backtest with tick data, get period datas

ct

Hi,

I have tick data in csv file. I want to calculate last n (x minutes, hourly, daily) period avg from this tick data. How I can backtest my strategy and get period value list?

Best

ct

time,last
2016-02-01 17:44:59,90.75
2016-02-01 17:44:59,90.75
2016-02-01 17:44:59,90.75
2016-02-01 17:44:59,90.75
2016-02-01 17:44:59,90.75
2016-02-01 17:44:59,90.72
2016-02-01 17:44:58,90.75
2016-02-01 17:44:58,90.75
2016-02-01 17:44:58,90.75

backtrader

You probably first need to reverse those ticks because lower ticks have an old timestamp.

Tick Data Resampling is covered for example in this Blog - Tick Data and Resampling

Since you only have last, the most obvious choice when passing that to the generic csv parser is:

    open=1,
    high=1,
    low=1,
    high=1,

to make sure the data has something that looks normal. You may also want to set volume and openinterest to -1 since you have none.

The generic csv data feed is documented with the others here: Docs - Data Feeds Reference

ct

I converted to ohlc tick manually and started cerebro with resampledata. You can see at below. I can't understand, how I can work on period datas in strategy next or other function?

I expected a property on strategy class for periods calculating on the fly for every tick. Next function calling for every tick am I right?

Thank you for quick response and interest

Best

ct

Datetime,Open,High,Low,Close,Volume,OpenInterest
2016-02-01 17:44:59,90.75,90.75,90.75,90.75,1.0,0
2016-02-01 17:44:59,90.75,90.75,90.75,90.75,2.0,0
2016-02-01 17:44:59,90.75,90.75,90.75,90.75,1.0,0
2016-02-01 17:44:59,90.75,90.75,90.75,90.75,40.0,0
2016-02-01 17:44:59,90.75,90.75,90.75,90.75,2.0,0
2016-02-01 17:44:59,90.72,90.72,90.72,90.72,2.0,0
2016-02-01 17:44:58,90.75,90.75,90.75,90.75,4.0,0
2016-02-01 17:44:58,90.75,90.75,90.75,90.75,4.0,0
2016-02-01 17:44:58,90.75,90.75,90.75,90.75,1.0,0


class TestStrategy(bt.Strategy):

    def log(self, txt, dt=None):
        ''' Logging function fot this strategy'''
        dt = dt or self.datas[0].datetime.date(0)
        print('%s, %s' % (dt.isoformat(), txt))

    def __init__(self):
        # Keep a reference to the "close" line in the data[0] dataseries
        self.dataclose = self.datas[0].close

    def next(self):
        # Simply log the closing price of the series from the reference
        self.log('Close, %.2f' % self.dataclose[0])

if __name__ == '__main__':
    # Create a cerebro entity
    cerebro = bt.Cerebro()

    # Add a strategy
    cerebro.addstrategy(TestStrategy)
    # Load the Data
    datapath = 'csv/tickdata.csv'

    data = btfeeds.BacktraderCSVData(
        dataname=datapath,
        timeframe=bt.TimeFrame.Ticks,
        compression=1,  # 1 is the default
        rtbar=True,  # use RealTimeBars
    )

    # Add the Data Feed to Cerebro
    cerebro.resampledata(data, timeframe=bt.TimeFrame.Days, compression=20)

    # Set our desired cash start
    cerebro.broker.setcash(100000.0)

backtrader

first need to reverse those ticks because lower ticks have an old timestamp.

Your ticks are in the wrong order. The resampling process can only work forward. That's the reason your ticks are not being resampled.

The more recent timestamps are at the top of the file and most of the world (Yahoo being an exception) works with files which have the more recent timestamps at the bottom.