Introduction to Candlestick Bars in Market Data for Algo Programmers
In this video, we introduce you to Candlestick Bars, a store of Historic Market Data, how to access that data via Pythons Lists and how pointers work in lists.
The following code in Python will work with CloudQuant’s backtesting simulation environment to see the bar data.
# Python Code to retreive information about the symbol and the daily bars market 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
Output for symbol Google.
GOOG
Open 1 day ago 1042.68005371
High 1 day ago 1044.07995605
Low 1 day ago 1015.65002441
Close 1 day ago 1021.65997314
Volume 1 day ago 2459426
Close 1 day ago 1021.65997314
Close 2 days ago 1047.41003418
Close 3 days ago 1054.20996094
Close 4 days ago 1040.60998535
Close 5 days ago 1035.95996094
Close for all fetched bars [ 1025.5 1025.57995605 1032.47998047 1025.90002441 1033.32995605
1039.84997559 1031.26000977 1028.06994629 1025.75 1026.
1020.90997314 1032.5 1019.09002686 1018.38000488 1034.48999023
1035.95996094 1040.60998535 1054.20996094 1047.41003418 1021.65997314]
Average Volume for all fetched bars 1131964
Average Volume for most recent 10 bars 1194879
Average Volume for 10 bars before that 1069049
