{
"cells": [
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"Activating profile profile1\n",
"\n"
],
"text/plain": [
"Activating profile profile1\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"Profile profile1 loaded successfully.\n",
"\n"
],
"text/plain": [
"Profile profile1 loaded successfully.\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"Current values:\n",
"{\n",
" 'AGG_EXCLUDED_TRADES': ['C', 'O', '4', 'B', '7', 'V', 'P', 'W', 'U', 'Z', 'F'],\n",
" 'BT_DELAYS': {\n",
" 'trigger_to_strat': 0.02,\n",
" 'strat_to_sub': 0.023,\n",
" 'sub_to_fill': 0.008,\n",
" 'fill_to_not': 0.023,\n",
" 'limit_order_offset': 0\n",
" },\n",
" 'BT_FILL_CONDITION_BUY_LIMIT': <FillCondition.SLOW: 'slow'>,\n",
" 'BT_FILL_CONDITION_SELL_LIMIT': <FillCondition.SLOW: 'slow'>,\n",
" 'BT_FILL_CONS_TRADES_REQUIRED': 2,\n",
" 'BT_FILL_LOG_SURROUNDING_TRADES': 10,\n",
" 'BT_FILL_PRICE_MARKET_ORDER_PREMIUM': 0.005,\n",
" 'COUNT_API_REQUESTS': False,\n",
" 'GROUP_TRADES_WITH_TIMESTAMP_LESS_THAN': 0.003,\n",
" 'ILOG_SAVE_LEVEL_FROM': 1,\n",
" 'LIVE_DATA_FEED': 'sip',\n",
" 'NORMALIZED_TICK_BASE_PRICE': 30.0,\n",
" 'OFFLINE_MODE': False,\n",
" 'PROD_SERVER_HOSTNAMES': ['tradingeastcoast', 'David-MacBook-Pro.local'],\n",
" 'QUIET_MODE': True,\n",
" 'TEST_SERVER_HOSTNAMES': ['tradingtest']\n",
"}\n",
"\n"
],
"text/plain": [
"Current values:\n",
"\u001b[1m{\u001b[0m\n",
" \u001b[32m'AGG_EXCLUDED_TRADES'\u001b[0m: \u001b[1m[\u001b[0m\u001b[32m'C'\u001b[0m, \u001b[32m'O'\u001b[0m, \u001b[32m'4'\u001b[0m, \u001b[32m'B'\u001b[0m, \u001b[32m'7'\u001b[0m, \u001b[32m'V'\u001b[0m, \u001b[32m'P'\u001b[0m, \u001b[32m'W'\u001b[0m, \u001b[32m'U'\u001b[0m, \u001b[32m'Z'\u001b[0m, \u001b[32m'F'\u001b[0m\u001b[1m]\u001b[0m,\n",
" \u001b[32m'BT_DELAYS'\u001b[0m: \u001b[1m{\u001b[0m\n",
" \u001b[32m'trigger_to_strat'\u001b[0m: \u001b[1;36m0.02\u001b[0m,\n",
" \u001b[32m'strat_to_sub'\u001b[0m: \u001b[1;36m0.023\u001b[0m,\n",
" \u001b[32m'sub_to_fill'\u001b[0m: \u001b[1;36m0.008\u001b[0m,\n",
" \u001b[32m'fill_to_not'\u001b[0m: \u001b[1;36m0.023\u001b[0m,\n",
" \u001b[32m'limit_order_offset'\u001b[0m: \u001b[1;36m0\u001b[0m\n",
" \u001b[1m}\u001b[0m,\n",
" \u001b[32m'BT_FILL_CONDITION_BUY_LIMIT'\u001b[0m: \u001b[1m<\u001b[0m\u001b[1;95mFillCondition.SLOW:\u001b[0m\u001b[39m \u001b[0m\u001b[32m'slow'\u001b[0m\u001b[39m>,\u001b[0m\n",
"\u001b[39m \u001b[0m\u001b[32m'BT_FILL_CONDITION_SELL_LIMIT'\u001b[0m\u001b[39m: \u001b[0m,\n",
" \u001b[32m'BT_FILL_CONS_TRADES_REQUIRED'\u001b[0m: \u001b[1;36m2\u001b[0m,\n",
" \u001b[32m'BT_FILL_LOG_SURROUNDING_TRADES'\u001b[0m: \u001b[1;36m10\u001b[0m,\n",
" \u001b[32m'BT_FILL_PRICE_MARKET_ORDER_PREMIUM'\u001b[0m: \u001b[1;36m0.005\u001b[0m,\n",
" \u001b[32m'COUNT_API_REQUESTS'\u001b[0m: \u001b[3;91mFalse\u001b[0m,\n",
" \u001b[32m'GROUP_TRADES_WITH_TIMESTAMP_LESS_THAN'\u001b[0m: \u001b[1;36m0.003\u001b[0m,\n",
" \u001b[32m'ILOG_SAVE_LEVEL_FROM'\u001b[0m: \u001b[1;36m1\u001b[0m,\n",
" \u001b[32m'LIVE_DATA_FEED'\u001b[0m: \u001b[32m'sip'\u001b[0m,\n",
" \u001b[32m'NORMALIZED_TICK_BASE_PRICE'\u001b[0m: \u001b[1;36m30.0\u001b[0m,\n",
" \u001b[32m'OFFLINE_MODE'\u001b[0m: \u001b[3;91mFalse\u001b[0m,\n",
" \u001b[32m'PROD_SERVER_HOSTNAMES'\u001b[0m: \u001b[1m[\u001b[0m\u001b[32m'tradingeastcoast'\u001b[0m, \u001b[32m'David-MacBook-Pro.local'\u001b[0m\u001b[1m]\u001b[0m,\n",
" \u001b[32m'QUIET_MODE'\u001b[0m: \u001b[3;92mTrue\u001b[0m,\n",
" \u001b[32m'TEST_SERVER_HOSTNAMES'\u001b[0m: \u001b[1m[\u001b[0m\u001b[32m'tradingtest'\u001b[0m\u001b[1m]\u001b[0m\n",
"\u001b[1m}\u001b[0m\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"config_handler.active_profile='profile1'\n",
"\n"
],
"text/plain": [
"config_handler.\u001b[33mactive_profile\u001b[0m=\u001b[32m'profile1'\u001b[0m\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"config handler initialized\n",
"\n"
],
"text/plain": [
"config handler initialized\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Realtime Websocket connection will use FEED: sip and credential of ACCOUNT1\n"
]
},
{
"data": {
"text/html": [
"Resolution : 23\n",
"\n"
],
"text/plain": [
"Resolution : \u001b[1;36m23\u001b[0m\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"NOTE: DUPLICATES 100/3034 in bars. REMOVING.\n",
"\n"
],
"text/plain": [
"NOTE: DUPLICATES \u001b[1;36m100\u001b[0m/\u001b[1;36m3034\u001b[0m in bars. REMOVING.\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"Now there are 0/2934\n",
"\n"
],
"text/plain": [
"Now there are \u001b[1;36m0\u001b[0m/\u001b[1;36m2934\u001b[0m\n"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from v2realbot.tools.loadbatch import load_batch\n",
"from v2realbot.utils.utils import zoneNY\n",
"import pandas as pd\n",
"import numpy as np\n",
"import vectorbtpro as vbt\n",
"\n",
"vbt.settings.set_theme(\"dark\")\n",
"vbt.settings['plotting']['layout']['width'] = 1280\n",
"vbt.settings.plotting.auto_rangebreaks = True\n",
"# Set the option to display with pagination\n",
"pd.set_option('display.notebook_repr_html', True)\n",
"pd.set_option('display.max_rows', 10) # Number of rows per page\n",
"\n",
"res, df = load_batch(batch_id=\"e44a5075\",\n",
" space_resolution_evenly=False,\n",
" indicators_columns=[\"Rsi14\"],\n",
" main_session_only=True)\n",
"if res < 0:\n",
" print(\"Error\" + str(res) + str(df))\n",
"df = df[\"bars\"]\n",
"\n",
"#df"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# filter dates"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.plotly.v1+json": {
"config": {
"plotlyServerURL": "https://plot.ly"
},
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"source": [
"#naloadujeme do vbt symbol as column\n",
"basic_data = vbt.Data.from_data({\"BAC\": df}, tz_convert=zoneNY)\n",
"start_date = pd.Timestamp('2024-03-12 09:30', tz=zoneNY)\n",
"end_date = pd.Timestamp('2024-03-13 16:00', tz=zoneNY)\n",
"\n",
"#basic_data = basic_data.transform(lambda df: df[df.index.date == start_date.date()])\n",
"basic_data = basic_data.transform(lambda df: df[(df.index >= start_date) & (df.index <= end_date)])\n",
"#basic_data.data[\"BAC\"].info()\n",
"\n",
"# fig = basic_data.plot(plot_volume=False)\n",
"# pivot_info = basic_data.run(\"pivotinfo\", up_th=0.003, down_th=0.002)\n",
"# #pivot_info.plot()\n",
"# pivot_info.plot(fig=fig, conf_value_trace_kwargs=dict(visible=True))\n",
"# fig.show()\n",
"\n",
"\n",
"# rsi14 = basic_data.data[\"BAC\"][\"Rsi14\"].rename(\"Rsi14\")\n",
"\n",
"# rsi14.vbt.plot().show()\n",
"# basic_data.data[\"BAC\"].vbt.ohlcv.plot().show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"@vbt.njit\n",
"def long_entry_place_func_nb(c, low, close, time_in_ns, rsi14, window_open, window_close):\n",
" market_open_minutes = 570 # 9 hours * 60 minutes + 30 minutes\n",
"\n",
" for out_i in range(len(c.out)):\n",
" i = c.from_i + out_i\n",
"\n",
" current_minutes = vbt.dt_nb.hour_nb(time_in_ns[i]) * 60 + vbt.dt_nb.minute_nb(time_in_ns[i])\n",
" #print(\"current_minutes\", current_minutes)\n",
" # Calculate elapsed minutes since market open at 9:30 AM\n",
" elapsed_from_open = current_minutes - market_open_minutes\n",
" elapsed_from_open = elapsed_from_open if elapsed_from_open >= 0 else 0\n",
" #print( \"elapsed_from_open\", elapsed_from_open)\n",
"\n",
" #elapsed_from_open = elapsed_minutes_from_open_nb(time_in_ns) \n",
" in_window = elapsed_from_open > window_open and elapsed_from_open < window_close\n",
" #print(\"in_window\", in_window)\n",
" # if in_window:\n",
" # print(\"in window\")\n",
"\n",
" if in_window and rsi14[i] > 60: # and low[i, c.col] <= hit_price: # and hour == 9: # (4)!\n",
" return out_i\n",
" return -1\n",
"\n",
"@vbt.njit\n",
"def long_exit_place_func_nb(c, high, close, time_index, tp, sl): # (5)!\n",
" entry_i = c.from_i - c.wait\n",
" entry_price = close[entry_i, c.col]\n",
" hit_price = entry_price * (1 + tp)\n",
" stop_price = entry_price * (1 - sl)\n",
" for out_i in range(len(c.out)):\n",
" i = c.from_i + out_i\n",
" last_bar_of_day = vbt.dt_nb.day_changed_nb(time_index[i], time_index[i + 1])\n",
"\n",
" #print(next_day)\n",
" if last_bar_of_day: #pokud je dalsi next day, tak zavirame posledni\n",
" print(\"ted\",out_i)\n",
" return out_i\n",
" if close[i, c.col] >= hit_price or close[i, c.col] <= stop_price :\n",
" return out_i\n",
" return -1\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
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