Backtrader Community

run-out

can I get that in init function? I want to use it in next function!

But you already have the close values available in next. What exactly are you trying to do?

run-out

You could track you stop loss orders in a list/dictionary, and in notify_order when an order executes you could check the list, if it's in there you print or save in an analyzer.

run-out

You can get all of the close values at the end of the backtest in stop.

    def stop(self):
        a = self.data.get(0,len(self.data))

run-out

@AlfredSisley

How about this if I understand you correctly.

def __init__(self):
    
        self.roc = {}
        self.percentrank = {}
        
        for i, d in enumerate(self.datas):   
              roc = bt.ind.ROC(self.datas[i], period=self.p.period
              prank = bt.ind.PctRank(roc, period=self.p.period)
             
              self.roc[d] =roc
              self.percentrank[d] = prank

Then when you are in next, you can access the values like:

for d in self.datas:
    # then your prank value per data
    whatever_list_or_var = self.percentrank[d]

run-out

For one indicator comparing againt itself and going back n periods.

# In the strategy class...
 def __init__(self):
        self.prank = bt.ind.PctRank(period=5)

# results in with 0.00 the bottom and 0..80 the top rank: 
2005-05-17T00:00:00, o 12.26	h 12.28	l 11.98	c 12.21	v 61633100	prank 0.40
2005-05-18T00:00:00, o 12.21	h 12.43	l 12.13	c 12.33	v 44940000	prank 0.40
2005-05-19T00:00:00, o 12.36	h 12.64	l 12.35	c 12.43	v 40463700	prank 0.80
2005-05-20T00:00:00, o 12.45	h 12.64	l 12.40	c 12.55	v 25230900	prank 0.80
2005-05-23T00:00:00, o 12.62	h 12.77	l 12.60	c 12.70	v 47390500	prank 0.80
2005-05-24T00:00:00, o 12.66	h 12.86	l 12.64	c 12.80	v 43792600	prank 0.80
2005-05-25T00:00:00, o 12.72	h 12.79	l 12.61	c 12.75	v 32280900	prank 0.60
2005-05-26T00:00:00, o 12.82	h 12.98	l 12.77	c 12.92	v 31827400	prank 0.80
2005-05-27T00:00:00, o 12.86	h 12.90	l 12.79	c 12.85	v 21594400	prank 0.60
2005-05-31T00:00:00, o 12.77	h 12.87	l 12.69	c 12.80	v 28423900	prank 0.20
2005-06-01T00:00:00, o 12.79	h 12.97	l 12.77	c 12.89	v 33329000	prank 0.60

@AlfredSisley said in PercentRank:

Was originally trying to see if there was a way to somehow access all indicator values (value at each time period) in the data and apply percentile to see on any given day where it stands relative to history.

Could you clarify this maybe with an example?

run-out

Using analyzers. The return of running cerebro is a strategy object.

strat = cerebro.run()

'strat' in this case is a strategy object and will contain any analyzers you have built and added to the cerebro engine. The analyzer will be the data in the form of a dictionary. In your case because you desire your custom indicators along with your OHLCV, you could build a custom analyzer. Here is an example you can use for the class definition:


class OHLCMMS(bt.analyzers.Analyzer):
    """This analyzer reports the OHLCV +lines of each of datas.
    Params:
      - timeframe (default: ``None``)
        If ``None`` then the timeframe of the 1st data of the system will be
        used
      - compression (default: ``None``)
        Only used for sub-day timeframes to for example work on an hourly
        timeframe by specifying "TimeFrame.Minutes" and 60 as compression
        If ``None`` then the compression of the 1st data of the system will be
        used
    Methods:
      - get_analysis
        Returns a dictionary with returns as values and the datetime points for
        each return as keys
    """

    def start(self):
        tf = min(d._timeframe for d in self.datas)
        self._usedate = tf >= bt.TimeFrame.Days
        self.rets = {}

    def next(self):

        self.rets[self.data.datetime.datetime()] = [
            self.datas[0].open[0],
            self.datas[0].high[0],
            self.datas[0].low[0],
            self.datas[0].close[0],
            self.MA1[0],
            self.MA2[0],
            self.signal[0],
        ]

    def get_analysis(self):
        return self.rets

To add this to cerebro:

cerebro.addanalyzer(OHLCMMS, _name="OHLCMMS")

After you run the backtest you can extract your information from 'strat' as follows:

strat[0].analyzers.getbyname("OHLCMMS").get_analysis()

Which you can then turn into a dataframe as:

df = pd.DataFrame.from_dict(
        strat[0].analyzers.getbyname("OHLCMMS").get_analysis(),
        orient="index",
        columns=["open", "high", "low", "close", "MA1", "MA2", "signal"],
    )

run-out

Could you clarify what you are trying to do? Your error is most likely coming from

self.percentrank.append(bt.ind.EMA(self.datas[i],period=2),200)

You have defined self.percentrank as a list and you are trying to append two items to it, where only one is allowed.

I'm not sure where you are going with this. Provide some more information and we'll try to help you out.

run-out

You are selling short every 5 days and there's no offsetting buy to close out the short sale. If you want to close a position use self.close.

run-out

@run-out Forgot the link... https://www.backtrader.com/blog/posts/2017-04-01-bracket/bracket/#sample-usage

run-out

@Tim-Donnelly said in Sell bracket position after a holding period:

You should be able to use valid. See the sample usage, in particular here:

    params = dict(
        limdays=3,
        limdays2=1000,
)
...
valid1 = datetime.timedelta(self.p.limdays)
valid2 = valid3 = datetime.timedelta(self.p.limdays2)
...
os = self.buy_bracket(
                        price=p1, valid=valid1,
                        stopprice=p2, stopargs=dict(valid=valid2),
                        limitprice=p3, limitargs=dict(valid=valid3),)

run-out

Could you clarify your question and provide and example?

run-out

If you reduce the devfactor or increase the period you'll start to get hits on the top and bottom.

run-out

@tx_562 said in CrossOver value for boll.lines.top (lines object) always returns 0:

bt.ind.CrossOver(self.data.close, self.boll.lines.top)

I think you want mid. The close won't go over the top.

run-out

@Quỳnh-H-Nguyễn This is still an awesome tool. And if you wanted to create a line preloading into cerebro, this would make it dead easy. Cheers

run-out

In order to work with indicators you need to think of them as whole lines. Below I will create a new line by comparing data is greater at the current point less data shifted to the previous day.

This will create a new line of boolean 1 for greater and 0 for not.

To find how main wins over 100 days? Just add them up, all the wins are 1.

Then subtact from 100 to get all the losses.

Here's the code.

class BuyAndHold_More(bt.Strategy):

    params = (
        ('period', 100),
    )

    def __init__(self):
        self.win = self.data > self.data(-1)
        self.win_100 = bt.ind.SumN(self.win, period=self.p.period)
        self.lose_100 = self.p.period - self.win_100

I will set the period to 5 days so you can see the results here. Note that the starting period adjust to allow the indicator to get going.

2005-01-10T00:00:00, o 13.32	h 13.45	l 13.17	c 13.19	v 47571800	win 0	win_100 3	lose_100 2
2005-01-11T00:00:00, o 13.09	h 13.39	l 13.06	c 13.20	v 63973000	win 1	win_100 4	lose_100 1
2005-01-12T00:00:00, o 13.26	h 13.49	l 13.24	c 13.48	v 53420800	win 1	win_100 4	lose_100 1
2005-01-13T00:00:00, o 13.38	h 13.67	l 13.34	c 13.48	v 56987700	win 0	win_100 3	lose_100 2
2005-01-14T00:00:00, o 13.56	h 13.76	l 13.49	c 13.63	v 42509100	win 1	win_100 3	lose_100 2
2005-01-18T00:00:00, o 13.59	h 13.90	l 13.52	c 13.78	v 60758900	win 1	win_100 4	lose_100 1
2005-01-19T00:00:00, o 13.66	h 13.80	l 13.45	c 13.47	v 51115100	win 0	win_100 3	lose_100 2
2005-01-20T00:00:00, o 13.44	h 13.68	l 13.28	c 13.28	v 45253200	win 0	win_100 2	lose_100 3
2005-01-21T00:00:00, o 13.35	h 13.49	l 13.28	c 13.31	v 40716100	win 1	win_100 3	lose_100 2
2005-01-24T00:00:00, o 13.36	h 13.50	l 13.21	c 13.24	v 37540700	win 0	win_100 2	lose_100 3
2005-01-25T00:00:00, o 13.49	h 13.74	l 13.46	c 13.59	v 48682500	win 1	win_100 2	lose_100 3
2005-01-26T00:00:00, o 13.96	h 14.01	l 13.61	c 13.62	v 78543500	win 1	win_100 3	lose_100 2

run-out

@Quỳnh-H-Nguyễn I could be wrong of course, I'm only reading the docs. But the main docs make no mention or show no real integration into the backtrader engine. Please let us know if I've got that wrong. It's all very new.

run-out

@Sabir-Jana said in ZeroDivisionError: float division by zero:

@Ronny-Li said in ZeroDivisionError: float division by zero:

inv = [bt.DivByZero(bt.LineNum(1), v) for v in vs]

Hello Ronny, Thanks a ton!! it worked.
If I may share another issue faced by me is monthly rebalancing. The workaround I do to resample data for monthly frequency and run the backtest. I tried below code to trigger monthly rebalancing on daily price series however looking at the log I understand it's not working. Appreciate help/ pointers

class Strategy(bt.Strategy):
    params = dict(
        selcperc=0.15,  # percentage of stocks to select from the universe
        rperiod=1,  # period for the returns calculation, default 1 period
        vperiod=126,  # lookback period for volatility - default 36 periods
        mperiod=126,  # lookback period for momentum - default 12 periods
        reserve=0.05,  # 5% reserve capital
        when=bt.timer.SESSION_END, #SESSION_START,
        timer=True,
        monthdays=[1],
        monthcarry=True
    )
    
    def log(self, arg):
            print('{} {}'.format(self.datetime.date(), arg))   

    def __init__(self):
        
#         bt.indicators.Stochastic(self.datas[0], safediv=True)
        
        # calculate 1st the amount of stocks that will be selected
        self.selnum = int(len(self.datas) * self.p.selcperc)

        # allocation perc per stock
        # reserve kept to make sure orders are not rejected due to
        # margin. Prices are calculated when known (close), but orders can only
        # be executed next day (opening price). Price can gap upwards
        self.perctarget = (1.0 - self.p.reserve) / self.selnum

        # returns, volatilities and momentums
        rs = [bt.ind.PctChange(d, period=self.p.rperiod) for d in self.datas] # safediv safezero
        vs = [bt.ind.StdDev(ret, period=self.p.vperiod) for ret in rs]
        ms = [bt.ind.ROC(d, period=self.p.mperiod) for d in self.datas]

        # simple rank formula: (momentum * net payout) / volatility
        # the highest ranked: low vol, large momentum, large payout
#         self.ranks = {d: d.npy * m / v for d, v, m in zip(self.datas, vs, ms)}
        self.ranks = {d: m / v for d, v, m in zip(self.datas, vs, ms)}

#         self.add_timer(
#             when=self.p.when,
#             monthdays=self.p.monthdays,
#             monthcarry=self.p.monthcarry
#         )

        # Add a timer which will be called on the 1st trading day of the month
        self.add_timer(
            bt.timer.SESSION_END,  # when it will be called
            monthdays=[1],  # called on the 1st day of the month
            monthcarry=self.p.monthcarry,  # called on the 2nd day if the 1st is holiday
        )

    def notify_timer(self, timer, when, *args, **kwargs):
        if self._getminperstatus() < 0:
            self.rebalance()

    def rebalance(self):
        # sort data and current rank
        ranks = sorted(
            self.ranks.items(),  # get the (d, rank), pair
            key=lambda x: x[1][0],  # use rank (elem 1) and current time "0"
            reverse=True,  # highest ranked 1st ... please
        )

        # put top ranked in dict with data as key to test for presence
        rtop = dict(ranks[:self.selnum])


        # For logging purposes of stocks leaving the portfolio
        rbot = dict(ranks[self.selnum:])

        # prepare quick lookup list of stocks currently holding a position
        posdata = [d for d, pos in self.getpositions().items() if pos]

        # remove those no longer top ranked
        # do this first to issue sell orders and free cash
        for d in (d for d in posdata if d not in rtop):
            self.log('Leave {} - Rank {:.2f}'.format(d._name, rbot[d][0]))
            self.order_target_percent(d, target=0.0)

        # rebalance those already top ranked and still there
        for d in (d for d in posdata if d in rtop):
            self.log('Rebal {} - Rank {:.2f}'.format(d._name, rtop[d][0]))
            self.order_target_percent(d, target=self.perctarget)
            del rtop[d]  # remove it, to simplify next iteration

        # issue a target order for the newly top ranked stocks
        # do this last, as this will generate buy orders consuming cash
        for d in rtop:
            self.log('Enter {} - Rank {:.2f}'.format(d._name, rtop[d][0]))
            self.order_target_percent(d, target=self.perctarget) 
            
    def next(self):
        self.notify_timer(self, self.p.timer, self.p.when)

Execution Log:

Starting Portfolio Value: 100000.00
2014-07-07 Enter CONCOR.NS - Rank 46.67
2014-07-07 Enter AUROPHARMA.NS - Rank 43.93
2014-07-07 Enter SHREECEM.NS - Rank 42.47
2014-07-07 Enter LT.NS - Rank 38.76
2014-07-07 Enter PFC.NS - Rank 36.94
2014-07-07 Enter SBIN.NS - Rank 36.59
2014-07-07 Enter ASHOKLEY.NS - Rank 35.69
2014-07-07 Enter MOTHERSUMI.NS - Rank 34.47
2014-07-07 Enter EICHERMOT.NS - Rank 34.41
2014-07-07 Enter PNB.NS - Rank 34.04
2014-07-07 Enter PGHH.NS - Rank 33.73
2014-07-07 Enter TITAN.NS - Rank 32.30
2014-07-07 Enter BPCL.NS - Rank 31.73
2014-07-08 Leave ASHOKLEY.NS - Rank 28.06
2014-07-08 Leave TITAN.NS - Rank 27.23
2014-07-08 Rebal AUROPHARMA.NS - Rank 35.99
2014-07-08 Rebal BPCL.NS - Rank 31.08
2014-07-08 Rebal CONCOR.NS - Rank 38.02
2014-07-08 Rebal LT.NS - Rank 36.04
2014-07-08 Rebal MOTHERSUMI.NS - Rank 30.61
2014-07-08 Rebal PFC.NS - Rank 31.57
2014-07-08 Rebal PGHH.NS - Rank 32.45
2014-07-08 Rebal PNB.NS - Rank 30.18
2014-07-08 Rebal SBIN.NS - Rank 33.78
2014-07-08 Rebal SHREECEM.NS - Rank 40.49
2014-07-08 Enter EICHERMOT.NS - Rank 33.64
2014-07-08 Enter BAJAJHLDNG.NS - Rank 32.01
2014-07-08 Enter AXISBANK.NS - Rank 30.54
2014-07-09 Leave AUROPHARMA.NS - Rank 26.37
2014-07-09 Rebal AXISBANK.NS - Rank 30.17
2014-07-09 Rebal BAJAJHLDNG.NS - Rank 29.87
2014-07-09 Rebal BPCL.NS - Rank 32.39
2014-07-09 Rebal CONCOR.NS - Rank 37.63
2014-07-09 Rebal LT.NS - Rank 34.93
2014-07-09 Rebal MOTHERSUMI.NS - Rank 29.34
2014-07-09 Rebal PFC.NS - Rank 30.32
2014-07-09 Rebal PGHH.NS - Rank 30.47
2014-07-09 Rebal PNB.NS - Rank 30.50
2014-07-09 Rebal SBIN.NS - Rank 35.63
2014-07-09 Rebal SHREECEM.NS - Rank 38.99
2014-07-09 Enter EICHERMOT.NS - Rank 31.73
2014-07-09 Enter ICICIBANK.NS - Rank 28.64
2014-07-10 Leave BAJAJHLDNG.NS - Rank 29.43
2014-07-10 Leave ICICIBANK.NS - Rank 27.20
2014-07-10 Rebal AXISBANK.NS - Rank 31.25
2014-07-10 Rebal BPCL.NS - Rank 33.67
2014-07-10 Rebal CONCOR.NS - Rank 40.36
2014-07-10 Rebal LT.NS - Rank 34.31
2014-07-10 Rebal MOTHERSUMI.NS - Rank 33.70
2014-07-10 Rebal PFC.NS - Rank 34.81
2014-07-10 Rebal PGHH.NS - Rank 29.82
2014-07-10 Rebal PNB.NS - Rank 30.65
2014-07-10 Rebal SBIN.NS - Rank 35.79
2014-07-10 Rebal SHREECEM.NS - Rank 39.86
2014-07-10 Enter EICHERMOT.NS - Rank 30.94
2014-07-10 Enter PAGEIND.NS - Rank 30.30
2014-07-10 Enter ADANIPORTS.NS - Rank 29.64
2014-07-11 Leave ADANIPORTS.NS - Rank 21.94
2014-07-11 Leave PFC.NS - Rank 26.35
2014-07-11 Leave PNB.NS - Rank 26.56
2014-07-11 Rebal AXISBANK.NS - Rank 30.62
2014-07-11 Rebal BPCL.NS - Rank 32.29
2014-07-11 Rebal CONCOR.NS - Rank 34.57
2014-07-11 Rebal LT.NS - Rank 30.98
2014-07-11 Rebal MOTHERSUMI.NS - Rank 30.25
2014-07-11 Rebal PGHH.NS - Rank 28.42
2014-07-11 Rebal SBIN.NS - Rank 31.46
2014-07-11 Rebal SHREECEM.NS - Rank 37.59
2014-07-11 Enter EICHERMOT.NS - Rank 30.97
2014-07-11 Enter PAGEIND.NS - Rank 28.64
2014-07-11 Enter IOC.NS - Rank 28.58
2014-07-11 Enter AUROPHARMA.NS - Rank 28.29
2014-07-11 Enter HINDPETRO.NS - Rank 27.17
2014-07-14 Leave IOC.NS - Rank 26.02
2014-07-14 Leave MOTHERSUMI.NS - Rank 26.31
2014-07-14 Rebal AUROPHARMA.NS - Rank 30.59
2014-07-14 Rebal AXISBANK.NS - Rank 34.12
2014-07-14 Rebal BPCL.NS - Rank 31.61
2014-07-14 Rebal CONCOR.NS - Rank 34.03
2014-07-14 Rebal HINDPETRO.NS - Rank 27.88
2014-07-14 Rebal LT.NS - Rank 34.89
2014-07-14 Rebal PGHH.NS - Rank 28.22
2014-07-14 Rebal SBIN.NS - Rank 31.84
2014-07-14 Rebal SHREECEM.NS - Rank 38.14
2014-07-14 Enter EICHERMOT.NS - Rank 31.50
2014-07-14 Enter PFC.NS - Rank 29.32
2014-07-14 Enter PNB.NS - Rank 28.90
2014-07-14 Enter HAVELLS.NS - Rank 27.97
2014-07-15 Leave HAVELLS.NS - Rank 29.65
2014-07-15 Rebal AUROPHARMA.NS - Rank 34.18
2014-07-15 Rebal AXISBANK.NS - Rank 38.14
2014-07-15 Rebal BPCL.NS - Rank 32.98
2014-07-15 Rebal CONCOR.NS - Rank 36.38
2014-07-15 Rebal HINDPETRO.NS - Rank 29.95
2014-07-15 Rebal LT.NS - Rank 38.46
2014-07-15 Rebal PFC.NS - Rank 32.38
2014-07-15 Rebal PGHH.NS - Rank 30.71
2014-07-15 Rebal PNB.NS - Rank 31.95
2014-07-15 Rebal SBIN.NS - Rank 36.52
2014-07-15 Rebal SHREECEM.NS - Rank 37.98
2014-07-15 Enter EICHERMOT.NS - Rank 34.44
2014-07-15 Enter MOTHERSUMI.NS - Rank 30.71
2014-07-16 Leave PFC.NS - Rank 28.23
2014-07-16 Rebal AUROPHARMA.NS - Rank 37.10
2014-07-16 Rebal AXISBANK.NS - Rank 39.30
2014-07-16 Rebal BPCL.NS - Rank 32.91
2014-07-16 Rebal CONCOR.NS - Rank 38.53
2014-07-16 Rebal HINDPETRO.NS - Rank 30.86
2014-07-16 Rebal LT.NS - Rank 37.69
2014-07-16 Rebal MOTHERSUMI.NS - Rank 35.12
2014-07-16 Rebal PGHH.NS - Rank 31.92
2014-07-16 Rebal PNB.NS - Rank 31.67
2014-07-16 Rebal SBIN.NS - Rank 36.63
2014-07-16 Rebal SHREECEM.NS - Rank 38.88
2014-07-16 Enter EICHERMOT.NS - Rank 33.98
2014-07-16 Enter ADANIPORTS.NS - Rank 31.71
2014-07-17 Leave ADANIPORTS.NS - Rank 31.33
2014-07-17 Leave PGHH.NS - Rank 28.79
2014-07-17 Rebal AUROPHARMA.NS - Rank 36.68
2014-07-17 Rebal AXISBANK.NS - Rank 39.47
2014-07-17 Rebal BPCL.NS - Rank 33.75
2014-07-17 Rebal CONCOR.NS - Rank 40.51
2014-07-17 Rebal HINDPETRO.NS - Rank 31.85
2014-07-17 Rebal LT.NS - Rank 39.13
2014-07-17 Rebal MOTHERSUMI.NS - Rank 35.79
2014-07-17 Rebal PNB.NS - Rank 32.22
2014-07-17 Rebal SBIN.NS - Rank 38.27
2014-07-17 Rebal SHREECEM.NS - Rank 39.25
2014-07-17 Enter EICHERMOT.NS - Rank 36.00
2014-07-17 Enter HAVELLS.NS - Rank 34.63
2014-07-17 Enter ULTRACEMCO.NS - Rank 32.15
2014-07-18 Leave HINDPETRO.NS - Rank 28.44
2014-07-18 Leave PNB.NS - Rank 29.86
2014-07-18 Leave ULTRACEMCO.NS - Rank 27.88
2014-07-18 Rebal AUROPHARMA.NS - Rank 37.18
2014-07-18 Rebal AXISBANK.NS - Rank 41.21
2014-07-18 Rebal BPCL.NS - Rank 32.85
2014-07-18 Rebal CONCOR.NS - Rank 40.39
2014-07-18 Rebal HAVELLS.NS - Rank 36.26
2014-07-18 Rebal LT.NS - Rank 37.78
2014-07-18 Rebal MOTHERSUMI.NS - Rank 35.56
2014-07-18 Rebal SBIN.NS - Rank 36.24
2014-07-18 Rebal SHREECEM.NS - Rank 38.80
2014-07-18 Enter EICHERMOT.NS - Rank 36.03
2014-07-18 Enter ICICIBANK.NS - Rank 30.90
2014-07-18 Enter ASHOKLEY.NS - Rank 30.70
2014-07-18 Enter ADANIPORTS.NS - Rank 30.63
2014-07-21 Leave ASHOKLEY.NS - Rank 29.98
2014-07-21 Rebal ADANIPORTS.NS - Rank 30.28
2014-07-21 Rebal AUROPHARMA.NS - Rank 33.30
2014-07-21 Rebal AXISBANK.NS - Rank 42.66
2014-07-21 Rebal BPCL.NS - Rank 31.95
2014-07-21 Rebal CONCOR.NS - Rank 40.64
2014-07-21 Rebal HAVELLS.NS - Rank 33.77
2014-07-21 Rebal ICICIBANK.NS - Rank 30.98
2014-07-21 Rebal LT.NS - Rank 36.36
2014-07-21 Rebal MOTHERSUMI.NS - Rank 34.23
2014-07-21 Rebal SBIN.NS - Rank 35.12
2014-07-21 Rebal SHREECEM.NS - Rank 40.04
2014-07-21 Enter EICHERMOT.NS - Rank 35.67
2014-07-21 Enter PAGEIND.NS - Rank 30.67
2014-07-22 Leave ADANIPORTS.NS - Rank 30.48
2014-07-22 Leave BPCL.NS - Rank 30.13
2014-07-22 Rebal AUROPHARMA.NS - Rank 35.39
2014-07-22 Rebal AXISBANK.NS - Rank 44.50
2014-07-22 Rebal CONCOR.NS - Rank 44.00
2014-07-22 Rebal HAVELLS.NS - Rank 34.87
2014-07-22 Rebal ICICIBANK.NS - Rank 33.02
2014-07-22 Rebal LT.NS - Rank 35.56
2014-07-22 Rebal MOTHERSUMI.NS - Rank 34.47
2014-07-22 Rebal SBIN.NS - Rank 35.92
2014-07-22 Rebal SHREECEM.NS - Rank 37.68
2014-07-22 Enter EICHERMOT.NS - Rank 35.59
2014-07-22 Enter PNB.NS - Rank 31.50
2014-07-22 Enter PFC.NS - Rank 30.66
2014-07-22 Enter ASHOKLEY.NS - Rank 30.55
2014-07-23 Leave PFC.NS - Rank 30.53
2014-07-23 Rebal ASHOKLEY.NS - Rank 31.39
2014-07-23 Rebal AUROPHARMA.NS - Rank 31.51
2014-07-23 Rebal AXISBANK.NS - Rank 42.79
2014-07-23 Rebal CONCOR.NS - Rank 41.76
2014-07-23 Rebal HAVELLS.NS - Rank 31.93
2014-07-23 Rebal ICICIBANK.NS - Rank 33.48
2014-07-23 Rebal LT.NS - Rank 35.85
2014-07-23 Rebal MOTHERSUMI.NS - Rank 30.82
2014-07-23 Rebal PNB.NS - Rank 31.00
2014-07-23 Rebal SBIN.NS - Rank 35.45
2014-07-23 Rebal SHREECEM.NS - Rank 37.84
2014-07-23 Enter EICHERMOT.NS - Rank 33.90
2014-07-23 Enter BPCL.NS - Rank 31.62
2014-07-24 Leave AUROPHARMA.NS - Rank 28.30
2014-07-24 Rebal ASHOKLEY.NS - Rank 32.42
2014-07-24 Rebal AXISBANK.NS - Rank 40.71
2014-07-24 Rebal BPCL.NS - Rank 33.21
2014-07-24 Rebal CONCOR.NS - Rank 42.58
2014-07-24 Rebal HAVELLS.NS - Rank 32.82
2014-07-24 Rebal ICICIBANK.NS - Rank 31.19
2014-07-24 Rebal LT.NS - Rank 35.29
2014-07-24 Rebal MOTHERSUMI.NS - Rank 30.00
2014-07-24 Rebal PNB.NS - Rank 30.52
2014-07-24 Rebal SBIN.NS - Rank 35.13
2014-07-24 Rebal SHREECEM.NS - Rank 34.77
2014-07-24 Enter EICHERMOT.NS - Rank 32.88
2014-07-24 Enter PFC.NS - Rank 29.63
2014-07-25 Leave PFC.NS - Rank 27.90
2014-07-25 Rebal ASHOKLEY.NS - Rank 29.14
2014-07-25 Rebal AXISBANK.NS - Rank 40.14
2014-07-25 Rebal BPCL.NS - Rank 30.27
2014-07-25 Rebal CONCOR.NS - Rank 42.54
2014-07-25 Rebal HAVELLS.NS - Rank 33.57
2014-07-25 Rebal ICICIBANK.NS - Rank 28.78
2014-07-25 Rebal LT.NS - Rank 35.62
2014-07-25 Rebal MOTHERSUMI.NS - Rank 29.60
2014-07-25 Rebal PNB.NS - Rank 29.44
2014-07-25 Rebal SBIN.NS - Rank 33.82
2014-07-25 Rebal SHREECEM.NS - Rank 37.58
2014-07-25 Enter EICHERMOT.NS - Rank 34.59
2014-07-25 Enter PETRONET.NS - Rank 29.75
2014-07-28 Leave ASHOKLEY.NS - Rank 26.90
2014-07-28 Rebal AXISBANK.NS - Rank 37.76
2014-07-28 Rebal BPCL.NS - Rank 27.34
2014-07-28 Rebal CONCOR.NS - Rank 37.34
2014-07-28 Rebal HAVELLS.NS - Rank 32.27
2014-07-28 Rebal ICICIBANK.NS - Rank 28.04
2014-07-28 Rebal LT.NS - Rank 32.41
2014-07-28 Rebal MOTHERSUMI.NS - Rank 33.21
2014-07-28 Rebal PETRONET.NS - Rank 29.41
2014-07-28 Rebal PNB.NS - Rank 31.49
2014-07-28 Rebal SBIN.NS - Rank 32.93
2014-07-28 Rebal SHREECEM.NS - Rank 39.10
2014-07-28 Enter EICHERMOT.NS - Rank 35.07
2014-07-28 Enter PFC.NS - Rank 27.19
2014-07-30 Leave BPCL.NS - Rank 28.06
2014-07-30 Leave LT.NS - Rank 26.83
2014-07-30 Rebal AXISBANK.NS - Rank 40.11
2014-07-30 Rebal CONCOR.NS - Rank 40.12
2014-07-30 Rebal HAVELLS.NS - Rank 30.97
2014-07-30 Rebal ICICIBANK.NS - Rank 31.50
2014-07-30 Rebal MOTHERSUMI.NS - Rank 34.60
2014-07-30 Rebal PETRONET.NS - Rank 30.49
2014-07-30 Rebal PFC.NS - Rank 31.60
2014-07-30 Rebal PNB.NS - Rank 37.99
2014-07-30 Rebal SBIN.NS - Rank 34.20
2014-07-30 Rebal SHREECEM.NS - Rank 40.88
2014-07-30 Enter EICHERMOT.NS - Rank 36.10
2014-07-30 Enter ASHOKLEY.NS - Rank 32.29
2014-07-30 Enter TITAN.NS - Rank 29.98
2014-07-31 Leave TITAN.NS - Rank 30.74
2014-07-31 Rebal ASHOKLEY.NS - Rank 33.71
2014-07-31 Rebal AXISBANK.NS - Rank 41.55
2014-07-31 Rebal CONCOR.NS - Rank 39.78
2014-07-31 Rebal HAVELLS.NS - Rank 37.30
2014-07-31 Rebal ICICIBANK.NS - Rank 34.95
2014-07-31 Rebal MOTHERSUMI.NS - Rank 38.18
2014-07-31 Rebal PETRONET.NS - Rank 35.87
2014-07-31 Rebal PFC.NS - Rank 36.63
2014-07-31 Rebal PNB.NS - Rank 41.66
2014-07-31 Rebal SBIN.NS - Rank 34.58
2014-07-31 Rebal SHREECEM.NS - Rank 44.88
2014-07-31 Enter EICHERMOT.NS - Rank 37.48
2014-07-31 Enter PGHH.NS - Rank 31.19
2014-08-01 Leave PGHH.NS - Rank 31.49
2014-08-01 Rebal ASHOKLEY.NS - Rank 33.93
2014-08-01 Rebal AXISBANK.NS - Rank 44.33
2014-08-01 Rebal CONCOR.NS - Rank 36.67
2014-08-01 Rebal HAVELLS.NS - Rank 32.24
2014-08-01 Rebal ICICIBANK.NS - Rank 34.48
2014-08-01 Rebal MOTHERSUMI.NS - Rank 35.42
2014-08-01 Rebal PETRONET.NS - Rank 37.81
2014-08-01 Rebal PFC.NS - Rank 34.10
2014-08-01 Rebal PNB.NS - Rank 41.39
2014-08-01 Rebal SBIN.NS - Rank 34.42
2014-08-01 Rebal SHREECEM.NS - Rank 44.25
2014-08-01 Enter EICHERMOT.NS - Rank 37.08
2014-08-01 Enter MARUTI.NS - Rank 34.32
2014-08-04 Leave HAVELLS.NS - Rank 29.66
2014-08-04 Rebal ASHOKLEY.NS - Rank 36.26
2014-08-04 Rebal AXISBANK.NS - Rank 43.75
2014-08-04 Rebal CONCOR.NS - Rank 36.85
2014-08-04 Rebal ICICIBANK.NS - Rank 36.91
2014-08-04 Rebal MARUTI.NS - Rank 31.97
2014-08-04 Rebal MOTHERSUMI.NS - Rank 37.13
2014-08-04 Rebal PETRONET.NS - Rank 33.84
2014-08-04 Rebal PFC.NS - Rank 33.88
2014-08-04 Rebal PNB.NS - Rank 43.70
2014-08-04 Rebal SBIN.NS - Rank 36.44
2014-08-04 Rebal SHREECEM.NS - Rank 42.08
2014-08-04 Enter EICHERMOT.NS - Rank 38.96
2014-08-04 Enter TATAMTRDVR.NS - Rank 31.49
2014-08-05 Leave PETRONET.NS - Rank 30.15
2014-08-05 Leave TATAMTRDVR.NS - Rank 31.60
2014-08-05 Rebal ASHOKLEY.NS - Rank 37.32
2014-08-05 Rebal AXISBANK.NS - Rank 47.66
2014-08-05 Rebal CONCOR.NS - Rank 37.98
2014-08-05 Rebal ICICIBANK.NS - Rank 39.26
2014-08-05 Rebal MARUTI.NS - Rank 34.96
2014-08-05 Rebal MOTHERSUMI.NS - Rank 39.71
.......

Perhaps you could open a separate question so future searchers will be able to see it as a distinct topic. :)

run-out

You have the notify_timer, but you didn't initiate the timer. You also need to add in a monthdays parameter.

I've simplified your example just to get the cash added.

class BuyAndHold_More(bt.Strategy):
    params = dict(
        monthly_cash=1000.0,  # amount of cash to buy every month
        when=bt.timer.SESSION_START,
        timer=True,
        monthdays=[1],
    )

    def __init__(self):
        self.add_timer(
            when=self.p.when,
            monthdays=self.p.monthdays,
        )

    def log(self, txt, dt=None):
        """ Logging function fot this strategy"""
        dt = dt or self.data.datetime[0]
        if isinstance(dt, float):
            dt = bt.num2date(dt)
        print("%s, %s" % (dt.isoformat(), txt))

    def start(self):
        self.cash_start = self.broker.get_cash()
        self.val_start = 100.0

        # Add a timer which will be called on the 1st trading day of the month
        self.add_timer(
            bt.timer.SESSION_END,  # when it will be called
            monthdays=[1],  # called on the 1st day of the month
            monthcarry=True,  # called on the 2nd day if the 1st is holiday
        )

    def notify_timer(self, timer, when, *args, **kwargs):
        # Add the influx of monthly cash to the broker
        self.broker.add_cash(self.p.monthly_cash)
        print("Cash Added!")
        
    def next(self):
        self.log("Cash {} Value {}".format(self.broker.cash, self.broker.get_value()))

    def stop(self):
        # calculate the actual returns
        self.roi = (self.broker.get_value() / self.cash_start) - 1.0
        print("ROI:        {:.2f}%".format(self.roi))

This yields:

2005-01-03T00:00:00, Cash 10000.0 Value 10000.0
2005-01-04T00:00:00, Cash 11000.0 Value 11000.0
2005-01-05T00:00:00, Cash 11000.0 Value 11000.0
2005-01-06T00:00:00, Cash 11000.0 Value 11000.0
2005-01-07T00:00:00, Cash 11000.0 Value 11000.0
2005-01-10T00:00:00, Cash 11000.0 Value 11000.0
2005-01-11T00:00:00, Cash 11000.0 Value 11000.0
2005-01-12T00:00:00, Cash 11000.0 Value 11000.0
2005-01-13T00:00:00, Cash 11000.0 Value 11000.0
2005-01-14T00:00:00, Cash 11000.0 Value 11000.0
2005-01-18T00:00:00, Cash 11000.0 Value 11000.0
2005-01-19T00:00:00, Cash 11000.0 Value 11000.0
2005-01-20T00:00:00, Cash 11000.0 Value 11000.0
2005-01-21T00:00:00, Cash 11000.0 Value 11000.0
2005-01-24T00:00:00, Cash 11000.0 Value 11000.0
2005-01-25T00:00:00, Cash 11000.0 Value 11000.0
2005-01-26T00:00:00, Cash 11000.0 Value 11000.0
2005-01-27T00:00:00, Cash 11000.0 Value 11000.0
2005-01-28T00:00:00, Cash 11000.0 Value 11000.0
2005-01-31T00:00:00, Cash 11000.0 Value 11000.0
Cash Added!
2005-02-01T00:00:00, Cash 11000.0 Value 11000.0
2005-02-02T00:00:00, Cash 12000.0 Value 12000.0
2005-02-03T00:00:00, Cash 12000.0 Value 12000.0
2005-02-04T00:00:00, Cash 12000.0 Value 12000.0
2005-02-07T00:00:00, Cash 12000.0 Value 12000.0
2005-02-08T00:00:00, Cash 12000.0 Value 12000.0
2005-02-09T00:00:00, Cash 12000.0 Value 12000.0
2005-02-10T00:00:00, Cash 12000.0 Value 12000.0
2005-02-11T00:00:00, Cash 12000.0 Value 12000.0
2005-02-14T00:00:00, Cash 12000.0 Value 12000.0
2005-02-15T00:00:00, Cash 12000.0 Value 12000.0
2005-02-16T00:00:00, Cash 12000.0 Value 12000.0
2005-02-17T00:00:00, Cash 12000.0 Value 12000.0
2005-02-18T00:00:00, Cash 12000.0 Value 12000.0
2005-02-22T00:00:00, Cash 12000.0 Value 12000.0
2005-02-23T00:00:00, Cash 12000.0 Value 12000.0
2005-02-24T00:00:00, Cash 12000.0 Value 12000.0
2005-02-25T00:00:00, Cash 12000.0 Value 12000.0
2005-02-28T00:00:00, Cash 12000.0 Value 12000.0
Cash Added!
2005-03-01T00:00:00, Cash 12000.0 Value 12000.0
2005-03-02T00:00:00, Cash 13000.0 Value 13000.0
2005-03-03T00:00:00, Cash 13000.0 Value 13000.0
2005-03-04T00:00:00, Cash 13000.0 Value 13000.0
2005-03-07T00:00:00, Cash 13000.0 Value 13000.0
2005-03-08T00:00:00, Cash 13000.0 Value 13000.0
2005-03-09T00:00:00, Cash 13000.0 Value 13000.0
2005-03-10T00:00:00, Cash 13000.0 Value 13000.0
2005-03-11T00:00:00, Cash 13000.0 Value 13000.0
2005-03-14T00:00:00, Cash 13000.0 Value 13000.0
2005-03-15T00:00:00, Cash 13000.0 Value 13000.0
2005-03-16T00:00:00, Cash 13000.0 Value 13000.0
2005-03-17T00:00:00, Cash 13000.0 Value 13000.0
2005-03-18T00:00:00, Cash 13000.0 Value 13000.0
2005-03-21T00:00:00, Cash 13000.0 Value 13000.0
2005-03-22T00:00:00, Cash 13000.0 Value 13000.0
2005-03-23T00:00:00, Cash 13000.0 Value 13000.0
2005-03-24T00:00:00, Cash 13000.0 Value 13000.0
2005-03-28T00:00:00, Cash 13000.0 Value 13000.0
2005-03-29T00:00:00, Cash 13000.0 Value 13000.0
2005-03-30T00:00:00, Cash 13000.0 Value 13000.0
2005-03-31T00:00:00, Cash 13000.0 Value 13000.0
Cash Added!
2005-04-01T00:00:00, Cash 13000.0 Value 13000.0
2005-04-04T00:00:00, Cash 14000.0 Value 14000.0
2005-04-05T00:00:00, Cash 14000.0 Value 14000.0
2005-04-06T00:00:00, Cash 14000.0 Value 14000.0
2005-04-07T00:00:00, Cash 14000.0 Value 14000.0
2005-04-08T00:00:00, Cash 14000.0 Value 14000.0
2005-04-11T00:00:00, Cash 14000.0 Value 14000.0
2005-04-12T00:00:00, Cash 14000.0 Value 14000.0
2005-04-13T00:00:00, Cash 14000.0 Value 14000.0
2005-04-14T00:00:00, Cash 14000.0 Value 14000.0
2005-04-15T00:00:00, Cash 14000.0 Value 14000.0
2005-04-18T00:00:00, Cash 14000.0 Value 14000.0
2005-04-19T00:00:00, Cash 14000.0 Value 14000.0
2005-04-20T00:00:00, Cash 14000.0 Value 14000.0
2005-04-21T00:00:00, Cash 14000.0 Value 14000.0
2005-04-22T00:00:00, Cash 14000.0 Value 14000.0
2005-04-25T00:00:00, Cash 14000.0 Value 14000.0
2005-04-26T00:00:00, Cash 14000.0 Value 14000.0
2005-04-27T00:00:00, Cash 14000.0 Value 14000.0
2005-04-28T00:00:00, Cash 14000.0 Value 14000.0
2005-04-29T00:00:00, Cash 14000.0 Value 14000.0
Cash Added!
2005-05-02T00:00:00, Cash 14000.0 Value 14000.0
2005-05-03T00:00:00, Cash 15000.0 Value 15000.0
2005-05-04T00:00:00, Cash 15000.0 Value 15000.0
2005-05-05T00:00:00, Cash 15000.0 Value 15000.0

run-out

btalib is not meant to be used in backtrader as a replacement for the built in indicators. bta-lib takes in a dataframe and returns a signal.

run-out

Best to create your highest indicator in the init.
See example here and reference here.

def __init__():
    self.highest_value = bt.ind.Highest(self.data.high, period=self.p.period)
def next():
    if self.dataclose[0] > self.highest_value[0]:
        etc...

Posts made by run-out