def market_status():
market_symbol = 'SPY'
market_quotes = yahoo.get_historical_prices(market_symbol, start_date, end_date)[1:]
market_direction = _close(market_quotes[0]) > _close(market_quotes[-1])
cur_quotes = yahoo.get_all(market_symbol)
above_200ma = cur_quotes['price'] > cur_quotes['200day_moving_avg']
above_50ma = cur_quotes['price'] > cur_quotes['50day_moving_avg']
ma50_above_ma200 = cur_quotes['50day_moving_avg'] > cur_quotes['200day_moving_avg']
print "For period from %s to %s" % (start_date, end_date)
print "SP 500 is %s " % ("UP" if market_direction else "DOWN")
print "Current price level is %s its 50 MA" % ("above" if above_50ma else "below")
print "Current price level is %s its 200 MA" % ("above" if above_200ma else "below")
print "Current 50 MA is %s 200 MA" % ("above" if ma50_above_ma200 else "below")
print
def measure_success(self, candidates, start_date, end_date, position):
def register_profit(profit, signals):
for signal in signals:
total_profit = self.profits.setdefault(signal, 0.0)
self.profits[signal] = (total_profit + profit)
if profit > 0.0:
self.losers.setdefault(signal, 0)
count = self.winners.setdefault(signal, 0)
self.winners[signal] = (count + 1)
else:
self.winners.setdefault(signal, 0)
count = self.losers.setdefault(signal, 0)
self.losers[signal] = (count + 1)
def is_in_trade_range(close_price, open_price):
delta = abs((close_price - open_price) / open_price)
say("Delta is %.2f" % delta)
return delta <= TRADE_RANGE
def get_my_signals(signals, position):
if position == LONG:
my_signals = list(BULL_SIGNALS.intersection(signals))
if len(my_signals) > 0:
return my_signals
else:
my_signals = list(BEAR_SIGNALS.intersection(signals))
if len(my_signals) > 0:
return my_signals
return None
# historic quotes
def is_a_trade(historic_quotes, position):
start_day_close = _close(historic_quotes[0])
next_day_open = _open(historic_quotes[1])
if position == LONG:
say("LONG: %.2f %.2f" % (start_day_close, next_day_open))
return next_day_open >= start_day_close and is_in_trade_range(start_day_close, next_day_open)
else:
say("SHORT: %.2f %.2f" % (start_day_close, next_day_open))
return next_day_open <= start_day_close and is_in_trade_range(start_day_close, next_day_open)
def get_profit(historic_quotes, position):
acquired_price = _open(historic_quotes[1])
exit_price = acquired_price
previous_day_low = low(historic_quotes[0])
previous_day_high = high(historic_quotes[0])
for quote in historic_quotes[1:]:
if position == LONG:
today_low = low(quote)
if today_low < (previous_day_low - 0.01):
exit_price = previous_day_low
break
else:
previous_day_low = today_low
exit_price = _close(quote)
else:
today_high = high(quote)
if today_high > (previous_day_high + 0.01):
exit_price = previous_day_high
break
else:
previous_day_high = today_high
exit_price = _close(quote)
if position == LONG:
return (exit_price - acquired_price) / acquired_price
else:
return (acquired_price - exit_price) / acquired_price
for symbol, signals in candidates.items():
my_signals = get_my_signals(signals, position)
if my_signals is None:
say("Skip symbol %s for non-interested signals %s " % (symbol, signals))
continue
try:
historic_quotes = yahoo.get_historical_prices(symbol, start_date, end_date)[1:]
if historic_quotes:
if is_a_trade(historic_quotes, position):
profit = get_profit(historic_quotes, position)
say("Register profit for %s" % symbol)
register_profit(profit, my_signals)
else:
say("Skip symbol %s as it is out trading range " % (symbol))
else:
print "No historic data for %s" % symbol
except Exception, e:
print "Failed to evaluate %s due to %s" % (symbol, e)
def _yahoo(self, symbol, time):
today = datetime.datetime.today().date().strftime("%Y%m%d")
#today = "20120428"
start = time.strftime("%Y%m%d")
data = ya.get_historical_prices(symbol, start, today)
return np.sort(data, order='date')
