2_AutoRegressive_Strategy_Example.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Autoregressive Strategy Simulator\n",
    "\n",
    "This notebook modifies the reset strategy from the ```ResetStrategyImplementer.py``` to use a more complex statistical model to dynamically set the center and width of the liquidity provision ranges  depending on recent behavior of the market. For example, it will broaden the ranges when there have been recent large price movements, in order to ensure we are in range for longer, mitigating impermanent loss by reducing the concentration of liquidity. \n",
    "\n",
    "The statistical model embeds the concept of mean reversion, by allowing to forecast autoregressive term for the return, which shifts the center of the base and limit ranges in the direction that the model expects the price to go, hence the name ```AutoRegressiveStrategy```. This feature seeks to further increase the time spent in-range and mitigating impermanent loss.\n",
    "\n",
    "The underlying model is a simple AR(1)-GARCH(1,1) model, which estimates the recent expected return and the volatility of the price based on recent observations. This new strategy is implemented in ```AutoRegressiveStrategyImplementer.py```.\n",
    "\n",
    "Suppose that the price at time $t$ of the USDC-WETH 0.3% pool is $q_t$, then the price in USDC terms would be $p_t = 1/q_t$. The return is defined as $r_t = p_t / p_{t-1} - 1$, and this is the time series we model:\n",
    "\n",
    "$$ r_t = c + \\rho r_{t-1} + \\sigma_t \\varepsilon_t$$\n",
    "$$ \\sigma_t^2 = \\omega + \\alpha \\varepsilon_{t-1} + \\beta\\sigma_{t-1}^2$$\n",
    "\n",
    "For the strategy, we estimate the model only with the data that was available at that time, therefore making the simulations more realistic. Note that automatically setting bin width is part of the well-known Bollinger Bands strategy. Imposing a consistent statistical model gives more structure to the optimization problem, as well as allowing for forecasting and simulation more easily, which are part of our current plans."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import scipy\n",
    "import GetPoolData\n",
    "import ActiveStrategyFramework\n",
    "import AutoRegressiveStrategy\n",
    "import itertools\n",
    "import arch\n",
    "from matplotlib import pyplot\n",
    "from statsmodels.graphics.tsaplots import plot_acf\n",
    "import plotly.graph_objects as go\n",
    "from plotly.subplots import make_subplots\n",
    "\n",
    "# Create config.py in this directory and enter your own Bitquery API Token\n",
    "from config import BITQUERY_API_TOKEN\n",
    "\n",
    "#################\n",
    "#\n",
    "# Download data\n",
    "#\n",
    "################\n",
    "# Get Swap Data\n",
    "DOWNLOAD_DATA      = True\n",
    "pool_address       = '0x8ad599c3a0ff1de082011efddc58f1908eb6e6d8'\n",
    "token_0_address    = '0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48'\n",
    "token_1_address    = '0xc02aaa39b223fe8d0a0e5c4f27ead9083c756cc2'\n",
    "\n",
    "flipside_queries   = ['https://api.flipsidecrypto.com/api/v2/queries/85a454a3-0f72-470a-bd5b-d39323c376bb/data/latest',\n",
    "                      'https://api.flipsidecrypto.com/api/v2/queries/6f0aec42-5fb8-41b3-9fc1-7bafcf68a9a2/data/latest',\n",
    "                      'https://api.flipsidecrypto.com/api/v2/queries/669fc9f7-8b2d-4dd2-948f-668de9eb4e8a/data/latest']\n",
    "\n",
    "# Price data for theThese must be month ends\n",
    "price_data_begin         = '2020-12-31'\n",
    "price_data_end           = '2022-12-31'\n",
    "file_name                = 'eth_usdc'\n",
    "\n",
    "swap_data  = GetPoolData.get_pool_data_flipside(pool_address,flipside_queries,file_name,DOWNLOAD_DATA)  \n",
    "price_data = GetPoolData.get_price_data_bitquery(token_0_address,token_1_address,price_data_begin,price_data_end,BITQUERY_API_TOKEN,file_name,DOWNLOAD_DATA)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model Evaluation\n",
    "\n",
    "Let's assess how much does the predicted volatility vary over time, and how large are the standardized residuals of the estimated time series process. To compute returns we will be using a one-day interval, which implies that this will be the time horizon for each forecasting step that we do as well. Due to numerical concerns, the price return process is scaled up by a factor of 10, which must be taken into account when looking at the plots.\n",
    "\n",
    "The plot shows these periods of relatively high volatility clusters ocurring peridiocally in the pool. The strategy will respond by wideining the bounds in these regimes, and narrowing them when the volatility cluster ends automatically. \n",
    "\n",
    "Additionally, we can see from the autocorrelation plot that there doesn't appear to be significant autocorrelation of the price return dataset, which as stated before are 1-day returns. The plot shows that even at the one-day frequency, knowing how ETH/USDC did today did not provide meaningful information about how it would do tomorrow, indicating that there will be limited impact from the AR(1) component of the model.\n",
    "\n",
    "On the other hand, the model finds interesting time series structure in the volatility process, with relevant amounts of persistence in the variance itself, as can be seen by the $\\beta=0.8701$ coefficient being highly significant."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "AGGREGATED_MINUTES  = 'D'\n",
    "price_data_filtered = ActiveStrategyFramework.aggregate_price_data(price_data,frequency = AGGREGATED_MINUTES)\n",
    "price_data_filtered = price_data_filtered[abs(price_data_filtered.price_return) <= .9]\n",
    "\n",
    "ar                  = arch.univariate.ARX(price_data_filtered['price_return'].to_numpy()*10, lags=1)\n",
    "ar.volatility       = arch.univariate.GARCH(p=1,q=1)\n",
    "res                 = ar.fit(update_freq=0, disp=\"on\")\n",
    "fig                 = res.plot(annualize='D')\n",
    "\n",
    "%matplotlib inline\n",
    "plot_acf(price_data_filtered['price_return'].to_numpy())\n",
    "pyplot.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "To further assess the impact of the autoregressive term, we run the model at different time frequencies beyond the one-day interval, to understand if the degree of aggregation is significantly impacting model estimation. In the next chart we fit the model for different values of frequency aggregation, with 1 standard deviation error bounds plotted as well.\n",
    "\n",
    "The chart shows that at one minute frequencies you find a negative coefficient. At this one minute frequency the model estimation is subject to significant market microstructure noise, thus the estimation results are unlikely to be useful for longer term price movement estimations. \n",
    "\n",
    "At 30 minute data frequency and above, the coefficient gets closer to zero as the magnitude of volatility $\\sigma_t$ takes on a bigger impact at this frequency than the expected return, but $\\beta$ is still relatively negative consistently. For the strategy simulation we will stick with the one-day estimation frequency (1,440 minutes) to be consistent with prior work."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "periods = [1, 30, 60, 60*12, 60*24, 60*24*3, 60*24*5]\n",
    "ar_coefficient = []\n",
    "\n",
    "price_data_filled = ActiveStrategyFramework.fill_time(price_data)\n",
    "\n",
    "for p in periods:\n",
    "    price_data_filtered = price_data_filled.resample(str(p)+' min',closed='right',label='right').last()\n",
    "    price_data_filtered['price_return'] = price_data_filtered['quotePrice'].pct_change()\n",
    "    ar_p                = arch.univariate.ARX(price_data_filtered['price_return'].to_numpy()[1:]*100, lags=1,rescale=False)\n",
    "    ar_p.volatility     = arch.univariate.GARCH(p=1,q=1)\n",
    "    res_p               = ar_p.fit(update_freq=0, disp=\"off\")\n",
    "    ar_coefficient.append({\n",
    "        'ar_coeff': res_p.params[1],\n",
    "        'ar_std'  : res_p.std_err[1]\n",
    "    })\n",
    "    \n",
    "ar_coefficient_pd = pd.DataFrame(ar_coefficient)\n",
    "\n",
    "CHART_SIZE = 300\n",
    "\n",
    "fig_ar_beta = go.Figure()\n",
    "\n",
    "fig_ar_beta.add_trace(go.Scatter(\n",
    "    x=list(periods), \n",
    "    y=ar_coefficient_pd['ar_coeff'],\n",
    "    error_y=dict(\n",
    "    type='data',\n",
    "    array=ar_coefficient_pd['ar_std'],\n",
    "    visible=True),\n",
    "    fill=None,\n",
    "    mode='lines',\n",
    "    showlegend = False,\n",
    "    line_color='#ff0000'))\n",
    "\n",
    "fig_ar_beta.add_hline(y=0.0)\n",
    "\n",
    "fig_ar_beta.update_layout(\n",
    "    margin=dict(l=20, r=20, t=40, b=20),\n",
    "    height= CHART_SIZE,\n",
    "    title = 'Autoregressive Coefficient',\n",
    "    xaxis_title=\"Minute Frequency Used\",\n",
    "    yaxis_title=r'$\\beta \\text{ coefficient}$',\n",
    ")\n",
    "\n",
    "fig_ar_beta.update_xaxes(type='category')\n",
    "\n",
    "fig_ar_beta.show(renderer=\"png\")    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Comparison with ResetStrategy\n",
    "\n",
    "The parametrization of the ResetStrategy that was analyzed previously for the period July 15th — July 28th (```alpha_param = 0.50```, ```tau_param = 0.95```, ```and limit_param = 0.5```) had a Sharpe Ratio of 4.12. Let's see if we can do better with the more complex AutoRegressive Strategy. An initial version of this strategy used the $\\alpha$ and $\\tau$ parameters to extract ranges from the implied probability distrubtion around the expected return, but we have moved towards simply using them to represent number of annualized standard deviations around the current expected return to infer the ranges. \n",
    "\n",
    "This strategy requires a new parameter in the ```check_strategy``` step to assess if bounds need to be narrowed following a volatility spike, once it has subsided. It checks every hour whether current volatility is less than or equal to ```volatility_param``` percent relative to the last reset. We only need to do check when volatility goes down, as when volatility increases, it will cross a reset range that will indicate a rebalance, where the ranges will be automatically set according to current volatility.\n",
    "\n",
    "### Evaluate Strategy\n",
    "\n",
    "Let's study the strategy by varying the range parameters:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(0.5, 0.25, 0.85)\n",
      "(0.5, 0.25, 0.95)\n",
      "(0.5, 0.75, 0.85)\n",
      "(0.5, 0.75, 0.95)\n",
      "(0.75, 0.25, 0.85)\n",
      "(0.75, 0.25, 0.95)\n",
      "(0.75, 0.75, 0.85)\n",
      "(0.75, 0.75, 0.95)\n",
      "(0.95, 0.25, 0.85)\n",
      "(0.95, 0.25, 0.95)\n",
      "(0.95, 0.75, 0.85)\n",
      "(0.95, 0.75, 0.95)\n",
      "(1.15, 0.25, 0.85)\n",
      "(1.15, 0.25, 0.95)\n",
      "(1.15, 0.75, 0.85)\n",
      "(1.15, 0.75, 0.95)\n"
     ]
    }
   ],
   "source": [
    "#################\n",
    "#\n",
    "# Run Auto Regressive Strategy\n",
    "#\n",
    "################\n",
    "\n",
    "# Select date ranges for strategy simulation\n",
    "DATE_BEGIN                 = pd.to_datetime('2021-07-15 00:00PM',utc=True)\n",
    "DATE_END                   = pd.to_datetime('2021-07-28 00:00PM',utc=True)\n",
    "z_score_cutoff             = 5\n",
    "window_size                = 60\n",
    "\n",
    "# Data for strategy simulation cleaning \n",
    "STRATEGY_FREQUENCY                      = 'H'\n",
    "simulate_data_filtered                   = ActiveStrategyFramework.aggregate_price_data(price_data,STRATEGY_FREQUENCY)\n",
    "simulate_data_filtered_roll              = simulate_data_filtered.quotePrice.rolling(window=window_size) \n",
    "simulate_data_filtered['roll_median']    = simulate_data_filtered_roll.median()\n",
    "roll_dev                                 = np.abs(simulate_data_filtered.quotePrice - simulate_data_filtered.roll_median)\n",
    "simulate_data_filtered['median_abs_dev'] = 1.4826*roll_dev.rolling(window=window_size).median()\n",
    "outlier_indices                          = np.abs(simulate_data_filtered.quotePrice - simulate_data_filtered.roll_median) >= z_score_cutoff*simulate_data_filtered['median_abs_dev']\n",
    "simulate_data_price                      = simulate_data_filtered[~outlier_indices]['quotePrice'][DATE_BEGIN:DATE_END]\n",
    "\n",
    "\n",
    "# Data for statistical analaysis (AGGREGATED_MINUTES frequency data)\n",
    "STAT_MODEL_FREQUENCY       = 'H' # forecast returns at a daily frequency\n",
    "\n",
    "# Initial Position Details\n",
    "INITIAL_TOKEN_0            = 100000\n",
    "INITIAL_TOKEN_1            = INITIAL_TOKEN_0*simulate_data_price[0]\n",
    "INITIAL_POSITION_VALUE     = 2*INITIAL_TOKEN_0\n",
    "FEE_TIER                   = 0.003\n",
    "\n",
    "# Set decimals according to your pool\n",
    "DECIMALS_0 = 6\n",
    "DECIMALS_1 = 18\n",
    "swap_data['virtual_liquidity'] = swap_data['VIRTUAL_LIQUIDITY_ADJUSTED']*(10**((DECIMALS_1  + DECIMALS_0)/2))\n",
    "swap_data['traded_in']         = swap_data.apply(lambda x: -x['amount0'] if (x['amount0'] < 0) else -x['amount1'],axis=1).astype(float)\n",
    "swap_data['traded_out']        = swap_data.apply(lambda x:  x['amount0'] if (x['amount0'] > 0) else  x['amount1'],axis=1).astype(float)\n",
    "\n",
    "# Strategy Parameters\n",
    "alpha_range      = [.50,.75,.95,1.15]\n",
    "tau_range        = [.25,0.75]\n",
    "vol_range        = [0.85,.95]\n",
    "sim_performance  = []\n",
    "sim_results      = []\n",
    "sim_data_collect = []\n",
    "\n",
    "for j in list(itertools.product(alpha_range,tau_range,vol_range)):\n",
    "    print(j)\n",
    "    AR_Strategy                      = AutoRegressiveStrategy.AutoRegressiveStrategy(price_data,j[0],j[1],j[2],data_frequency=STAT_MODEL_FREQUENCY,z_score_cutoff=6,return_forecast_cutoff=.5)\n",
    "    simulated_strategy               = ActiveStrategyFramework.simulate_strategy(simulate_data_price,swap_data,AR_Strategy,INITIAL_TOKEN_0,INITIAL_TOKEN_1,FEE_TIER,DECIMALS_0,DECIMALS_1)\n",
    "    sim_data                         = ActiveStrategyFramework.generate_simulation_series(simulated_strategy,AR_Strategy)\n",
    "    strat_result                     = ActiveStrategyFramework.analyze_strategy(sim_data,frequency=STRATEGY_FREQUENCY)\n",
    "    strat_result['alpha_param']      = j[0]\n",
    "    strat_result['tau_param']        = j[1]\n",
    "    strat_result['volatility_param'] = j[2]\n",
    "    sim_results.append(simulated_strategy)\n",
    "    sim_performance.append(strat_result)\n",
    "    sim_data_collect.append(sim_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>days_strategy</th>\n",
       "      <th>gross_fee_apr</th>\n",
       "      <th>gross_fee_return</th>\n",
       "      <th>net_apr</th>\n",
       "      <th>net_return</th>\n",
       "      <th>rebalances</th>\n",
       "      <th>compounds</th>\n",
       "      <th>max_drawdown</th>\n",
       "      <th>volatility</th>\n",
       "      <th>sharpe_ratio</th>\n",
       "      <th>impermanent_loss</th>\n",
       "      <th>mean_base_position</th>\n",
       "      <th>median_base_position</th>\n",
       "      <th>mean_base_width</th>\n",
       "      <th>median_base_width</th>\n",
       "      <th>final_value</th>\n",
       "      <th>alpha_param</th>\n",
       "      <th>tau_param</th>\n",
       "      <th>volatility_param</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>13</td>\n",
       "      <td>0.379447</td>\n",
       "      <td>0.013515</td>\n",
       "      <td>3.110081</td>\n",
       "      <td>0.110770</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0.153079</td>\n",
       "      <td>0.420480</td>\n",
       "      <td>7.396502</td>\n",
       "      <td>0.007930</td>\n",
       "      <td>0.830956</td>\n",
       "      <td>0.808860</td>\n",
       "      <td>0.866413</td>\n",
       "      <td>0.836215</td>\n",
       "      <td>222154.003345</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>13</td>\n",
       "      <td>0.456518</td>\n",
       "      <td>0.016260</td>\n",
       "      <td>3.139078</td>\n",
       "      <td>0.111803</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0.150707</td>\n",
       "      <td>0.415455</td>\n",
       "      <td>7.555766</td>\n",
       "      <td>0.008867</td>\n",
       "      <td>0.789455</td>\n",
       "      <td>0.807839</td>\n",
       "      <td>0.848622</td>\n",
       "      <td>0.850117</td>\n",
       "      <td>222360.554852</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>13</td>\n",
       "      <td>0.396019</td>\n",
       "      <td>0.014105</td>\n",
       "      <td>2.741138</td>\n",
       "      <td>0.097630</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.141284</td>\n",
       "      <td>0.394987</td>\n",
       "      <td>6.939824</td>\n",
       "      <td>-0.003994</td>\n",
       "      <td>0.815566</td>\n",
       "      <td>0.814858</td>\n",
       "      <td>0.842470</td>\n",
       "      <td>0.836215</td>\n",
       "      <td>219525.912946</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>13</td>\n",
       "      <td>0.411457</td>\n",
       "      <td>0.014655</td>\n",
       "      <td>2.618373</td>\n",
       "      <td>0.093257</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0.135561</td>\n",
       "      <td>0.378688</td>\n",
       "      <td>6.914333</td>\n",
       "      <td>-0.007962</td>\n",
       "      <td>0.774231</td>\n",
       "      <td>0.807649</td>\n",
       "      <td>0.772137</td>\n",
       "      <td>0.761467</td>\n",
       "      <td>218651.424950</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>13</td>\n",
       "      <td>0.302736</td>\n",
       "      <td>0.010782</td>\n",
       "      <td>2.836051</td>\n",
       "      <td>0.101010</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0.146262</td>\n",
       "      <td>0.419090</td>\n",
       "      <td>6.767165</td>\n",
       "      <td>-0.000926</td>\n",
       "      <td>0.741739</td>\n",
       "      <td>0.763328</td>\n",
       "      <td>1.290080</td>\n",
       "      <td>1.254322</td>\n",
       "      <td>220202.006212</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>13</td>\n",
       "      <td>0.281046</td>\n",
       "      <td>0.010010</td>\n",
       "      <td>2.734440</td>\n",
       "      <td>0.097391</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0.142260</td>\n",
       "      <td>0.401179</td>\n",
       "      <td>6.816006</td>\n",
       "      <td>-0.004210</td>\n",
       "      <td>0.754111</td>\n",
       "      <td>0.768511</td>\n",
       "      <td>1.158206</td>\n",
       "      <td>1.142200</td>\n",
       "      <td>219478.201085</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>13</td>\n",
       "      <td>0.260685</td>\n",
       "      <td>0.009285</td>\n",
       "      <td>2.806550</td>\n",
       "      <td>0.099959</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.146226</td>\n",
       "      <td>0.413299</td>\n",
       "      <td>6.790605</td>\n",
       "      <td>-0.001880</td>\n",
       "      <td>0.768840</td>\n",
       "      <td>0.768302</td>\n",
       "      <td>1.263705</td>\n",
       "      <td>1.254322</td>\n",
       "      <td>219991.866215</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>13</td>\n",
       "      <td>0.281046</td>\n",
       "      <td>0.010010</td>\n",
       "      <td>2.734440</td>\n",
       "      <td>0.097391</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0.142260</td>\n",
       "      <td>0.401179</td>\n",
       "      <td>6.816006</td>\n",
       "      <td>-0.004210</td>\n",
       "      <td>0.754111</td>\n",
       "      <td>0.768511</td>\n",
       "      <td>1.158206</td>\n",
       "      <td>1.142200</td>\n",
       "      <td>219478.201085</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>13</td>\n",
       "      <td>0.198830</td>\n",
       "      <td>0.007082</td>\n",
       "      <td>2.838804</td>\n",
       "      <td>0.101108</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.148607</td>\n",
       "      <td>0.422994</td>\n",
       "      <td>6.711218</td>\n",
       "      <td>-0.000837</td>\n",
       "      <td>0.729343</td>\n",
       "      <td>0.729121</td>\n",
       "      <td>1.600693</td>\n",
       "      <td>1.588808</td>\n",
       "      <td>220221.615459</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>13</td>\n",
       "      <td>0.221302</td>\n",
       "      <td>0.007882</td>\n",
       "      <td>2.787160</td>\n",
       "      <td>0.099269</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0.145466</td>\n",
       "      <td>0.412984</td>\n",
       "      <td>6.748838</td>\n",
       "      <td>-0.002507</td>\n",
       "      <td>0.727360</td>\n",
       "      <td>0.728902</td>\n",
       "      <td>1.467061</td>\n",
       "      <td>1.446787</td>\n",
       "      <td>219853.741755</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>13</td>\n",
       "      <td>0.198830</td>\n",
       "      <td>0.007082</td>\n",
       "      <td>2.838804</td>\n",
       "      <td>0.101108</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.148607</td>\n",
       "      <td>0.422994</td>\n",
       "      <td>6.711218</td>\n",
       "      <td>-0.000837</td>\n",
       "      <td>0.729343</td>\n",
       "      <td>0.729121</td>\n",
       "      <td>1.600693</td>\n",
       "      <td>1.588808</td>\n",
       "      <td>220221.615459</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>13</td>\n",
       "      <td>0.221302</td>\n",
       "      <td>0.007882</td>\n",
       "      <td>2.787160</td>\n",
       "      <td>0.099269</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0.145466</td>\n",
       "      <td>0.412984</td>\n",
       "      <td>6.748838</td>\n",
       "      <td>-0.002507</td>\n",
       "      <td>0.727360</td>\n",
       "      <td>0.728902</td>\n",
       "      <td>1.467061</td>\n",
       "      <td>1.446787</td>\n",
       "      <td>219853.741755</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>0.152728</td>\n",
       "      <td>0.005440</td>\n",
       "      <td>2.867228</td>\n",
       "      <td>0.102120</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.150578</td>\n",
       "      <td>0.431239</td>\n",
       "      <td>6.648812</td>\n",
       "      <td>0.000081</td>\n",
       "      <td>0.678811</td>\n",
       "      <td>0.676772</td>\n",
       "      <td>1.931765</td>\n",
       "      <td>1.923294</td>\n",
       "      <td>220424.088456</td>\n",
       "      <td>1.15</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>13</td>\n",
       "      <td>0.178273</td>\n",
       "      <td>0.006349</td>\n",
       "      <td>2.825438</td>\n",
       "      <td>0.100632</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0.147788</td>\n",
       "      <td>0.421920</td>\n",
       "      <td>6.696620</td>\n",
       "      <td>-0.001269</td>\n",
       "      <td>0.694204</td>\n",
       "      <td>0.698188</td>\n",
       "      <td>1.772487</td>\n",
       "      <td>1.751374</td>\n",
       "      <td>220126.408825</td>\n",
       "      <td>1.15</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>13</td>\n",
       "      <td>0.152728</td>\n",
       "      <td>0.005440</td>\n",
       "      <td>2.867228</td>\n",
       "      <td>0.102120</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.150578</td>\n",
       "      <td>0.431239</td>\n",
       "      <td>6.648812</td>\n",
       "      <td>0.000081</td>\n",
       "      <td>0.678811</td>\n",
       "      <td>0.676772</td>\n",
       "      <td>1.931765</td>\n",
       "      <td>1.923294</td>\n",
       "      <td>220424.088456</td>\n",
       "      <td>1.15</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>13</td>\n",
       "      <td>0.178273</td>\n",
       "      <td>0.006349</td>\n",
       "      <td>2.825438</td>\n",
       "      <td>0.100632</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0.147788</td>\n",
       "      <td>0.421920</td>\n",
       "      <td>6.696620</td>\n",
       "      <td>-0.001269</td>\n",
       "      <td>0.694204</td>\n",
       "      <td>0.698188</td>\n",
       "      <td>1.772487</td>\n",
       "      <td>1.751374</td>\n",
       "      <td>220126.408825</td>\n",
       "      <td>1.15</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.95</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    days_strategy  gross_fee_apr  gross_fee_return   net_apr  net_return  \\\n",
       "0              13       0.379447          0.013515  3.110081    0.110770   \n",
       "1              13       0.456518          0.016260  3.139078    0.111803   \n",
       "2              13       0.396019          0.014105  2.741138    0.097630   \n",
       "3              13       0.411457          0.014655  2.618373    0.093257   \n",
       "4              13       0.302736          0.010782  2.836051    0.101010   \n",
       "5              13       0.281046          0.010010  2.734440    0.097391   \n",
       "6              13       0.260685          0.009285  2.806550    0.099959   \n",
       "7              13       0.281046          0.010010  2.734440    0.097391   \n",
       "8              13       0.198830          0.007082  2.838804    0.101108   \n",
       "9              13       0.221302          0.007882  2.787160    0.099269   \n",
       "10             13       0.198830          0.007082  2.838804    0.101108   \n",
       "11             13       0.221302          0.007882  2.787160    0.099269   \n",
       "12             13       0.152728          0.005440  2.867228    0.102120   \n",
       "13             13       0.178273          0.006349  2.825438    0.100632   \n",
       "14             13       0.152728          0.005440  2.867228    0.102120   \n",
       "15             13       0.178273          0.006349  2.825438    0.100632   \n",
       "\n",
       "    rebalances  compounds  max_drawdown  volatility  sharpe_ratio  \\\n",
       "0            4          0      0.153079    0.420480      7.396502   \n",
       "1           12          0      0.150707    0.415455      7.555766   \n",
       "2            1          0      0.141284    0.394987      6.939824   \n",
       "3            6          0      0.135561    0.378688      6.914333   \n",
       "4            3          0      0.146262    0.419090      6.767165   \n",
       "5            6          0      0.142260    0.401179      6.816006   \n",
       "6            1          0      0.146226    0.413299      6.790605   \n",
       "7            6          0      0.142260    0.401179      6.816006   \n",
       "8            1          0      0.148607    0.422994      6.711218   \n",
       "9            6          0      0.145466    0.412984      6.748838   \n",
       "10           1          0      0.148607    0.422994      6.711218   \n",
       "11           6          0      0.145466    0.412984      6.748838   \n",
       "12           1          0      0.150578    0.431239      6.648812   \n",
       "13           6          0      0.147788    0.421920      6.696620   \n",
       "14           1          0      0.150578    0.431239      6.648812   \n",
       "15           6          0      0.147788    0.421920      6.696620   \n",
       "\n",
       "    impermanent_loss  mean_base_position  median_base_position  \\\n",
       "0           0.007930            0.830956              0.808860   \n",
       "1           0.008867            0.789455              0.807839   \n",
       "2          -0.003994            0.815566              0.814858   \n",
       "3          -0.007962            0.774231              0.807649   \n",
       "4          -0.000926            0.741739              0.763328   \n",
       "5          -0.004210            0.754111              0.768511   \n",
       "6          -0.001880            0.768840              0.768302   \n",
       "7          -0.004210            0.754111              0.768511   \n",
       "8          -0.000837            0.729343              0.729121   \n",
       "9          -0.002507            0.727360              0.728902   \n",
       "10         -0.000837            0.729343              0.729121   \n",
       "11         -0.002507            0.727360              0.728902   \n",
       "12          0.000081            0.678811              0.676772   \n",
       "13         -0.001269            0.694204              0.698188   \n",
       "14          0.000081            0.678811              0.676772   \n",
       "15         -0.001269            0.694204              0.698188   \n",
       "\n",
       "    mean_base_width  median_base_width    final_value  alpha_param  tau_param  \\\n",
       "0          0.866413           0.836215  222154.003345         0.50       0.25   \n",
       "1          0.848622           0.850117  222360.554852         0.50       0.25   \n",
       "2          0.842470           0.836215  219525.912946         0.50       0.75   \n",
       "3          0.772137           0.761467  218651.424950         0.50       0.75   \n",
       "4          1.290080           1.254322  220202.006212         0.75       0.25   \n",
       "5          1.158206           1.142200  219478.201085         0.75       0.25   \n",
       "6          1.263705           1.254322  219991.866215         0.75       0.75   \n",
       "7          1.158206           1.142200  219478.201085         0.75       0.75   \n",
       "8          1.600693           1.588808  220221.615459         0.95       0.25   \n",
       "9          1.467061           1.446787  219853.741755         0.95       0.25   \n",
       "10         1.600693           1.588808  220221.615459         0.95       0.75   \n",
       "11         1.467061           1.446787  219853.741755         0.95       0.75   \n",
       "12         1.931765           1.923294  220424.088456         1.15       0.25   \n",
       "13         1.772487           1.751374  220126.408825         1.15       0.25   \n",
       "14         1.931765           1.923294  220424.088456         1.15       0.75   \n",
       "15         1.772487           1.751374  220126.408825         1.15       0.75   \n",
       "\n",
       "    volatility_param  \n",
       "0               0.85  \n",
       "1               0.95  \n",
       "2               0.85  \n",
       "3               0.95  \n",
       "4               0.85  \n",
       "5               0.95  \n",
       "6               0.85  \n",
       "7               0.95  \n",
       "8               0.85  \n",
       "9               0.95  \n",
       "10              0.85  \n",
       "11              0.95  \n",
       "12              0.85  \n",
       "13              0.95  \n",
       "14              0.85  \n",
       "15              0.95  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(sim_performance)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this case, the strategy with ```alpha_param = .50```, ```tau_param = .25``` & ```volatility_param = 0.95```, for the small parameter space studied here can lead to an 83% improvement in Sharpe Ratio, up to 7.55. Let's see what the strategy looks like in the following plot. The ranges set by this strategy were quite wide, with only one rebalance occurring, minimizing impermanent loss in this period."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "SELECTED_STRATEGY  = 1\n",
    "resulting_strat    = sim_results[SELECTED_STRATEGY]\n",
    "resulting_data     = ActiveStrategyFramework.generate_simulation_series(resulting_strat,AR_Strategy)\n",
    "p                  = ActiveStrategyFramework.plot_strategy(resulting_data,'ETH / USDC Price')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Longer Period Estimation\n",
    "\n",
    "In this section we will evaluate the strategy over a longer and more recent time period, September 1st to December 10th 2021, and compare the performance over the same time period for the ResetStrategy.\n",
    "\n",
    "As you can see, the Sharpe ratio for the Autoregressive Strategy is 1.80, whereas the prior optimal reset strategy provides only a 0.05 Sharpe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(0.5, 0.25, 0.85)\n",
      "(0.5, 0.25, 0.95)\n",
      "(0.5, 0.75, 0.85)\n",
      "(0.5, 0.75, 0.95)\n",
      "(0.75, 0.25, 0.85)\n",
      "(0.75, 0.25, 0.95)\n",
      "(0.75, 0.75, 0.85)\n",
      "(0.75, 0.75, 0.95)\n",
      "(0.95, 0.25, 0.85)\n",
      "(0.95, 0.25, 0.95)\n",
      "(0.95, 0.75, 0.85)\n",
      "(0.95, 0.75, 0.95)\n"
     ]
    }
   ],
   "source": [
    "#################\n",
    "#\n",
    "# Run Auto Regressive Strategy\n",
    "#\n",
    "################\n",
    "# Select date ranges for strategy simulation\n",
    "DATE_BEGIN                 = pd.to_datetime('2021-09-01 00:00PM',utc=True)\n",
    "DATE_END                   = pd.to_datetime('2021-12-10 00:00PM',utc=True)\n",
    "\n",
    "# Data for strategy simulation. We can use aggregate_price_data to analyze the strategy at a coarser STRATEGY_FREQUENCY in minutes\n",
    "simulate_data_price        = simulate_data_filtered['quotePrice'][DATE_BEGIN:DATE_END]\n",
    "\n",
    "# Initial Position Details\n",
    "INITIAL_TOKEN_0            = 100000\n",
    "INITIAL_TOKEN_1            = INITIAL_TOKEN_0*simulate_data_price[0]\n",
    "\n",
    "import importlib\n",
    "importlib.reload(ActiveStrategyFramework)\n",
    "importlib.reload(AutoRegressiveStrategy)\n",
    "\n",
    "# Strategy Parameters\n",
    "alpha_range      = [.50,.75,.95]\n",
    "tau_range        = [.25,0.75]\n",
    "vol_range        = [0.85,.95]\n",
    "sim_performance  = []\n",
    "sim_results      = []\n",
    "sim_data_collect = []\n",
    "\n",
    "for j in list(itertools.product(alpha_range,tau_range,vol_range)):\n",
    "    print(j)\n",
    "    AR_Strategy                      = AutoRegressiveStrategy.AutoRegressiveStrategy(price_data,j[0],j[1],j[2],data_frequency=STAT_MODEL_FREQUENCY,return_forecast_cutoff=.5)\n",
    "    simulated_strategy               = ActiveStrategyFramework.simulate_strategy(simulate_data_price,swap_data,AR_Strategy,INITIAL_TOKEN_0,INITIAL_TOKEN_1,FEE_TIER,DECIMALS_0,DECIMALS_1)\n",
    "    sim_data                         = ActiveStrategyFramework.generate_simulation_series(simulated_strategy,AR_Strategy)\n",
    "    strat_result                     = ActiveStrategyFramework.analyze_strategy(sim_data,frequency=STRATEGY_FREQUENCY)\n",
    "    strat_result['alpha_param']      = j[0]\n",
    "    strat_result['tau_param']        = j[1]\n",
    "    strat_result['volatility_param'] = j[2]\n",
    "    sim_results.append(simulated_strategy)\n",
    "    sim_performance.append(strat_result)\n",
    "    sim_data_collect.append(sim_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>days_strategy</th>\n",
       "      <th>gross_fee_apr</th>\n",
       "      <th>gross_fee_return</th>\n",
       "      <th>net_apr</th>\n",
       "      <th>net_return</th>\n",
       "      <th>rebalances</th>\n",
       "      <th>compounds</th>\n",
       "      <th>max_drawdown</th>\n",
       "      <th>volatility</th>\n",
       "      <th>sharpe_ratio</th>\n",
       "      <th>impermanent_loss</th>\n",
       "      <th>mean_base_position</th>\n",
       "      <th>median_base_position</th>\n",
       "      <th>mean_base_width</th>\n",
       "      <th>median_base_width</th>\n",
       "      <th>final_value</th>\n",
       "      <th>alpha_param</th>\n",
       "      <th>tau_param</th>\n",
       "      <th>volatility_param</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>100</td>\n",
       "      <td>0.434064</td>\n",
       "      <td>0.118922</td>\n",
       "      <td>0.582648</td>\n",
       "      <td>0.159630</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>0.310601</td>\n",
       "      <td>0.491336</td>\n",
       "      <td>1.185844</td>\n",
       "      <td>0.065872</td>\n",
       "      <td>0.776935</td>\n",
       "      <td>0.795864</td>\n",
       "      <td>0.795923</td>\n",
       "      <td>0.735442</td>\n",
       "      <td>231925.909952</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>100</td>\n",
       "      <td>0.449585</td>\n",
       "      <td>0.123174</td>\n",
       "      <td>0.514317</td>\n",
       "      <td>0.140909</td>\n",
       "      <td>63</td>\n",
       "      <td>0</td>\n",
       "      <td>0.292525</td>\n",
       "      <td>0.472102</td>\n",
       "      <td>1.089420</td>\n",
       "      <td>0.048665</td>\n",
       "      <td>0.732438</td>\n",
       "      <td>0.758697</td>\n",
       "      <td>0.762280</td>\n",
       "      <td>0.738792</td>\n",
       "      <td>228181.768893</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>100</td>\n",
       "      <td>0.620518</td>\n",
       "      <td>0.170005</td>\n",
       "      <td>0.968073</td>\n",
       "      <td>0.265226</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0.352552</td>\n",
       "      <td>0.533443</td>\n",
       "      <td>1.814764</td>\n",
       "      <td>0.162930</td>\n",
       "      <td>0.578733</td>\n",
       "      <td>0.613102</td>\n",
       "      <td>0.698930</td>\n",
       "      <td>0.719570</td>\n",
       "      <td>253045.122095</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>100</td>\n",
       "      <td>0.535545</td>\n",
       "      <td>0.146725</td>\n",
       "      <td>0.840197</td>\n",
       "      <td>0.230191</td>\n",
       "      <td>22</td>\n",
       "      <td>0</td>\n",
       "      <td>0.357622</td>\n",
       "      <td>0.559954</td>\n",
       "      <td>1.500475</td>\n",
       "      <td>0.130728</td>\n",
       "      <td>0.726787</td>\n",
       "      <td>0.710523</td>\n",
       "      <td>0.704880</td>\n",
       "      <td>0.737300</td>\n",
       "      <td>246038.204627</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>100</td>\n",
       "      <td>0.289802</td>\n",
       "      <td>0.079398</td>\n",
       "      <td>0.612897</td>\n",
       "      <td>0.167917</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>0.314990</td>\n",
       "      <td>0.492830</td>\n",
       "      <td>1.243629</td>\n",
       "      <td>0.073489</td>\n",
       "      <td>0.856140</td>\n",
       "      <td>0.874029</td>\n",
       "      <td>1.176164</td>\n",
       "      <td>1.217739</td>\n",
       "      <td>233583.416140</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>100</td>\n",
       "      <td>0.320511</td>\n",
       "      <td>0.087811</td>\n",
       "      <td>0.620312</td>\n",
       "      <td>0.169948</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>0.310011</td>\n",
       "      <td>0.485597</td>\n",
       "      <td>1.277422</td>\n",
       "      <td>0.075356</td>\n",
       "      <td>0.859649</td>\n",
       "      <td>0.890620</td>\n",
       "      <td>1.097780</td>\n",
       "      <td>1.063564</td>\n",
       "      <td>233989.672237</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>100</td>\n",
       "      <td>0.392523</td>\n",
       "      <td>0.107540</td>\n",
       "      <td>0.846484</td>\n",
       "      <td>0.231913</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>0.350901</td>\n",
       "      <td>0.543974</td>\n",
       "      <td>1.556112</td>\n",
       "      <td>0.132311</td>\n",
       "      <td>0.712572</td>\n",
       "      <td>0.739035</td>\n",
       "      <td>1.066805</td>\n",
       "      <td>1.097355</td>\n",
       "      <td>246382.681312</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>100</td>\n",
       "      <td>0.446611</td>\n",
       "      <td>0.122359</td>\n",
       "      <td>0.881398</td>\n",
       "      <td>0.241479</td>\n",
       "      <td>22</td>\n",
       "      <td>0</td>\n",
       "      <td>0.352331</td>\n",
       "      <td>0.547980</td>\n",
       "      <td>1.608449</td>\n",
       "      <td>0.141103</td>\n",
       "      <td>0.756026</td>\n",
       "      <td>0.726085</td>\n",
       "      <td>0.992582</td>\n",
       "      <td>0.986227</td>\n",
       "      <td>248295.779846</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>100</td>\n",
       "      <td>0.240051</td>\n",
       "      <td>0.065767</td>\n",
       "      <td>0.618172</td>\n",
       "      <td>0.169362</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>0.325163</td>\n",
       "      <td>0.521943</td>\n",
       "      <td>1.184368</td>\n",
       "      <td>0.074818</td>\n",
       "      <td>0.908958</td>\n",
       "      <td>0.948207</td>\n",
       "      <td>1.442628</td>\n",
       "      <td>1.389982</td>\n",
       "      <td>233872.465189</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>100</td>\n",
       "      <td>0.248997</td>\n",
       "      <td>0.068218</td>\n",
       "      <td>0.629694</td>\n",
       "      <td>0.172519</td>\n",
       "      <td>43</td>\n",
       "      <td>0</td>\n",
       "      <td>0.321233</td>\n",
       "      <td>0.510927</td>\n",
       "      <td>1.232456</td>\n",
       "      <td>0.077719</td>\n",
       "      <td>0.898287</td>\n",
       "      <td>0.921157</td>\n",
       "      <td>1.415444</td>\n",
       "      <td>1.393178</td>\n",
       "      <td>234503.795631</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>100</td>\n",
       "      <td>0.408338</td>\n",
       "      <td>0.111874</td>\n",
       "      <td>0.697385</td>\n",
       "      <td>0.191064</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0.321085</td>\n",
       "      <td>0.503322</td>\n",
       "      <td>1.385564</td>\n",
       "      <td>0.094765</td>\n",
       "      <td>0.715517</td>\n",
       "      <td>0.734892</td>\n",
       "      <td>1.172010</td>\n",
       "      <td>1.209029</td>\n",
       "      <td>238212.873277</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>100</td>\n",
       "      <td>0.351525</td>\n",
       "      <td>0.096308</td>\n",
       "      <td>0.876235</td>\n",
       "      <td>0.240065</td>\n",
       "      <td>26</td>\n",
       "      <td>0</td>\n",
       "      <td>0.354791</td>\n",
       "      <td>0.556932</td>\n",
       "      <td>1.573325</td>\n",
       "      <td>0.139803</td>\n",
       "      <td>0.809568</td>\n",
       "      <td>0.846850</td>\n",
       "      <td>1.244352</td>\n",
       "      <td>1.273826</td>\n",
       "      <td>248012.900197</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.95</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    days_strategy  gross_fee_apr  gross_fee_return   net_apr  net_return  \\\n",
       "0             100       0.434064          0.118922  0.582648    0.159630   \n",
       "1             100       0.449585          0.123174  0.514317    0.140909   \n",
       "2             100       0.620518          0.170005  0.968073    0.265226   \n",
       "3             100       0.535545          0.146725  0.840197    0.230191   \n",
       "4             100       0.289802          0.079398  0.612897    0.167917   \n",
       "5             100       0.320511          0.087811  0.620312    0.169948   \n",
       "6             100       0.392523          0.107540  0.846484    0.231913   \n",
       "7             100       0.446611          0.122359  0.881398    0.241479   \n",
       "8             100       0.240051          0.065767  0.618172    0.169362   \n",
       "9             100       0.248997          0.068218  0.629694    0.172519   \n",
       "10            100       0.408338          0.111874  0.697385    0.191064   \n",
       "11            100       0.351525          0.096308  0.876235    0.240065   \n",
       "\n",
       "    rebalances  compounds  max_drawdown  volatility  sharpe_ratio  \\\n",
       "0           29          0      0.310601    0.491336      1.185844   \n",
       "1           63          0      0.292525    0.472102      1.089420   \n",
       "2            6          0      0.352552    0.533443      1.814764   \n",
       "3           22          0      0.357622    0.559954      1.500475   \n",
       "4           11          0      0.314990    0.492830      1.243629   \n",
       "5           29          0      0.310011    0.485597      1.277422   \n",
       "6            7          0      0.350901    0.543974      1.556112   \n",
       "7           22          0      0.352331    0.547980      1.608449   \n",
       "8           16          0      0.325163    0.521943      1.184368   \n",
       "9           43          0      0.321233    0.510927      1.232456   \n",
       "10           3          0      0.321085    0.503322      1.385564   \n",
       "11          26          0      0.354791    0.556932      1.573325   \n",
       "\n",
       "    impermanent_loss  mean_base_position  median_base_position  \\\n",
       "0           0.065872            0.776935              0.795864   \n",
       "1           0.048665            0.732438              0.758697   \n",
       "2           0.162930            0.578733              0.613102   \n",
       "3           0.130728            0.726787              0.710523   \n",
       "4           0.073489            0.856140              0.874029   \n",
       "5           0.075356            0.859649              0.890620   \n",
       "6           0.132311            0.712572              0.739035   \n",
       "7           0.141103            0.756026              0.726085   \n",
       "8           0.074818            0.908958              0.948207   \n",
       "9           0.077719            0.898287              0.921157   \n",
       "10          0.094765            0.715517              0.734892   \n",
       "11          0.139803            0.809568              0.846850   \n",
       "\n",
       "    mean_base_width  median_base_width    final_value  alpha_param  tau_param  \\\n",
       "0          0.795923           0.735442  231925.909952         0.50       0.25   \n",
       "1          0.762280           0.738792  228181.768893         0.50       0.25   \n",
       "2          0.698930           0.719570  253045.122095         0.50       0.75   \n",
       "3          0.704880           0.737300  246038.204627         0.50       0.75   \n",
       "4          1.176164           1.217739  233583.416140         0.75       0.25   \n",
       "5          1.097780           1.063564  233989.672237         0.75       0.25   \n",
       "6          1.066805           1.097355  246382.681312         0.75       0.75   \n",
       "7          0.992582           0.986227  248295.779846         0.75       0.75   \n",
       "8          1.442628           1.389982  233872.465189         0.95       0.25   \n",
       "9          1.415444           1.393178  234503.795631         0.95       0.25   \n",
       "10         1.172010           1.209029  238212.873277         0.95       0.75   \n",
       "11         1.244352           1.273826  248012.900197         0.95       0.75   \n",
       "\n",
       "    volatility_param  \n",
       "0               0.85  \n",
       "1               0.95  \n",
       "2               0.85  \n",
       "3               0.95  \n",
       "4               0.85  \n",
       "5               0.95  \n",
       "6               0.85  \n",
       "7               0.95  \n",
       "8               0.85  \n",
       "9               0.95  \n",
       "10              0.85  \n",
       "11              0.95  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(sim_performance)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'days_strategy': 100,\n",
       " 'gross_fee_apr': 1.4359373546400909,\n",
       " 'gross_fee_return': 0.39340749442194267,\n",
       " 'net_apr': 0.03176507357299968,\n",
       " 'net_return': 0.008702759883013611,\n",
       " 'rebalances': 51,\n",
       " 'max_drawdown': 0.387670561648326,\n",
       " 'volatility': 0.6311926245862107,\n",
       " 'sharpe_ratio': 0.05032548280142504,\n",
       " 'impermanent_loss': -0.0728523730579233,\n",
       " 'mean_base_position': 0.49068293763810333,\n",
       " 'median_base_position': 0.624121769295907,\n",
       " 'mean_base_width': 0.059156253367325995,\n",
       " 'median_base_width': 0.059156253367325995,\n",
       " 'final_value': 201740.55197660273}"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#################\n",
    "#\n",
    "# Run Reset Strategy\n",
    "#\n",
    "################\n",
    "import ResetStrategy\n",
    "\n",
    "# Strategy Parameters\n",
    "alpha_param = .50\n",
    "tau_param   = .95\n",
    "limit_param = .50\n",
    "\n",
    "# Data for strategy estimation\n",
    "STATISTICAL_FREQUENCY        = 'D' \n",
    "statistical_data             = ActiveStrategyFramework.aggregate_price_data(price_data,STATISTICAL_FREQUENCY)\n",
    "statistical_data['z_scores'] = np.abs(scipy.stats.zscore(statistical_data['quotePrice']))\n",
    "statistical_data             = statistical_data.drop(statistical_data[abs(statistical_data.z_scores) > 3].index)\n",
    "statistical_data_filtered    = statistical_data.sort_index()\n",
    "\n",
    "Reset_Strategy      = ResetStrategy.ResetStrategy(statistical_data_filtered,alpha_param,tau_param,limit_param)\n",
    "simulated_strategy  = ActiveStrategyFramework.simulate_strategy(simulate_data_price,swap_data,Reset_Strategy,INITIAL_TOKEN_0,INITIAL_TOKEN_1,FEE_TIER,DECIMALS_0,DECIMALS_1)\n",
    "resulting_data      = ActiveStrategyFramework.generate_simulation_series(simulated_strategy,Reset_Strategy)\n",
    "ActiveStrategyFramework.analyze_strategy(resulting_data,frequency=STRATEGY_FREQUENCY)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "p = ActiveStrategyFramework.plot_strategy(resulting_data,'ETH / USDC Price','#0000FF')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Performance Analysis\n",
    "\n",
    "Let's look at the performance analytics for the optimal AR Strategy:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "SELECTED_STRATEGY  = 2\n",
    "resulting_strat    = sim_results[SELECTED_STRATEGY]\n",
    "resulting_data     = ActiveStrategyFramework.generate_simulation_series(resulting_strat,AR_Strategy)\n",
    "p = ActiveStrategyFramework.plot_strategy(resulting_data,'ETH Price')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "p = ActiveStrategyFramework.plot_position_value(resulting_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "p = ActiveStrategyFramework.plot_asset_composition(resulting_data,'USDC','WETH')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "p = ActiveStrategyFramework.plot_position_return_decomposition(resulting_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "p = ActiveStrategyFramework.plot_position_composition(resulting_data)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}