def stocks_from_file():
companies = list()
with open(SELECTED_STOCKS, mode='r', encoding='UTF-8') as file:
for line in file:
trade_code = line.split(';')[1]
companies.append(db.stock_by_trade_code(trade_code))
return companies
def process_stock(a, count, num, sort_action, upload_files):
if a[4] == property.STOCKS:
if count is not None and count == num:
return
trade_code = a[7]
LOG.info('Process stock %s in thred %s' % (trade_code, threading.get_ident()))
try:
stock = db.stock_by_trade_code(trade_code)
except db.NotFoundStock as e:
stock = s.Stock()
stock_line(stock, line=a)
## TODO: need to add loading history of the stock
# LOG.info("Will updated finance document company " + str(a))
# load_files(stock.trade_code, stock.url)
# stock.files_name = get_list(property.TYPE2_PATH + "/" + stock.trade_code + property.ARCHIVES + '/')
stock.short_name = get_short_name(stock.trade_code)
stock.finame_em = finam_code(stock.trade_code)
# update_stock_from_file(stock.emitent_full_name, False)
stock.lot = get_lot(stock.trade_code)
sort_action.append(stock)
# if upload_files:
stock.save()
LOG.info("Save stock %s" % str(stock._id))
return num
def get_stock_from_portfolio(portfolios):
stocks = list()
sharpes = list()
for portfolio in portfolios:
portfolio_stock = list()
sharpes.append(portfolio.max_item.sharpe_ratio)
for stock in portfolio.max_item.stocks:
portfolio_stock.append(db.stock_by_trade_code(stock.trade_code))
stocks.append(portfolio_stock)
return stocks, sharpes
def process_stock_tivest(num, ta):
trade_code = ta.ticker
LOG.info('Process stock %s in thread %s' % (trade_code, threading.get_ident()))
try:
stock = db.stock_by_trade_code(trade_code)
except db.NotFoundStock as e:
stock = s.Stock()
stock.update_from_tinvest(ta)
stock.save()
LOG.info("Save stock %s" % str(stock._id))
return num
def load_history(trade_code):
LOG.info('[%s]' % trade_code)
stock = db.stock_by_trade_code(trade_code)
stock.month_history = list()
stock.week_history = list()
stock.day_history = list()
stock.hour_history = list()
for period in property.FINAM_PERIODS:
process_by_period(stock, period)
stock.save()
return trade_code
def update_stock_from_file(name, download, is_priviledged=False):
try:
LOG.info('Update from file')
if name == "" or name is None:
raise db.NotFoundStock
stock = db.stock_by_trade_code(name, is_priviledged)
action = read_to_list(property.DATA)
stock_file = None
for a in action:
stock_file = stock_from_line(name, a, download)
if stock_file is not None:
break
stock.update_file(stock_file)
stock.save()
except db.NotFoundStock:
LOG.error('Not found stock. Update all.')
load_stocks(upload_files=download)
def load_history_tinvest(trade_code):
LOG.info('[%s]' % trade_code)
try:
stock = db.stock_by_trade_code(trade_code)
except db.NotFoundStock as e:
return ""
stock.month_history = list()
stock.week_history = list()
stock.day_history = list()
stock.hour_history = list()
for period in property.TINVESE_PERIODS:
process_by_period_tinvest(stock, period)
time.sleep(0.5)
stock.save()
return trade_code
def predict(porftolio: pf.ItemPortfolio,
money: int,
from_date=(datetime.today() - timedelta(days=21)),
to_date=datetime.today() - timedelta(days=1)):
income = list()
correct_summ = list()
table = texttable.Texttable()
table.add_row([
'Code', 'SHORT', 'LOT', 'COUNT', 'COUNT_LOT', 'BASE_COUNT', 'PRICE',
'PART', 'FULL', 'INCOME'
])
for stock in porftolio.stocks:
try:
part = float(stock.value)
trade_code = str(stock.trade_code)
stock_orm = db.stock_by_trade_code(trade_code)
lot = int(stock_orm.lot)
from_price = load_price(stock_orm, from_date)
count, before_correct_count, full = correct_on_lot(
lot, part, money, from_price)
correct_full_pirce = count * from_price
correct_summ.append(correct_full_pirce)
to_price = load_price(stock_orm, to_date)
income.append(float(count * to_price))
row = [
stock_orm.trade_code, stock_orm.short_name, stock_orm.lot,
count, full, before_correct_count, from_price, part,
count * from_price, to_price
]
table.add_row(row)
except AttributeError:
LOG.error('For stock %s not found attribute' % stock.trade_code)
result = sum(income)
print(table.draw())
LOG.info('Portfolio base price %s (%s) from %s to %s with price %s' %
(money, sum(correct_summ), from_date, to_date, result))
return result, sum(correct_summ)
sharpes_sm = list()
sharpes_nsga = list()
sharpes_nsgaiii = list()
wgmean_sm = list()
wgmean_nsga = list()
wgmean_nsgaiii = list()
time_sm = list()
time_nsga = list()
time_nsgaiii = list()
trade_codes = list()
for stock in ordered.max_item.stocks:
trade_codes.append(stock.trade_code)
stocks = list()
for trade_code in trade_codes:
stocks.append(db.stock_by_trade_code(trade_code))
for num, iter in enumerate(iterations):
fig = plt.figure('compare-' + str(iter))
data = solver.get_stock_price(stocks)
returns = data.pct_change()
days = len(stocks[0].day_history)
LOG.info('History length %d' % int(days))
mean_daily_returns = returns.mean()
cov_matrix = returns.cov()
avr_gmean, gmeans = solver.average_gmean(returns)
LOG.info('Geometric mean: %.8f, Daily meand: %.8f, Gmeans: %.8f' %
(avr_gmean, np.average(mean_daily_returns), gmeans))
def all_stock(stocks):
companies = list()
for trade_code in stocks:
companies.append(db.stock_by_trade_code(trade_code))
return companies