Use next_open and cheat_on_open See: Community - Release 1.9.44.116 For Cheat-On-Open see Blog - Cheat On Open

My hack above worked today, so I will take your much more elegant bit of python and replace a few lines. My python foo is still a bit green... Thanks!

@backtrader How to read dataset in following cases: When there is no time column: Date,Open,High,Low,Close,Volume 12/29/2000,30.87,31.31,28.69,29.06,31655500 12/28/2000,30.56,31.12,30.37,31.06,25055600 12/27/2000,30.37,31.06,29.37,30.69,26441700 When time is in separate column: "Date","Time","O","H","L","C","U","D" 01/02/2006,1530,2821.10,2836.70,2804.00,2819.80,0,0 01/03/2006,1530,2823.00,2872.00,2815.10,2868.70,0,0 01/04/2006,1530,2885.00,2896.00,2873.30,2890.40,0,0 01/05/2006,1530,2892.30,2895.80,2868.00,2886.00,0,0 For "1" case I am trying in this way but is it not working: bt.feeds.GenericCSVData( dataname='orcl-2000.csv', fromdate=datetime.datetime(2000,12,29), dtformat=('%m/%d/%y'), datetime=0, open=1, high=2, low=3, close=4, volume=5, openinterest=-1) It is giving me this error: data_string[found.end():]) ValueError: unconverted data remains: 00

@jf not sure what to answer. I just wrote a code posted above. Within the strategy I defined self.sl_price variable which kept stop price calculated for every open position. This variable can be obtained from observer using self._owner.sl_price name.

@Roman-Semko said in Backtesting oanda/forex: I guess my question is whether the size calculation takes into the account that the price/margin needed for one unit of a currency pair depends on the currency pair being traded. That's why custom sizers can be used. You override _getsizing and then provide the actual exchange rate, which may actually be dynamically fetched from somewhere. Or else directly in the CommissionInfo object.

@asuralm said in How to correctly trade on data1 and data2?: Am I using the bt.observers.BuySell._stclock=True correctly? There is nothing right or wrong about it. It was a hack. @asuralm said in How to correctly trade on data1 and data2?: Yes they are indeed different data feeds but it seems the plotting is not correct when multi data feed the testing engineer no matter what. If each example you present has different feeds, different logic (summary: everything is different) there is no way to discern where a/the problem may be.

@ab_trader In theory yes, because there was a use case with spreads (which oscillate around 0). The problem there was that some of Python tests for existence would fail because the price was zero. It was dealt with a long time ago.

That's all in the link above: Docs - Platform Concepts There is a section about indexing and how 0 is the current point in time. Last is the last produced value before the current point in time and addressable with -1

@Curtis-Miller Thanks!! I will check the PyFolio

@Taewoo-Kim said in Simultaneous bracket order - Cancel one when another has been submitted & accepted: putting the order.cancel in order. accepted / submitted As stated in the answer above. The right place is Completed. Using any of the ones mentioned above guarantees that you will be cancelling the other bracket immediately, yes or yes (unless there isn't cash enough and you receive a Margin) @Taewoo-Kim said in Simultaneous bracket order - Cancel one when another has been submitted & accepted: Still, all the orders are cancelling each other out simultaneously. Probably due to the fact that you are cancelling them immediately upon receiving Accepted or Submitted as stated above. @Taewoo-Kim said in Simultaneous bracket order - Cancel one when another has been submitted & accepted: When the "main" order of a bracket order is converted into a position, how is BT notified? via notify_order or notify_trade? A position is your current status in an asset. An order is not converted to a position. The results of the execution are applied to the current position. Orders are always notified via notify_order, hence the name. Docs - Strategy / notify_order @Taewoo-Kim said in Simultaneous bracket order - Cancel one when another has been submitted & accepted: Is there a sample code that achieves what I'm trying to do? I am trying to Not in the samples.

@yelloww said in Save cerebro data to file for later plotting it on another computer: pickle.HIGHEST_PROTOCOL Update: I found this package, dill which successfully saves a pickle of cerebro. However, upon trying to unpickle or load, it fails :( import dill import pickle import backtrader # open a file, where you stored the pickled data pickled_file = open('pickled_cerebro_willy-v0.07', 'rb') # pull information into the world eat_the_pickle = dill.load(pickled_file) # close the file pickled_file.close() error: --------------------------------------------------------------------------- AttributeError Traceback (most recent call last) <ipython-input-8-1c94c425ea19> in <module>() 4 5 # pull information into the world ----> 6 eat_the_pickle = dill.load(pickled_file) 7 8 # close the file /anaconda3/lib/python3.6/site-packages/dill-0.2.9.dev0-py3.6.egg/dill/_dill.py in load(file, ignore) 302 # apply kwd settings 303 pik._ignore = bool(ignore) --> 304 obj = pik.load() 305 if type(obj).__module__ == getattr(_main_module, '__name__', '__main__'): 306 if not ignore: /anaconda3/lib/python3.6/site-packages/dill-0.2.9.dev0-py3.6.egg/dill/_dill.py in find_class(self, module, name) 463 return type(None) #XXX: special case: NoneType missing 464 if module == 'dill.dill': module = 'dill._dill' --> 465 return StockUnpickler.find_class(self, module, name) 466 467 def __init__(self, *args, **kwds): AttributeError: Can't get attribute 'AutoInfoClass_LineRoot_LineMultiple_LineSeries_LineIterator_DataAccessor_StrategyBase_Strategy_BigWillyStyle' on <module 'backtrader.metabase' from '/anaconda3/lib/python3.6/site-packages/backtrader/metabase.py'>

Hi guys, if anyone wants to use this Kelly performance measure, you can get it here; https://github.com/rich-oregan/backtrader Don't mean to teach you to suck eggs but some newbies here and want to make easy for everyone :) There are two files. "kelly. py" [main file] "init.py" [contains just one small bit of code at the bottom;] from .kelly import * I've got a much better set of performance measures I've created. I just need to write some notes/comments for.. stay tuned.

Cerebro doesn't know that you are looping and cannot know it. The runs inside the optimization re-use the file which has already been loaded, but the runs doesn't know that you had another set of runs before with the same file. You could try to keep the data feed outside of the loop and execute a data.home() after the cerebro.run(...) is done to reset the pointer. Completely untested and may absolutely not work.

Thanks for your replies guys!

@samar-sandhu said in Indicator That Is Aware Of Current Date / Time: Its not working that way Which way? You could at least let us know what doesn't work. Because as the former president of the USA said: "Yes, you can!" (or something like that)

@taylerallen6 What do you mean by depreciated and no longer works ? I had a mod suggest to me the original Oanda API just last week. That said I haven't tried implementation yet. Also, click the link above you, go to the issues section, and under "Which features are missing" is a thread of their progress.

Here is the CSV-based version, however I can't figure out why, but sometimes the entire file isn't flushed. This version works much faster. import backtrader as bt import re import os import os.path from typing import List import datetime as dt import logging import math import pytz import csv def getTableName(data): name = getattr(data,'_name',data.__class__.__name__).strip() # Replace spaces with underscores name = re.sub('\s+','_',name) # Remove invalid characters name = re.sub('[^0-9a-zA-Z_]', '', name) # Remove leading characters until we find a letter or underscore name = re.sub('^[^a-zA-Z_]+', '', name) return name def getTableColumns(data): columns = dict( datetime = dt.datetime ) for line in data.lines.getlinealiases(): if line == 'datetime': continue columns[line] = float return columns class PersistToCSV(bt.Observer): lines = ('ignored',) params = dict( debug = False, rootpath = '/path/to/csv/output/root/' ) def __init__(self): bt.Observer.__init__(self) if not os.path.isdir(self.p.rootpath): os.makedirs(self.p.rootpath) self._csvs:List[csv.DictWriter] = [] self._metadata = [] self._objects = self._owner.datas + list(self._owner.observers) for obj in self._objects: name = getTableName(obj) columns = getTableColumns(obj) path = os.path.join(self.p.rootpath,name+'.csv') metadata = (name,columns,open(path,'a'),) exists = os.path.isfile(path) csvfile = csv.DictWriter(metadata[2],[c for (c,_) in columns.items()]) if not exists: csvfile.writeheader() self._metadata.append(metadata) self._csvs.append(csvfile) def next(self): for (obj,meta,csv) in zip(self._objects,self._metadata,self._csvs): try: self._persist(obj,meta,csv) except: logging.exception("EXCEPTION OCCURRED WHILE WRITING TO CSV") def _persist(self,data:bt.DataBase,meta,csv:csv.DictWriter): name,columns = meta[0],meta[1] row = dict() foundValue = False for name,column in columns.items(): column:Column value = getattr(data.lines,name,None) if value is not None: if column == dt.datetime: value = data.datetime.datetime(0) # # Convert to UTC if data.contractdetails is not None: tz = pytz.timezone(data.contractdetails.m_timeZoneId) value = tz.normalize(tz.localize(value)).astimezone(pytz.utc) else: value = value[0] if type(value) == float and math.isnan(value): print("HI") continue foundValue = True row[name] = value if len(getattr(data,'datetime',[])) <= 1: data = self._owner.data0 value = data.datetime.datetime(0) if data.contractdetails is not None: tz = pytz.timezone(data.contractdetails.m_timeZoneId) value = tz.normalize(tz.localize(value)).astimezone(pytz.utc) row['datetime'] = value if foundValue: csv.writerow(row) def stop(self): for (name,columns,fd) in self._metadata: fd.flush() fd.close()

@andreyapopov said in Wrong execution price during the backtesting: I think another option would be to use YahooFinanceFeed with parameter adjclose=False, especially for things like SPY. It's too bad we can't choose to NOT adjust for dividends, but do adjust for splits. Yahoo is 100% broken. With quirks and random changes in what's the adjusted close across a data set. Unless you can identify a segment which is safe, don't use it. @andreyapopov said in Wrong execution price during the backtesting: Traceback (most recent call last): File "test.py", line 115, in <module> cerebro.run() File "/Library/Python/2.7/site-packages/backtrader/cerebro.py", line 1127, in run runstrat = self.runstrategies(iterstrat) File "/Library/Python/2.7/site-packages/backtrader/cerebro.py", line 1209, in runstrategies data.preload() File "/Library/Python/2.7/site-packages/backtrader/feed.py", line 692, in preload self.f.close() AttributeError: 'NoneType' object has no attribute 'close' It will be really difficult for @ab_trader (or anyone else) to identify what your problem is if you don't supply sample code. The error alone doesn't help.

@anfei I did something similar in my post. Putting it in a dictionary was an easy way to access it. You can see in the last comment here : link text