Quick_Start_SMA_w_Trailing_Stop.ipynb

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      "/home/sergey/anaconda3/lib/python3.7/site-packages/backtesting/_plotting.py:45: UserWarning: Jupyter Notebook detected. Setting Bokeh output to notebook. This may not work in Jupyter clients without JavaScript support (e.g. PyCharm, Spyder IDE). Reset with `backtesting.set_bokeh_output(notebook=False)`.\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2015-12-17</th>\n",
       "      <td>GAZP.ME</td>\n",
       "      <td>138.690002</td>\n",
       "      <td>134.649994</td>\n",
       "      <td>134.649994</td>\n",
       "      <td>137.899994</td>\n",
       "      <td>45419720.0</td>\n",
       "      <td>137.899994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-18</th>\n",
       "      <td>GAZP.ME</td>\n",
       "      <td>137.389999</td>\n",
       "      <td>132.250000</td>\n",
       "      <td>137.289993</td>\n",
       "      <td>132.250000</td>\n",
       "      <td>38544860.0</td>\n",
       "      <td>132.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-21</th>\n",
       "      <td>GAZP.ME</td>\n",
       "      <td>133.940002</td>\n",
       "      <td>131.000000</td>\n",
       "      <td>132.000000</td>\n",
       "      <td>131.500000</td>\n",
       "      <td>28393100.0</td>\n",
       "      <td>131.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-22</th>\n",
       "      <td>GAZP.ME</td>\n",
       "      <td>133.539993</td>\n",
       "      <td>131.809998</td>\n",
       "      <td>132.000000</td>\n",
       "      <td>133.199997</td>\n",
       "      <td>20022420.0</td>\n",
       "      <td>133.199997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-23</th>\n",
       "      <td>GAZP.ME</td>\n",
       "      <td>135.300003</td>\n",
       "      <td>133.350006</td>\n",
       "      <td>133.550003</td>\n",
       "      <td>135.300003</td>\n",
       "      <td>26760910.0</td>\n",
       "      <td>135.300003</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             ticker        High         Low        Open       Close  \\\n",
       "Date                                                                  \n",
       "2015-12-17  GAZP.ME  138.690002  134.649994  134.649994  137.899994   \n",
       "2015-12-18  GAZP.ME  137.389999  132.250000  137.289993  132.250000   \n",
       "2015-12-21  GAZP.ME  133.940002  131.000000  132.000000  131.500000   \n",
       "2015-12-22  GAZP.ME  133.539993  131.809998  132.000000  133.199997   \n",
       "2015-12-23  GAZP.ME  135.300003  133.350006  133.550003  135.300003   \n",
       "\n",
       "                Volume   Adj Close  \n",
       "Date                                \n",
       "2015-12-17  45419720.0  137.899994  \n",
       "2015-12-18  38544860.0  132.250000  \n",
       "2015-12-21  28393100.0  131.500000  \n",
       "2015-12-22  20022420.0  133.199997  \n",
       "2015-12-23  26760910.0  135.300003  "
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import backtesting\n",
    "from backtesting import Backtest\n",
    "from backtesting.lib import crossover, SignalStrategy, TrailingStrategy\n",
    "from backtesting.test import SMA\n",
    "import pandas_datareader.data as dtr\n",
    "import requests_cache\n",
    "import datetime\n",
    "expire_after = datetime.timedelta(days = 7)\n",
    "session = requests_cache.CachedSession(cache_name='cache', backend='sqlite', expire_after=expire_after)\n",
    "\n",
    "tickers = [\"LNTA.ME\",\"MGNT.ME\",\"PIKK.ME\",\n",
    "           \"MTSS.ME\",\"MGTS.ME\",\"RTKM.ME\",\n",
    "           \"ROSN.ME\",\"GAZP.ME\",\"NVTK.ME\",\"LKOH.ME\",\"TATN.ME\",\"SNGS.ME\",\"SIBN.ME\",\n",
    "           \"PLZL.ME\",\"NLMK.ME\",\"CHMF.ME\",\"POLY.ME\",\"RUAL.ME\",\"ALRS.ME\",\n",
    "           \"SBER.ME\",\"VTBR.ME\",\"MOEX.ME\",\"CBOM.ME\",\"YNDX.ME\",\"CBOM.ME\",\"ROSB.ME\",\n",
    "           \"HYDR.ME\",\"RSTI.ME\",\"FEES.ME\"\n",
    "          ]\n",
    "\n",
    "df = pd.DataFrame()\n",
    "\n",
    "for ticker in tickers:\n",
    "    try:\n",
    "        df_ = dtr.DataReader(ticker, data_source=\"yahoo\" , session=session, retry_count=1)\n",
    "        df_.insert(0, \"ticker\", ticker)\n",
    "    except:\n",
    "        print(f\"ticker '{ticker}' failed\")\n",
    "        pass\n",
    "    df = df.append(df_)\n",
    "\n",
    "GAZP = df[df.ticker == \"GAZP.ME\"]\n",
    "GAZP.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.9, 0.5048275058688446)"
      ]
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     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "class SmaCross(SignalStrategy, TrailingStrategy):\n",
    "    \n",
    "    n1 = 10\n",
    "    n2 = 30\n",
    "    \n",
    "    def init(self):\n",
    "        super().init()\n",
    "        sma1 = self.I(SMA, self.data.Close, self.n1)\n",
    "        sma2 = self.I(SMA, self.data.Close, self.n2)\n",
    "        # Where sma1 crosses sma2 upwards. Diff gives us [-1,0, *1*]\n",
    "        signal = (pd.Series(sma1) > sma2).astype(int).diff().fillna(0)\n",
    "        # Upwards/long only\n",
    "        signal = signal.replace(-1, 0)\n",
    "        # Use 95% of available liquidity (at the time) on each order.\n",
    "        # (Leaving a value of 1. would instead buy a single share.)\n",
    "        entry_size = signal * .95\n",
    "        # Set order entry sizes using the method provided by \n",
    "        # `SignalStrategy`. See the docs.\n",
    "        self.set_signal(entry_size=entry_size)\n",
    "        # Set trailing stop-loss to 2x ATR using\n",
    "        # the method provided by `TrailingStrategy`\n",
    "        self.set_trailing_sl(2)\n",
    "\n",
    "ret = 0\n",
    "for m in [i/10 for i in range(1,10)]:\n",
    "    bt = Backtest(GAZP, SmaCross, commission = .002, margin =m)\n",
    "    stats=bt.run()\n",
    "    if stats['Sharpe Ratio'] > ret:\n",
    "        ret = stats['Sharpe Ratio']\n",
    "        margin = m \n",
    "margin, ret"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
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     "data": {
      "text/plain": [
       "Start                     2015-12-17 00:00:00\n",
       "End                       2020-12-14 00:00:00\n",
       "Duration                   1824 days 00:00:00\n",
       "Exposure Time [%]                     29.7686\n",
       "Equity Final [$]                      36393.6\n",
       "Equity Peak [$]                       36393.6\n",
       "Return [%]                            263.936\n",
       "Buy & Hold Return [%]                 44.6773\n",
       "Return (Ann.) [%]                     29.6677\n",
       "Volatility (Ann.) [%]                 31.9495\n",
       "Sharpe Ratio                         0.928579\n",
       "Sortino Ratio                         2.66769\n",
       "Calmar Ratio                          1.41188\n",
       "Max. Drawdown [%]                    -21.0129\n",
       "Avg. Drawdown [%]                    -5.02658\n",
       "Max. Drawdown Duration      372 days 00:00:00\n",
       "Avg. Drawdown Duration       52 days 00:00:00\n",
       "# Trades                                   15\n",
       "Win Rate [%]                          73.3333\n",
       "Best Trade [%]                        22.9381\n",
       "Worst Trade [%]                      -5.98213\n",
       "Avg. Trade [%]                         7.1127\n",
       "Max. Trade Duration         182 days 00:00:00\n",
       "Avg. Trade Duration          51 days 00:00:00\n",
       "Profit Factor                         9.00158\n",
       "Expectancy [%]                        7.46645\n",
       "SQN                                   2.35141\n",
       "_strategy                 SmaCross(n1=25,n...\n",
       "_equity_curve                             ...\n",
       "_trades                       Size  EntryB...\n",
       "dtype: object"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bt = Backtest(GAZP, SmaCross, commission = .002, margin=.5)\n",
    "stats = bt.optimize(n1 = range(10,30,5),\n",
    "                    n2 = range(20,70,5),\n",
    "                    maximize = 'Sharpe Ratio',\n",
    "                    constraint = lambda param: param.n1 < param.n2\n",
    "                   )\n",
    "stats"
   ]
  }
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