def read(cls, value_list):
repo = EXTRACT.instance().repo
ret = {}
for name, data in STOCK_TIMESERIES.read(repo, value_list):
logging.info((name, type(data), data.shape))
ret[name] = data
return ret
def load(file_list, value_list):
ret = {}
for name, data in STOCK_TIMESERIES.read(file_list, value_list):
if len(data) < 7 * FINANCE.YEAR:
logging.info(
"{} of length {} rejected for being less than {}".format(
name, len(data), 7 * FINANCE.YEAR))
continue
data = MONTECARLO.find(data['Adj Close'], period=FINANCE.YEAR)
#filter stocks that have less than a year
sharpe = data.get('sharpe', 0)
if sharpe == 0:
continue
#filter stocks that have negative returns
returns = data.get('returns', 0)
if returns <= 0:
logging.info(
"{} of returns {} rejected for being unprofitable".format(
name, returns))
continue
key_list = data.keys()
value_list = map(lambda x: data[x], key_list)
value_list = map(lambda x: round(x, 2), value_list)
msg = dict(zip(key_list, value_list))
logging.info((name, msg))
ret[name] = data
return ret
def read(cls, value_list) :
repo = VARIABLES().repo_stock
ret = {}
for name, data in STOCK_TIMESERIES.read(repo, value_list) :
logging.info((name,type(data),data.shape))
ret[name] = data
return ret
def load(file_list, stock_list) :
name_list = []
data_list = pd.DataFrame()
for name, stock in STOCK_TIMESERIES.read(file_list, stock_list) :
try :
data_list[name] = stock['Adj Close']
name_list.append(name)
except Exception as e : logging.error(e, exc_info=True)
finally : pass
return name_list, data_list
def load(value_list) :
file_list = PREP.singleton().file_list
ret = {}
for name, data in STOCK_TIMESERIES.read(file_list, value_list) :
flag, data = HELPER.is_stock_invalid(name, data)
if flag :
continue
ret[name] = data
msg = HELPER.round_values(**data)
logging.info((name, msg))
return ret
def process(file_list, value_list):
ret = {}
for name, data in STOCK_TIMESERIES.read(file_list, value_list):
data.sort_index(inplace=True)
data = data['Adj Close']
data = MONTECARLO.find(data,
risk_free_rate=0.02,
period=FINANCE.YEAR,
span=0)
# filter stocks that have less than a year
sharpe = data.get('sharpe', 0)
if sharpe == 0: continue
ret[name] = data
return ret
def load(file_list, value_list):
ret = {}
for name, data in STOCK_TIMESERIES.read(file_list, value_list):
data = MONTECARLO.find(data['Adj Close'], period=FINANCE.YEAR)
#filter stocks that have less than a year
sharpe = data.get('sharpe', 0)
if sharpe == 0: continue
#filter stocks that have negative returns
returns = data.get('returns', 0)
if returns <= 0: continue
key_list = data.keys()
value_list = map(lambda x: data[x], key_list)
value_list = map(lambda x: round(x, 2), value_list)
msg = dict(zip(key_list, value_list))
logging.info((name, msg))
ret[name] = data
return ret
def load(cls, value_list):
ret = {}
for name, data in STOCK_TIMESERIES.read(cls.stock_data, value_list):
ret[name] = data['Adj Close']
return ret
def load(cls, value_list):
file_list = cls.singleton().file_list
ret = {}
for name, data in STOCK_TIMESERIES.read(file_list, value_list):
ret[name] = data['Adj Close']
return ret
