Yes, that code is terribly wrong. The assignment of a bt.indicators.SMA instance to spread_mean[0] which is in an array.array of type d (aka double or float in Python) is bound to fail each an every time.
Lines objects (Indicators et al.) are meant to be instantiated during __init__.
There may be two ways for it, which may be used simultaneously or not:
Using a category in the forum for user examples/contributed code
Creating a pull request in the main repository https://github.com/mementum/backtrader
There could be also a contrib package with for example the following sub-packages:
indicatorsstrategiesanalyzersobserversPlotting options are detailed here: https://www.backtrader.com/docu/plotting/plotting.html
The default mode of the broker unless you say otherwise with a defined comission scheme is to work with stock-like products.
In this scenario when you sell something you get cash from the action of selling that something. It is difficult to get a margin call if you are getting cash injected.
When you buy cash is detracted from your account. Your description doesn't indicate what your stake is and how much cash you have configured the broker with (the default is 10000). Without code and details one cannot say what's going wrong.
The problem with the snippet being that pd.ols chokes on regular Python array-like structures (array.array, list, etc) needing pandas specific structures.
The adapted and working code
class OLS_Beta(bt.indicators.PeriodN):
_mindatas = 2 # ensure at least 2 data feeds are passed
lines = (('beta'),)
params = (('period', 30),)
def next(self):
y, x = (pd.Series(d.get(size=self.p.period)) for d in self.datas)
r_beta = pd.ols(y=y, x=x, window_type='full_sample')
self.lines.beta[0] = r_beta.beta['x']
In which the values from the dataX feeds is put into a pd.Series instance. There is, imho, no need to use a rolling operation because pd.ols only receives the needed data each time (the latest available data).
The same concept can be applied other pandas operations and I guess to the code ported over to statsmodel
The snippet above is meant to have the order expiring at the end of the next day, which was your use case above. As such the order will obviously be expired for the third day. To have the order still active, you would need to add extra days to the datetime.timedelta.
If your operational plan for live trading includes having the orders expire after x days, you are going to have to deal with trading calendars yourself.
There may be brokers which offer something like: VALID FOR THE NEXT 3 TRADING SESSIONS, which in theory would skip bank holidays and weekends. If you know of such a broker, just post it here.
This is a non-expected usage pattern and for sure one which is not going to work.
LineBuffer is an internal object which is not meant for user consumption. And of course self.dval1 is turning into a float, you are assigning a float to the member attribute you created yourself.
This is not the same as self.lines.xxx = yyy during the __init__ phase, because in that case self.lines is an object, and xxx is constructed by means of Descriptors, which allows controlling things like assignment (via __set__). But assignment cannot be controlled on a member attribute you have created.
The use case is actually a lot easier:
def __init__(self):
self.dval1 = bt.ind.Lowest(self.data.low, period=10) # or bt.ind.MinN(self.data.low, period=10)
def next(self):
print('the current lowest value is:', self.dval1[0])
The indicator family is big and tries to cover all possible aspects
Those were typed snippets no actual tested code. The actual line which produced the error would be helpful in understanding what part of the snippet is trying to iterate a builtin_function_or_method
This was a quick update to introduce some errors introduced in plotting with the improvements added in 1.9.18.105, which didn't cover all the cases for overlay volume plotting and the display of the legend in the charts.
There is also a new functionality to be able to compare a line against a datetime.time object, which should aid in creating comparisons for signals/indicators in __init__ rather than having to do a manual if comparison in next
The changelog
1.9.19.105
This is a minor release adding some extra plot capabilities, some checks in order validity input and a pull request to correct the parameter candleFormat in the Oanda data feed. The changelog:
1.9.18.105
The plotting changes come with an associated blog post (there is the motivation for the changes).