def marketsim(cash, orders_file, data_item):
# Read orders
orders = defaultdict(list)
symbols = set([])
for year, month, day, sym, action, num in csv.reader(
open(orders_file, "rU")):
orders[date(int(year), int(month), int(day))].append(
(sym, action, int(num)))
symbols.add(sym)
days = orders.keys()
days.sort()
day, end = days[0], days[-1]
# Reading the Data for the list of Symbols.
timestamps = getNYSEdays(datetime(day.year, day.month, day.day),
datetime(end.year, end.month, end.day + 1),
timedelta(hours=16))
dataobj = DataAccess('Yahoo')
close = dataobj.get_data(timestamps, symbols, data_item)
values = []
portfolio = Portfolio(cash)
for i, t in enumerate(timestamps):
for sym, action, num in orders[date(t.year, t.month, t.day)]:
if action == 'Sell': num *= -1
portfolio.update(sym, num, close[sym][i])
entry = (t.year, t.month, t.day, portfolio.value(close, i))
values.append(entry)
return values
def marketsim(cash, orders_file, data_item):
# Read orders
orders = defaultdict(list)
symbols = set([])
for year, month, day, sym, action, num in csv.reader(open(orders_file, "rU")):
orders[date(int(year), int(month), int(day))].append((sym, action, int(num)))
symbols.add(sym)
days = orders.keys()
days.sort()
day, end = days[0], days[-1]
# Reading the Data for the list of Symbols.
timestamps = getNYSEdays(datetime(day.year,day.month,day.day),
datetime(end.year,end.month,end.day+1),
timedelta(hours=16))
dataobj = DataAccess('Yahoo')
close = dataobj.get_data(timestamps, symbols, data_item)
values = []
portfolio = Portfolio(cash)
for i, t in enumerate(timestamps):
for sym, action, num in orders[date(t.year, t.month, t.day)]:
if action == 'Sell': num *= -1
portfolio.update(sym, num, close[sym][i])
entry = (t.year, t.month, t.day, portfolio.value(close, i))
values.append(entry)
return values
def findEvents(symbols_year, startday, endday, event, data_item="close"):
dataobj = DataAccess('Yahoo')
symbols = dataobj.get_symbols_from_list("sp500%d" % symbols_year)
symbols.append('SPY')
# Reading the Data for the list of Symbols.
timestamps = getNYSEdays(startday, endday, timedelta(hours=16))
# Reading the Data
print "# reading data"
close = dataobj.get_data(timestamps, symbols, data_item)
# Generating the Event Matrix
print "# finding events"
eventmat = copy.deepcopy(close)
for sym in symbols:
for time in timestamps:
eventmat[sym][time] = NAN
for symbol in symbols:
event(eventmat, symbol, close[symbol], timestamps)
return eventmat
def findEvents(symbols_year, startday, endday, event, data_item="close"):
dataobj = DataAccess('Yahoo')
symbols = dataobj.get_symbols_from_list("sp500%d" % symbols_year)
symbols.append('SPY')
# Reading the Data for the list of Symbols.
timestamps = getNYSEdays(startday, endday, timedelta(hours=16))
# Reading the Data
print "# reading data"
close = dataobj.get_data(timestamps, symbols, data_item)
# Generating the Event Matrix
print "# finding events"
eventmat = copy.deepcopy(close)
for sym in symbols:
for time in timestamps:
eventmat[sym][time] = NAN
for symbol in symbols:
event(eventmat, symbol, close[symbol], timestamps)
return eventmat
len(self.values))
def __str__(self):
return '\n'.join([
"\n[%s]" % (self.name if self.name is not None else "Equities"),
"Sharpe Ratio : %.6f" % self.sharpe_ratio(),
"Total Return : %.4f" % self.tot_return(),
"Average Daily Ret: %.6f" % self.average_return(),
"STDEV Daily Ret : %.6f" % self.stdev_return(),
])
if __name__ == '__main__':
# TODO: sharp ratio higher than 4?
PORTFOLIO = (('AAPL', 0.6), ('GLD', 0.2), ('WMT', 0.1), ('CVX', 0.1))
YEAR = 2011
timestamps = getNYSEdays(datetime(YEAR, 1, 1), datetime(YEAR, 12, 31),
timedelta(hours=16))
BENCHMARK = 'SPY'
symbols = [s for s, _ in PORTFOLIO] + [BENCHMARK]
close = DataAccess('Yahoo').get_data(timestamps, symbols, "close")
print Equities(
[sum([close[s][i] for s in symbols]) for i in range(len(timestamps))],
"Portfolio")
print Equities([close[BENCHMARK][i] for i in range(len(timestamps))],
"Benchmark")
