3. Stock prediction using sentiment analysis error
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Stock prediction using sentiment analysis error


  • I've been getting different errors and since I'm new to backtrader, its been difficult to resolve it.
    First I was using YahooFinance Data and it was giving me this error:
    AttributeError: 'NoneType' object has no attribute 'close'

    Then I changed it to Quandl and now it is giving me this error:

    Starting Portfolio Value: 100000.00
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-71-0bf63207fcf8> in <module>
    145     cerebro.broker.setcommission(commission=0.001)
    146     print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())
--> 147     cerebro.run()
    148     print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())
    149 

~/Library/Python/3.7/lib/python/site-packages/backtrader/cerebro.py in run(self, **kwargs)
   1125             # let's skip process "spawning"
   1126             for iterstrat in iterstrats:
-> 1127                 runstrat = self.runstrategies(iterstrat)
   1128                 self.runstrats.append(runstrat)
   1129                 if self._dooptimize:

~/Library/Python/3.7/lib/python/site-packages/backtrader/cerebro.py in runstrategies(self, iterstrat, predata)
   1291                     self._runonce_old(runstrats)
   1292                 else:
-> 1293                     self._runonce(runstrats)
   1294             else:
   1295                 if self.p.oldsync:

~/Library/Python/3.7/lib/python/site-packages/backtrader/cerebro.py in _runonce(self, runstrats)
   1650         '''
   1651         for strat in runstrats:
-> 1652             strat._once()
   1653             strat.reset()  # strat called next by next - reset lines
   1654 

~/Library/Python/3.7/lib/python/site-packages/backtrader/lineiterator.py in _once(self)
    295 
    296         for indicator in self._lineiterators[LineIterator.IndType]:
--> 297             indicator._once()
    298 
    299         for observer in self._lineiterators[LineIterator.ObsType]:

~/Library/Python/3.7/lib/python/site-packages/backtrader/lineiterator.py in _once(self)
    315         # indicators are each called with its min period
    316         self.preonce(0, self._minperiod - 1)
--> 317         self.oncestart(self._minperiod - 1, self._minperiod)
    318         self.once(self._minperiod, self.buflen())
    319 

~/Library/Python/3.7/lib/python/site-packages/backtrader/indicator.py in oncestart_via_nextstart(self, start, end)
    122 
    123             self.advance()
--> 124             self.nextstart()
    125 
    126     def once_via_next(self, start, end):

~/Library/Python/3.7/lib/python/site-packages/backtrader/lineiterator.py in nextstart(self)
    345 
    346         # Called once for 1st full calculation - defaults to regular next
--> 347         self.next()
    348 
    349     def next(self):

<ipython-input-71-0bf63207fcf8> in next(self)
     25         if date in date_sentiment:
     26             self.sentiment = date_sentiment[date]
---> 27         self.lines.sentiment[0] = self.sentiment
     28 
     29 

~/Library/Python/3.7/lib/python/site-packages/backtrader/linebuffer.py in __setitem__(self, ago, value)
    220             value (variable): value to be set
    221         '''
--> 222         self.array[self.idx + ago] = value
    223         for binding in self.bindings:
    224             binding[ago] = value

TypeError: must be real number, not LineBuffer

    Here's my code:

    from __future__ import (absolute_import, division, print_function,
                            unicode_literals)

%matplotlib inline
import warnings
warnings.filterwarnings('ignore')

import backtrader as bt
import backtrader.indicators as btind
import datetime
import os.path
import sys

class Sentiment(bt.Indicator):
    lines = ('sentiment',)
    plotinfo = dict(
        plotymargin=0.15,
        plothlines=[0],
        plotyticks=[1.0, 0, -1.0])
    
    def next(self):
        self.date = self.data.datetime
        date = bt.num2date(self.date[0]).date()
        prev_sentiment = self.sentiment
        if date in date_sentiment:
            self.sentiment = date_sentiment[date]
        self.lines.sentiment[0] = self.sentiment



class SentimentStrat(bt.Strategy):
    params = (
        ('period', 15),
        ('printlog', True),
    )

    def log(self, txt, dt=None, doprint=False):
        ''' Logging function for this strategy'''
        if self.params.printlog or doprint:
            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
        # Keep track of pending orders
        self.order = None
        self.buyprice = None
        self.buycomm = None
        self.sma = bt.indicators.SimpleMovingAverage(
            self.datas[0], period=self.params.period)
        self.date = self.data.datetime
        self.sentiment = None
        Sentiment(self.data)
        
    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 enough 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')
            
        # Write down: no pending order
        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))
    
    ### Main Strat ###
    def next(self):
        # log closing price of the series from the reference
        self.log('Close, %.2f' % self.dataclose[0])
        
        date = bt.num2date(self.date[0]).date()
        prev_sentiment = self.sentiment
        if date in date_sentiment:
            self.sentiment = date_sentiment[date]
        
        # Check if an order is pending. if yes, we cannot send a 2nd one
        if self.order:
            return
        print(self.sentiment)
        # If not in the market and previous sentiment not none
        if not self.position and prev_sentiment:
            # buy if current close more than sma AND sentiment increased by >= 0.5
            if self.dataclose[0] > self.sma[0] and self.sentiment - prev_sentiment >= 0.5:
                self.log('BUY CREATE, %.2f' % self.dataclose[0])
                self.order = self.buy()
                
        # Already in the market and previous sentiment not none
        elif prev_sentiment:
            # sell if current close less than sma AND sentiment decreased by >= 0.5
            if self.dataclose[0] < self.sma[0] and self.sentiment - prev_sentiment <= -0.5:
                self.log('SELL CREATE, %.2f' % self.dataclose[0])
                self.order = self.sell()

    def stop(self):
        self.log('(MA Period %2d) Ending Value %.2f' %
                 (self.params.period, self.broker.getvalue()), doprint=True)
        
    
if __name__ == '__main__':
    cerebro = bt.Cerebro()
    
    # Strategy
    cerebro.addstrategy(SentimentStrat)

    # Data Feed
    data = bt.feeds.Quandl(
        dataname = 'FB',
#        fromdate = earliest_date,
        fromdata = datetime.datetime(2019,10,4),
        todate = datetime.datetime(2019,10,22),
        reverse = False
    )
    
    cerebro.adddata(data)

    cerebro.broker.setcash(100000.0)
    cerebro.addsizer(bt.sizers.FixedSize, stake=10)
    cerebro.broker.setcommission(commission=0.001)
    print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())
    cerebro.run()
    print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())
    
    cerebro.plot()
    0
    B
     1 Reply
  • A

    @Shubham-Puri said in Stock prediction using sentiment analysis error:

        if date in date_sentiment:
        self.sentiment = date_sentiment[date]

    seems that date_sentiment is not defined in the Sentiment class. Also self.sentiment is not defined as well. At least in the code shown.

    1
  • B
    administrators

    @Shubham-Puri said in Stock prediction using sentiment analysis error:

            if date in date_sentiment:
            self.sentiment = date_sentiment[date]
        self.lines.sentiment[0] = self.sentiment

    The first time you go into the code the if date in date_sentiment evaluates to False. As such the declaration and assigment of self.sentiment = xxxxxxx is not executed and this member attribute does NOT exist.

    You then do

    self.lines.sentiment[0] = self.sentiment

    The best the indicator can do, given the undefined self.sentiment is to look in the lines declaration and see if sentiment exists there ... and yes. It is a line buffer which you try to assign to itself in a point in time.

    Define self.sentiment to have another name and you will quickly see the error popping up.

    0
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