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David Brazda
2024-10-16 12:27:27 +02:00
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SNIPPETS.MD
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@ -1,3 +1,39 @@
- [FETCHING DATA](#fetching-data)
- [DISCOVERY](#discovery)
- [DATA/WRAPPER](#datawrapper)
- [create WRAPPER manually](#create-wrapper-manually)
- [RESAMPLING](#resampling)
- [config](#config)
- [REALIGN](#realign)
- [REALIGN\_CLOSING accessors](#realign_closing-accessors)
- [SIGNALS](#signals)
- [ENTRIES/EXITS time based](#entriesexits-time-based)
- [STOPS](#stops)
- [OHLCSTX modul](#ohlcstx-modul)
- [WINDOW OPEN/CLOSE](#window-openclose)
- [END OF DAY EXITS](#end-of-day-exits)
- [DF/SR ACCESSORS](#dfsr-accessors)
- [Generic](#generic)
- [SIGNAL ACCESSORS](#signal-accessors)
- [RANKING - partitioning](#ranking---partitioning)
- [Base Accessors](#base-accessors)
- [Stoploss/Takeprofit](#stoplosstakeprofit)
- [SL - ATR based](#sl---atr-based)
- [EXIT after time](#exit-after-time)
- [CALLBACKS -](#callbacks--)
- [MEMORY](#memory)
- [INDICATORS DEV](#indicators-dev)
- [FAV INDICATORS](#fav-indicators)
- [GROUPING - SPLITTING](#grouping---splitting)
- [CHARTING](#charting)
- [MULTIACCOUNT](#multiaccount)
- [CUSTOM SIMULATION](#custom-simulation)
- [ANALYSIS](#analysis)
- [ROBUSTNESS](#robustness)
- [UTILS](#utils)
```python
import vectorbtpro as vbt
from lightweight_charts import Panel, chart, PlotDFAccessor, PlotSRAccessor
t15data = None
@ -7,6 +43,7 @@ if not hasattr(pd.Series, 'lw'):
if not hasattr(pd.DataFrame, 'lw'):
pd.api.extensions.register_dataframe_accessor("lw")(PlotDFAccessor)
```
# FETCHING DATA
@ -27,6 +64,7 @@ data = vbt.YFData.pull(symbols, start="2024-09-28", end="now", timeframe="1H", m
#endregion
# DISCOVERY
#get parameters of method
vbt.IF.list_locations() #lists categories
vbt.IF.list_indicators(pattern="vbt") #all in category vbt
@ -34,9 +72,6 @@ vbt.IF.list_indicators("*sma")
vbt.phelp(vbt.indicator("talib:MOM").run)
#endregion
# DATA/WRAPPER
Available [methods for data](http://5.161.179.223:8000/vbt-doc/api/data/base/index.html#vectorbtpro.data.base.Data)
@ -122,20 +157,22 @@ t1data = t1data.transform(lambda df: df.between_time('09:30', '16:00').dropna())
resampler_s = vbt.Resampler(target_data.index, source_data.index, source_freq="1T", target_freq="1s")
basic_data.resample(resampler_s)
#endregion
# REALIGN
#REALIGN method - runs on data object (OHLCV) - (open feature realigns leftbound, rest of features rightboud) .resample("1T").first().ffill()
# ffill=True = same frequency as t1data.index
# ffill=False = keeps original frequency but moved to where data are available ie. instead of 15:30 to 15:44 for 15T bar
t15data_realigned = t15data.realign(t1data.index, ffill=True, freq="1T") #freq - target frequency
`REALIGN` method - runs on data object (OHLCV) - (open feature realigns leftbound, rest of features rightboud) .resample("1T").first().ffill()
#REALIGN_CLOSING accessors
```python
ffill=True = same frequency as t1data.index
ffill=False = keeps original frequency but moved to where data are available ie. instead of 15:30 to 15:44 for 15T bar
t15data_realigned = t15data.realign(t1data.index, ffill=True, freq="1T") #freq - target frequency
```
## REALIGN_CLOSING accessors
```python
t15data_realigned_close = t15data.close.vbt.realign_closing(t1data.index, ffill=True, freq="1T")
t15data_realigned_open = t15data.open.vbt.realign_open(t1data.index, ffill=True, freq="1T")
```
#realign_closing accessor just calls
#return self.realign(*args, source_rbound=False, target_rbound=False, **kwargs)
@ -147,9 +184,9 @@ t15data_realigned_open = t15data.open.vbt.realign_open(t1data.index, ffill=True,
resampler_s = vbt.Resampler(t15data.index, t1data.index, source_freq="1T", target_freq="1s")
t15close_realigned_with_resampler = t1data.data["BAC"].realign_closing(resampler_s)
#endregion
# #SIGNALS
# SIGNALS
```python
cond1 = data.get("Low") < bb.lowerband
#comparing with previous value
cond2 = bandwidth > bandwidth.shift(1)
@ -157,8 +194,10 @@ cond2 = bandwidth > bandwidth.shift(1)
cond2 = bandwidth > bandwidth.vbt.ago("7d")
mask = cond1 & cond2
mask.sum()
```
#ENTRIES/EXITS time based
## ENTRIES/EXITS time based
```python
#create entries/exits based on open of first symbol
entries = pd.DataFrame.vbt.signals.empty_like(data.open.iloc[:,0])
@ -181,11 +220,12 @@ exits.vbt.set(
indexer_method="ffill", # this time or before
inplace=True
)
```
## STOPS
[doc from_signal](http://5.161.179.223:8000/vbt-doc/api/portfolio/base/#vectorbtpro.portfolio.base.Portfolio.from_signals)
#STOPS
#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?)
@ -193,18 +233,18 @@ price = close.vbt.wrapper.fill()
price[entries] = entry_price
price[exits] = exit_price
#OHLCSTX modul - exit signal generator based on price and stop values
#http://5.161.179.223:8000/vbt-doc/api/signals/generators/ohlcstx/index.html
## OHLCSTX modul
- exit signal generator based on price and stop values
[doc](ttp://5.161.179.223:8000/vbt-doc/api/signals/generators/ohlcstx/index.html)
## WINDOW OPEN/CLOSE
#WINDOW OPEN/CLOSE
#END OF DAY EXITS
## END OF DAY EXITS
```python
sr = t1data.data["BAC"]
last_n_daily_rows = sr.groupby(sr.index.date).tail(4) #or N last rows
second_last_daily_row = sr.groupby(sr.index.date).nth(-2) #or Nth last row
@ -224,15 +264,18 @@ exits.vbt.set(
inplace=True
)
#endregion
```
# DF/SR ACCESSORS
## GENERIC - for common taks - http://5.161.179.223:8000/vbt-doc/api/generic/accessors/index.html#vectorbtpro.generic.accessors.GenericAccessor
## Generic
- for common taks ([docs](http://5.161.179.223:8000/vbt-doc/api/generic/accessors/index.html#vectorbtpro.generic.accessors.GenericAccessor))
#ROLLING_APPLY - runs custom function over a rolling window of a fixed size (number of bars or frequency)
#EXPANDING_APPLY - runs custome function over expanding the window from the start of the data to the current poin
`rolling_apply` - runs custom function over a rolling window of a fixed size (number of bars or frequency)
`expanding_apply` - runs custome function over expanding the window from the start of the data to the current poin
```python
from numba import njit
mean_nb = njit(lambda a: np.nanmean(a))
hourly_anchored_expanding_mean = t1data.close.vbt.rolling_apply("1H", mean_nb) #ROLLING to FREQENCY or with fixed windows rolling_apply(10,mean_nb)
@ -240,11 +283,14 @@ t1data.ohlcv.data["BAC"].lw.plot(right=[(t1data.close,"close"),(hourly_anchored_
#NOTE for anchored "1D" frequency - it measures timedelta that means requires 1 day between reseting (16:00 end of market, 9:30 start - not a full day, so it is enOugh to set 7H)
df['a'].vbt.overlay_with_heatmap(df['b']).show()
```
##SIGNAL ACCESSORS - http://5.161.179.223:8000/vbt-doc/api/signals/accessors/#vectorbtpro.signals.accessors.SignalsAccessor
## SIGNAL ACCESSORS
- http://5.161.179.223:8000/vbt-doc/api/signals/accessors/#vectorbtpro.signals.accessors.SignalsAccessor
#RANKING - partitioning
## RANKING - partitioning
```python
#pos_rank -1 when False, 0, 1 ... for consecutive Trues, allow_gaps defautlne False
# sample_mask = pd.Series([True, True, False, True, True])
ranked = sample_mask.vbt.signals.pos_rank()
@ -265,10 +311,12 @@ entries.vbt.signals.total_partitions
#partition_pos_rank - all members of each partition have the same rank
ranked = sample_mask.vbt.signals.partition_pos_rank(allow_gaps=True) #0,0,-1,1,1
ranked == 1 # the whole second partition
```
## Base Accessors
* low level accessors - http://5.161.179.223:8000/vbt-doc/api/base/accessors/index.html#vectorbtpro.base.accessors.BaseAccessor
##BASE ACCESSORS -low level accessors - http://5.161.179.223:8000/vbt-doc/api/base/accessors/index.html#vectorbtpro.base.accessors.BaseAccessor
```python
exits.vbt.set(
True,
every="W-MON",
@ -276,23 +324,25 @@ exits.vbt.set(
indexer_method="ffill", # this time or before
inplace=True
)
```
# Stoploss/Takeprofit
[doc StopOrders](http://5.161.179.223:8000/vbt-doc/documentation/portfolio/from-signals/index.html#stop-orders)
#endregion
# STOPLOSS/TAKEPROFIT
#doc StopOrders http://5.161.179.223:8000/vbt-doc/documentation/portfolio/from-signals/index.html#stop-orders
#SL - ATR based
## 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
## EXIT after time
using [from signals](http://5.161.179.223:8000/vbt-doc/cookbook/portfolio/index.html#from-signals)
```python
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)
@ -304,43 +354,41 @@ 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)
## 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)
- an adjustment function (`adjust_func_nb`) - [doc](http://5.161.179.223:8000/vbt-doc/documentation/portfolio/from-signals/#adjustment)
- 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
- 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)
- 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 ...
all of them are accessing [SignalContext](http://5.161.179.223:8000/vbt-doc/api/portfolio/enums/index.html#vectorbtpro.portfolio.enums.SignalContext) `(c)` as named tuple
SignalContaxt (contains various metrics) such as:
* 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
### MEMORY
save an information piece at one timestamp and re-use at a later timestamp when using [callbacks memory](http://5.161.179.223:8000/vbt-doc/cookbook/portfolio/index.html#callbacks)
Usecases:
* [MULTIPLE simultaneuos 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](http://5.161.179.223:8000/vbt-doc/cookbook/portfolio/index.html#callbacks) - signal function
#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
# INDICATORS DEV
```python
#REGISTER CUSTOM INDICATOR
vbt.IndicatorFactory.register_custom_indicator(
SupportResistance,
@ -362,11 +410,12 @@ WMA = vbt.IF(
wma = WMA.run(t1data.close, window=10)
wma.wma
```
#endregion
# FAV INDICATORS
```python
#for TALIB indicator always use skipna=True
#TALIB INDICATORS can do realing closing : timeframe=["1T"]
@ -409,10 +458,11 @@ mom = vbt.indicator("talib:MOM").run(t1data.data["BAC"].close, timeperiod=10, sk
#macd = vbt.indicator("talib:MACD").run(t1data.data["BAC"].close) #, timeframe=["1T"]) #,
t1data.ohlcv.data["BAC"].lw.plot(auto_scale=[mom_anch_d, mom])
#endregion
```
# GROUPING - SPLITTING
```python
#SPLITTER - splitting wrapper based on index
#http://5.161.179.223:8000/vbt-doc/tutorials/cross-validation/splitter/index.html#anchored
daily_splitter = vbt.Splitter.from_grouper(t1data.index, "D", split=None) #DOES contain last DAY
@ -454,12 +504,13 @@ for name, indices in daily_grouper.iter_groups():
#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')):
print(name, group)
```
#endregion
# CHARTING
Using [custom lightweight-charts-python](https://github.com/drew2323/lightweight-charts-python)
```python
#LW df/sr accessor
t1data.ohlcv.data["BAC"].lw.plot(left=[(mom_multi, "mom_multi")]) #OHLCV with indicators on top
@ -495,35 +546,29 @@ pane1 = Panel(
pane2 = Panel(....)
ch = chart([pane1, pane2], size="s")
```
#endregion
# 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)
Simultaneous LONG and short (hedging)
In vbt 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 [column stacking](http://5.161.179.223:8000/vbt-doc/features/productivity/#column-stacking)
pf_join = vbt.PF.column_stack((pf1, pf2), group_by=True)
#endregion
# CUSTOM SIMULATION
#endregion
# ANALYSIS
#ROBUSTNESS
## ROBUSTNESS
```python
pf_stats.sort_values(by='Sharpe Ratio', ascending=False).iloc[::-1].vbt.heatmap().show() #works when there are more metrics
```
#endregion
# UTILS
```python
#MEMORY
sr.info()
@ -556,5 +601,4 @@ print(vbt.timeit(my_pipeline))
#numba doesnt return error when indexing out of bound, this raises the error
import os
os.environ["NUMBA_BOUNDSCHECK"] = "1"
#endregion
```