def main(argv):
l_event_strategies = []
l_event_strategies.append(es.UnderThreshold('sp5002012', 'actual_close', 9))
#l_event_strategies.append(es.RelativeStrength('sp5002008', 'close', -5, 'SPY', 2))
#l_event_strategies.append(es.DailyChange('sp5002008', 'close', -10, '%'))
#l_event_strategies.append(es.RelativeStrengthWithVolume('sp5002008', 'close', -5, 'SPY', 2))
dt_start = dt.datetime(2008, 1, 1)
dt_end = dt.datetime(2009, 12, 31)
print 'AnalysisEngine : Events to Analyze:'
i = 0
for e in l_event_strategies:
i += 1
print 'AnalysisEngine : %00d - %s' % (i, e.getName())
print
print 'AnalysisEngine : Profiling Events'
ep.profile_events(dt_start, dt_end, l_event_strategies)
print
print 'AnalysisEngine : Simulating Orders'
ms.simulate_orders(50000, l_event_strategies)
print
print 'AnalysisEngine : Analyzing Results'
pa.analize_results('$SPX', l_event_strategies, dt_start, dt_end)
def main(argv):
# parameters
s_list_name = "sp5002012"
dt_start = dt.datetime(2008, 1, 1)
dt_end = dt.datetime(2009, 12, 31)
s_bench_sym = "SPY"
i_initial_cash = 100000
print "TechInv : Bollinger Event Study"
# read market data
dataobj = da.DataAccess("Yahoo")
ls_symbols = dataobj.get_symbols_from_list(s_list_name)
ls_symbols.append(s_bench_sym)
d_data = get_symbol_data(dataobj, ls_symbols, dt_start, dt_end)
# create the object that implements the strategy
event_strategy = es.BollingerRelWeakness(s_list_name, d_data, i_initial_cash, 20)
df_events, i_event_counter = event_strategy.find_events(ls_symbols, "close", 2.0, s_bench_sym, 1.3)
print "EventProfiler : For the %1.1f %s event with the components of %s, we find %d events. Date Range = (%s) to (%s)." % (
event_strategy.f_size,
event_strategy.s_feature,
event_strategy.s_list_name,
i_event_counter,
dt_start,
dt_end,
)
print "TechInv : Profiling Events"
ep.profile_event(event_strategy, ls_symbols, dt_start, dt_end, df_events, 100, 5)
print ""
ms.simulate_market(event_strategy)
event_strategy.s_bench_sym = "$SPX"
print ""
pa.analyze_event(event_strategy, dt_start, dt_end)
