OLS_Slope_InterceptN

jirathh

Could you please give an example on how to use 'OLS_Slope_InterceptN' class?

Thank you.

jirathh

from datetime import datetime
import backtrader as bt

class TestStrategy(bt.Strategy):
params = (
('period', 14),
('sma_atr', 5),
('ols_length',15),
('macd1', 12),
('macd2', 26),
('macdsig', 9),
)

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

    # To keep track of pending orders and buy price/commission
    self.order = None
    self.buyprice = None
    self.buycomm = None

    # Add ATR Indicator
    self.atr = bt.indicators.ATR(
        self.datas[0], period=self.params.period)
    self.sma_atr = bt.indicators.SMA(
        self.atr, period=self.params.sma_atr)
    self.my_macd = bt.indicators.MACD(
        self.datas[0], period_me1=self.p.macd1, period_me2=self.p.macd2, period_signal=self.p.macdsig)

    self.my_ols1, self.my_ols2 = bt.indicators.OLS_Slope_InterceptN(self.datas[0].close, self.datas[0].close)

def notify_order(self, order):
    if order.status in [order.Submitted, order.Accepted]:
        # Buy/Sell order submitted/accepted to/by broker - Nothing to do
        return

    # Check if an order has been completed
    # Attention: broker could reject order if not enougth cash
    if order.status in [order.Completed]:
        if order.isbuy():
            self.log(
                'BUY EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f' %
                (order.executed.price,
                 order.executed.value,
                 order.executed.comm))

            self.buyprice = order.executed.price
            self.buycomm = order.executed.comm
        else:  # Sell
            self.log('SELL EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f' %
                     (order.executed.price,
                      order.executed.value,
                      order.executed.comm))

        self.bar_executed = len(self)

    elif order.status in [order.Canceled, order.Margin, order.Rejected]:
        self.log('Order Canceled/Margin/Rejected')

    self.order = None

def notify_trade(self, trade):
    if not trade.isclosed:
        return

    self.log('OPERATION PROFIT, GROSS %.2f, NET %.2f' %
             (trade.pnl, trade.pnlcomm))

def next(self):

    # Simply log the closing price of the series from the reference
    self.log('Close, %.2f' % self.dataclose[0])
    self.log('ATR, %.2f' % self.atr[0])
    self.log('SMA_ATR, %.2f' % self.sma_atr[0])
    self.log('MACD, %.2f' % self.my_macd.macd[0])
    self.log('SIGNAL, %.2f' % self.my_macd.signal[0])


    # Check if an order is pending ... if yes, we cannot send a 2nd one
    if self.order:
        return

    # Check if we are in the market
    if not self.position:

        # Not yet ... we MIGHT BUY if ...
        if (self.atr[0] > self.sma_atr[0]) and (self.my_macd.macd[0] > 0) and ((self.my_macd.signal[0] > 0) and (self.my_macd.macd[0] > self.my_macd.signal[0])):

            # BUY, BUY, BUY!!! (with all possible default parameters)
            self.log('BUY CREATE, %.2f' % self.dataclose[0])

            # Keep track of the created order to avoid a 2nd order
            self.order = self.order_target_percent(target=0.9)

    else:

        if self.atr[0] < self.sma_atr[0]:
            # SELL, SELL, SELL!!! (with all possible default parameters)
            self.log('SELL CREATE, %.2f' % self.dataclose[0])

            # Keep track of the created order to avoid a 2nd order
            self.order = self.order_target_percent(target=0)

if name == 'main':
cerebro = bt.Cerebro()
# Add a strategy
cerebro.addstrategy(TestStrategy, period=14, sma_atr=3, ols_length=15)

# Basic Setup of the trade
cerebro.broker.setcash(1000000.0)
# Set the commission - 0.1% ... divide by 100 to remove the %
cerebro.broker.setcommission(commission=0.001)
# Add a FixedSize sizer according to the stake
cerebro.addsizer(bt.sizers.FixedSize, stake=100)

#https://community.backtrader.com/topic/279/don-t-understand-buy-amount/6
cerebro.broker.set_coc(True)

data = bt.feeds.YahooFinanceData(dataname='IBM', fromdate=datetime(2017, 1, 1),
                                 todate=datetime(2017, 11, 27))
cerebro.adddata(data)

# Print out the starting conditions
print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())
cerebro.run()
# Print out the final result
print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())
cerebro.plot()

jirathh

C:\Users\jirath\Anaconda2\python.exe C:/Users/jirath/PycharmProjects/BackTrader.com/atr_trade.py
Starting Portfolio Value: 1000000.00
C:\Users\jirath\Anaconda2\lib\site-packages\statsmodels\compat\pandas.py:56: FutureWarning: The pandas.core.datetools module is deprecated and will be removed in a future version. Please use the pandas.tseries module instead.
from pandas.core import datetools
Traceback (most recent call last):
File "C:/Users/jirath/PycharmProjects/BackTrader.com/atr_trade.py", line 133, in <module>
cerebro.run()
File "C:\Users\jirath\Anaconda2\lib\site-packages\backtrader\cerebro.py", line 1142, in run
runstrat = self.runstrategies(iterstrat)
File "C:\Users\jirath\Anaconda2\lib\site-packages\backtrader\cerebro.py", line 1229, in runstrategies
strat = stratcls(*sargs, **skwargs)
File "C:\Users\jirath\Anaconda2\lib\site-packages\backtrader\metabase.py", line 88, in call
_obj, args, kwargs = cls.doinit(_obj, *args, **kwargs)
File "C:\Users\jirath\Anaconda2\lib\site-packages\backtrader\metabase.py", line 78, in doinit
_obj.init(*args, **kwargs)
File "C:/Users/jirath/PycharmProjects/BackTrader.com/atr_trade.py", line 36, in init
self.my_ols1, self.my_ols2, self.ols = bt.indicators.OLS_Slope_InterceptN(self.datas[0].close, self.datas[0].close)
ValueError: need more than 0 values to unpack

Process finished with exit code 1

Please any one suggest above error.

Paska Houso

@jirathh said in OLS_Slope_InterceptN:

self.my_ols1, self.my_ols2, self.ols = bt.indicators.OLS_Slope_InterceptN(self.datas[0].close, self.datas[0].close)
ValueError: need more than 0 values to unpack

Obviously there is only 1 return value there.

jirathh

I used this one:

self.my_ols = bt.indicators.OLS_Slope_InterceptN(self.datas[0], self.datas[0], period=30)

but still got this error

C:\Users\jirath\Anaconda2\python.exe C:/Users/jirath/PycharmProjects/BackTrader.com/atr_trade.py
Starting Portfolio Value: 1000000.00
C:\Users\jirath\Anaconda2\lib\site-packages\statsmodels\compat\pandas.py:56: FutureWarning: The pandas.core.datetools module is deprecated and will be removed in a future version. Please use the pandas.tseries module instead.
from pandas.core import datetools
Traceback (most recent call last):
File "C:/Users/jirath/PycharmProjects/BackTrader.com/atr_trade.py", line 133, in <module>
cerebro.run()
File "C:\Users\jirath\Anaconda2\lib\site-packages\backtrader\cerebro.py", line 1142, in run
runstrat = self.runstrategies(iterstrat)
File "C:\Users\jirath\Anaconda2\lib\site-packages\backtrader\cerebro.py", line 1305, in runstrategies
self._runonce(runstrats)
File "C:\Users\jirath\Anaconda2\lib\site-packages\backtrader\cerebro.py", line 1663, in _runonce
strat._once()
File "C:\Users\jirath\Anaconda2\lib\site-packages\backtrader\lineiterator.py", line 292, in _once
indicator._once()
File "C:\Users\jirath\Anaconda2\lib\site-packages\backtrader\lineiterator.py", line 313, in _once
self.once(self._minperiod, self.buflen())
File "C:\Users\jirath\Anaconda2\lib\site-packages\backtrader\indicator.py", line 136, in once_via_next
self.next()
File "C:\Users\jirath\Anaconda2\lib\site-packages\backtrader\indicators\ols.py", line 52, in next
slope, intercept = sm.OLS(p0, p1).fit().params
ValueError: need more than 1 value to unpack

Process finished with exit code 1

ab_trader

I didn't dig deeply, but looks like by default bt script requires 2 data feeds for this indicator. Maybe this is a problem. I would add 2nd data feed and call indicator as follows:

self.my_ols = bt.indicators.OLS_Slope_InterceptN(period=whatever_period_you_want)

Default period is 10.
Otherwise you can write your own implementation.

jirathh

thank you @ab_trader . I tried but still got this error.

self.my_ols = bt.indicators.OLS_Slope_InterceptN(period=30)

C:\Users\jirath\Anaconda2\python.exe C:/Users/jirath/PycharmProjects/BackTrader.com/atr_trade.py
Starting Portfolio Value: 1000000.00
C:\Users\jirath\Anaconda2\lib\site-packages\statsmodels\compat\pandas.py:56: FutureWarning: The pandas.core.datetools module is deprecated and will be removed in a future version. Please use the pandas.tseries module instead.
from pandas.core import datetools
Traceback (most recent call last):
File "C:/Users/jirath/PycharmProjects/BackTrader.com/atr_trade.py", line 151, in <module>
cerebro.run()
File "C:\Users\jirath\Anaconda2\lib\site-packages\backtrader\cerebro.py", line 1142, in run
runstrat = self.runstrategies(iterstrat)
File "C:\Users\jirath\Anaconda2\lib\site-packages\backtrader\cerebro.py", line 1305, in runstrategies
self._runonce(runstrats)
File "C:\Users\jirath\Anaconda2\lib\site-packages\backtrader\cerebro.py", line 1663, in _runonce
strat._once()
File "C:\Users\jirath\Anaconda2\lib\site-packages\backtrader\lineiterator.py", line 292, in _once
indicator._once()
File "C:\Users\jirath\Anaconda2\lib\site-packages\backtrader\lineiterator.py", line 312, in _once
self.oncestart(self._minperiod - 1, self._minperiod)
File "C:\Users\jirath\Anaconda2\lib\site-packages\backtrader\indicator.py", line 124, in oncestart_via_nextstart
self.nextstart()
File "C:\Users\jirath\Anaconda2\lib\site-packages\backtrader\lineiterator.py", line 342, in nextstart
self.next()
File "C:\Users\jirath\Anaconda2\lib\site-packages\backtrader\indicators\ols.py", line 50, in next
p1 = pd.Series(self.data1.get(size=self.p.period))
File "C:\Users\jirath\Anaconda2\lib\site-packages\backtrader\lineseries.py", line 461, in getattr
return getattr(self.lines, name)
AttributeError: 'Lines_LineSeries_LineIterator_DataAccessor_Indicat' object has no attribute 'data1'

Process finished with exit code 1

ab_trader

Did you add second data feed in cerebro?

Paska Houso

@jirathh said in OLS_Slope_InterceptN:

slope, intercept = sm.OLS(p0, p1).fit().params
ValueError: need more than 1 value to unpack

This is a clear indication that the version of sm.OLS you are using is not compatible with the code in that indicator. The statsmodels API changes overtime. See this:

https://stackoverflow.com/questions/20701484/why-do-i-get-only-one-parameter-from-a-statsmodels-ols-fit

jirathh

@Paska-Houso , thank you so much for your information.

In this case, I need to modify and run ols algorithm locally.

Could you please suggest how can I run backtrader locally?

I think we need to set something like interpreter or structure the project correctly. I use PyCharm on Windows. Please make suggestions. Thank you.

Paska Houso

I suggest you look at the many samples ... the blog is full of them. For example:

https://www.backtrader.com/blog/posts/2015-07-18-developing-an-indicator/developing-an-indicator.html

jirathh

Thank you so much, @Paska-Houso .
I managed to create a new indicator of OLS to be used in my strategy! :)

Here is the code:

class TORO_OLS_Slope_InterceptN(bt.Indicator):
packages = (
('pandas', 'pd'),
('sklearn.linear_model', 'lm'),
)
lines = ('slope', 'intercept',)
params = (
('period', 10),
)
def init(self):
self.addminperiod(self.params.period)

def next(self):
    p0 = pd.Series(self.data.close.get(size=self.p.period))
    p1 = np.arange(self.p.period).reshape(-1, 1)
    p1 = sm.add_constant(p1, prepend=True)
    slope, intercept = sm.OLS(p0, p1).fit().params
    self.lines.slope[0] = slope
    self.lines.intercept[0] = intercept