Understanding Daily Market Data and Candlesticks
td753764
Posts: 67
in Start Here
In this online post we introduce how to use the md.bar.daily market data daily bars and output some values.
`from cloudquant.interfaces import Strategy
class barsDemo(Strategy):
@classmethod
def is_symbol_qualified(cls, symbol, md, service, account):
return symbol=="GOOG"
# called at the beginning of each instance
def on_start(self, md, order, service, account):
daily_bars = md.bar.daily(start=-20,include_empty=False) # grab 20 bars of historical data
print self.symbol
print
print "Open 1 day ago",daily_bars.open[-1]
print "High 1 day ago",daily_bars.high[-1]
print "Low 1 day ago",daily_bars.low[-1]
print "Close 1 day ago",daily_bars.close[-1]
print "Volume 1 day ago",daily_bars.volume[-1]
print
print "Close 1 day ago",daily_bars.close[-1]
print "Close 2 days ago",daily_bars.close[-2]
print "Close 3 days ago",daily_bars.close[-3]
print "Close 4 days ago",daily_bars.close[-4]
print "Close 5 days ago",daily_bars.close[-5]
print
print "Close for all fetched bars",daily_bars.close[:]
print
print "Average Volume for all fetched bars",sum(daily_bars.volume)/len(daily_bars.volume)
print
print "Average Volume for most recent 10 bars",sum(daily_bars.volume[-10:])/len(daily_bars.volume[-10:])
print
print "Average Volume for 10 bars before that",sum(daily_bars.volume[-20:-10])/len(daily_bars.volume[-20:-10])
print
service.terminate()`
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