const 1.2322 0.352 3.505 0.000 0.542 1.922\n",
"usd 0.0068 0.003 2.190 0.029 0.001 0.013\n",
"gbp 0.0124 0.002 5.930 0.000 0.008 0.016\n",
"eur 0.0599 0.004 14.851 0.000 0.052 0.068\n",
"brent 0.0004 1.08e-05 38.071 0.000 0.000 0.000\n",
"causal_size_step200 0.2572 0.036 7.066 0.000 0.186 0.329\n",
"causal_size_step60 0.3353 0.029 11.402 0.000 0.278 0.393\n",
"causal_size_step20 -0.0194 0.024 -0.815 0.415 -0.066 0.027\n",
"causal_size_step10 -0.0066 0.019 -0.343 0.732 -0.045 0.031\n",
"==============================================================================\n",
"Omnibus: 39.928 Durbin-Watson: 0.231\n",
"Prob(Omnibus): 0.000 Jarque-Bera (JB): 48.051\n",
"Skew: 0.421 Prob(JB): 3.68e-11\n",
"Kurtosis: 3.639 Cond. No. 2.69e+05\n",
"==============================================================================\n",
"\n",
"Warnings:\n",
"[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
"[2] The condition number is large, 2.69e+05. This might indicate that there are\n",
"strong multicollinearity or other numerical problems. \n",
"\n"
]
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "z5_EinFK0T8n"
},
"source": [
"Sometimes condition numbers are used (see the appendix). An informal rule of thumb is that if the condition number is 15, multicollinearity is a concern; if it is greater than 30 multicollinearity is a very serious concern. (But again, these are just informal rules of thumb.)"
]
},
{
"cell_type": "code",
"metadata": {
"id": "bzWvyShUyYRg",
"outputId": "6dc3b0f5-d5be-4cec-d219-9fb7aa063fd5",
"colab": {
"base_uri": "https://localhost:8080/"
}
},
"source": [
"#from the summary (above) you can tell there is multicollinearity\n",
"#the condition number is skyrocketing\n",
"#alternatively, i can use elastic net regression to achieve the convergence\n",
"m=en(alphas=[0.0001, 0.0005, 0.001, 0.01, 0.1, 1, 10],\n",
" l1_ratio=[.01, .1, .5, .9, .99], max_iter=5000).fit(x0[x0.index<'2017-04-25'], y)\n",
"print(m.intercept_,m.coef_)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"3.8681806302685704 [ 0.00288207 0.02039073 0.0282364 0.00049658 0. 0.\n",
" -0. -0. ]\n"
]
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "GfdQVfHy2F7t",
"outputId": "9fbfa8a3-872c-4fc3-9928-36ebe9d1ac46",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 342
}
},
"source": [
"#calculate the fitted value of nok\n",
"df['sk_fit']=(df['usd']*m.coef_[0]+df['gbp']*m.coef_[1]+\n",
" df['eur']*m.coef_[2]+df['brent']*m.coef_[3]+m.intercept_)\n",
"\n",
"\n",
"# In[6]:\n",
"\n",
"\n",
"#getting the residual\n",
"df['sk_residual']=df['nok']-df['sk_fit']\n",
"\n",
"\n",
"#one can always argue what if we eliminate some regressors\n",
"#in econometrics, if adding extra variables do not decrease adjusted r squared\n",
"#or worsen AIC, BIC\n",
"#we should include more information as long as it makes sense\n",
"\n",
"#lets generate signals based on the elastic net\n",
"#we set one sigma of the residual as thresholds\n",
"#two sigmas of the residual as stop orders\n",
"#which is common practise in statistics\n",
"upper=np.std(df['sk_residual'][df.index<'2017-04-25'])\n",
"lower=-upper\n",
"\n",
"signals=pd.concat([df[i] for i in ['nok', 'usd', 'eur', 'gbp', 'brent', 'sk_fit','sk_residual']], \\\n",
" axis=1)[df.index>='2017-04-25']\n",
"signals['fitted']=signals['sk_fit']\n",
"del signals['sk_fit']\n",
"\n",
"signals['upper']=signals['fitted']+upper\n",
"signals['lower']=signals['fitted']+lower\n",
"signals['stop profit']=signals['fitted']+2*upper\n",
"signals['stop loss']=signals['fitted']+2*lower\n",
"signals['signals']=0\n",
"\n",
"#while doing a traversal\n",
"#we apply the rules mentioned before\n",
"#if actual price goes beyond upper threshold\n",
"#we take a short and bet on its reversion process\n",
"#vice versa\n",
"#we use cumsum to make sure our signals only get generated\n",
"#for the first time condions are met\n",
"#when actual price hits the stop order boundary\n",
"#we revert our positions\n",
"#u may wonder whats next for breaking the boundary\n",
"#well, we stop the signal generation algorithm\n",
"#we need to recalibrate our model or use other trend following strategies\n",
"\n",
"index=list(signals.columns).index('signals')\n",
"\n",
"for j in range(len(signals)):\n",
"\n",
" if signals['nok'].iloc[j]>signals['upper'].iloc[j]:\n",
" signals.iloc[j,index]=-1\n",
"\n",
" if signals['nok'].iloc[j]<signals['lower'].iloc[j]:\n",
" signals.iloc[j,index]=1\n",
"\n",
" signals['cumsum']=signals['signals'].cumsum()\n",
"\n",
" if signals['cumsum'].iloc[j]>1 or signals['cumsum'].iloc[j]<-1:\n",
" signals.iloc[j,index]=0\n",
"\n",
" if signals['nok'].iloc[j]>signals['stop profit'].iloc[j]:\n",
" signals['cumsum']=signals['signals'].cumsum()\n",
" signals.iloc[j,index]=-signals['cumsum'].iloc[j]+1\n",
" signals['cumsum']=signals['signals'].cumsum()\n",
" break\n",
"\n",
" if signals['nok'].iloc[j]<signals['stop loss'].iloc[j]:\n",
" signals['cumsum']=signals['signals'].cumsum()\n",
" signals.iloc[j,index]=-signals['cumsum'].iloc[j]-1\n",
" signals['cumsum']=signals['signals'].cumsum()\n",
" break\n",
"\n",
"\n",
"# In[9]:\n",
"\n",
"\n",
"#next, we plot the usual positions as the first figure\n",
"ax=plt.figure(figsize=(10,5)).add_subplot(111)\n",
"ax.spines['top'].set_visible(False)\n",
"ax.spines['right'].set_visible(False)\n",
"\n",
"signals['nok'].plot(label='NOKJPY',c='#594f4f',alpha=0.5)\n",
"ax.plot(signals.loc[signals['signals']>0].index,\n",
" signals['nok'][signals['signals']>0],\n",
" lw=0,marker='^',c='#83af9b',label='LONG', markersize=10)\n",
"ax.plot(signals.loc[signals['signals']<0].index,\n",
" signals['nok'][signals['signals']<0],\n",
" lw=0,marker='v',c='#fe4365',label='SHORT', markersize=10)\n",
"ax.plot(pd.to_datetime('2017-12-20'),\n",
" signals['nok'].loc['2017-12-20'],\n",
" lw=0,marker='*',c='#f9d423', markersize=15, alpha=0.8,\n",
" label='Potential Exit Point of Momentum Trading')\n",
"\n",
"# plt.axvline('2017/11/15',linestyle=':',c='k',label='Exit')\n",
"plt.legend()\n",
"plt.title('NOKJPY Positions')\n",
"plt.ylabel('NOKJPY')\n",
"plt.xlabel('Date')\n",
"plt.show()\n"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
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p6OzkyY99zFkjF2lp4djJk2RKKr57PB5dc6YWZZfNsFuVBfx+zZypVVmz3prGmAtAt/2zFaDdb4yZM48hIj7gb4A/Nsb81VqNT6mtIp1Ok4jHnSClliat9WYu1/Kv+7q6u3n/8mVnYfVijDFLFrfNZbMk4nGnddQ9x48zOTHBXUeP4nK7cRuD2+0mmUgQjUbZtXv3gsc7eMcdjI2OOs/l9njIaXCmFmH31fRYr1t/MKgbAtSq1LOUxp8DrwN3isiAiHx2iXPvF5EvWT/+I+DDwE+IyNvW18l6jVOprSCbzXL96lWMMVy6cIEXn33W+UCpleUWn52vq6eHQqHA+BLrR6Ozs/ztX/3V0udYfTrt7N32nTs5evw4LrcbABGhqamJ6elpMul02f6fIsLDjz3GI9YUqNvtJm9NXSk1n/235CvJnOmGALUadcucGWM+XeH2fSXfnwE+Z33/p8Cf1mtcSm1FA7duce7MGVpaW5mZniafzzN6+zY7d++u2XNMTU1RKBSWvVPTVlrvbPuOHWXPudXX5+yc7FxknWl0dhaA8BJN14NNTUxamw8Wa85emk1zu93kNXO26UyMjXHt6lUeePjhFWV7bfa0ppM5CwQ0c6ZWRTsEKLUFxK3F7NNTU8zOzAAwPDRU0+ewd1q2rzBz5vF4aO/sZHSRgq/GGPr7+oDiYv7FRKNRRGTRoAuKwVnOyoSFQqGKY9PgbHO6fu0a/X19JFfZqDxpLf4PBoNAMTjL5XLOa0yp5dLgTKktIG4FM8ODg2QyGdxuN8NDQzVtzjw5MUE4HHbqPK1Ez7ZtTE1OOtmvUlOTk8SsKcv4EsFZLBqlORTCbU1jltPU3AwUs2PN1QRnHo9+0G4yxhhGbt8GiptDViMRj+N2u53uAE4LJ82eqRXS4EypLcDONNlZqb3795NOpZzSF6tljCluBlhh1sy2/8ABXC4X195/f8Ftg/39uFwuOru7l8ycTU9NLTmlCR9kOJqampYM4myaOdt8pqemnKnHajJnqWSSwYGBsq+9RDxOU3OzMxVuX6Do1KZaqTXbramUWj92jS47U3b4rru4eeMGQ4ODK17AXyoej5NKJle83swWCAbZs28ffb29HD12bE4LqKnJSVrb2mhtbaWvt7fsrs1YLEZ0dpYDhw4t+Tx25mypqc9SHo9HNwRsMiMlzeyXCvYB3r98mQtvv+38/YTCYbq6u+nu6WHnrl3E43GardcUFF/HgJbTUCummTOlNrlcNks6laK1rQ0orrcKhUJ0dXcz2N9fk6lNe3H9aoMzgDvuvJN8Pj+nx6UxhumpKVrb2mhqbiabzTqLsEsNDw4CLLqhwNbU1ARUH5xp5mzzuX37Nm3t7fj9/jnTmsYYzp05w80bN5xjvdeu0d7RwUeefJIT991HpKWFwf5+vvvaa/TdvFkMzkqmx50WTlqIVq2QBmdKbXL2+ix7Z2ZLS4vzcywadTYIrMbkxAQej4eW1tZVP1ZLaytHjh6lr7fX+YCMx+NkMhla29qcDEW5dWfDQ0NEWloqBl1NTU34fL6qg0l7zVkt1+ip9RWLRp1gvzQ4G7h1i+tXr3Lp3XcxxpBJp4lGo2zfsYOunh7uuPNOHn38cb7vh34IfyDAyPAwmXTaycYCztozzZypldLgTKlNzg5iunt6CDY1OdOYO3buREQYGhhY9XPYRV9XU46g1F1Hj9Ld08Pbb73FzPQ0M1NTAM6Hqf2ctmw2y2B/f7EMh9WyaSker5dPfOpT7Nm3r6rx2OvSNHu2ORQKBdKpFIFgkGBTk7PmLJvN8s65c3i9XhLxOGOjo07D+7Z5gbzL5aK9vd3Z9Vw6rel2u/H5fLrmTK2YrjlTapOzy2iEwmE+9olPOIFGIBiko7OTgf5+7rrnnlU9RzqdnrM+bLVcLhcPPvIIz37rW7zxne+wbft2XC4XkZYWp43S7MwMiUSC4aEhxkdHKRQK+P1+9u7fX9VzeDzVv/3Z5+bz+WXdTzWmdDqNMYZAIEC2qclpG3bp3XdJpVJ8+IkneO2VV+jr7XWysOU6arR3djrBWWnmDIpTm7pbU62UvssotcnEolHSqRT+YJBgMEg8FsPj8eDz+RYsoN+xaxfvnDtHLBqtev1VOZl0mtZ5H06rFQgGeeiRR3j5hRe4Fo0SiUTweDwYtxuv1+tMO0VaWjh0+DDbd+woFrKtYvflcjmZs1wOahiEqvVhrwULBALk83kymQzjY2Ncf/999h04QFdPD7v27KG/r49wJEI4EsHn8y14nPaSgG1BcKaFaNUqaHCm1Cbz0vPPzykNICJEWlrK9qPcaQVngwMD3HnXXSt+znQmU/bDa7W6enq4+9gxLr7zDi3Whga7NtnszAwPP/ZYTbscLMYOzrS/5uZgZ7QCwaCzjvDN11/H6/Vyz4kTABy5+24GBwaYmpxcNBtrT3V6PJ4F9f0CgQCzZer1KVUNDc6UqtLVK1fI53IcOXp0vYeyKGMMqWSS3Xv30rNtG6lkkmQySfe2bWXPbw6FaGtvZ2gVwVmhUCCbydR0WrPUkbvvppDPs237dufYvadOgUhNyoBUw21NZRY0ONsUSjNntkQ8zqkHH3SCrOZQiIceeYRXX3qJru7uso/j8/mKFz6w4OLHHwiQsqZLlVouDc6UqtKNa9cQkYYOzrKZDMYY2js62HfgQFX32blrF+++8w6JRMIpMbEcGes5V9MZYCkiwtHjx+cc61ikr2a9eEqnNdWGV5o5s6fBOzo7F/zN9Gzfzic+9aklX9tHjx/HFAoLjvv9fjLpNIV8vi5T7Wpz092aSlUhl8sRi0Ybvm5Rxqr9tZwpxh3WtOBKd22u5Dk3GjtzptOam0MqmcTn9+N2uwkEAhy/914eePjhslP/wWBwyV3IO3ftYteePQuOO4Voy9TjU6oSDc6UqkJ0drZY8yiTaegei3ZdpeUESpFIhEhLy7KCs1w265SVyFjPWa/MWSPQUhqbSyqVcqY0RYTDR46sakNMOVqIVq2GBmdKVWFmetr5vpG3xztZrGUGSjt37WJsdLTqopmvvvQSZ0+fBkoCwq0QnDVwYK6ql0om56w3qwctRKtWQ4MzpapQGpylG/hKOLvCKcYdu3ZhjKk6exaNRrk9POxUUAfNnKm1k0mn5/xNLlfKKkBbT3bwp+U01EpocKZUFWamp53io8kGfrNdaRarta0Nn9/vVENfSqFQIJNOk06liEajK5pK3WicNWeaOWsI7128yPPPPEPMKrC8HPaO5rXKnDVypl01Lg3OlKrAGMPM9DTdPT1AY68hyWQyiAher3dZ9xMRwuEwsWi0quewa0ONj46SSadxu91OALMZeTRz1lCis7Pk83neOXdu2ffNWusl650583g8uN1uzZypFdHgTKkK0qkU6XSazu5uRKSh32wz6TRen29FPS5D4TDRKoKz0t9/YnycjFXjrNxOt83CDjx1zVljiMdiuN1uhgYGGLl9e1n3jVqFYeudORMRAoGArjlTK6LBmVIV2G+uTU1NBAIBkhUyZ4V83sksrbXMKir1h0IhkomEM3V388YNhgYHF5xn///wBwJO5mwzrzeD4get2+2uKnM2OzPjBACq9gqFAvF4nAOHDtEcCnH+7NmqigPPzszw6ksv8cK3vw1Q892Z5fgDgYbOtKvGVbfgTES+LCKjIvJumdt+TkSMiJQt7y0iPy4iV62vH6/XGJWqRjabBcDj9RIIBhesISkUCrz52mtcOH8eYwzf+vrXufb+++sx1FUFSvaHVTwWI5NOc+7MGa5evrzgPDtztmv3buLxOJOTk5t6p6bN7fFUXHOWSCR48bnneMvayapqL5VMUigUCEciHL/3XmZnZrhx/fqi52fSad5+6y2effppJsfHOXrsGH//e7+Xdqv1Uj35/X7nYuadc+cY044Bqkr1XCTyFeD3gT8uPSgiu4GPAbfK3UlE2oFfA+4HDPCWiPydMWaqjmNValF2cOb1ehdkzowxnD97llt9fbS1t5O7+27i8fiqdpKtRiaTcRYiL5cdnMWiUUZHRsjn82Wv+u0Pm4N33EHv9eukkkk617hi/3qolDkzxnDmu98lk05r5qyO4tYmgOZQiO6eHnq2bePShQvs2rNnwVTlYH8/Z0+fJpPJsP/gQe4+dqzu05mlAsEg01NT5PN53r98GQOLtoJSqlTdMmfGmJeBclu/fhf4RYqBVzkfB75tjJm0ArJvA0/VZ5RKVWaXp/CWyZxde/99rl+9itfrJZVMOsHMeq1Ly6TTK5/WtIKzaDRKr5WJSCaTC6Zo06kULpeLcCRCj9Wzc7NPa0JxU8BSwdnszAyjt28TCodJp1JOiRFVW/F4HCgGZyLCifvuI5fLcenChQXnXrxwAZ/fz9/7+Me574EH1jQwgw8yZ/YFXc660FOqkjVdcyYinwIGjTHnlzhtJ9Bf8vOAdUypdWFPZXl9PgLBIOlUikKhwODAAO+cO8eu3bs5eMcdpNNpJzhbr+3zmUxmxYGSHXz2Xr/O7MwMLS0t5HK5BVN5qVTK2QCwd/9+YHMXoLW5PZ4lNwTY//Y7dhbfrlZS5kFVFo/FcLlcNFm7LSMtLRw4dKiYxZ33d5dOp+nq7qa1rW09hoo/EKBQKBCdmQG0FIuq3poFZyLSBPwy8IUaPubnReSMiJwZGxur1cMqNUemNHMWCGCMoa+3l9Ovv05bezv3P/wwgWCQQqHAjPUmvB47tAr5PNlsdlX1xkKhEPFYjLb2dg7fdRcAyURizjnpknVt23fupGfbti0xVeN2u5fsrWkHBnZT9mrKkqjli8diBJua5jQT7962DWPMnNeqMYbsKjbI1IKdqZu2ljlo5kxVay0zZweB/cB5EbkJ7ALOisi2eecNArtLft5lHVvAGPOHxpj7jTH3d22BNS9qfWSzWVwuF263m9bWVlwuF2+9+SZ+v59HH38cj8fj1Eyy15qlykwH1psTRK7iwygcieByubj/oYdoamoCWLA7NZ1KOeva3G43jz/xhFMDbjNzezwU8nmiqQR//MrXiKXmBq1OcNbZiYhUVZZELV88Hqc5FJpzzA6CStdI5nI5CoXCumZ17b8T+31BM2eqWmsWnBljLhhjuo0x+4wx+yhOV95njJlfpOZbwMdEpE1E2ihuHvjWWo1Tqfly2SxerxcRoaOri0/+4A/y4COP8PiTTzpBmXOFPFXct1IoFJy1aqVi0Wjd3qDt4Gw167+OHjvG93z0o7S0tjq/2/xNAel0msAWmMacLy+G8/Fhnr/4Jv0Tt3nl8twCqKlUCo/Hg9/vp6m5eU7mLJ/PMzgwUFXJB7W0WCxGc3PznGOBMtX4Mw3QucL+W5yx3hc0OFPVqmcpjT8HXgfuFJEBEfnsEufeLyJfAjDGTAJfBE5bX//WOqbUushmMnhKKu77/X727NtHqOTq3f5wmLWmNQFS86Y2Z2dneeYb36hbmY3MCvtqlgoEg06JgaAVnC2VOdtK+lJTRE2adweuY4Dzt96fkz1LJ5P4A4EF3RaGBgd55hvf4PVXXuH6tWvrNPrNIZ/Pk06lnKyurVyrJOfvYR0vJOwLHHv9oU5rqmrVrZSGMebTFW7fV/L9GeBzJT9/Gfhyvcam1HJUs47LDs5Kd/Olk0mIRJyfL5w7R6FQWLCGq1ZW2ldzMR6vF5/PN2e8uVyObDa7JXZnloqmEgylilNT9nS1MYZXLp/je08+BljNtK3XQSgcZnxsjO+89BLDQ0NEWloIRyLcvH6dQ4cPb+puCvVkZ3Hnt15yu934/P45Wd5GyJz5rG4dhUIB0MyZqp52CFCqgmw26zQ9X4zH63XOabKmXEqv4keGhxkeGgLqV2bD/jCqZeA0v3RIpqQ7wFby6uWzFOZV/8mbwpzsWSqVcoKGUDhMLpdjbHSU4/fey0c//nEOHznCzMwMk+Pjxfvn89y8cYMbmk2rmv1aLFcSIxAIlM+crWNwJiJzLpY0OFPV2rydipWqkWw2u2ABcjmBYJBYNEpLSwuJeNzJZBUKBd45d47mUKj4AVKnnZx20FfLaZxAMOhkI4wx3OrrA7ZWcBZNJTh/62rZ20qzZ6lUytm1umfvXrLZLPsOHHCmh3fv2cP5s2e5+O67HL3nHt58/XWnZlc4HIByoeQAACAASURBVKZrC2yqWC0nOCvTtLz0tQolmeR1DM7AChrtOme5HMYYzZyqijRzplQFWWtDQCX21XykpQWXy+W8Id+8cYOZmRmOnzxJMBisW3HSdDqNtySDVwvBYJBkMkksFuOVF17g3fPn6dm2bUvszrS9evmsMy01n509m4lHyaTTzmvA5/dz19GjTmAGxezqsZMnGRsZ4YVnn6VgDI99+MM0h0KcPX26qr6dW91i05qwMHOWbYDMGXyQyXa5XBhjlqyVp5RNM2dKVZDNZJYVnAWCQacyeCaT4eKFC3R1d7Nj1y5GR0ZI16m/Xj0W6geDQZKJBM9+85uICKcefJB9Bw5smSt/O2s2f0qzlDGGl997C6icUTx4xx2EQiFu9fVxz4kTBINBxOXi1Rdf5MqlS9x97FhNx7/ZpFIpRKTs1H0gECCdSjmZqYz1d1taD209+EvWIc7OzJDL5eZsMFKqHA3OlFqCMYZcLldV7TD7TTgQCOC3pjKuXLpEJp3m+L33OutPMpkMhUIBl6u2ievUKpqeL6Y5FMIYQ2dXF/c98ICznm6rWCprZsubAu8O3WA//rIZnfl6tm+nZ/t25+dt27ezZ+9eLl+6xK69e4mUbCJRc6WsHbHl/nYCwaDT0cLr9ZJZ5wK0zrjs4CwUcoIzpSrR4EypJWSzWYwx1WXOSmqeBQIBpqamGLl9m73799PW3g4UpziMMWQymZr3+UunUgvqP63W3n37aGltpa29fctky2zVZM1sxhjGvdkV/5sev/debg8Pc+70aT785JNb7v91tVLJ5KL/j+3jyWQSr9dLOp1uiLZipZkz0E0Bqjq65kypJdh1iaoJzuz1RYFg0MmchSMR7jlxwjnH/gCpx47NdDpd82lNl9tNe0fHlgwWXr18tuouDwVjSLryKw7OAsEg95w4wdjoKH29vSt6jK2gtFzJfPZrP22tS1vv1k22UDiMy+WipbUVKF7wKVWJZs6Uopj5mJ2ZIRwOz1mjkl1GcLZrzx48Hg/hSITde/fi8Xg4duLEnPUl9pV8Nb030+k005OTeDwep1/jUuPP1GFacysbmBwlb5ae0gToibTzoe7DXLxwYVXB8f6DB7l18yYX3n7beS2puVKplBPkzDe/S0AmnW6IafgdO3fy1Pd9n1PMWTNnqhr616+2vKnJSd549VXi8Tjf98xF/P0fLNiPAD8C8EcvzJ3cOrgb+S+/OudxPB4Pu/bsAYrriLaVrCuy2cFTNZmzV154gempKVwuFz/wIz+y5Id11lrHtpVKXNTbTz35w0ve3tfby+k33uAjjzzG5UuXaA6FcK9i8bmIcPiuu3jt5ZeZnpqiU/sFz2GMIb1E5szOXNvBWbpBMmciQlNzs3Ohp7s1VTV0WlNteTdv3CCdTuNyuYjt6gJPhQ9YjxuOHljRczlTL1VkzhLxOG63m0Kh4BTUXEyqDgVo1dJ27t6Nz+fj0rvvMjoywp59+1b9mHbrrMmJiVU/1maTTqcpFAqLbrrwWtX4U9aOzUaZ1rTZ2XfNnKlqaHCmtrzpqSla29sJNjVx60NHodIuSpcLPvN9K3oun8+HiFQMzgr5PJlMxil+W6knn52J08zZ2vF4POzZt4+x0VGMMeytQXAWCARoDoWcLgLqA+klCtBCMUNlF6LNZjIYYxpiQ4DNznzrmjNVDQ3O1JZWKBSYmZ6mtbWVpqYmZt3Axx9dPHvmccNTjyLtLSt6PpfLhc/nqzitaWfK7N2X2QqZs7RmztbF/oMHAejo7HR2461WR0cHE5o5W8Bes7XUpgu7Gn8jtG6azw7ONHOmqqHBmdrS4rEYuVyO1rY2mpqbSSQS8JlPLp49W0XWzOYPBCp2CbCDLfsDP1vhDV0zZ+ujpbWVe44fn7Mjd7XaOjpIJhLF16JyJK3/H0vVkrO7BNSjldlqudxuXC6XBmeqKhqcqS1tZnoaKH7IBq0pEdMWKZ89W2XWzObz+yv217SDN3tas2LmzA7OGihTsFUcOXrU6alZC/a6synNns0Rj8VwuVw0NTUteo7fCs7swHapc9eD1+utuERBKdDgTG1x9m7ISEsLTc3NFAqF4m6vz3wSM7+2Vw2yZgABv7/itGbanta0g7NKa86sgpvr3apGrZ5dKmJ2dnadR9JYYrEYzc3NS3bWsHvXxmMxgIYopVHK4/Fo5kxVRYMztaVNT08TjkRwu90EravsZDxOoTVM/5Gd5N3Wn0iNsmZQnKqMx2JLTm3at4WqCM4ymQzTU1O63myT8Hg8Ov1VRjwWo7nCur5AMIgxhsnJSXw+X1X1CdeSBmeqWlrnTG1p9/w/X6VlfBbzO3/DNj6oaQawp/TEfKEmWTMolmC4fOkSQ4OD7DtQviSHveasycoULDYVkstmefbpp0nE4xw9frwm41PrT6e/5jLGEItG6ejsXPI8e83l1MREw2XNADz676qqpJkztWWlUinGO0MUqpkK3Lu9JlkzgNa2NppDIQZu3Vr0nEw6jdfrxe1247GaOJczPT1NIh7nwUce4a6jR2syPrX+PF6vllwokU6nyWazFXfElvbXbMjgTDNnqkoanKkta2Z6msv37kNcFfpGisAvf7Zmzysi7Nqzh9GRkUXrnZU2bfZ6PIt+UM/OzABUzCiojcXj8WiGpUQ8GgU+WIO5mNIyG422GQA0c6aqp8GZ2rJmpqdJNfkp/P2Hl65r9v0fRg7srulz79ixg0KhwMQixUZL+2R6fb5F39BnZ2bweDwNmSVQK+f1ejXDUiJqBWehSsFZSZmNRvyb0MyZqpYGZ2rLmp6aItjUhPvHf6Cudc3KsTcfLLZrszRz5vF6ySwRnEVaWpD5O0vVhqbTmnPZZTSaKwRcbrfb+btp1OCsUs1CpaCOwZmIfFlERkXk3ZJjXxSRd0TkbRF5RkR2LHLf/ygiF0XkPRH5PdFPHlUHM1NTtLa2Ih2tda1rVo69cDm1SHBWmjnzLTEVMmMFZ2pz0Q0Bc8ViMYJNTVWVirGnNisFcuvB7/eTSacp5PPrPZQtbaC/n5TVcaJR1TNz9hXgqXnHfssYc9wYcxL4GvCF+XcSkUeBx4DjwD3AA8BH6jhOtQXl83mi0SitbW3FA+W6AtQpawbWFf4SbZzmrDnz+chmMowMD3PxwgWnwKZdCV2Ds81HMywfKOTzjI+OOvXfKrGDs2ADrjmzp13TFYpKq5UbHxvj6a99jZs3bmCMWXB7LBrljVdf5cp7763D6KpXt1IaxpiXRWTfvGOlVRWbgYX/54rHAoAPEMALjNRnlGqrmpmeplAo0GIFZ9LRivn4o/DNVyGXr2vWzOb3+8tuCMjlcuRyOafav/1BffnSJcZGR7ly6RK79+51KslrcLb56MLxDwwNDZFMJrlvkbIz8wUCATweT0PW/bPHlE6lCC7Rhkqt3O2hIWLRKGe++10mxse574EH5iz7GBwYAGB0pLHDijWvcyYivwH8GDADPDH/dmPM6yLyAjBMMTj7fWNMY4e4asO5fvUqHo+Hzq6uDw5+5pPwrdeAfF2zZja/1aR5Pqdpsz2taW0IiEajbN+xg+ZQiJs3btDX2wtocLYZea2F44VCYcmK+FvBjatXaW5upmf79qrO33/wIG0dHQ25DtNezlCpQ4haudmZGcKRCDt37eLypUv4fD6OnTzp3D5kBWcz09OkUqk5O3xtiUSCfC5HOBJZs3HPt+Z/9caYXzHG7Ab+DPhn828XkUPAXcAuYCfwpIg8Xu6xROTzInJGRM6MjY3Vc9hqE4nOznLr5k32Hzo05w/TWXsmUvesGRSv8Mtlzpw+mSUbAgqFAqlkko6uLk6eOsUnfuAHOHr8OIcOH9Yr8E3IY1W23+o7+2ZnZhgdGWH/oUNVB6ldPT3cceeddR7Zyth/04utNVWrNzs7S0trK0ePH+fgHXdw5b33nCnMRCLBxPg423cUl7uPj44uuH82m+W1l1/m1RdfXNe1get5SfZnWAXZ5/kh4A1jTMwYEwO+CTxS7gGMMX9ojLnfGHN/V2kGRKklXL50CZfLxZ1Hjiy88TOfhHsO1T1rBsWr6PlX0Llslgtvv42IOAU3S1vQ2FdyPr+fu44e5eSpUw2ZIVCr4/EUJzW2+tTmjWvXcLlci3bS2GiczNkSrds2grGREZ5/5pklLx7Krfeqt1wuRzwWo8XawX7y1Cl2793Lhbffpvf6da5cugTAPSdO4PV6F0xt5nI5vvvaa8zOzHDvAw+sa6/iNQ3OROSOkh8/BVwuc9ot4CMi4hERL8XNADqtqWoiFo3S39fHgUOH5tREsklHK/K7v1D3rBl8sOasUCgAxenMV158kbHRUe5/6CFnAXS54Extbva/eTabZWxkZF0+6NZbLpulr7eXXXv2lJ162ojsrh8bcVrTGMPYyAiFQoHe69eZnJhgemqq7LnZbJZv/O3fLtkFpR6is7MYYwhbSz1EhAceeoht27fz1ptvcv3qVe64805aWlvp7Ori9vCwkx2bnZnhhWeeYWR4mJOnTrGtymn0elkyOJu/oH85ROTPgdeBO0VkQEQ+C/ymiLwrIu8AHwP+hXXu/SLyJeuufwVcBy4A54HzxpivrnQcSpV67+JFRITDd9213kOZcxWdTqd55YUXmJqc5KHHHmPv/v3OeV5rY4DL5SLUgOUBVO3Z05q3h4d56fnnmVykWPFmdquvj2w2y8FDh9Z7KDUjIsW1phswOBsfG+Ol55/n2vvvc3t4GGDR4Gx4cJBkMkl0drbs7fVid0wpXYfrcrt5+LHH2LZjB/sOHOD4vfcCcODQIRLxODd7e+nr7eX5Z54hlU7zoY98hAMN8JqrtCHgWSto+m1jzLIWPxhjPl3m8B8tcu4Z4HPW93ngny7nuZSa78a1a0xPTXHfAw84x0qzZo2wTsvOBsxOT3P+3DnisRiPPP64sx7C5rWmuJqbm9c1za7Wjj2tOWN9+KU2+DTYchljuH71Kq1tbbRvstZkfr9/Q2bORqyA7OI775C3sk0z09Nlz7V3RK71msnZmZniRey8ThIer5cPfWRuRa5tO3bQ2dXF+bNnyefzdHV38+CjjzbEZwNUnta8F+gB3lpsUb5SjWiwv5+B/v45xy5fuoSIcOfdd6/TqOayM2cXL1wgFo3yoY98ZEFgBh9kznRKc+uwpzVnrczDVlt7Njk+zsz0NAcOHdp0ayr9i2wEanSjIyN4vV7y+Twul4uOzs6ymbNcNsvtoaHi92sYnCUSCUZu3ybS0lLV5hER4diJE4gId91zD48/8UTDBGZQIXNmjIkCPysip4DnRGQAKFAscWGMMcfXYIxKLVsiHncqcbvcbmKxGLdu3myYrBl8sHNrcmKCzu5uunp6yp5nT3FpcLZ12P/m9rTQVmvldP3aNbxeL3v27l3vodRcIBBYNOPUqDLpNFOTkxw5epShgQFC4TDNzc1cv3p1QbmXocFB8vk8IrJmwVkikeCZr3+dQqHAyVOnqr5fR1cXn/oH/6AhLwAq1jkTkSeB/wR8CfgDisGZUg2rUCgQj8eB4nRQU1MTfTduADTEWjNb6YaEpRafBgIBtu3YwfadO9diWKoB2Jkze/poK2XOUqkUA7duceDQISdI3UzsXdrGmIYMCsoZHR3FGMO2bds4fOQIIsLQwECx04pVugKKFxEXzp+npaUFw9plzkZv3yaXy/Hkxz7mFOeuVqP+GywZnInIX1CsN/aPjTEX1mZISq1OKpl0dkCmUymampq4PTxMW3s7TQ3U0sXj8eB2u8nn82WnM20ul2vBegm1udlrzmxbqZXTzRs3KBQKHLjjjsonb0B+v59CoUA2k3EKTTeiRCLB8OAgw4ODjI6M4Pf7aevocLJkdkD23sWLNDU1kc/ni4Vdk0ke+dCHOH/27JplfMdGR/EHArS1t6/J862FihsCgL8F9opIqzFmY+Vi1ZZkZ83A6j+ZTjM9NcXd99yzjqNayN65ZYzRKv9qDrfbjcvlci4ytkrmrFAo0HvtGt09PUQ26TS+vREoVdI/F4oblpKJxKLLG9bS22+9xbX33wcgFA5z8PBh9u3fP2f6MmxNbQ7cuuVcaLrcbu45cYL2jg48VpeLtTA+NkZnV1fDZsFWopr2Te8CN4D9IvJ5Y8zf1XlMSq1KPBZzvk+nUozevo0xhu5t29ZxVOXt3rOHQDC4qd5UVG14vV5n4Xi1GYiN3u5pbGSEeDzOMavcwWZU2l+TkgD0rTffZGpyku//4R9maGAAfyBA9zoFauNjY7S1t/PAI48QDofLvj+53G6e+v7vB8pPDXq83rLt6Ywx9F6/zo5du2pSvy6RSBCPxTh0+PCqH6uRVArO/jfgHmPMmIgcoFjVX4Mz1dASJZmzdDpNdHYWn9/fkCnv0p5vamsz//SLcP2DHcbze1QY/t/iNwd3I//lVxfcP5NO882vfpVTDz7Irj176jjS+hkfH0dE2NaAF1K1Yq81LQ1cYrEYY1YrodtDQ7z15pu0tbevW3CWy+Vob2+vmL1c6qJyscxZIh7n7OnTZDIZjtRg57zdgqlzk3UJqnSJlTHGjAEYY24AjTtBrpQlHo/T1NyMx+MhlUoxNjpKd3f3hs4oqC3g7gPgqVDHzuOGo+VbGU1NTZHNZrl182btx7ZGpiYniUQim3IjgK3ZKiQdK8nw9/X2IiK43W7eOXeOXC5HNBpdryGSzWZxe6qZWFvcYsGZveyk9CK6GplMhmeffpqpyck5x4cGB/H5fM4auM2i0qfVLhH5PfurzM9KNZx4LEZTczP+QIB4LFbstdbWtt7DUmppn/kkVLqAcLkW7ftqV0cfHRnZUA3Tc7kcLz73HBNjY0xNTtLagBnuWvJ4vQSDQWJW8FUoFOjr7aVn+3a6eno+2GmeTJIpUw/t2vvvM2zVEauXfC43p23cSiyVOSv9b7VmpqaYnppyuhNAsQ7gYH8/+w8d2nQX35V+m18A3ir5mv+zUg0nHo/T3NxMIBBgfGwMQBfcq4YnHa3w8UcXz5553PDUo4v2fbVrZ+VyuQUNnRtZdHaW8dFR3j57lnQq1ZDLD2qtORx21saOjYyQiMfZd+CAU1LHzgLNzmt/NNjfz9tvvcV3v/Mdbg8P8+zTTzuV+2ulUCiQy+UW7BheLo/HQz6fdza12OzgM77M4MzONNoXIQBXLl3C7XZzx513rmqsjWjJ4MwY89+W+lqrQSpVrUw6TSqZJBQK4ff7nSvPFg3O1EawVPZsXtYsFo3yra9/3clAzExP09ndjdfrZXhwcC1GWxOJRALAma5abp2qjSgcDjvBxs3eXvx+P9t37GDX7t10b9vm9H8s7U2ZTCY5e/q0E7i9+uKLTE9NMTkxUdOx2dmu1U4t29Oi87NndlCaiMcxxlT9eHam0Q7OYrEY/X197D90qCYbCxpNpTpnXwUW+7+Xptig/A+MMf2LnKPUmhro7y8WS9yxw3nTd7vdNGnDcLUBSEcr5uOPwjdfhVzeOZ53Ce55WbOpycli1mlsjF3BINHZWeeDanhoaMMUOU1af6dQrOm32dYOldMcCpFKJonHYgz293Pwjjtwu924g0E+/MQTGGPweDxO5swYw1tvvkk+n+ehxx5jcnycq1euEI/Fat5E3QnOapA5sx/PZ7Wggw+mM/P5PKlUquqOLXYwG52dpZDPc8Vqx3f4yJFVjbNRVfq//9sV7nsU+O/AIzUbkVKrcOvmTSItLbS2tTlXU9X2WlOqIXzmk/Ct14APgjMjgvn091IaatllNmamp2lrbyeXy9HS0kJbWxsDt24xNTm5IbJQiXgct9tNW3s7xhjc7gqbIjaBUDgMFAu4FgoF9u7fP+d2ESEciRC1skQ3rl3j9tAQJ0+dIhKJEIlE2HfgAN/6+tdr3kTdrqlXizVnUD5zFggGSSWTJGKx6oOzaBQRoVAoMDo6Sl9vL/sPHmyYdny1VukTy2eMeancF/AxY8zvARfXYJxKVRSLxRgfG2PP3r1OgVfQ9WZqY5m/9qzgdtN3xzZykbnZX/tDeWZ6mhnrQ7yltZWe7dsRkVVPbd68cYM3Xn11VY9RjUQiQVNTE48+/jiPPP543Z+vEYRCIaC4S7OtvZ3WMhuWwuEw0dlZorOzXHj7bbZt387BeV0T/IEAqTKbBowxDPb3r6hCf60yZ04LspLgLJ/Pk0wm6eruBqpfd2aMIR6LOeUyzp05A8CdDdSOr9YqBWd/ICKfLD0gIi4R+QpwAsAY87k6jU2pZenv6wNgt9UsOaDBmdqoSteeuYT37t234IO2NHM2NTGBy+UiHIng9/vp6OpiaJXB2fDQEAP9/TWfNpsvmUgQbG7G5/dvyrVD5djBmTFmQdbMFm5pIR6P8+Jzz+Fyuzn10EMLpqkDfn/ZzNngwACvv/oq71++vOyx2a+zmk1rlrxu7SlNOzirdsdmMpkkl8uxfedORIR4LMbe/fs39XKVSsHZx4HfEZEfAhCRIMUitD7g++s8NqWqZozh1s2bdHZ302y98QWtPpqtW2ANi9pcnOyZCInHT5Bu8i+YHrKDs2Qyyc3eXrp7epwPxB07dzIzPT2nW8Zy2R+cUzVecF7ueRqp5+1asMtpuN1u9lgXk/PtO3CAQ4cPEw6HeeChh8pO3/kDAed1YMvlclw4dw6Agb6+ZS26t+9vj3E17PuXvm7tTFk4EiEQDFadOYtbmwFaWltpDoVwuVzcWYMCto1sydDYGNMrIh8FviUiPcBngNPGmJ9dk9EpVaXpqSmis7NztlS3d3TwPR/9KB2dnes4MqVW6DOfhJtDpH74STh3pmzmzO6/mU6l5nQF2L5jB++cO8fw0NCK29rYgd3kxATbd+5c+e+xhIK1KHyrBWcA23fuxO3xLNr8PBgMcvLUqSUfIxAIkEmnKeTzuKy1elevXCEej7Nn715u9fUxMz1ddtp0MfkaTWvauzWzZTJnzaEQzc3NVQdn9maAUCjEgUOHyOfzTvZxs1oycyYi9wHdwC8BvwEMAH8iIvdZtynVEG7dvInL5WLX7t3OMRHZdM1w1dYhHa3I7/4C7q5i3a8FwVkqRbt14eF2u9mxa5dzWzgSIRyJrHjdWSaTIZPJADAxPr6ix6hGIpnEGLOpp6cWc98DD3BilT1E7XW1aevfKpFIcOXSJXbu3s2JU6dwuVz037q15GMYY3j26aedRufZOm4IiMdiuFwugsFgMTirsgtCdHa2eL+mJg4fOcJdR4+uamwbQaXQ+HdKvn8H6Ck5ZoAn6zEopZajUCjQf+sW23fuXPQqVKmNqtzaHShmzrp7eojHYnR0dMwpVwDFqc2rV66QzWaX/UFrZziCwSCTExN1a6ietJ9nC2bOaqG0iXowGOTiO+9QKBQ4dvIkfr+fzq4uRm/fhhMnFn2MTCbD9NQUY6OjHDp8uC6lNGx2gXB7N2r/rVtVFbydnpqipbV1S+26rzSt+cRaDUSplRobGSGVTC66dkOpjcxeu1OaOSsUCmTSafx+Px958skFgRkUp82uvPceI8PDy26Ebk837dqzh6tXrhCdna1L/TG7FuFWnNasBTtzlkqlmBgfp6+3lyN33+1M+QWCwYrrDmNWLTW7yGsumy32+axRcFa6WzNh9T2GYnbXGEMsGl1y2tUYw/TU1LJfwxtdxTBURLpF5N+IyF9ZX/9GRLrXYnBKVeNWXx8+n49tO3as91CUqjlvmYXVducLn99PKBwumzFu7+jA6/UyNjpa1fO89eabTomCRElwBvWZ2kwlk/TdvImIaOZshezMWSqZ5PzZswSDwTkL5b1eb8VyGnaD9XgshjHGyWStdjmIy+XC7XYvmNYsDc5gbheEcuKxGJlMZku09SpVac3ZY8Bp68c/tr4A3rRuW+q+XxaRURF5t+TYF0XkHRF5W0SeEZGyn6Yisse6/T0RuSQi+6r9hdTWkstmGezvZ+fu3VuieKXaeuwPytIPWXuH3lKlJ1wuF01NTVWXwpgYH3fKbyTicTweD+0dHfj9/pq2CDLG0Hv9Os984xtMjI1x4r77Vj2FtlXZmbNbN28yOTHB0ePH50xh+/x+stnskjs2nYxZLkcykSCbzdbs36O0+XkumyWdTju76UPhMCKyoH/ofHZbr60WnFWz5uwHjTHnSo79nYj8DfBfgIeWuO9XgN/ng4AO4LeMMb8KICL/HPgC8NNl7vvHwG8YY74tIiGgUOYcpZiYmCCXy7GzZCOAUpuJiBQ/5MoEZ5XWWPoDgaoryGcyGVLJJOl0es7aoPaOjpoFZ7Ozs5w7fZqx0VG6uru574EHnAyKWj6v14vL5WJ0ZASfz7dgaYfX68UYQzaTWfS1EitZlB+LxYqZs1VuBrCVBmf2VHmzlTlzu900h0IVM2dTk5O43W4iW+x1UmlaMzIvMAPAGPM2EF7qjsaYl4HJecdK/xWaKdO3U0TuBjzGmG9b94kZYxLzz1MKPkiJay0ztZl5vF6SyaTzsx1w+WsUnBljnKnS6ampOWuD2js7mZ2ZIZPJYIzhzddeY2xkZNm/w5X33uO5p59mZnqaUw8+yIeffFIDs1USEQJW/bPtO3c65TRs9lrEzBJTm9GSNV+xaLSqBfrVKhuclZTAsLsgLGVqcpLWtrYFv9tmVyk4ExFZsFJPRNqruO9iD/gbItIP/CjFzNl8h4FpEflrETknIr8lIlvrX0VVbWZ6Gr/f76T3ldqMunt6GLh1i/PnzhXrmlmBVKXXfSAQqGpaM5vNUigUJyimJifnrA2y+3NOTkyQTCS41dfH0NDQssY/a7Ug6tm2jY994hPsP3hQS9zUiB2gl5s98FrBWdYqtTGf3Rapq7sbt9tNNBolt4LdvYvxeL1Oxtdex1haNiUciRCLRp3XXjmzMzNbsstLpQDrd4FnROQjIhK2vr4H+KZ127IZY37FGLMb+DPgn5U5xQM8Dvw88ABwAPiJco8lIp8XkTMicmZsbGwlw1Eb3OzMDOGWFn2jV5vaRlYwyQAAIABJREFUqQcf5NDhw1y9fJnXX3mFeCyGiJTdpVnKb605yufzS56XKakyf/3998lms3T19ADF4ExEmBwfd7IcycTyJjNGb98G4Ph99zmZHlUb/kAAj8dDz7ZtC25zMmeLBGd2W6RwJEIoHCY2O1vTzJm7NHMWi+HxeOZkeyMtLeTz+UV3lBpjyGQyW6atV6lKpTT+UESGgC8CdtW3i8CvG2O+usrn/jPgG8CvzTs+ALxtjLkBICL/A3gY+KNy4wP+EOD+++9fXo8KteEZY4jOzjq9NJXarFwuFydPnSLS0sLbb73F8NAQfr+/Yt0np0hpKrVkoVf7w9vtdpNMJmlqbmaH1RXA6/USiUSYnJhw1i0tNzgbGx2lubnZWW+kaufI3XeTOnCg7IYo37zMWSwWo6+3l0I+T6FQcP4dQ+EwoXCY2ZkZCoVCzdaceb1e0tZ0fOk6RptdJPzmjRscO3lywf3zuRzGmJqNZyOpGB4bY74GfK0WTyYidxhjrlo/fgoo15X1NNAqIl3GmDGKhW7P1OL51eaSTCbJZDK6bkVtGQcOHaI5FOK73/lOVeUnSutgLRWc2dOknV1djNy+zYFDh+YEfu2dnQz29zuPUbr+rZJCocDY6Cg7rKbVqrY6u7oWvc07L3N25dIleq9fx+1243K5cLlctLS00NraSqSlhaGBAdxud80yZz6f74PuBSXrGG2hcJjde/dy/epV7jhyZEGGrFYFcTeiJX9jESm3JsxmjDFfXOK+fw58D9ApIgMUM2SfEJE7Ke6+7MPaqSki9wM/bYz5nDEmLyI/Dzwnxb/kt4D/uozfSW0R0ZkZAFq24HoEtXX1bNvGR596ilyFqUr4oNRGpU0B9rTmvgMHKBQKHDh4cM7tHZ2d9F6/zrC11iyVTFbdNWBmepqM1c1ArS3fvALG41aQ/OiHP7zg3O7ubt57911yuVzN1pw1NTeTSiadqctygeSRo0fp7+vj2pUr3DOvk0GtWkltRJXC0XJdSZuBzwIdFKc7yzLGfLrM4QVTk9a5Z4DPlfz8beB4hbGpLW7GCs7CGpypLabaXpROe5+SNWXl2Lf3bNtWdpmAvSkgmUh80Gw9nSZYxfqxcWs9cJcGZ2vO7fHgcrmcMinRaJT9hw6VPbe9s9PZXVmrTJXd+WF6aopsNlv2dRuJROjs6uL28PCC4MzJnG3B4GzJyx5jzO/YXxTXdgWBnwT+guJCfaXW1O3hYd56800K+TzR2Vn8fv+WXCyqVDXsac14LMZ3XnqJmenpsudlMxlcLpczDTZfOBJx1i/ZxUBTVU5txmMxvF5vVYGcqi0Rwevzkc1knCB5sWlQt9tNR2dn8fsaB2f2cy+25rC7p8fJsJZyMmdbcFqzmvZN7SLy6xQbn3uA+4wxv2SMqa4niFI1cuvmTV57+WV6r19nZmaGaDSq682UWoLH48Hj8XCrr4/hoSFuXLtW9rx0Oo3X51t0TZiIOEFZt7UrMFHlpoBkMqntmdaRz+cjk8kwNjqKx+NZsiak/W9bq2nEoBWM2S3ESmuclerq6cEYs6DVmB2caeZsHhH5LYoL9KPAMWPMvzbGTK3JyJQqUSgUOH/unJMWj87OEo9GCYWXrIWs1JZX2vx6eGiobCsfu4n6UtqtrEp3d7G1cnR2trhGqULvxmQioVmzdeQryZx1dHYuWcx12/btwNJtwZYjGAwiIkxYmbPFpuPb29vxeDwLgjP7tbUVNwRUypz9HLAD+FfAkIjMWl9REVm6rK9SNTQxPk46leLue+7B5XIxNTlJMpkktMiVmFKqyA66XC4XiXicyfFxxkZH5wRp6XS6Ys20A4cOcfzee+ns7sblcnH1yhUuXrjAaIXG6v9/e3ceHmV5NX78e2YmmexhS8JOWI1AQlhEi4KAClgVtdpSxSKK+hOXtmoRq63i1gurrdSlRX1tse6tVmx9fYtLRcGlshgVEFkDhC0QIPsyydy/P55nxknIzkxmkpzPdeWCeeZ5Zu45mSRnzr2Vl5Vp5SyMoqKjKSsro6iw0N9t2ZDkLl2Y9v3v07N3vdtet5jT6SQmJgaPx0N0dHSD7zGH3aVad+cJ35izzjghoKkxZw5jTKwxJtEYkxTwlWiM0f4k1Wb27tmD0+mkd58+xMXH+2eNJWi3plKN8o07GzxsGCLCqpUr+fD99/lmwwb/OVWN7L3oExsby7CMDESE2NhY/wzQxmaCemtqqKio0OQsjKKjoiguKsIY469+NiYpyIt6+6plDXVp+qSkpVFYWFhrRwvt1lQqghlj2JuXR1qvXriiokhMTPRv1puo3ZpKNcpXOes/YAApdtWrZ+/ebNqwwT8GrTndmoECk636krOSkhJW/O//UnBoFyN7vUlcTMPb86jQCpzk0c0eN9iWfO+VpmYYp9jd5YcDKrHVHg8Oh6PeBXY7us7XkavaHd+efpn2NOvEpCR/5aypT2NKdXbdunfnyOHDJHfpwmlnnAH2iuufrlrFF2vXEu12W92aLUjO4uLicDqdiEi9y3Qczs+nuKiIY3n/oHeXjVS5vgBGHf9AKuR8XYmJiYkt+h4Hi2/GZlO7Q3Tt1o2oqCjyDx6kb//+gFU5c0VFdcrFi7VypiLe3j17/J/2Af8Mzdi4uE45UFSplhg4eDDnfP/7OBwOa9yPve3TqaefTrfu3fn8k0/wer1NjjkLdPLIkZxx5pnEBHRvBrIq24ZE7wpqaqKJq3673okIKvR8lbPmdGmGgq9i1lTlzOFw0CMlpda4s+rq6k65jAZocqYinDGGvXv2kNqzp/+Ph2+GpnZpKtV6LpeL0ydN8v88taRbMzEpiZS0NNxuNxX1VM5KiotJjt1PtKuQqppYnN7DmIpNQWu7ar6669O1tdhmVs7AGndWXFzsX6bF4/F02g/gmpypiHbs6FFKS0vp07ev/5ivcqbLaCh1YqLdbs4480z69uvX6B6NDXG73fVWzoqLiujbJQcwiDhADN7C5UFosWqpOHuzcd+YrraW1rMnI7Ky/GuoNabuuLPq6upOORkAdMyZinC+Ls3eAcmZ2+1m8NCh9O3XL4wtU6pjiIuPt8aitYI7JoajR45Qvf9+vMXv+o+f0qsMhwMqqmJwOB3gSMBb+G+qilbUut6ROA1Xr1+dUPtV41JSUzn3gguaveVXsLlcLk4eMaJZ5yZ36UK0203+wYP0T0+n2l6CozPS5ExFLF+XZo/U1FpdLiLC6HHjwtgypRTYlbPKShzd5mAqt2Cq8vAST1U1xMbFQlU5DocDESe4rP05jfGCtxiJ7oez+5wwv4KOT0TClpi1lH/cmV05a2g/zs5AuzVVxCqyt2gK7NJUSkUOd0wMXq+Xanri6v8MjqQZmJoiHFKN0+XC6XLWWgbBeCvBW4wj6Vxc/Z9GovuHsfUqEqWmpVFaUkJpSQnVHk+nXIAWtHKmItjePXsQEU3OlIpQvop2RWUl0e4kXD0XcvBoCvHOP+J0OElMTILAVRBMGc60O3AmnxueBquI5xt3dig/XycEKBWJ9ubl0T0lhRjdl0+piOTbfSBwUkBhWVe8xmV3ZwoSmJ2JG4d7SFs3U7UjScnJuGNiyD94sFNPCNDkTEUkb00NRYWFYZthpJRqmm+DbN9CtHvz8ijMX4fLZf1pMd4STE0RxltiX1GNqdwWjqaqdsI3s/TA/v1A59xXEzQ5UxGqoqICY4x/dWmlVOTxdWtWVlRwcP9+/vvxx6R1LSDGHYWpKUSieuPq8xskqhemphBMDd7yDU08qursUtPSqLIT/s7ardk5X7WKeOX2IoTapalU5PJtB7R/714OHzpEUnIyfVOLwVOFI+linKk/RRwxSGw2Nfl/wFu4HFPxdZhbrSJdj4Aek85aOdPkTEWk8vJyAK2cKRXBHA4HbrebA/v3k5iUxBmTJ+M48hnSYy7OpLP954kjBlfPhdTEjcWUrA5ji1V7kJiYSGxsLOXl5Z12zJkmZyoi+ZKzWK2cKRXR4uLjcUVFMXHKFGsMWu9FDZ7rTDobApI2peojIqSkpbE7N1e7NZWKJOVlZTidTv+mvUqpyPS9iRNxOZ3+Lk6lgiHVTs5asudrRxKyCQEi8mcRyReRDQHH7heRr0QkR0TeEZHejVyfJCJ5IvJEqNqoIld5eTmxcXGISNMnK6XCJi4uThMzFXT909OZOGUKScnJ4W5KWIRytuYyYEadYw8bY7KMMdnAW8DdjVx/P/BRiNqmIlx5eblOBlBKqU7K4XCQ1ozN0juqkCVnxpiPgCN1jhUF3IwHTH3XishYIA14J1TtU5GtvKyMOE3OlFJKdUJtPuZMRB4E5gCFwJR67ncAvwOuAHTkaCdkjKHC7tZUSimlOps2X4TWGHOXMaYf8CJwUz2n3AC8bYzJa+qxROQ6EVkrImsPHToU7KaqMKmqqqKmpka7NZVSSnVK4dwh4EXgknqOfw+4SURygUeAOSKyuL4HMMY8bYwZZ4wZl5KSErqWthMH9+9n3eefh7sZJ8y3AK1WzpRSSnVGbZqcicjQgJsXApvrnmOMmW2M6W+MSQd+AfzVGHNHGzWxXdu+dSs7t2+nqqoq3E05If41zux9+5RSSqnOJJRLabwMfAqcZC+JMQ9YLCIbROQrYBrwM/vccSLyP6FqS2fg9Xo5lJ8PQGlJSRNnR7aS4mIA4hMSwtwSpZRSqu2FbEKAMeayeg4/28C5a4Fr6jm+DGtJjk7ryy++oLS4mAmTJjV63tGCAjweD2AlZ127dWuL5oXEsaNHiY2N1TFnSimlOiXdISDCHc7Pp6qyssnz8g8eREQwxvgrT+3VsSNH6NK1a7iboZRSSoVFOCcEqCYYYyguKsJTXd3gOVVVVWz6+mt25+bSpWtXYmJjKWnH3ZrV1dUUFRXRpR1X/pRSSqkToclZBKuoqKC6uppqu7uyPls3b2bThg2UlZXRb8AAEhIS2uWYs2qPh5Xvv8+ObdswxmjlTCmlVKel3ZoRrKTI2lDB6/VSU1OD0+msdX+1x8P2bdvo3bcvEyZOBKDw2DHyDx5s87aeqNLSUg7n51Ngr1fXVZMzpZRSnZRWziJYccDYsep6ujZzd+6kqrKSYRkZ/mMJCQmUl5XVe34k8y3/YYzB7XbrGmdKKaU6LU3OIljgwH5Pna5Nr9fL1m+/pXuPHvQIWIDXt/xEWWlp2zQySHyvLzExkbRevRCRMLdIKaWUCg/t1oxggclZ3XFn+/LyKC0pISs7u9ZxX3JWUlJCUnJy6BsZJL7XN2HSJBKTksLcGqWUUip8tHIWwYqLi4mOjgZqd2saY9iyeTMJiYn06tOn1jXJycm4XC4O7NvXpm09Ub5uzSj79SqllFKdlVbOIpS3pobSkhJ6pKSQf/BgrW7Nw4cOcaSggNHjxuFw1M6vXVFR9OnXj7zdu8kaPRqXq318i32Vs6ioqDC3RKnI4vF4yMvLo6KiItxNUUq1QkxMDH379m3R37f28Ze7E8rbswev10vP3r3JP3iwVrfm1s2bcbvdDBg4sN5r0wcOZNfOnezLy6N/enobtfjEeDwenE7ncTNSlers8vLySExMJD09XcdiKtXOGGMoKCggLy+PgQ38za6PdmtGIGMM337zDUnJyfTt1w/4rluzqKiIfXv3Mnjo0AarYj1SU4lPSCB3x442a/OJqqqq0i5NpepRUVFB9+7dNTFTqh0SEbp3797iyrcmZxHo4IEDFB47xrCMDFx2GdTXrbl3zx4ABg0d2uD1IsLAwYPJP3iQosLC0Dc4CKqrq4lqJ12wSrU1TcyUar9a8/OryVkE2vLNN8TGxdF/wAB/dczXrVlZUUFUVBQxMTGNPkb6oEE4HA62b90a8vYGg0crZ0oppRSgyVnEOXrkCPkHDzL0pJNwOJ04HA5cLpe/W9Pj8fhncDYmJiaGfgMGsDs397g10iKRx+PxVwmVUpFFRLjtttv8tx955BEWLVrkv/3000+TkZFBRkYG48ePZ/Xq1f77Jk+ezNq1awHYuXMnQ4cOZcWKFaxcuZLzzz8fgGXLlpGSkkJ2djbDhw/nmWee4ZlnnmHWrFn+xykqKmLw4MHsaEfDNZRqLU3OIsy333xDdHQ0AwcP9h9zRUX5E6yqyspmV5gGDx2Kx+Nhd25uKJoaVB6Ph2hNzpSKSG63m3/84x8cPnz4uPveeustnnrqKVavXs3mzZtZunQpl19+OQcOHKh1Xl5eHjNmzOB3v/sd06dPP+5xZs2aRU5ODitXruTOO+9k5syZ7Nmzh/feew+Au+++m6uvvppBgwaF5kUqFUE0OQsjYwwbvvySo0eOANais3v37GHgkCG1pty2pnIG0K17d7p268b2rVsxxgT/BQSRdmsqFblcLhfXXXcdjz766HH3PfTQQzz88MP06NEDgDFjxnDllVfy5JNP+s/Zv38/06ZN48EHH2TmzJmNPldqaiqDBw9m165dLF26lJ///OesXbuW999/nwULFgT3hSkVoXQEdhh5qqrYvGkTe3bv5pwZM9j67beICEOGDat1XlRUlH/MWVVVVYtW0B88dChr//tfDuXnk5qWFtT2B5N2ayrVtC/Xr+fY0aNBfcwuXbsyasyYJs+78cYbycrK4vbbb691fOPGjYwdO7bWsXHjxvHcc8/5b1955ZU88MADXHrppU0+z44dO9ixYwdDhgyhW7duTJ8+nbPOOos333yz2R9MlWrvtHIWRlV2wlVaUsLHH31E7o4dDBg4kNjY2FrnuVwuPL7KWVVVi35B9e3fH7fbzY4InhjgramhurpauzWVimBJSUnMmTOHxx57rMXXnn322bzwwguUlZU1eM6rr75KdnY2l112GU899RTdunUDrKSwT58+TJ48ubVNV6rd0cpZGHnsLYt6pKZSXFxMQkICJ5188nHnuVwuysvLAaty1pLkzOVykT5oEFu//ZaysjLi4uKC0/gg8iWe2q2pVOOaU+EKpZ///OeMGTOGq666yn9s+PDhrFu3jqlTp/qPrVu3jhEjRvhv33777Tz//PP88Ic/5M0336x3jcZZs2bxxBNPHHfc4XActxOKUh2dvuPDyLef5IjMTM6/6CLO+f73SUhMPO68qKgoqqurqampoaampsVbHA0aMgRjDDu3bQtKu4PNN9mhvWw1pVRn1a1bN370ox/x7LPP+o/dfvvtLFy4kIKCAgBycnJYtmwZN9xwQ61rlyxZQlJSEvPmzYv4MbBKhZsmZ2Hkq5w1VQnzzdb0JXPRbneLnic+IYFevXtH7I4BHt30XKl247bbbqs1a3PmzJlcffXVTJgwgYyMDK699lpeeOEFevXqVes6EeG5555j//793H777VRXV+Nu4e8ypTqLkJUqROTPwPlAvjFmpH3sfuBCwAvkA3ONMfvqXJcN/AlIAmqAB40xr4aqneFU1cykxOVyUe3xfJfEtGJsVrcePdi3dy8ejyfiNhf3Vc50zJlSkamkpMT//7S0tOPGjs2fP5/58+fXe+3KlSv9/4+Ojuadd94B4A9/+AOD7SWD5s6dy9y5c+u9Pj09nQ0bNpxA65Vqf0JZOVsGzKhz7GFjTJYxJht4C7i7nuvKgDnGmBH29UtEpEsI2xk2Vc2snEVFRVFTU0OlvTdXa2YsxcfHA1DeyIDccPF3a2pyplSnMG/ePF566SVuvPHGcDdFqYgUssqZMeYjEUmvc6wo4GY8cNzAA2PMloD/7xORfCAFOBaaloaPp6oKh8OB0+ls9Dxf0uKbFNCa7j/fRIDS0lKSkpNbfH0oabemUp1L4Jg1pdTx2nwEtog8CMwBCoEpTZw7HogGtjdw/3XAdQD9+/cPbkPbQFVVFdFud5ObovoGypeWlgKtq5zFtoPKWaR1tyqllFLh0OYTAowxdxlj+gEvAjc1dJ6I9AKeB64yxngbeKynjTHjjDHjUlJSQtPgEPJUVTUrIfGdU2YnZ62pMMXExOBwOPyPEUl83bWanCmllFLhna35InBJfXeISBLwv8BdxpjP2rRVbaiqmVsx+ZKWkuLiWrdbwuFwEBsb2+gikG2tuKiIzz7+mM2bNpHcpYuuZaSUUkrRxt2aIjLUGONbqv5CYHM950QDbwB/Nca81pbta2ueqircMTFNntfFXim74PBhoqKiWp3ExMbH+5Mzr9dLcVERyV3afq5FRXk5G7/+ml07d+JwODh55EiGnnRSm7dDqY6quKKMN9b8hx+cMpWEmMhbeFop1biQlSpE5GXgU+AkEckTkXnAYhHZICJfAdOAn9nnjhOR/7Ev/REwCZgrIjn2V3ao2hlOzV3t3+12k5ScjNfrPaG95eLi4ii3uzV35+by3r//XWuKfFtZv3Ytu3buZNCQIcw4/3xGZGbqnnlKBdHqzevZU3CAVZu/CMrjJSQkHHessLCQOXPmMGTIEAYPHsycOXMoLCwEIDc3FxHh8ccf959/0003sWzZMv/t3//+92RkZJCZmcmoUaO49dZb/eNPlersQpacGWMuM8b0MsZEGWP6GmOeNcZcYowZaS+ncYExZq997lpjzDX2/1+wr8kO+MoJVTvDqbljzgB62GPqTmRGY1xcHOXl5Xi9XvIPHsQYw7EjR1r9eK117OhR+vbvT/bYscTU2UdUKXViiivK+HL3Vgzw5e4tlFSEZijDvHnzGDRoENu2bWP79u0MHDiQa665xn9/amoqf/jDH/xLBgVaunQp77zzDp999hlff/01a9asITU11T8jXanOTgf5hIkxBo/H0+zV/n3J2QlVzuLj8Xq9VJSXU2Cv8H3s6NFWP15rVHs8lJWWkpiU1KbPq1RnsXrzev/2SMaYoFXPAm3bto1169bx61//2n/s7rvvZu3atWzfbk2uT0lJ4ayzzuK555477voHH3yQP/3pT3Sxh1VER0dzxx13kKS/F5QCNDkLG09VFcaYtq2c2ctpHDlyhFK7O/PYsbZdPq7YntSgyZlSweermtXYE9xrjDck1bNNmzaRnZ1da41Gp9NJdnY2Gzdu9B9buHAhjzzyCDU1Nf5jRUVFlJSUMHDgwKC2SamORJOzMKnybVnUzGQrLj6e5C5d6t0Yvbl840a+3bQJgMTERArbuHJWXFTkf26lVHAFVs18QlU9a45BgwZx6qmn8tJLLzV4zooVK8jOziY9PZ1PPvmkDVunVOTS5CxMWrMq/tRp0xiRmdnq50xITCR90CCOHjmC0+lkwKBBlJeXU9GG4zxKiosRkRNKMpVSx6tbNfMJRfVs+PDh5OTk4PV+91xer5ecnByGDx9e69w777yThx56yJ80JiUlkZCQwM6dOwGYPn06OTk5jBw5st7xaUp1RpqchUlz99UM5HQ6T3gtsKzRo4mNjaVb9+50694dgMIgdm3W/dReV3FxMfEJCU1uWaWUapn6qmY+wa6eDRkyhNGjR/PAAw/4jz3wwAOMGTOGIUOG1Do3IyOD4cOH869//ct/7Je//CXz58/3D6swxlBhL0atlArD9k3K4mlFchYM0dHRTJk2DRHBaSd6RwoKSOvV64Qfe3duLus+/5zuPXqQ2rMnPXv1IrlLl1rbUxUXFWnVTKkga6hq5uOrnk3MGN2qdc/Kysro27ev//att97Ks88+y80338zgwYMB+N73vtfgnpl33XUXo0eP9t+eP38+paWlnHrqqbjdbhISEjj99NNrnaNUZ6bJWYgZY1i1ciWJiYlkjhrl38S8srISCM9m375N0AFSUlPZvm0bQ086yd+21jp65AjGGCorK9nw5Zds+PJL4uLjmXLOOcTGxmKMobioiJS0tBN9CUqpAI1VzXx81bNzs09v8eMHdl8GeuGFF+o9np6ezoYNG/y3R40aVesxRIQFCxawYMGCFrdFqc5AuzVDrKa6mvwDB9i+dSvvr1jhT2B27dxJfHw8Mc3YISCURmRlUVFezratW5s+uQnlZWXEJyRwzrnnct5FFzEyK4uy0lL/WmplpaXU1NToZAClgizvSH6DVTOfGuMl78jBNmqRUupEaOUsxHyzMgcMHEj+wYN88O679O3XjyMFBYwdPz7s+0n2SEmhV+/ebPnmGwYNHtzsddfqU15eTqxdlYuNjSV90CA2fPUVpfauBLqMhlKhce3UH4S7CUqpINLKWYhV28lZz169OGfGDPr068fuXbuIj49nQHp6eBtnG5GVRVVVFVs2H7fVaYuUlZURG7DivzsmBpfL9V1y5ltGQ5MzpZRSqkFaOQuxwCUzot1uxn/ve/QfMIDYuDgcETJjsUvXrvQfMIBtW7YwZNiwVm2p5PV6qayoqJWciQhx8fGUBSRn0W437hOozimllFIdnVbOQszXrRnlsvJgEaFXnz506do1nM06zvDMTLxeL98ErO7dEpWVlXi9Xn+3pk/d5CwxMbHW7E2llFJK1aaVsxDzdWuGY1ZmS/gWqN25fTtDMzL8uwk0V3mZtcBl3eQsPj6eIwUFgDXmrGcQluxQStVm/t/9sH1P0ycO7oc89eumz1NKhZVWzkLMYydnJ7pMRVvIGDECEWHLN9+0+Fp/clanSzQuPp6qykrKSkupKC/X8WZKhcLwQeBqYpiEywkjBrX6KR588EFGjBhBVlYW2dnZ/Pe//2Xy5MmsXbvWf05ubi4jR4703169ejXjx48nIyODjIwMnn76af99ixYtok+fPmRnZzN8+HBefvll/vKXv5CdnU12djbR0dFkZmaSnZ3NHXfc0ep2K9UeaeUsxHzJWXQ7SM7i4uLo2r07RfbA/ZYot7eAqpucxdsVuAP79wM6GUCpkLjiPFjxCVDT8DkOB1xxfqse/tNPP+Wtt95i/fr1uN1uDh8+3ORWSwcOHODyyy9n+fLljBkzhsOHDzN9+nT69OnDeeedB8Att9zCL37xC7Zu3crYsWMpKCjgqquuAqy10j744AN69OjRqjYr1Z5p5SzEPFVVOBwOnK72kQe73W489gK5TcndsYOvc3IAKzlzOBy466zbFh9Iffl9AAAgAElEQVQfD8DBAwcAdHcApUJAuneB6RMarp65nDBjAtItuVWPv3//fnr06OGfzNOjRw969+7d6DVPPvkkc+fOZcyYMf5rfvvb37J48eLjzh06dChxcXEcPXq0Ve1TqqPR5CzEPB4PrqiodjMIPjo6utmbD+/ZtYttW7bg9Xopt5fRqPs64+zkbP/evURFRZFg31ZKBdkV51nVsfqcQNUMYNq0aezZs4dhw4Zxww038OGHH/rvmz17tr8r8vvf/77/+MaNGxk7dmytxxk3bhwb65l0tH79eoYOHUpqamqr26hUR6LJWYh5PB6i2kGXpk90dDSVlZVNbgUDVrWspqaG4qIiKzmLO37PvujoaFx21fDU00+PmOVDlOpoGqyenWDVDCAhIYF169bx9NNPk5KSwqxZs1i2bBkAL774Ijk5OeTk5PD222+36HEfffRRRowYwamnnspdd93V6vYp1dFochZk5eXlfPDuu3yzYQPVHg/V7S05c7vxer3UVFc3ea5vEsCxo0cpLS2tNzkTEbJGj+b0SZN0pqZSoVZf9ewEq2Y+TqeTyZMnc++99/LEE0/w+uuvN3r+8OHDWbduXa1j69atY8SIEf7bt9xyCxs3buT1119n3rx5VFRUnHA7leoINDkLstwdOyg4fJiNX3/NF+vWUdXekjN7yY+mujarqqr8kx327NpFWWkpPVJS6j130JAhpGliplTIHVc9C0LVDODbb79la8D+uzk5OQwYMKDRa2688UaWLVtGjj0utaCggIULF3L77bcfd+7MmTMZN24czz333Am1U6mOQpOzIDLGkLtjB6lpafTu25ejR47gqapql8lZZROTAnxVM/huJmavPn1C1zClVPMEVs+CVDUrKSnhyiuvZPjw4WRlZbFp0yYWLVrU6DW9evXihRde4NprryUjI4MJEyZw9dVXc8EFF9R7/t13383vf/97vN7GN3BXqjMI2RRCEfkzcD6Qb4wZaR+7H7gQ8AL5wFxjzL56rr0S+JV98wFjTLv4OHU4P5/SkhJGZGZy9OhR8g8cINrtjvgFaAP5Nj5vqnLmWzojuUsXCo8do2u3bsTV062plGpb0r0LZvoEeOujoFTNAMaOHcsnn3xy3PGVK1fWup2ens6GDRv8tydNmsSaNWvqfcy6yd3YsWP59ttv/bdzc3Nb3V6l2rtQVs6WATPqHHvYGJNljMkG3gLurnuRiHQD7gFOBcYD94hIZO11VIcxht25ufz300+Jdrvp3bcv8fHxVFdXU15W1i4rZ56mkjO7ctbbrpb17ts3tA1TSjXfFefByCFBqZoppdpeyCpnxpiPRCS9zrHA1U3jgfqmBE4H3jXGHAEQkXexkryXQ9PSE1NcVMQX69aRf+AAXbt1Y+z48bhcLv/6XsaY9pWc2ZWzpro1y8rKEBEGDBzIgf376dfE+BOlVNuR7l3g0QXhboZSqpXafGVUEXkQmAMUAlPqOaUPELhJXJ59rL7Hug64DqB///7BbWg9iivKeGPNf/jBKVNxeGH7li1s27IFh8PB6HHjGDh4MA57rEd8wN6U7alb093AhABvTU2tZTDKy8qIiYkhITGRs6ZPb9M2KqWUUh1Zm08IMMbcZYzpB7wI3HSCj/W0MWacMWZcSgMzBYNp9eb17Ck4wAcb1/Du22+zZfNm+vTty7TzzmPw0KH+xAy+W3wV8K/z1R44nE5cLlet5Kzw2DGWv/Yaa//7X//xhtY1U0qFn6kppnrf3Zia4nA3RSnVCuGcrfkicEk9x/cC/QJu97WPhVVxRRlf7t6KATbkbafcU8kZZ57J+AkTjttPEqyELMY+Ht2OKmdgdW1WBXRr5h88iNfrZXduLu++/Tb79+6lrKxMJwAoFaG8xf/BW/R/eIv/E+6mKKVaoU2TMxEZGnDzQmBzPaetAKaJSFd7IsA0+1hYrd683r9qvjGGw1EeujWxIa9v3JmrHY05A2t/zcDkrODwYeLi45lyzjlEu918/NFHFBcVaeVMqQhkjMF79BWQOLxHX23Wbh9KqcgSsuRMRF4GPgVOEpE8EZkHLBaRDSLyFVbS9TP73HEi8j8A9kSA+4E19td9vskB4eKrmtUYa/0dL4ZCVzWVNZ5Gr/MlZ+1pQgBYY+QCuzULDh+me48edO3WjbOmTePkkSNxOBwkd+kSxlYqpepjKjZiPPng7ILxHMRUbDrhx3Q6nWRnZzNy5Eh++MMfUhawzmFdK1eurHfZjeY6duwYf/zjH/239+3bx6WXXtroNbm5uYwcObLe47Gxsf69P7Ozs/nrX//a6GNNmDDBf+1LL73U4PP5Hnf48OFcf/31ja7PtnTp0iaftzXbXwFcdtllZGVl8eijj9Y6vmjRIkSEbdu2+Y8tWbIEEWHt2rUtfp5gWLJkSaPvnda6+OKLyc7OZsiQISQnJ/u/1615Hy5atIhHHnkEsNbee++994Ld3GYJ5WzNy+o5/GwD564Frgm4/WfgzyFqWosFVs0Crdr8Bedmn97gdb5JAe1pQgBYlbNjpaWANSuzvKyM7naV0OF0MiIzk5NOPhmn7pOpVMTxFr4JeBERDF68hctxxI5o8rrGxMbG+lf6nz17NkuXLuXWW2+t99yVK1eSkJDgT3Jaypec3XDDDQD07t2b1157rXUNBwYPHuxve3P4/qD7krPLL7+80cetrq5m6tSpLF++nB/84Af1nnv99dc3+bw5OTmsXbu21ubxTTlw4ABr1qyplYAFyszM5JVXXuFXv7KWDf373/9ea/ustrZkyRKuuOKKoA+JeeONNwDrvffII4/w1ltv1bq/urq6VWO/77vvvqC0rzV0h4Am1K2a+Rjgy91bKKlo+FNAt+7diYqKqndMWiSLDqicHTl8GLBeSyCXy4WItHnblFLfqd5/P1VbJtX68hb+Gxz2bHFHAt7Cfx93TvX+B1r9nBMnTmTbtm0cOXKEiy66iKysLE477TS++uorcnNzWbp0KY8++ijZ2dmsWrWKQ4cOcckll3DKKadwyimn8PHHHwNWheLqq69m8uTJDBo0iMceewyAO+64g+3bt5Odnc2CBQtqVcVyc3OZOHEiY8aMYcyYMa2u0O3atYuhQ4dy+PBhvF4vEydO5J133gGsTd597Vi1ahXZ2dnHVaUCuVwuJkyYwLZt28jNzWXq1KlkZWVx1llnsXv3bv9r9VVjJk+ezMKFCxk/fjzDhg1j1apVVFVVcffdd/Pqq6+SnZ3Nq6++Wus5KioquOqqq8jMzGT06NF88MEHAEybNo29e/f6Y13XRRddxJtvvgnA9u3bSU5OpkfAcJyXX36ZzMxMRo4cycKFC/3HExISWLBgASNGjODss8/m888/93+f/vnPfwJQU1PDggULOOWUU8jKyuKpp54CrARp8uTJXHrppWRkZDB79myMMTz22GPs27ePKVOmMGXKlFqxBnjttdeYO3cuAHPnzmX+/PmcdtppDBo0iJUrV3L11Vdz8skn+89pyrJly5g5cyZTp07lrLPOoqSkhLPOOosxY8aQmZnpjwvAgw8+yLBhwzjjjDNqLYQ8d+5c/weD9PR07rnnHv/1mzdbo7IOHTrEOeecw4gRI7jmmmsYMGAAh+2/mydCk7MmNFQ1A2tsx6rNXzR4ba8+fbjgBz9od92avuTMGMPhQ4dwOp100S5MpSKOs/uVSPQAwAmOLoizG+LqjohV1RZxWred3cDRBXAi0ek4u89p1fNVV1fzf//3f2RmZnLPPfcwevRovvrqK37zm98wZ84c0tPTuf7667nlllvIyclh4sSJ/OxnP+OWW25hzZo1vP7661xzjb+ThM2bN7NixQo+//xz7r33XjweD4sXL/ZXpR5++OFaz5+amsq7777L+vXrefXVV/npT3/aZJt9iZ7va9WqVQwYMICFCxcyf/58fve73zF8+HCmTZtW67rFixczceJEcnJyuOWWWxp8/LKyMt5//30yMzO5+eabufLKK/nqq6+YPXt2g+2rrq7m888/Z8mSJdx7771ER0dz3333MWvWLHJycpg1a1at85988klEhK+//pqXX36ZK6+8koqKCv75z3/6YzVx4sTjnicpKYl+/fqxYcMGXnnllVqPu2/fPhYuXMh//vMfcnJyWLNmDcuXLwegtLSUqVOnsnHjRhITE/nVr37Fu+++yxtvvMHdd1trxz/77LMkJyezZs0a1qxZwzPPPMPOnTsB+OKLL1iyZAmbNm1ix44dfPzxx/z0pz+ld+/efPDBB/7ksjFHjx7l008/5dFHH2XmzJnccsstbNy4ka+//rrZldD169fz2muv8eGHHxITE8Mbb7zB+vXr+eCDD7jtttswxrBu3TpeeeUVf7dyQztaAPTo0YP169czf/58f7J97733+mN16aWX+hPyE9V+1ngIg4aqZj41xsuXu7cwMWM0CTH1l2kDl9doL6LdbowxlJaWsmfXLnr27l1rjTOlVGSQ6P64+j9DTf4f8Bb9GyOxiOP4YRTGWwmmAkfSuThTf4o4Ylr0POXl5WRnZwNW5WzevHmceuqpvP766wBMnTqVgoICioqKjrv2vffeY9Om78a9FRUVUVJSAsB5552H2+3G7XaTmprKwYMHG22Hx+PhpptuIicnB6fTyZYtW5pse0Pdmtdccw1///vfWbp0aYu6PX18SZ+IcOGFF3Luuefyk5/8hH/84x8A/OQnP6l3k3fA3/05duzYZm1TtXr1am6++WYAMjIyGDBgAFu2bCEpKanJa3/84x/zyiuvsGLFCt5//33+8pe/ALBmzRomT56Mbxmq2bNn89FHH3HRRRcRHR3NjBnWBj+ZmZm43W6ioqLIzMz0t/edd97hq6++8leWCgsL2bp1K9HR0YwfP56+9q4x2dnZ5ObmcsYZZzTZ1kAXXHABIkJmZiZpaWlkZmYCMGLECHJzc/3vx8acc845dOvWDbCKKXfeeScfffQRDoeDvXv3cvDgQVatWsXFF1/s72qdOXNmg48X+H3zfZ9Xr17t71adMWMGXbsGZ0MjTc4a0VjVzMdXPWts7Fl7k5qWhsPhYPXKlVRWVjJ46NCmL1JKhYU4YnD1XEhNbBY1BxcD9YxxNWU40+7AmXxuq54jcMxZS3m9Xj777DNiYo5PCN32jiRgTTqorq5u9LEeffRR0tLS+PLLL/F6vfU+ZnOVlZWRl5cHWBu7JyYmtuj6lo5lC+R73c15zSfq/PPPZ8GCBYwbN65ZyRxYk9h8w1YcDoe/vQ6Hw99eYwyPP/440+ssQr5y5cpmf18Dh8ZUVFTUui/wOQMfL7ANTYkPWG/0xRdf5NChQ6xbt46oqCjS09OPe86mtOX3rf2VddpQ3pH8BqtmPjXGS96Rxj/ttTfJXbowZNgwSoqLSU5OJiU1NdxNUko1QdyDQRqYfCRuHO4hQX2+iRMn8uKLLwLWH+QePXqQlJREYmIixcXfLX47bdo0Hn/8cf/tphKautcHKiwspFevXjgcDp5//nlqampa3f6FCxcye/Zs7rvvPq699toWtaMhEyZM4JVXXgGsZKC+rsaGNPZ8gbHesmULu3fv5qSTTmrW48bFxfHQQw9x11131To+fvx4PvzwQw4fPkxNTQ0vv/wyZ555ZrPbO336dP70pz/h8Xj87Sq1J5I1pO5rTEtL45tvvsHr9fqrT6FSWFhIamoqUVFRfPDBB+zatQuASZMmsXz5csrLyykuLuZf//pXix739NNP529/+xtgVROPHj0alPZq5awR106tf+ZNZzB85EiOHT3K4KFDdeC/Uu1B5TbA+jBpvCVgvCAOxJEAVGMqtyExwauC+wb0Z2VlERcXx3PPPQdY3VGXXnopb775Jo8//jiPPfYYN954I1lZWVRXVzNp0iSWLl3a4ON2796d008/nZEjR3Luuedy4403+u+74YYbuOSSS/jrX//KjBkzalVGGuLrfvS5+uqrGTVqFGvWrOHjjz/G6XTy+uuv85e//IWrrrrKf15WVhZOp5NRo0Yxd+7cRsed+Tz++ONcddVVPPzww6SkpPi7EJtjypQpLF68mOzsbH75y1/WGh92ww03MH/+fDIzM3G5XCxbtqxWNakpP/7xj4871qtXLxYvXsyUKVMwxnDeeedx4YUXNvsxr7nmGnJzcxkzZgzGGFJSUvxj1hpy3XXXMWPGDP/Ys8WLF3P++eeTkpLCuHHj/N3doTB79mwuuOACMjMzGTduHBkZGQCMGTOGWbNmMWrUKFJTUznllFNa9Lj33HMPl112Gc8//zzf+9736NmzZ4ursPWRjrJA4bhx40y41m5RSqlQ+eabbzj55JObPK/6wEN4i94GHEh0P5wpN1Bz6ElMVR7gxZF0Pq6euhm6UsFUWVmJ09728NNPP2X+/Pn1Vocb+DlusPKhlTOllOoATMVGMFU4ki/2D/qX2GxrskDhckzF1+FuolIdzu7du/nRj36E1+slOjqaZ555JiiPq8mZUkp1ABI9CEe3OTiTzv7umG+yQNxYTMnqMLZOqY5p6NChfPFFw0tqtZYmZ0opFeGMMU2O/XT1XtTgfc6ksyEgaVNKtZ3WDB/T2ZpKKRXBYmJiKCgo0A3MlWqHjDEUFBS0eNkXrZwppVQE69u3L3l5eRw6dCjcTVFKtUJMTIx/Ud7m0uRMKaUiWFRUFAMHDgx3M5RSbUi7NZVSSimlIogmZ0oppZRSEUSTM6WUUkqpCNJhdggQkUPArnC3A+gBHA53IzoYjWnoaGyDT2MafBrT4NA4Bt+JxPSwMWZGfXd0mOQsUojIWmPMuHC3oyPRmIaOxjb4NKbBpzENDo1j8IUqptqtqZRSSikVQTQ5U0oppZSKIJqcBd/T4W5AB6QxDR2NbfBpTINPYxocGsfgC0lMdcyZUkoppVQE0cqZUkoppVQE0eRMKaWUUiqCaHKmVAcmIhLuNiil2o7+zHcMmpy1goicJCIauyASkctFZJT9f/3lEjz6PlXtgv5OVZFKRPq09XPqD0MLiMg5IvJf4Bo0dkEhImeLyCpgCTAawOgslRMmIueJyFvA/SJyerjb0xGIyEUi8riIdAt3WzoKEZkpIreGux0dgYjMEJE3sX7mdaHZILD/Pq0Drm/r53a19RO2N3YVxwX8GrgMWGiM+Ufg/ZpMtIwd0xjgOSAVeAC4EIiz73caY2rC18L2TUTGAvcAi4Ak4EoRGWqMWSYiDmOMN6wNbGfs9+vFwINAIrBSRN7QOLaeiLiA24D5QH8R+Y8xJkd/9lvGfm+6gaXAEOC3wFRgnojkGmN0q6YWsmMahVUwmAAsMsYsD7y/Lf7ma/WnCcbiAbzAa77ETEQmikhUeFvXPtkxLQdeNMZMNsasAD4BfmLfr7+cT8zZwCpjzNvAm8AB4KcikmyM8Wq3ccvYv4h3AGcAPwOuAPqGtVHtnDGmGvgWyABuBZ6yj+vPfgvYv0srsH7OzzTG/BP4B9YyWZqYtYId0yqsYsFyY8xyEXH4ht20VTFG1zlrgIj8FMgE1hhjnhaRnsBiwADjgFzgKPChMeZZraA1LSCmnxtjngk47gROA64C7jXG7AlTE9ulunEVkfHAC8CpxpijIvJrrE/Tnxpj7gxnW9sLEbkS2GeMede+7bITCkTkb1gfJv5o/xJXzWC/T3sD640xfxORKPuDLyKyE7jLGPNS4HFVv7qxDDj+I+BJYCOwClhhjFkdnla2LwEx/cIY86qIDMZaYPYLrA+8e4D9wOt2QSGktHJWDxGZC1wOvA7MFpFfAZXAciAa+CEw077/ByLSXxOzxtWJ6RUicqeIDAL/p+UiYBRwLGyNbIfqietdWB8cVgDP2+P5BmF9sOgiIvFhamq7ICJdReQ1rHj9zv7gABBYcfwDcAEwss61WpGsh1huAWYBa4F77fdt14DTbgUeBtDErGENxVJE0uxT8rE+iJ0N7APmikhKeFrbPtQT00UiMs8Ysx3rb36Gfd/lwAbgYhHpEep2aXJWv7OAh4wx/8YaF+EG/p/d73ydMWaznYx9hZVM6C+TptWNaTRW9xAAxpivgQrgx+FpXrtVN64xwBxjzM3ADcB9xpirsGIba4wpDV9TI58x5ijwDnAysA64O+A+Y//7MZADnCsiGSJyXeD9qjY7LlOAXxljXgNuAbKA6QHnvAFsEZFfgDUQOxxtjXQNxHIUMMO+f6Ux5mu7yvs1Vtdcebja2x40FFMR+ZEx5nHgx8aYb40xxVg/90lAWajbpclZgICp3F8A5wMYY9YCHwMDReT0On/crgRisbo3VT0aielnQB8ROcM+T7CqPTFagWhaE+/VYSIy0Riz29ctB5wHbG/7lrYfAe+7vxpjjgF/xKqMD7DH6jkD4r4E+CXwIdakFq2ccXwMAuK1FpgIYH+Q2AqMEJGTAk6fD/xWRA4Abb50QaRpQSy3ACeLyLA6DzENKzHT5MzWgph+A4wVkZOMMSUBl5yDlZhVhLqtnTo5E5HT7X5lAAJmX30MOERkkn17A1Zfc2/7uktE5Eus7qL59oBMRYtjug/oZZ9nsP7IlWoF4nitiGtP+7pJIvIhMBRrRpey1RNTX2Wswv53DfB/WLM0McbU2ElaGvAE8B8g2xjzQOD1nVxs4I2A9+k2IFFEMu3bHwLJWLNfEZFs4Bms7vkxxpjn2qa5Ea2lsUwSkWgR+YmIfAWkA7/USRa1tCSmSXz3/vyxiGwABgB3mjaYqd0pkzMRGSMi72D9ck0OOO6Lx1asAZWzxJranQekAQPt+7cA1xtj5hhjDrZh0yNWK2PaE+sXiM8vjDF/bqMmtwtBeK/mAjcYYy7W2VuWRmIqcvxCqE8AQ0RkhIikiMhA4DBwszFmpjFmf9u1PHKJyGki8jrwpIhM843VE2vJDIDPgWpgmliTKzZhVcd863EVYL1Pf2iM2dfW7Y8kJxDLsfYElT1YRYM5xpj8cLyGSBOE9+cu2jimnSo5E5EoEXkKawbGY1jdaJPt+5wB2XAx1kwXN/CIWEtmdMX6pYzdp/9pGzc/IgUhpgW+x9KZb98J4nt1tzFmYxs3PyI1I6bGrozFikgCWPED3sAav7MK6GpX0HaH5UVEIBGZjNUF/A+s5TGuALqKtaZeNYAxZhtW19Fg4A770kqsP3oYY/bY4047tSDFcqU9LlIRtJh+aoxZ1Zbt7lTJGdYfsI+AicaYt7C+WSfbmXINgIjcC7wEFGItPNsV65dyIdaiqao2jWloaFyDrzkxvQd4EWvIAiJyGdbEikeATGPM+rC0PLJlYS059CLWEi5RQInvA4SIPCAiz2JNsHgMGC/WqutHsBJk9Z0TieU7YWpzpGuX788Ov0OAiJwGHDHGbMEaz/RiwN1OoMYYU20PFMzEGptzh7Gm0SIiVwPx9kwNhcY0VDSuwdeKmJ4ELPDFFNgJTDbG7GzThkewOjEFK+FdJCL7sBLZb4A/isgKrC62QcDdxphc+/rLAZc96aJT01gGX4eJqTGmQ34BXYD/xer2+RXWHy0AARz2/4cAB7G6KsBelNf+vyPcryHSvjSmGtf28hWEmDrD/Roi7auemCYE3Dce+DNwiX17HtYA/1EB5+j7VGOpMW3mV0fu1ozHKknebP9/Evi3ZvDaA39z7XPO9N0H1mBro/vm1UdjGhoa1+A70ZjqDLfj1Y3pRN8dxpjPgRTsMTpYky26YC8zpO/T42gsg69DxbRDJWciMkdEzhSRJGPMXqyBv3/DWpPkVBHxLYUh9jfCbV9a4TsOtabXdnoa09DQuAafxjT4WhBTN9aWVjfYl54FdLPP05iisQyFjhzTdp+ciaWXiHyAtSjsbOBPItLDGFNhjCkD3sMaLD0VrE/I9uysUqwYnOY7Hp5XEVk0pqGhcQ0+jWnwtTCmZwEYYyqBfwIJIvIRcBlwk+nkSzloLIOvs8S0XU8IsH/B1ohIIrDXGHOFWOuXLMHKoH8A1nYrYm0GnSEiyYDH/gYCXG10CQc/jWloaFyDT2MafK2I6Uki0gWoNMZsFGvD+F7GmB1hexERQmMZfJ0ppu2ycibWNiq/AX4jImdizbCqAf8m2j8DJtj3+TwDJADvAjt95U79xWzRmIaGxjX4NKbBF4SY5opIH2NMeXv4wxdKGsvg64wxbXfJmR38dVgly23A/Vgbj0+xM2Vf//Ei+8vnPKz+5i+x1ivq1KtQB9KYhobGNfg0psEXhJjmYMV0b9u1OjJpLIOvs8a0PXZreoHfGWOeBxCR0Vhb1dwN/Alrs1IHsByYKiLpxlq/pAI42xjzUXiaHdE0pqGhcQ0+jWnwaUyDR2MZfJ0ypu2ucoaVQf/N7mcGa+Pn/saYZYBTRG62s+i+WAtM5gIYY95sr9+kNqAxDQ2Na/BpTINPYxo8Gsvg65QxbXfJmTGmzBhTab5bh+gc4JD9/6uwtmN5C3gZWA/fTZFX9dOYhobGNfg0psGnMQ0ejWXwddaYtsduTcAaIAgYIA1riixYKwPfCYwEdvr6mI3RKfLNoTENDY1r8GlMg09jGjway+DrbDFtd5WzAF6sDUwPA1l25vxrwGuMWd3eBv9FCI1paGhcg09jGnwa0+DRWAZfp4qptOcEU6wNTj+xv/5ijHk2zE1q9zSmoaFxDT6NafBpTINHYxl8nSmm7T056wv8BPi9sVYAVidIYxoaGtfg05gGn8Y0eDSWwdeZYtqukzOllFJKqY6mPY85U0oppZTqcDQ5U0oppZSKIJqcKaWUUkpFEE3OlFJKKaUiiCZnSimllFIRRJMzpVSnJCI1IpIjIhtF5EsRuc3eQLmxa9JF5PK2aqNSqnPS5Ewp1VmVG2OyjTEjsPbrOxe4p4lr0gFNzpRSIaXrnCmlOiURKTHGJATcHgSsAXoAA4DngXj77puMMZ+IyGfAycBO4DngMWAxMBlwA08aY55qsxehlOqQNDlTSnVKdZMz+9gx4CSsDZW9xpgKERkKvGyMGScik4FfGGPOt8+/DurUABsAAAEVSURBVEg1xjwgIm7gY+CHxpidbfpilFIdiivcDVBKqQgUBTwhItlADTCsgfOmYW3CfKl9OxkYilVZU0qpVtHkTCml8Hdr1gD5WGPPDgKjsMbmVjR0GXCzMWZFmzRSKdUp6IQApVSnJyIpwFLgCWON9UgG9htjvFgbLTvtU4uBxIBLVwDzRSTKfpxhIhKPUkqdAK2cKaU6q1gRycHqwqzGmgDwe/u+PwKvi8gc4N9AqX38K6BGRL4ElgF/wJrBuV5EBDgEXNRWL0Ap1THphACllFJKqQii3ZpKKaWUUhFEkzOllFJKqQiiyZlSSimlVATR5EwppZRSKoJocqaUUkopFUE0OVNKKaWUiiCanCmllFJKRZD/D5QeLYcGy58JAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "tnEkMrVO1sjM",
"outputId": "3bf983bc-c73b-4f67-ae4e-3b97cd02fb00",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 342
}
},
"source": [
"#the second figure explores thresholds and boundaries for signal generation\n",
"#we can see after 2017/11/15, nokjpy price went skyrocketing\n",
"#as a data scientist, we must ask why?\n",
"#is it a problem of our model identification\n",
"#or the fundamental situation of nokjpy or oil changed\n",
"\n",
"ax=plt.figure(figsize=(10,5)).add_subplot(111)\n",
"ax.spines['top'].set_visible(False)\n",
"ax.spines['right'].set_visible(False)\n",
"\n",
"signals['fitted'].plot(lw=2.5,label='Fitted',c='w',alpha=0.6)\n",
"signals['nok'].plot(lw=2,label='Actual',c='#04060f',alpha=0.8)\n",
"ax.fill_between(signals.index,signals['upper'],\n",
" signals['lower'],alpha=0.2,label='1 Sigma',color='#2a3457')\n",
"ax.fill_between(signals.index,signals['stop profit'],\n",
" signals['stop loss'],alpha=0.1,label='2 Sigma',color='#720017')\n",
"\n",
"plt.legend(loc='best')\n",
"plt.title('Fitted vs Actual')\n",
"plt.ylabel('NOKJPY')\n",
"plt.xlabel('Date')\n",
"plt.show()"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "YTU82or52slg",
"outputId": "4c96fd10-1f14-4c84-880c-1d0de24504e7",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 334
}
},
"source": [
"#if we decompose nokjpy into long term trend and short term random process\n",
"#we could clearly see that brent crude price has dominated short term random process\n",
"#so what changed the long term trend?\n",
"#there are a few possible reasons\n",
"#saudi and iran endorsed an extension of production caps on that particular date\n",
"#donald trump got elected as potus so he would encourage a depreciated us dollar\n",
"#which ultimately pushed up the oil price\n",
"\n",
"# In[12]:\n",
"\n",
"#lets normalize all prices by 100\n",
"#its easy to see that nok follows euro\n",
"#and economics explanation would be norway is in eea\n",
"#its economy heavily relies on eu\n",
"ax=plt.figure(figsize=(10,5)).add_subplot(111)\n",
"ax.spines['top'].set_visible(False)\n",
"ax.spines['right'].set_visible(False)\n",
"\n",
"(df['nok']/df['nok'][0]*100).plot(c='#ff8c94',label='Norwegian Krone',alpha=0.9)\n",
"(df['usd']/df['usd'][0]*100).plot(c='#9de0ad',label='US Dollar',alpha=0.9)\n",
"(df['eur']/df['eur'][0]*100).plot(c='#45ada8',label='Euro',alpha=0.9)\n",
"(df['gbp']/df['gbp'][0]*100).plot(c='#f8b195',label='UK Sterling',alpha=0.9)\n",
"(df['brent']/df['brent'][0]*100).plot(c='#6c5b7c',label='Brent Crude',alpha=0.5)\n",
"\n",
"plt.legend(loc='best')\n",
"plt.ylabel('Normalized Price by 100')\n",
"plt.xlabel('Date')\n",
"plt.title('Trend')\n",
"plt.show()"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "ply4Ih694bCX",
"outputId": "6cddff4a-6780-418a-a213-760eb3a8ced1",
"colab": {
"base_uri": "https://localhost:8080/"
}
},
"source": [
"#that still doesnt sound convincable\n",
"#lets try cointegration test\n",
"#academically we should use johansen test which works on multi dimensions\n",
"#unfortunately, there is no johansen test in statsmodels (at the time i wrote this script)\n",
"#well, here we go again\n",
"#we have to use Engle-Granger two step!\n",
"\n",
"\n",
"x2=df['eur'][df.index<'2017-04-25']\n",
"x3=sm.add_constant(x2)\n",
"\n",
"model=sm.OLS(y,x3).fit()\n",
"ero=model.resid\n",
"\n",
"print(adf(ero))\n",
"print(model.summary())"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"(-2.6304210139887494, 0.08687143224904925, 3, 1027, {'1%': -3.4367333690404767, '5%': -2.8643583648001925, '10%': -2.568270618452702}, -757.83914799221)\n",
" OLS Regression Results \n",
"==============================================================================\n",
"Dep. Variable: nok R-squared: 0.730\n",
"Model: OLS Adj. R-squared: 0.730\n",
"Method: Least Squares F-statistic: 2787.\n",
"Date: Mon, 31 Jan 2022 Prob (F-statistic): 4.25e-295\n",
"Time: 16:11:01 Log-Likelihood: -1314.0\n",
"No. Observations: 1031 AIC: 2632.\n",
"Df Residuals: 1029 BIC: 2642.\n",
"Df Model: 1 \n",
"Covariance Type: nonrobust \n",
"==============================================================================\n",
" coef std err t P>|t| [0.025 0.975]\n",
"------------------------------------------------------------------------------\n",
"const -5.9076 0.399 -14.807 0.000 -6.691 -5.125\n",
"eur 0.1604 0.003 52.790 0.000 0.154 0.166\n",
"==============================================================================\n",
"Omnibus: 34.290 Durbin-Watson: 0.045\n",
"Prob(Omnibus): 0.000 Jarque-Bera (JB): 36.868\n",
"Skew: 0.456 Prob(JB): 9.87e-09\n",
"Kurtosis: 3.159 Cond. No. 1.94e+03\n",
"==============================================================================\n",
"\n",
"Warnings:\n",
"[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
"[2] The condition number is large, 1.94e+03. This might indicate that there are\n",
"strong multicollinearity or other numerical problems.\n"
]
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "alPC2BAd5Hsv",
"outputId": "7103b01a-f921-47af-abcf-e68ac2c78838",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 350
}
},
"source": [
"#unfortunately, the residual hasnt even reached 90% confidence interval\n",
"#we cant conclude any cointegration from the test\n",
"#still, from the visualization\n",
"#we can tell nok and eur are somewhat correlated\n",
"#our rsquared suggested euro has the power of 73% explanation on nok\n",
"\n",
"#then lets do a pnl analysis\n",
"capital0=2000\n",
"positions=100\n",
"portfolio=pd.DataFrame(index=signals.index)\n",
"portfolio['holding']=signals['nok']*signals['cumsum']*positions\n",
"portfolio['cash']=capital0-(signals['nok']*signals['signals']*positions).cumsum()\n",
"portfolio['total asset']=portfolio['holding']+portfolio['cash']\n",
"portfolio['signals']=signals['signals']\n",
"\n",
"\n",
"# In[15]:\n",
"\n",
"\n",
"portfolio=portfolio[portfolio.index>'2017-10-01']\n",
"portfolio=portfolio[portfolio.index<'2018-01-01']\n",
"\n",
"\n",
"# In[16]:\n",
"\n",
"\n",
"#we plot how our asset value changes over time\n",
"ax=plt.figure(figsize=(10,5)).add_subplot(111)\n",
"ax.spines['top'].set_visible(False)\n",
"ax.spines['right'].set_visible(False)\n",
"\n",
"portfolio['total asset'].plot(c='#594f4f',alpha=0.5,label='Total Asset')\n",
"ax.plot(portfolio.loc[portfolio['signals']>0].index,portfolio['total asset'][portfolio['signals']>0],\n",
" lw=0,marker='^',c='#2a3457',label='LONG',markersize=10,alpha=0.5)\n",
"ax.plot(portfolio.loc[portfolio['signals']<0].index,portfolio['total asset'][portfolio['signals']<0],\n",
" lw=0,marker='v',c='#720017',label='The Big Short',markersize=15,alpha=0.5)\n",
"ax.fill_between(portfolio['2017-11-20':'2017-12-20'].index,\n",
" (portfolio['total asset']+np.std(portfolio['total asset']))['2017-11-20':'2017-12-20'],\n",
" (portfolio['total asset']-np.std(portfolio['total asset']))['2017-11-20':'2017-12-20'],\n",
" alpha=0.2, color='#547980')\n",
"\n",
"plt.text(pd.to_datetime('2017-12-20'),\n",
" (portfolio['total asset']+np.std(portfolio['total asset'])).loc['2017-12-20'],\n",
" 'What if we use MACD here?')\n",
"# plt.axvline('2017/11/15',linestyle=':',label='Exit',c='#ff847c')\n",
"plt.legend()\n",
"plt.title('Portfolio Performance')\n",
"plt.ylabel('Asset Value')\n",
"plt.xlabel('Date')\n",
"plt.show()"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "12v5yp5k5eK0",
"outputId": "29556470-805c-4822-a234-fe8a4aaf6770",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 713
}
},
"source": [
"#surprising when our model is valid for prediction\n",
"#its difficult to make money from thresholds oscillating\n",
"#when actual price goes beyond stop order boundary\n",
"#that is basically the most profitable trade ever\n",
"#best to follow up with a momentum strategy\n",
"#maybe this is not a statistical arbitrage after all\n",
"#the model is a trend following entry indicator\n",
"import copy\n",
"\n",
"\n",
"def oil_money(dataset):\n",
"\n",
" df=copy.deepcopy(dataset)\n",
"\n",
" df['signals']=0\n",
" df['pos2 sigma']=0.0\n",
" df['neg2 sigma']=0.0\n",
" df['pos1 sigma']=0.0\n",
" df['neg1 sigma']=0.0\n",
" df['forecast']=0.0\n",
"\n",
" return df\n",
"\n",
"def signal_generation(dataset,x,y,method, \\\n",
" holding_threshold=10, \\\n",
" stop=0.5,rsquared_threshold=0.7, \\\n",
" train_len=50):\n",
"\n",
" df=method(dataset)\n",
"\n",
" #variable holding takes 3 values, -1,0,1\n",
" #0 implies no holding positions\n",
" #1 implies long, -1 implies short\n",
" #when we wanna clear our positions\n",
" #we just reverse the sign of holding\n",
" #which is quite convenient\n",
" holding=0\n",
"\n",
" #trained is a boolean value\n",
" #it indicates whether the current model is valid\n",
" #in another word,when trained==True, r squared is over 0.7 by default\n",
" #and the regressand is within two sigma range from the fitted value\n",
" trained=False\n",
"\n",
" #counter counts the days of position holding\n",
" counter=0\n",
"\n",
"\n",
" for i in range(train_len,len(df)):\n",
"\n",
" #when we have uncleared positions\n",
" if holding!=0:\n",
"\n",
" #when counter exceeds holding threshold\n",
" #we clear our positions and reset all the parameters\n",
" if counter>holding_threshold:\n",
" df.at[i,'signals']=-holding\n",
" holding=0\n",
" trained=False\n",
" counter=0\n",
"\n",
" #we use continue to skip this round of iteration\n",
" #only if the clearing condition gets triggered\n",
" continue\n",
"\n",
" #plz note i make stop loss and stop profit symmetric\n",
" #thats why we use absolute value of the spread between current price and entry price\n",
" #usually stop loss and stop profit are asymmetric\n",
" #as ppl cannot take as much loss as profit\n",
" if np.abs( \\\n",
" df[y].iloc[i]-df[y][df['signals']!=0].iloc[-1] \\\n",
" )>=stop:\n",
" df.at[i,'signals']=-holding\n",
" holding=0\n",
" trained=False\n",
" counter=0\n",
"\n",
" continue\n",
"\n",
" counter+=1\n",
"\n",
" else:\n",
"\n",
" #if we do not have a valid model yet\n",
" #we would keep trying the latest 50 data points\n",
" if not trained:\n",
" X=sm.add_constant(df[x].iloc[i-train_len:i])\n",
" Y=df[y].iloc[i-train_len:i]\n",
" m=sm.OLS(Y,X).fit()\n",
"\n",
" #if r squared meets the statistical request\n",
" #which is 0.7 by default\n",
" #we can start to build up confidence intervals\n",
" if m.rsquared>rsquared_threshold:\n",
" trained=True\n",
" sigma=np.std(Y-m.predict(X))\n",
"\n",
" #plz note that we set the forecast and confidence intervals\n",
" #for every data point after the current one\n",
" #this would fill in the blank once our model turns invalid\n",
" #when we have a new valid model\n",
" #the new forecast and confidence intervals would cover the former one\n",
" df.at[i:,'forecast']= \\\n",
" m.predict(sm.add_constant(df[x].iloc[i:]))\n",
"\n",
" df.at[i:,'pos2 sigma']= \\\n",
" df['forecast'].iloc[i:]+2*sigma\n",
"\n",
" df.at[i:,'neg2 sigma']= \\\n",
" df['forecast'].iloc[i:]-2*sigma\n",
"\n",
" df.at[i:,'pos1 sigma']= \\\n",
" df['forecast'].iloc[i:]+sigma\n",
"\n",
" df.at[i:,'neg1 sigma']= \\\n",
" df['forecast'].iloc[i:]-sigma\n",
"\n",
" #once we have a valid model\n",
" #we can feel free to generate trading signals\n",
" if trained:\n",
" if df[y].iloc[i]>df['pos2 sigma'].iloc[i]:\n",
" df.at[i,'signals']=1\n",
" holding=1\n",
"\n",
" #once the positions are entered\n",
" #we set confidence intervals back to the fitted value\n",
" #so we could avoid the confusion in our visualization\n",
" #for instance. if we dont do that,\n",
" #there would be confidence intervals even when the model is broken\n",
" #we could have been asking why no trade has been executed,\n",
" #even when actual price falls out of the confidence intervals?\n",
" df.at[i:,'pos2 sigma']=df['forecast']\n",
" df.at[i:,'neg2 sigma']=df['forecast']\n",
" df.at[i:,'pos1 sigma']=df['forecast']\n",
" df.at[i:,'neg1 sigma']=df['forecast']\n",
"\n",
" if df[y].iloc[i]<df['neg2 sigma'].iloc[i]:\n",
" df.at[i,'signals']=-1\n",
" holding=-1\n",
"\n",
" df.at[i:,'pos2 sigma']=df['forecast']\n",
" df.at[i:,'neg2 sigma']=df['forecast']\n",
" df.at[i:,'pos1 sigma']=df['forecast']\n",
" df.at[i:,'neg1 sigma']=df['forecast']\n",
"\n",
"\n",
" return df\n",
"\n",
"def portfolio(signals,close_price,capital0=5000,positions=250):\n",
"\n",
" portfolio=pd.DataFrame()\n",
" portfolio['close']=signals[close_price]\n",
" portfolio['signals']=signals['signals']\n",
"\n",
" portfolio['holding']=portfolio['signals'].cumsum()* \\\n",
" portfolio['close']*positions\n",
"\n",
" portfolio['cash']=capital0-(portfolio['signals']* \\\n",
" portfolio['close']*positions).cumsum()\n",
"\n",
" portfolio['asset']=portfolio['holding']+portfolio['cash']\n",
"\n",
"\n",
" return portfolio\n",
"\n",
"#plotting fitted vs actual price with confidence intervals and positions\n",
"def plot(signals,close_price):\n",
"\n",
" data=copy.deepcopy(signals[signals['forecast']!=0])\n",
" ax=plt.figure(figsize=(10,5)).add_subplot(111)\n",
" ax.spines['top'].set_visible(False)\n",
" ax.spines['right'].set_visible(False)\n",
"\n",
" data['forecast'].plot(label='Fitted',color='#f4f4f8',alpha=0.7)\n",
" data[close_price].plot(label='Actual',color='#3c2f2f',alpha=0.7)\n",
"\n",
" ax.fill_between(data.index,data['pos1 sigma'], \\\n",
" data['neg1 sigma'],alpha=0.3, \\\n",
" color='#011f4b', label='1 Sigma')\n",
" ax.fill_between(data.index,data['pos2 sigma'], \\\n",
" data['neg2 sigma'],alpha=0.3, \\\n",
" color='#ffc425', label='2 Sigma')\n",
"\n",
" ax.plot(data.loc[data['signals']==1].index, \\\n",
" data[close_price][data['signals']==1],marker='^', \\\n",
" c='#00b159',linewidth=0,label='LONG',markersize=11, \\\n",
" alpha=1)\n",
" ax.plot(data.loc[data['signals']==-1].index, \\\n",
" data[close_price][data['signals']==-1],marker='v', \\\n",
" c='#ff6f69',linewidth=0,label='SHORT',markersize=11, \\\n",
" alpha=1)\n",
"\n",
" plt.title(f'Oil Money Project\\n{close_price.upper()} Positions')\n",
" plt.legend(loc='best')\n",
" plt.xlabel('Date')\n",
" plt.ylabel('Price')\n",
" plt.show()\n",
"\n",
"#plotting portfolio performance over time with positions\n",
"def profit(portfolio,close_price):\n",
"\n",
" data=copy.deepcopy(portfolio)\n",
" ax=plt.figure(figsize=(10,5)).add_subplot(111)\n",
" ax.spines['top'].set_visible(False)\n",
" ax.spines['right'].set_visible(False)\n",
"\n",
" data['asset'].plot(label='Total Asset',color='#58668b')\n",
"\n",
" ax.plot(data.loc[data['signals']==1].index, \\\n",
" data['asset'][data['signals']==1],marker='^', \\\n",
" c='#00b159',linewidth=0,label='LONG',markersize=11, \\\n",
" alpha=1)\n",
" ax.plot(data.loc[data['signals']==-1].index, \\\n",
" data['asset'][data['signals']==-1],marker='v', \\\n",
" c='#ff6f69',linewidth=0,label='SHORT',markersize=11, \\\n",
" alpha=1)\n",
"\n",
" plt.title(f'Oil Money Project\\n{close_price.upper()} Total Asset')\n",
" plt.legend(loc='best')\n",
" plt.xlabel('Date')\n",
" plt.ylabel('Asset Value')\n",
" plt.show()\n",
"\n",
"\n",
"#generate signals,monitor portfolio performance\n",
"#plot positions and total asset\n",
"\n",
"data=pd.read_csv('https://open-data.s3.filebase.com/brent_crude_nokjpy.csv')\n",
"signals=signal_generation(data,'brent','nok',oil_money)\n",
"p= portfolio(signals,'nok')\n",
"plot(signals,'nok')\n",
"profit(p,'nok')"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
}
},
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "3CuCzll557j-",
"outputId": "c8ac04c1-64cf-4624-b2a0-77a37462da41",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 704
}
},
"source": [
"#but thats not enough, we are not happy with the return\n",
"#come on, 2 percent return?\n",
"#i may as well as deposit the money into the current account\n",
"#and get 0.75% risk free interest rate\n",
"#therefore, we gotta try different holding period and stop loss/profit point\n",
"#the double loop is very slow, i almost wanna do it in julia\n",
"#plz go get a coffee or even lunch and dont wait for it\n",
"\n",
"\n",
"dic={}\n",
"for holdingt in range(5,20):\n",
" for stopp in np.arange(0.3,1.1,0.05):\n",
" signals=signal_generation(data,'brent','nok',oil_money,holding_threshold=holdingt, stop=stopp)\n",
"\n",
" p=portfolio(signals,'nok')\n",
" dic[holdingt,stopp]=p['asset'].iloc[-1]/p['asset'].iloc[0]-1\n",
"\n",
"\n",
"profile=pd.DataFrame({'params':list(dic.keys()),'return':list(dic.values())})\n",
"\n",
"\n",
"# In[18]:\n",
"\n",
"#plotting the distribution of return\n",
"#in average the return is 2%\n",
"#but we can get -6% and 6% as extreme values\n",
"#we want the largest positive return\n",
"\n",
"ax=plt.figure(figsize=(10,5)).add_subplot(111)\n",
"ax.spines['top'].set_visible(False)\n",
"ax.spines['right'].set_visible(False)\n",
"profile['return'].apply(lambda x:x*100).hist(histtype='bar', color='#f09e8c',width=0.45,bins=20)\n",
"plt.title('Distribution of Return on NOK Trading')\n",
"plt.grid(False)\n",
"plt.ylabel('Frequency')\n",
"plt.xlabel('Return (%)')\n",
"plt.show()\n",
"\n",
"\n",
"# In[19]:\n",
"\n",
"#plotting the heatmap of return under different parameters\n",
"#try to find the optimal parameters to maximize the return\n",
"\n",
"#turn the dataframe into a matrix format first\n",
"matrix=pd.DataFrame(columns= [round(i,2) for i in np.arange(0.3,1.1,0.05)])\n",
"\n",
"matrix['index']=np.arange(5,20)\n",
"matrix.set_index('index',inplace=True)\n",
"\n",
"for i,j in profile['params']:\n",
" matrix.at[i,round(j,2)]= profile['return'][profile['params']==(i,j)].item()*100\n",
"\n",
"for i in matrix.columns:\n",
" matrix[i]=matrix[i].apply(float)\n",
"\n",
"\n",
"#plotting\n",
"fig=plt.figure(figsize=(10,5))\n",
"ax=fig.add_subplot(111)\n",
"sns.heatmap(matrix,cmap='gist_heat_r',square=True, xticklabels=3,yticklabels=3)\n",
"ax.collections[0].colorbar.set_label('Return(%) \\n', rotation=270)\n",
"plt.xlabel('\\nStop Loss/Profit (points)')\n",
"plt.ylabel('Position Holding Period (days)\\n')\n",
"plt.title('Profit Heatmap\\n',fontsize=10)\n",
"plt.style.use('default')\n",
"\n",
"#it seems like the return doesnt depend on the stop profit/loss point\n",
"#it is correlated with the length of holding period\n",
"#the ideal one should be 9 trading days\n",
"#as for stop loss/profit point could range from 0.6 to 1.05"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
}
},
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x360 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
}
}
]
}
]
}
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