Hi,

Another way of doing this could be to create an indicator events, load the csv in a panda df during the init and at each bar check whether or not the date is in the df. So the indicator would return true if the date is an event and false if not.

This sounds suspicious. I use futures data with missing days but don't have this issue.
Do you load only one future when running your tests?

Also, you should include your code.

Hi,

I actually have an updated version of this UI. As this one had a few issues with Dash. Let me know if you would like to discuss further.

Thanks

It would be helpful to add some of your code for debugging. I don't load data from a database but from a csv file that I load in a panda DataFrame, so I suppose that there's a little issue along the way which we can't really find without any code.

Hi,
I did as ab_trader suggested and can confirm that it works pretty well. I am actually loading a future as a chain in backtrader via a default_strategy that I inherit when I create a new strategy. So my code works on a specific future and I am able to trade the whole curve.
Let me know if you have any questions.

Hi,

I would like to access the strategy parameters for a project I am working on.

However when trying to do so, I get the following:

ort.Test.params
Out[25]: backtrader.metabase.AutoInfoClass_LineRoot_LineMultiple_LineSeries_LineIterator_DataAccessor_StrategyBase_Strategy_Test1

So as a workaround, I put my parameters in a dictionary "parameters" and then passed these parameters as a tuple to params, see below:

   parameters = {'param1': 1}
   params = tuple(parameters.items())

This seems to be working but I am curious to know if there is a better/more elegant way of doing this?

Thanks!

If this is daily data that should work fine. I've had to do the same with an even bigger basket and I didn't have any issues.

@tianjixuetu You need to make sure to close the contracts that are expiring. In this case it seems a contract might have expired with a position.
I have a table which gives me LTD and FND (if applicable) for all futures.

Why not starting on some of these ideas and sharing with the community? That could be an idea, if you feel that you miss something you can always get it done for yourself.

Ok, I will aim to post it within a few days. I need to check a few things.

Why not starting on some of these ideas and sharing with the community? That could be an idea, if you feel that you miss something you can always get it done for yourself.

@tianjixuetu You need to make sure to close the contracts that are expiring. In this case it seems a contract might have expired with a position.
I have a table which gives me LTD and FND (if applicable) for all futures.

If this is daily data that should work fine. I've had to do the same with an even bigger basket and I didn't have any issues.

Hi,
I did as ab_trader suggested and can confirm that it works pretty well. I am actually loading a future as a chain in backtrader via a default_strategy that I inherit when I create a new strategy. So my code works on a specific future and I am able to trade the whole curve.
Let me know if you have any questions.

Ok, I will aim to post it within a few days. I need to check a few things.

Hi,

I actually have an updated version of this UI. As this one had a few issues with Dash. Let me know if you would like to discuss further.

Thanks

It might not be possible, I can't find the option. Do you have an email address I can contact you on?

Hi Pierre,
I could help you depending on what you are trying to achieve.
Pm me with more details.

Having more details would definitely help... Is the strategy trading a continuous timeserie or is it trading the term structure of crude oil?

@eduedix

Hi,

This is what I do to use pyfolio:

        cerebro = bt.Cerebro()
        cerebro.broker.setcash(cash)
        cerebro.addanalyzer(bt.analyzers.PyFolio, _name='pyfolio')

        for s in symbols:
            df = pd.read_csv(os.path.join(path_dir, '{}.csv'.format(s)), parse_dates=True, index_col=0)
            data = bt.feeds.PandasData(dataname=df)
            cerebro.adddata(data)

        cerebro.addstrategy(strategy, **params)

        results = cerebro.run()
        strat = results[0]
        pyfoliozer = strat.analyzers.getbyname('pyfolio')
        returns, positions, transactions, gross_lev = pyfoliozer.get_pf_items()

Hope this helps.