def eval(self, symbol, trend_up, midpoint, support, resist):
try:
quote = float(yahoo.get_all(symbol)['price'])
odds = 0.0
gap = 0.0
if trend_up:
stop = max(midpoint, support)
if quote > stop:
odds = (resist - quote) / (quote - stop)
gain = (resist - quote) / quote * 100.0
gap = (quote - stop) /quote * 100.0
shares = min(500, int(self.RISK_CAPITAL / (quote - stop)))
else:
stop = min(midpoint, resist)
if quote < stop:
odds = (quote - support) / (stop - quote)
gain = (quote - support) / quote * 100.0
gap = (stop - quote) /quote * 100.0
shares = min(500, int(self.RISK_CAPITAL / (stop - quote)))
if odds > 3.0 and gap > 0.5:
print "%s: %.2f, %.2f, %.2f, %.2f, %.2f, %.2f" % (symbol, odds, gap, gain, shares, quote, stop)
except Exception, e:
print "Failed to evaluate %s: %s " % (symbol, e)
def get_sector_trends(self):
for sector in self.SECTOR_INDEX:
change = float(yahoo.get_all(sector)['change'])
print "Sector fund %s: %.2f" % (sector, change)
if change > 0.0:
self.sector_trends.append('UP')
else:
self.sector_trends.append('DOWN')
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 evaluate_bear(self, symbol, meta):
try:
data = yahoo.get_all(symbol)
price = data['price']
change = data['change'] * -1.0
moving_average_50 = data['50day_moving_avg']
short_ratio = data['short_ratio']
# volume is less important for price dropping
if (price is None or change is None or change/price < self.PRICE_CHANGE_THRESHOLD) \
and (moving_average_50 is None or price < moving_average_50) :
print "Accept %s for its price volume pattern" % (symbol)
meta[symbol]['eval'].append("Price Volume Pattern")
meta[symbol]['weight'] = meta[symbol]['weight'] + self.WEIGHT
else:
print "Reject %s for its price volume pattern: Change: %.2f Price: %.2f MA: %.2f Short Ratio: %.2f"\
% (symbol, change or 0.0, price or 0.0, moving_average_50 or 0.0, short_ratio or 0.0)
meta[symbol]['weight'] = -1000
except Exception, e:
print "Failed to evaluate price volume pattern for symbol %s: %s" % (symbol, e)
def evaluate_bull(self, symbol, meta):
try:
data = yahoo.get_all(symbol)
price = data['price']
change = data['change']
volume = data['volume']
avg_volume = data['avg_daily_volume']
moving_average_50 = data['50day_moving_avg']
short_ratio = data['short_ratio']
if (volume is None or avg_volume is None or volume > avg_volume * self.VOLUME_THRESHOLD) \
and (moving_average_50 is None or price > moving_average_50) \
and (price is None or change is None or change/price < self.PRICE_CHANGE_THRESHOLD):
print "Accept %s for its price volume pattern" % (symbol)
meta[symbol]['eval'].append("Price Volume Pattern")
meta[symbol]['weight'] = meta[symbol]['weight'] + self.WEIGHT
else:
print "Reject %s for its price volume pattern: Change: %.2f Volume: %.2f Avg Volume: %.2f Price: %.2f MA: %.2f Short Ratio: %.2f"\
% (symbol, change or 0.0, volume or 0.0, avg_volume or 0.0, price or 0.0, moving_average_50 or 0.0, short_ratio or 0.0)
meta[symbol]['weight'] = -1000
except Exception, e:
print "Failed to evaluate price volume pattern for symbol %s: %s" % (symbol, e)
def is_market_up(self):
return float(yahoo.get_all(self.MARKET)['change']) > 0
import sys, operator
from siteutil import Site
from BeautifulSoup import BeautifulSoup
from statlib import stats
from debug import say
from optutil import get_opts
from msn import MsnReport
import yahoo
if __name__ == '__main__':
opts = get_opts({"s" : "symbol"})
symbol = opts["symbol"].upper()
data = yahoo.get_all(symbol)
print "Symbol -- %s (%s)" % (symbol, data['market_cap'])
print "---- Market ----"
print "Quote: %s Change: %s" % (data['price'], data['change'])
print "52-w High: %.2f 52-w Low: %.2f" % (float(data['52_week_high']), float(data['52_week_low']))
print "50 SMA: %.2f 200 SMA: %.2f" % (float(data['50day_moving_avg']), float(data['200day_moving_avg']))
volume = float(data['volume'])
avg_volume = float(data['avg_daily_volume'])
print "Volumn: %.0f Change: %.2f%%" % (volume, (volume - avg_volume)/volume * 100.0)
print "Book Value: %s Price Book Ration: %s" % (data['book_value'], data['price_book_ratio'])
print "EPS: %s Price Earning Ration: %s Price Earning Growth Ration: %s" % \
(data['earnings_per_share'], data['price_earnings_ratio'], data['price_earnings_growth_ratio'])
print "Ebitda: %s Price Sales raio: %s" % (data['ebitda'], data['price_sales_ratio'])
print "Dividend Yield: %s Divident Per Share: %s" % (data['dividend_yield'], data['dividend_per_share'])
print "Short Ratio: %s" % (data['short_ratio'])
