def run_analysis(self): self._read_my_holdings() self.mail_string = "" ; numSyms = len(self.smaArray) #for row in self.smaArray: for index in range(0,numSyms): symbol = self.smaArray[index][0] symbolData = symbol_analysis(symbol,self) retString = symbolData._analyze() if symbol in self.holdings: self.mail_string += '**' self.mail_string += retString self.mail_string += '\n' else: if (symbolData._reverseTrend | symbolData._crossing): self.mail_string += retString self.mail_string += '\n' #print retString print_colors.my_print (retString,'BOLD') if (self.mailit): mail_intf._send_my_mail(self.mail_string); return 0
def adj_row_price(self,priceRow): symbol = priceRow[0]; if (self._find_in_split_arr(symbol)): symbolData = symbol_analysis(symbol,self) return symbolData._adj_price() return priceRow
def adj_row_price(self, priceRow):
symbol = priceRow[0]
if (self._find_in_split_arr(symbol)):
symbolData = symbol_analysis(symbol, self)
return symbolData._adj_price()
return priceRow
def run_analysis(self): self._read_my_holdings() mail_string = "" ; for row in self.smaArray: symbol = row[0] symbolData = symbol_analysis(symbol,self) retString = symbolData._analyze() if symbol in self.holdings: mail_string += '**' mail_string += retString mail_string += '\n' else: if (symbolData._reverseTrend | symbolData._crossing): mail_string += retString mail_string += '\n' #print retString print_colors.my_print (retString,'BOLD') if (self.mailit): mail_intf._send_my_mail(mail_string); return 0
def run_analysis(self):
self._read_my_holdings()
self.mail_string = ""
numSyms = len(self.smaArray)
#for row in self.smaArray:
for index in range(0, numSyms):
symbol = self.smaArray[index][0]
symbolData = symbol_analysis(symbol, self)
retString = symbolData._analyze()
if symbol in self.holdings:
self.mail_string += '**'
self.mail_string += retString
self.mail_string += '\n'
else:
if (symbolData._reverseTrend | symbolData._crossing):
self.mail_string += retString
self.mail_string += '\n'
#print retString
print_colors.my_print(retString, 'BOLD')
if (self.mailit):
mail_intf._send_my_mail(self.mail_string)
return 0
def _analyze_symbol(self,symbol): symbolData = symbol_analysis(symbol,self) self.retString[symbol] = symbolData._analyze() self._symbolData[symbol] = symbolData if (symbolData._reverseTrend | symbolData._crossing | (symbolData._daily_chg > 10)): self.interestingResults[symbol] = 1 else: self.interestingResults[symbol] = 0
def _analyze_symbol(self,symbol):
symbolData = symbol_analysis(symbol,self)
self.retString[symbol] = symbolData._analyze()
self._symbolData[symbol] = symbolData
if (symbolData._reverseTrend | symbolData._crossing | (symbolData._daily_chg > 10)):
self.interestingResults[symbol] = 1
else:
self.interestingResults[symbol] = 0
def _analysis(self):
print "Run portfolio analysis %s" % (self._filename)
myPortfolio = read_portfolio_xml.read_portfolio(self._filename)
for ix1 in myPortfolio:
symbol = ix1['symbol']
symbolData = symbol_analysis(symbol, self._sma_ptr)
retString = symbolData._analyze()
print "%2s %s" % (ix1['pctg'], retString)
def _analysis(self): print "Run portfolio analysis %s" % (self._filename) myPortfolio = read_portfolio_xml.read_portfolio(self._filename) for ix1 in myPortfolio: symbol = ix1['symbol']; symbolData = symbol_analysis(symbol,self._sma_ptr) retString = symbolData._analyze() print "%2s %s" % (ix1['pctg'],retString)
def _rebalance(self):
# Rebalance Formula is
# set all falling trend to 5%
# For rising trend symbols,
# First set all to equal
# For reversal += 2
# For accelerating += 2
# For sharp += 2
# Now calculate Total and reduce all by same amount as
# necessary to get the required total
#
# Currently user defined weights are not implemented.
# Else, first apply user defined weights to get the starting
# values and then apply above algorithm
#
print "Run portfolio rebalance %s" % (self._filename)
myPortfolio = read_portfolio_xml.read_portfolio(self._filename)
myhash = {}
pctg = {}
for ix1 in myPortfolio:
symbol = ix1['symbol']
symbolData = symbol_analysis(symbol, self._sma_ptr)
myhash[symbol] = symbolData
totalNum = len(myPortfolio)
totalNumRem = totalNum
totalPctSoFar = 0
for symbol in myhash:
print symbol
symbolData = myhash[symbol]
retString = symbolData._analyze()
curPct = 0
if (symbolData._newTrend and symbolData._reverseTrend):
curPct += 2
if (symbolData._newTrend and symbolData._trendSpeed):
curPct += 2
if (symbolData._newTrend and symbolData._trendSlope):
curPct += 2
pctg[symbol] = curPct
totalPctSoFar += curPct
if (not symbolData._newTrend):
pctg[symbol] = 5
totalPctSoFar += 5
totalNumRem -= 1
DivideEq = int((100 - totalPctSoFar) / totalNumRem)
for symbol in myhash:
if (pctg[symbol] != 5):
pctg[symbol] += DivideEq
for ix1 in myPortfolio:
symbol = ix1['symbol']
symbolData = myhash[symbol]
print_colors.my_print(
"%2s %2s %s" %
(ix1['pctg'], pctg[symbol], symbolData._analyze()), 'RED')
def _rebalance(self):
# Rebalance Formula is
# set all falling trend to 5%
# For rising trend symbols,
# First set all to equal
# For reversal += 2
# For accelerating += 2
# For sharp += 2
# Now calculate Total and reduce all by same amount as
# necessary to get the required total
#
# Currently user defined weights are not implemented.
# Else, first apply user defined weights to get the starting
# values and then apply above algorithm
#
print "Run portfolio rebalance %s" % (self._filename)
myPortfolio = read_portfolio_xml.read_portfolio(self._filename)
myhash = {};
pctg = {};
for ix1 in myPortfolio:
symbol = ix1['symbol'];
symbolData = symbol_analysis(symbol,self._sma_ptr)
myhash[symbol] = symbolData
totalNum = len(myPortfolio)
totalNumRem = totalNum
totalPctSoFar = 0;
for symbol in myhash:
print symbol
symbolData = myhash[symbol]
retString = symbolData._analyze()
curPct = 0;
if (symbolData._newTrend and symbolData._reverseTrend):
curPct += 2;
if (symbolData._newTrend and symbolData._trendSpeed):
curPct += 2;
if (symbolData._newTrend and symbolData._trendSlope):
curPct += 2;
pctg[symbol] = curPct;
totalPctSoFar += curPct
if (not symbolData._newTrend):
pctg[symbol] = 5 ;
totalPctSoFar += 5;
totalNumRem -= 1;
DivideEq = int((100 - totalPctSoFar) / totalNumRem)
for symbol in myhash:
if (pctg[symbol] != 5):
pctg[symbol] += DivideEq
for ix1 in myPortfolio:
symbol = ix1['symbol'];
symbolData = myhash[symbol]
print_colors.my_print ( "%2s %2s %s" % (ix1['pctg'],pctg[symbol], symbolData._analyze()),'RED')
def _analysis(self):
print "Run portfolio analysis %s" % (self._filename)
myTriggers = read_trig_xml.read_triggers(self._filename)
returnVal = 0
retArray = []
for ix1 in myTriggers:
symbol = ix1["symbol"]
symbolData = symbol_analysis(symbol, self._sma_ptr)
(retType, retString) = symbolData._check_triggers(ix1)
if retType == "T":
returnVal = 1
# print "%s" % (retString)
retArray.append(retString)
return returnVal, retArray
def _analysis(self): print "Run portfolio analysis %s" % (self._filename) myTriggers = read_trig_xml.read_triggers(self._filename) returnVal = 0 retArray = []; for ix1 in myTriggers: symbol = ix1['symbol']; symbolData = symbol_analysis(symbol,self._sma_ptr) (retType,retString) = symbolData._check_triggers(ix1) if (retType == 'T'): returnVal = 1 #print "%s" % (retString) retArray.append(retString) return returnVal,retArray
def _price_check_symbol(self,symbol): symbolData = symbol_analysis(symbol,self) self.retString[symbol] = symbolData._find_adj()
def _price_check_symbol(self, symbol):
symbolData = symbol_analysis(symbol, self)
self.retString[symbol] = symbolData._find_adj()
