Hi, I have spend a while looking in the forum but cannot find anything which clearly shows how to only buy a certain percentage and only sell the amount bought from that percentage.

My account balance is $10,000 when buying I want to buy 5% worth, which will be $500 and when selling I want to sell the amount of shares I bought for that $500. e.g if I Bought 100 shares for $500, I want to then sell that 100 shares when it's time to sell

Hi all, I am trying to backtest RSI and MACD indicator strategies together like below. However When running my test it never takes any trade and I have tried it with 700 symbols so far. I have also tried just with the MACD and RSI separately and same thing? any help will highly appreciated thank you

import backtrader
from datetime import datetime
import pandas as pd
from services.trader_service import TraderService
import numpy,pprint
from matplotlib import warnings
#Create Strategy
class MACD_RSI_TestStrategy(backtrader.Strategy):
   params = dict(
       fastperiod=12,  
       slowperiod=26, 
       signalperiod=9,
       rsi_period=14,
       rsi_lookback=5,
       rsi_under=20,
       rsi_over=80
   )

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

   def __init__(self):
       self.movav= backtrader.talib.MACD(self.datas[0].close, fastperiod=self.params.fastperiod, slowperiod=self.params.slowperiod, signalperiod=self.params.signalperiod)
       self.rsi = backtrader.talib.RSI(self.datas[0].close,period=self.params.rsi_period)
       self.order = None
       self.macdabove = False
       self.dataclose = self.datas[0].close

   def notify_order(self, order):
       if order.status in [order.Submitted, order.Accepted]:
           return 
       if order.status in [order.Completed]:
           if order.isbuy():
               self.log('BUY EXECUTED {}'.format(order.executed.price))
           elif order.issell():
               self.log('SELL EXECUTED {}'.format(order.executed.price))

           self.bar_executed =len(self)

       self.order = None

   def next(self):
      
       if self.macdabove == False and self.movav.lines.macd[0] > self.movav.lines.macdsignal[0] and self.rsi.lines[0] < self.params.rsi_under:
           self.macdabove = True
           self.log(f'BUY CREATE, {self.dataclose[0]}')
           self.order = self.buy()
       elif self.macdabove == True and self.position and self.rsi.lines[0] > self.params.rsi_over:
           self.macdabove = False
           self.log('SELL CREATE {}'.format(self.dataclose[0]))
           self.order = self.close()

if __name__ == '__main__':
   trading_pair = 'ETH/USDT'
   chartTime= ['1m', '3m', '5m', '15m', '30m', '1h', '2h', '4h', '6h', '8h', '12h']
   date_of_trade="2021-05-03T12:00:00"
   trader = TraderService()
   account_balance=1000
   for  interval in chartTime:
       colums = ['timestamp', 'open','high', 'low', 'close', 'volume']
       klines =  trader.exchange.fetch_ohlcv(trading_pair, timeframe=interval, limit=1500,since=trader.exchange.parse8601(date_of_trade))
       dataFrame = pd.DataFrame(klines, columns=colums)
       dataFrame["timestamp"] = [datetime.fromtimestamp(t/1000) for t in dataFrame["timestamp"]]

       data = backtrader.feeds.PandasDirectData(dataname=dataFrame, 
       datetime=dataFrame.columns.get_loc("timestamp")+1, 
           open=dataFrame.columns.get_loc('open')+1, high=dataFrame.columns.get_loc('high')+1, low=dataFrame.columns.get_loc('low')+1, 
           close=dataFrame.columns.get_loc('close')+1,volume=dataFrame.columns.get_loc('volume')+1,openinterest=-1)

       cerebro = backtrader.Cerebro()
       cerebro.broker.setcash(account_balance)
       cerebro.addsizer(backtrader.sizers.FixedSize, stake=10)
       cerebro.adddata(data)
       cerebro.addstrategy(MACD_RSI_TestStrategy)
       cerebro.broker.setcommission(commission=0.10)
       print(f'timeframe {interval}')
       print(f'Pair {trading_pair}')
       print('Starting Balance: %.2f' % cerebro.broker.getvalue())
       cerebro.run()

       print('Final Balance: %.2f' % cerebro.broker.getvalue())