{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "celkovy optimalizacni backtest na vetsim oknu 1 - 300\n", "a možná take to udělat jako parametr\n", "zkusit CV\n", "zobrazit nejak robustnost parametru" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
Activating profile profile1\n",
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\n", "This is the init_notebook_mode cell from ITables v2.0.1
\n", "(you should not see this message - is your notebook trusted?)\n", "
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tato je shortovaci\n", "\n", "#8\t-0.06\t-0.2\t0.0028\t0.0048\t4.156254\n", "\n", "#short combination ok for train(4)/test(0.1) (window 1-90, fe 95-100)\n", "#2,\t-0.02,\t-0.25,\t0.0018,\t0.0068\n", "\n", "#dalsi ok hodnota shortu for train/test 4/1\n", "#70,\t8,\t-0.06,\t-0.2,\t0.0013,\t0.0053\t\n", "\n", "\n", "#kombinace bez roc_th, train/test 7/-1.5\n", "#70\t7\t-0.07\t0.0033\t0.0063\n", "\n", "#opet bez roc_th, train(5.77)/test 0.9 - spolus tsl_stop + tsl_th\n", "#29\t7\t-0.09\t0.0033\t0.0068\n", "\n", "#bez roc_th a s trailing sl train/test 8.1/-0.8 \n", "#70\t2\t-0.05\t0.0018\t0.0068\n", "\n", "\n", "#SPY - short\n", "# entry_window_closes\tmom_timeperiod\tmom_th\tsl_stop\ttp_stop\t\t\t\t\t\n", "# 10\t6\t-0.13\t0.0022\t0.0057\n", "\n", "#5\t7\t-0.19\t0.0037\t0.0042\n", "\n", "#SPY - long\n", "#45\t4\t0.27\t0.0047\t0.0067\n", "\n", "# TODO:\n", "#- vyzkouset zda nejvyhodnejsi kombinace krom train/testu funguje i na nasledujicich dnech po trainu\n", "# -zkusit najit v short datasetu neco vyhodneho co funguji i na testu\n", "# - dodelat kombinace pro long signaly\n", "# - zkusit walk forward\n", "# - vytvorit vysledkove totoznou na v2realbot\n", "# - podivat se jak detailne funguji tsl_stop a tsl_th\n", "\n", "#70,\t4,\t-0.07,\t0.0048,\t0.0068\t\n", "\n", "\n", "entry_window_closes, mom_timeperiod, mom_th, sl_stop, tp_stop = 8,\t3,\t0.07,\t0.0028,\t0.0033\t\n", "roc_th = 0\n", "momshort = vbt.indicator(\"talib:MOM\").run(basic_data.close, timeperiod=mom_timeperiod, short_name = \"slope_short\")\n", "rocp = vbt.indicator(\"talib:ROC\").run(basic_data.close, short_name = \"rocp\")\n", "#rate of change + momentum\n", "\n", "#momshort.plot rocp.real_crossed_below(roc_th) & \n", "short_signal = momshort.real_crossed_below(mom_th)\n", "\n", "long_signal = momshort.real_crossed_above(mom_th)\n", "\n", "# print(\"short signal\")\n", "# print(short_signal.value_counts())\n", "\n", "#forced_exit = pd.Series(False, index=close.index)\n", "forced_exit = basic_data.symbol_wrapper.fill(False)\n", "#entry_window_open = pd.Series(False, index=close.index)\n", "entry_window_open= basic_data.symbol_wrapper.fill(False)\n", "\n", "# Calculate the time difference in minutes from market open for each timestamp\n", "elapsed_min_from_open = (forced_exit.index.hour - market_open.hour) * 60 + (forced_exit.index.minute - market_open.minute)\n", "\n", "entry_window_open[(elapsed_min_from_open >= entry_window_opens) & (elapsed_min_from_open < entry_window_closes)] = True\n", "\n", "#print(entry_window_open.value_counts())\n", "\n", "forced_exit[(elapsed_min_from_open >= forced_exit_start) & (elapsed_min_from_open < forced_exit_end)] = True\n", "short_entries = (short_signal & entry_window_open)\n", "short_exits = forced_exit\n", "\n", "entries = (long_signal & entry_window_open)\n", "exits = forced_exit\n", "#long_entries.info()\n", "#number of trues and falses in long_entries\n", "# print(short_exits.value_counts())\n", "# print(short_entries.value_counts())\n", "\n", "#fig = plot_2y_close([],[momshort, rocp], close)\n", "#short_signal.vbt.signals.plot_as_entries(close, fig=fig, add_trace_kwargs=dict(secondary_y=False))\n", "#print(sl_stop)\n", "#short_entries=short_entries, short_exits=short_exits,\n", "pf = vbt.Portfolio.from_signals(close=basic_data, entries=entries, exits=exits, tsl_stop=sl_stop, tp_stop = tp_stop, fees=0.0167/100, freq=\"1s\") #sl_stop=sl_stop, tp_stop = sl_stop,\n" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", "\n", "\n", "\n", "
Order IdColumnSignal IndexCreation IndexFill IndexSizePriceFeesSideTypeStop Type
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\n", "Loading ITables v2.0.1 from the init_notebook_mode cell...\n", "(need help?)
\n", "\n" ], "text/plain": [ " Order Id Column Signal Index Creation Index \\\n", "0 0 0 2024-01-02 09:30:00-05:00 2024-01-02 09:30:00-05:00 \n", "1 1 0 2024-01-02 09:30:00-05:00 2024-01-02 09:30:00-05:00 \n", "2 2 0 2024-01-03 09:30:00-05:00 2024-01-03 09:30:00-05:00 \n", "3 3 0 2024-01-03 09:30:00-05:00 2024-01-03 10:00:00-05:00 \n", "4 4 0 2024-01-04 09:30:00-05:00 2024-01-04 09:30:00-05:00 \n", ".. ... ... ... ... \n", "191 191 0 2024-05-10 09:30:00-04:00 2024-05-10 10:00:00-04:00 \n", "192 192 0 2024-05-13 09:30:00-04:00 2024-05-13 09:30:00-04:00 \n", "193 193 0 2024-05-13 09:30:00-04:00 2024-05-13 11:00:00-04:00 \n", "194 194 0 2024-05-14 09:30:00-04:00 2024-05-14 09:30:00-04:00 \n", "195 195 0 2024-05-14 09:30:00-04:00 2024-05-14 10:30:00-04:00 \n", "\n", " Fill Index Size Price Fees Side Type \\\n", "0 2024-01-02 09:30:00-05:00 0.211618 472.470000 0.016697 Buy Market \n", "1 2024-01-02 09:30:00-05:00 0.211618 471.476160 0.016662 Sell Market \n", "2 2024-01-03 09:30:00-05:00 0.212072 470.310000 0.016657 Buy Market \n", "3 2024-01-03 10:00:00-05:00 0.212072 469.641312 0.016633 Sell Market \n", "4 2024-01-04 09:30:00-05:00 0.212554 468.420000 0.016627 Buy Market \n", ".. ... ... ... ... ... ... \n", "191 2024-05-10 10:00:00-04:00 0.178107 521.171622 0.015502 Sell Market \n", "192 2024-05-13 09:30:00-04:00 0.177624 522.415000 0.015496 Buy Market \n", "193 2024-05-13 11:00:00-04:00 0.177624 520.977168 0.015454 Sell Market \n", "194 2024-05-14 09:30:00-04:00 0.177461 521.280000 0.015449 Buy Market \n", "195 2024-05-14 10:30:00-04:00 0.177461 520.947252 0.015439 Sell Market \n", "\n", " Stop Type \n", "0 None \n", "1 TSL \n", "2 None \n", "3 TSL \n", "4 None \n", ".. ... \n", "191 TSL \n", "192 None \n", "193 TSL \n", "194 None \n", "195 TSL \n", "\n", "[196 rows x 11 columns]" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pf_B = pf.resample(\"30T\")\n", "\n", "pf_B.stats()\n", "pf_B.orders.records_readable\n" ] }, 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Drawdown IdColumnStart IndexValley IndexEnd IndexStart ValueValley ValueEnd ValueStatus
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\n", "\n" ], "text/plain": [ " Drawdown Id Column Start Index \\\n", "0 0 (0.0018, 0.0068) 2024-01-03 09:31:04-05:00 \n", "1 1 (0.0018, 0.0068) 2024-01-03 09:31:07-05:00 \n", "2 2 (0.0018, 0.0068) 2024-01-03 09:31:11-05:00 \n", "3 3 (0.0018, 0.0068) 2024-01-03 09:31:18-05:00 \n", "4 4 (0.0018, 0.0068) 2024-01-03 09:48:07-05:00 \n", ".. ... ... ... \n", "34 34 (0.0018, 0.0068) 2024-01-12 12:23:26-05:00 \n", "35 35 (0.0018, 0.0068) 2024-01-12 12:23:31-05:00 \n", "36 36 (0.0018, 0.0068) 2024-01-12 12:32:23-05:00 \n", "37 37 (0.0018, 0.0068) 2024-01-12 12:32:27-05:00 \n", "38 38 (0.0018, 0.0068) 2024-01-12 12:32:36-05:00 \n", "\n", " Valley Index End Index Start Value \\\n", "0 2024-01-03 09:31:05-05:00 2024-01-03 09:31:06-05:00 100.000000 \n", "1 2024-01-03 09:31:10-05:00 2024-01-03 09:31:11-05:00 100.057784 \n", "2 2024-01-03 09:31:13-05:00 2024-01-03 09:31:16-05:00 100.102472 \n", "3 2024-01-03 09:32:39-05:00 2024-01-03 09:48:05-05:00 100.162057 \n", "4 2024-01-03 09:48:08-05:00 2024-01-03 09:48:11-05:00 100.186396 \n", ".. ... ... ... \n", "34 2024-01-12 12:23:28-05:00 2024-01-12 12:23:29-05:00 100.981534 \n", "35 2024-01-12 12:26:27-05:00 2024-01-12 12:32:23-05:00 101.089545 \n", "36 2024-01-12 12:32:24-05:00 2024-01-12 12:32:25-05:00 101.089545 \n", "37 2024-01-12 12:32:28-05:00 2024-01-12 12:32:36-05:00 101.104975 \n", "38 2024-02-21 09:35:15-05:00 2024-02-28 15:59:59-05:00 101.104975 \n", "\n", " Valley Value End Value Status \n", "0 99.983303 100.057784 Recovered \n", "1 100.042888 100.102472 Recovered \n", "2 100.057784 100.102472 Recovered \n", "3 99.650958 100.171522 Recovered \n", "4 100.171522 100.201269 Recovered \n", ".. ... ... ... \n", "34 100.968881 101.043254 Recovered \n", "35 100.858092 101.089545 Recovered \n", "36 101.074115 101.089545 Recovered \n", "37 101.089545 101.104975 Recovered \n", "38 99.788058 99.788058 Active \n", "\n", "[39 rows x 9 columns]" ] }, "execution_count": 36, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pf.get_drawdowns().records_readable" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", "\n", "\n", "\n", "
Order IdColumnSignal IndexCreation IndexFill IndexSizePriceFeesSideTypeStop Type
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\n", "\n" ], "text/plain": [ " Order Id Column Signal Index Creation Index \\\n", "0 0 0 2024-01-02 09:31:19-05:00 2024-01-02 09:31:19-05:00 \n", "1 1 0 2024-01-02 09:31:19-05:00 2024-01-02 09:48:47-05:00 \n", "2 2 0 2024-01-03 09:31:25-05:00 2024-01-03 09:31:25-05:00 \n", "3 3 0 2024-01-03 09:31:25-05:00 2024-01-03 10:12:07-05:00 \n", "4 4 0 2024-01-04 09:31:25-05:00 2024-01-04 09:31:25-05:00 \n", ".. ... ... ... ... \n", "191 191 0 2024-05-10 09:31:36-04:00 2024-05-10 10:19:32-04:00 \n", "192 192 0 2024-05-13 09:31:28-04:00 2024-05-13 09:31:28-04:00 \n", "193 193 0 2024-05-13 09:31:28-04:00 2024-05-13 11:04:06-04:00 \n", "194 194 0 2024-05-14 09:31:17-04:00 2024-05-14 09:31:17-04:00 \n", "195 195 0 2024-05-14 09:31:17-04:00 2024-05-14 10:38:06-04:00 \n", "\n", " Fill Index Size Price Fees Side Type \\\n", "0 2024-01-02 09:31:19-05:00 0.211618 472.470000 0.016697 Buy Market \n", "1 2024-01-02 09:48:47-05:00 0.211618 471.476160 0.016662 Sell Market \n", "2 2024-01-03 09:31:25-05:00 0.212072 470.310000 0.016657 Buy Market \n", "3 2024-01-03 10:12:07-05:00 0.212072 469.641312 0.016633 Sell Market \n", "4 2024-01-04 09:31:25-05:00 0.212554 468.420000 0.016627 Buy Market \n", ".. ... ... ... ... ... ... \n", "191 2024-05-10 10:19:32-04:00 0.178107 521.171622 0.015502 Sell Market \n", "192 2024-05-13 09:31:28-04:00 0.177624 522.415000 0.015496 Buy Market \n", "193 2024-05-13 11:04:06-04:00 0.177624 520.977168 0.015454 Sell Market \n", "194 2024-05-14 09:31:17-04:00 0.177461 521.280000 0.015449 Buy Market \n", "195 2024-05-14 10:38:06-04:00 0.177461 520.947252 0.015439 Sell Market \n", "\n", " Stop Type \n", "0 None \n", "1 TSL \n", "2 None \n", "3 TSL \n", "4 None \n", ".. ... \n", "191 TSL \n", "192 None \n", "193 TSL \n", "194 None \n", "195 TSL \n", "\n", "[196 rows x 11 columns]" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pf.orders.records_readable" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pf.value.plot().show()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": ".venv", "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": "3.10.11" } }, "nbformat": 4, "nbformat_minor": 2 }