dwker/snippets
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

daily update

Browse Source
This commit is contained in:
David Brazda
2024-10-11 15:17:10 +02:00
parent f91fa42e3d
commit 503b32a46b
2 changed files with 112 additions and 13 deletions
Download Patch File Download Diff File Expand all files Collapse all files

23
vbt-helper.ipynb
View File

@ -2,34 +2,35 @@
"cells": [
{
"cell_type": "code",
"execution_count": 4,
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"MACD.run(\n",
"BBANDS.run(\n",
" close,\n",
" fastperiod=Default(value=12),\n",
" slowperiod=Default(value=26),\n",
" signalperiod=Default(value=9),\n",
" timeperiod=Default(value=5),\n",
" nbdevup=Default(value=2.0),\n",
" nbdevdn=Default(value=2.0),\n",
" matype=Default(value=0),\n",
" timeframe=Default(value=None),\n",
" short_name='macd',\n",
" short_name='bbands',\n",
" hide_params=None,\n",
" hide_default=True,\n",
" **kwargs\n",
"):\n",
" Run `MACD` indicator.\n",
" Run `BBANDS` indicator.\n",
" \n",
" * Inputs: `close`\n",
" * Parameters: `fastperiod`, `slowperiod`, `signalperiod`, `timeframe`\n",
" * Outputs: `macd`, `macdsignal`, `macdhist`\n",
" * Parameters: `timeperiod`, `nbdevup`, `nbdevdn`, `matype`, `timeframe`\n",
" * Outputs: `upperband`, `middleband`, `lowerband`\n",
" \n",
" Pass a list of parameter names as `hide_params` to hide their column levels, or True to hide all.\n",
" Set `hide_default` to False to show the column levels of the parameters with a default value.\n",
" \n",
" Other keyword arguments are passed to `MACD.run_pipeline`.\n"
" Other keyword arguments are passed to `BBANDS.run_pipeline`.\n"
]
}
],
@ -37,7 +38,7 @@
"import vectorbtpro as vbt\n",
"\n",
"vbt.IF.list_indicators(\"*SMA\")\n",
"vbt.phelp(vbt.indicator(\"talib:MACD\").run)\n"
"vbt.phelp(vbt.indicator(\"talib:BBANDS\").run)\n"
]
}
],

102
vbt.py
View File

@ -62,11 +62,18 @@ t1close_realigned = t1data.data["BAC"].close.vbt.realign_closing(resampler_s)
#endregion
#region ENTRIES/EXITS
#doc from_signal http://5.161.179.223:8000/vbt-doc/api/portfolio/base/#vectorbtpro.portfolio.base.Portfolio.from_signals
- StopExitPrice (Which price to use when exiting a position upon a stop signal?)
- StopEntryPrice (Which price to use as an initial stop price?)
price = close.vbt.wrapper.fill()
price[entries] = entry_price
price[exits] = exit_price
# window open/close
#END OF DAY EXITS
# end_of_day_dates = index.to_series().resample("1d").last().values
# exit_signals.loc[end_of_day_dates] = True
@ -75,6 +82,64 @@ df['exit'][df['exit'].index.isin(end_of_day_dates)] = True
# This index should be probably open_hours_index
# But also check that end_of_day_dates doesn't have nans (NaT), and if it has, you need to filter them out (edited)
#endregion
#region STOPLOSS/TAKEPROFIT
#doc StopOrders http://5.161.179.223:8000/vbt-doc/documentation/portfolio/from-signals/index.html#stop-orders
#SL - ATR based
atr = data.run("atr").atr
pf = vbt.Portfolio.from_signals(
data,
entries=entries,
sl_stop=atr / sub_data.close
)
#EXIT after time http://5.161.179.223:8000/vbt-doc/cookbook/portfolio/index.html#from-signals
f = vbt.PF.from_signals(..., td_stop="7 days")
pf = vbt.PF.from_signals(..., td_stop=pd.Timedelta(days=7))
pf = vbt.PF.from_signals(..., td_stop=td_arr)
#EXIT at time
pf = vbt.PF.from_signals(..., dt_stop="16:00") #exit at 16 and later
pf = vbt.PF.from_signals(..., dt_stop=datetime.time(16, 0))
pf = vbt.PF.from_signals( #exit last bar before
...,
dt_stop="16:00",
arg_config=dict(dt_stop=dict(last_before=True))
)
#CALLBACKS -
"""
- a signal function (signal_func_nb)
- can dynamically generate signals (True, True, False,False)
- runs at beginning of bar
- an adjustment function (adjust_func_nb)
- runs only if signal function above was not provided, but entry,exit arrays
- runs before default signal function ls_signal_func_nb http://5.161.179.223:8000/vbt-doc/api/portfolio/nb/from_signals/index.html#vectorbtpro.portfolio.nb.from_signals.ls_signal_func_nb
- can change pending limit orders etc.
- a post-signal function (post_signal_func_nb)
- post-segment function (post_segment_func_nb)
all of them are accessing SignalContext (c) as named tuple http://5.161.179.223:8000/vbt-doc/api/portfolio/enums/index.html#vectorbtpro.portfolio.enums.SignalContext
SignalContaxt (contains various metrics)
- last_limit_info - 1D with latest limit order per column
- order_counts
- last_return ...
"""
#MEMORY http://5.161.179.223:8000/vbt-doc/cookbook/portfolio/index.html#callbacks
#save an information piece at one timestamp and re-use at a later timestamp
#MULTIPLE LIMIT ORDERS at TIME http://5.161.179.223:8000/vbt-doc/cookbook/portfolio/index.html#callbacks
#IGNORE ENTRIES number of DAYS after losing trade - signal function http://5.161.179.223:8000/vbt-doc/cookbook/portfolio/index.html#callbacks
#adjust_func_nb http://5.161.179.223:8000/vbt-doc/documentation/portfolio/from-signals/#adjustment
#endregion
@ -88,6 +153,12 @@ t1vwap_h_real = t1vwap_h.vwap.vbt.realign_closing(resampler_s)
t1vwap_d_real = t1vwap_d.vwap.vbt.realign_closing(resampler_s)
t1vwap_t_real = t1vwap_t.vwap.vbt.realign_closing(resampler_s)
#BBANDS = vbt.indicator("pandas_ta:BBANDS")
mom_anch_d = AnchoredIndicator("talib:MOM", anchor='30min').run(t1data.data["BAC"].close, timeperiod=10)
mom = vbt.indicator("talib:MOM").run(t1data.data["BAC"].close, timeperiod=10, skipna=True)
#macd = vbt.indicator("talib:MACD").run(t1data.data["BAC"].close) #, timeframe=["1T"]) #,
t1data.ohlcv.data["BAC"].lw.plot(auto_scale=[mom_anch_d, mom])
#SMA - note for TALIB use skipna=True
mom_multi_beztf = vbt.indicator("talib:MOM").run(t1data.close, timeperiod=5, skipna=True)
@ -133,13 +204,19 @@ mom = vbt.indicator("talib:MOM").run(t1data.close, timeperiod=10, skipna=True)
t1data.ohlcv.data["BAC"].lw.plot(left=[(mom_daily, "daily_splitter"),(mom, "original mom")]) #OHLCV with indicators on top
#TAKING and APPLY AUTOMATIC
daily_splitter = vbt.Splitter.from_grouper(t1data.index, "D", split=None) #DOES contain last DAY
def indi_run(sr):
return vbt.indicator("talib:MOM").run(sr.close, timeperiod=10, skipna=True)
res = daily_splitter.apply(indi_run, vbt.Takeable(sr), merge_func="row_stack", freq="1T")
res = daily_splitter.apply(indi_run, vbt.Takeable(t1data), merge_func="row_stack", freq="1T")
#use of IDX accessor (docs:http://5.161.179.223:8000/vbt-doc/api/base/accessors/index.html#vectorbtpro.base.accessors.BaseIDXAccessor)
daily_grouper = t1data.index.vbt.get_grouper("D")
#grouper instance can be iterated over
for name, indices in daily_grouper.iter_groups():
print(name, indices)
#PANDAS GROUPING - series/df grouping resulting in GroupBySeries placeholder that can be aggregated(sum, mean), transformed iterated over or fitlered
for name, group in t1data.data["BAC"].close.groupby(pd.Grouper(freq='D')):
@ -176,4 +253,25 @@ ch = chart([pane1], size="s")
#endregion
#region MULTIACCOUNT
#simultaneous LONG and short (hedging)
#VBT: One position requires one column of data, so hedging is possible by using two columns representing the same asset but different directions,
# then stack both portfolio together (http://5.161.179.223:8000/vbt-doc/features/productivity/#column-stacking)
pf_join = vbt.PF.column_stack((pf1, pf2), group_by=True)
#endregion
#region CUSTOM SIMULATION
#endregion
#region ANALYSIS
#endregion