def formatMetrics(self):
''' output all calculated metrics '''
bestSymbol = None
bestMetric = None
worstSymbol = None
worstMetric = None
output = []
for symbols, metric in self.__calculated.items():
output.append("%s: %s" % (symbols, metric.formatResult()))
if bestSymbol == None or metric.result[BasicMetric.END_VALUE] > bestMetric.result[BasicMetric.END_VALUE]:
bestSymbol = symbols
bestMetric = metric
if worstSymbol == None or metric.result[BasicMetric.END_VALUE] < worstMetric.result[BasicMetric.END_VALUE]:
worstSymbol = symbols
worstMetric = metric
output.append("MEAN end value: %.1f, mean sharp ratio: %.2f" % (mean([m[BasicMetric.END_VALUE] for m in self.__calculated.values() if m[BasicMetric.END_VALUE] > 0]),
mean([m[BasicMetric.SRATIO] for m in self.__calculated.values() if m[BasicMetric.SRATIO] > -1])))
output.append("Best %s: %s" % (bestSymbol, bestMetric.formatResult()))
output.append("Worst %s: %s" % (worstSymbol, worstMetric.formatResult()))
return '\n'.join(output)
dam = DAMFactory.createDAM("sql", {'db': 'sqlite:////data/stock.sqlite'})
dateTicks = dam.readBatchTupleQuotes(symbols, 20031210, 20131210)
symbolTicks = {}
for timeStamp in sorted(dateTicks.iterkeys()):
for symbol, tick in dateTicks[timeStamp].iteritems():
if symbol not in symbolTicks:
symbolTicks[symbol] = []
symbolTicks[symbol].append(tick)
bads = []
goods = {} # symbol as key, std as value
for symbol, ticks in symbolTicks.iteritems():
avgClose = mean([tick.close for tick in ticks])
std = 100 * stddev([tick.close for tick in ticks]) / avgClose
print "std for %s is %f" % (symbol, std)
ticks = ticks[-30:]
avgVolumnDollar = mean([tick.volume * tick.close for tick in ticks])
if avgVolumnDollar > 1000000 and avgClose > 6 and avgClose < 100:
goods[symbol] = std
else:
bads.append(symbol)
print "=========bad %s==============" % len(bads)
print bads
sortedList = sorted(goods.iteritems(), key=lambda x: x[1])
dam = DAMFactory.createDAM("sql", {'db': 'sqlite:////data/stock.sqlite'})
dateTicks = dam.readBatchTupleQuotes(symbols, 20031210, 20131210)
symbolTicks = {}
for timeStamp in sorted(dateTicks.iterkeys()):
for symbol, tick in dateTicks[timeStamp].iteritems():
if symbol not in symbolTicks:
symbolTicks[symbol] = []
symbolTicks[symbol].append(tick)
bads = []
goods = {} # symbol as key, std as value
for symbol, ticks in symbolTicks.iteritems():
avgClose = mean([tick.close for tick in ticks])
std = 100 * stddev([tick.close for tick in ticks])/avgClose
print "std for %s is %f" % (symbol, std)
ticks = ticks[-30:]
avgVolumnDollar = mean([tick.volume * tick.close for tick in ticks])
if avgVolumnDollar > 1000000 and avgClose > 6 and avgClose < 100:
goods[symbol] = std
else:
bads.append(symbol)
print "=========bad %s==============" % len(bads)
print bads
sortedList = sorted(goods.iteritems(), key=lambda x: x[1])
