def ldt_timestamps(self):
"""
Return an array of datetime objects.
"""
ldt_index = self.index
dt_start = ldt_index[0]
dt_end = ldt_index[-1]
dt_timeofday = dt.timedelta(hours=16)
ldt_timestamps = du.getNYSEdays(dt_start, dt_end, dt_timeofday)
return ldt_timestamps
def ldt_timestamps(self):
"""
Return an array of datetime objects.
"""
ldt_index = self.total.index
dt_start = ldt_index[0]
dt_end = ldt_index[-1]
dt_timeofday = dt.timedelta(hours=16)
ldt_timestamps = du.getNYSEdays(dt_start, dt_end, dt_timeofday)
return ldt_timestamps
def setUp(self):
dt_start = dt.datetime(2008, 1, 1)
dt_end = dt.datetime(2009, 12, 31)
ldt_timestamps = du.getNYSEdays(dt_start, dt_end, dt.timedelta(hours=16))
dataobj = da.DataAccess('Yahoo', cachestalltime=0)
year = '2012'
stock_list = 'sp500' + year
ls_symbols = dataobj.get_symbols_from_list(stock_list)
ls_symbols.append('SPY')
ls_keys = ['open', 'high', 'low', 'close', 'volume', 'actual_close']
all_stocks = get_tickdata(ls_symbols=ls_symbols, ldt_timestamps=ldt_timestamps)
df_events = self.find_events(ls_symbols, all_stocks)
self.event_no = ep.eventprofiler(df_events, all_stocks, i_lookback=20, i_lookforward=20,
b_market_neutral=True, b_errorbars=True,
s_market_sym='SPY')
def setUp(self):
order_list = []
with open("orders.csv", 'rU') as csvfile:
order_reader = csv.reader(csvfile, delimiter=',', skipinitialspace=True)
for row in order_reader:
date = dt.datetime(int(row[0]),int(row[1]), int(row[2]), 16)
o = Order(action=row[4], date=date, tick=row[3], shares=row[5])
order_list.append(o)
# order_list needs to be sorted. Otherwise the algorithm won't work.
date_list = [x.date for x in order_list]
date_list.sort()
dt_timeofday = dt.timedelta(hours=16)
dt_start = date_list[0]
dt_end = date_list[-1]
tick_set = sets.Set([x.tick for x in order_list])
ls_symbols = ['$SPX']
while(tick_set):
ls_symbols.append(tick_set.pop())
ldt_timestamps = du.getNYSEdays(dt_start, dt_end, dt_timeofday)
cash = 1000000
all_stocks = get_tickdata(ls_symbols=ls_symbols, ldt_timestamps=ldt_timestamps)
self.pf = Portfolio(equities=all_stocks, cash=cash, dates=ldt_timestamps, order_list=order_list)
self.benchmark = self.pf.equities['$SPX']
self.pf.sim()
date = dateutil.parser.parse(row[0] + "-16")
if len(row) == 4:
o = Order(action=row[2], date=date, tick=row[1], shares=row[3])
else:
o = Order(action=row[2], date=date, tick=row[1], shares=row[3], price=row[4])
order_list.append(o)
# order_list needs to be sorted. Otherwise the algorithm won't work.
date_list = [x.date for x in order_list]
date_list.sort()
dt_start = date_list[0]
dt_end = date_list[-1]
tick_set = sets.Set([x.tick for x in order_list])
ls_symbols = ['$GSPC']
while(tick_set):
ls_symbols.append(tick_set.pop())
ldt_timestamps = du.getNYSEdays(dt_start, dt_end, dt_timeofday)
all_stocks = get_tickdata(ls_symbols=ls_symbols, ldt_timestamps=ldt_timestamps)
pf = Portfolio(equities=all_stocks, cash=cash, dates=ldt_timestamps, order_list=order_list)
pf.sim()
equity_col = ['buy', 'sell', 'close']
pf.csvwriter(csv_file=value_file, d=',', cash=False)
print "The final value of the portfolio using the sample file is -- ", pf.total[-1]
print "Details of the Performance of the portfolio :"
print "Data Range :", ldt_timestamps[0], "to", ldt_timestamps[-1]
print "Sharpe Ratio of Fund :", pf.sharpe_ratio()
print "Sortino Ratio of Fund :", pf.sortino()
print "Sharpe Ratio of $GSPC :", pf.equities['$GSPC'].sharpe_ratio()
print "Total Return of Fund :", pf.return_ratio()
print " Total Return of $GSPC :", pf.equities['$GSPC'].return_ratio()
print "Standard Deviation of Fund :", pf.std()
print " Standard Deviation of $GSPC :", pf.equities['$GSPC'].std()
o = Order(action=row[2],
date=date,
tick=row[1],
shares=row[3],
price=row[4])
order_list.append(o)
# order_list needs to be sorted. Otherwise the algorithm won't work.
date_list = [x.date for x in order_list]
date_list.sort()
dt_start = date_list[0]
dt_end = date_list[-1]
tick_set = sets.Set([x.tick for x in order_list])
ls_symbols = ['$GSPC']
while (tick_set):
ls_symbols.append(tick_set.pop())
ldt_timestamps = du.getNYSEdays(dt_start, dt_end, dt_timeofday)
all_stocks = get_tickdata(ls_symbols=ls_symbols,
ldt_timestamps=ldt_timestamps)
pf = Portfolio(equities=all_stocks,
cash=cash,
dates=ldt_timestamps,
order_list=order_list)
pf.sim()
equity_col = ['buy', 'sell', 'close']
pf.csvwriter(csv_file=value_file, d=',', cash=False)
print("The final value of the portfolio using the sample file is -- ",
pf.total[-1])
print("Details of the Performance of the portfolio :")
print("Data Range :", ldt_timestamps[0], "to", ldt_timestamps[-1])
print("Sharpe Ratio of Fund :", pf.sharpe_ratio())
print("Sortino Ratio of Fund :", pf.sortino())
