def load_intraday_data(folder, file_name):
picked_cols = [' Open', ' High', ' Low', 'Close', ' Volume']
renamed_cols = ['Open', 'High', 'Low', 'Close', 'Volume']
data_type = {'Close': np.float64, 'High': np.float64, 'Low': np.float64, 'Open': np.float64, \
'ProductId': np.int32, 'Symbol': np.bytes_, 'Timestamp': np.bytes_, 'Volume': np.int64}
tmp = pandas.read_csv(folder + '/' + file_name, dtype=data_type)
dates = [
Helper.datetime_to_string(Helper.parse_datetime(date_str))
for date_str in list(tmp[' Timestamp'])
]
return pandas.DataFrame(np.array(tmp[picked_cols]),
index=dates,
columns=renamed_cols)
def data_to_date(self, data, date, stock_code=None):
_data = {}
for _data_type in ['daily', 'weekly']:
if _data_type not in data:
continue
if stock_code is not None:
mask = data[_data_type][
stock_code].index < Helper.date_to_string(date)
_data[_data_type] = _data.get(_data_type, {})
_data[_data_type] = data[_data_type][stock_code][mask]
else:
codes = data[_data_type].keys()
for code in codes:
mask = data[_data_type][
code].index < Helper.date_to_string(date)
_data[_data_type] = _data.get(_data_type, {})
_data[_data_type][code] = data[_data_type][code][mask]
return _data
def moving_average(date, data, type, x):
closes = []
if type == 'day':
closes = data.iloc[-x:]['Close']
elif type in ['week', 'month']:
start_day, end_day = None, date
last_date_func = Helper.last_friday if type == 'week' else Helper.previous_last_day_of_month
for _ in range(x):
end_day = last_date_func(end_day)
delta_days = 4 if type == 'week' else (end_day.day + 1)
start_day = end_day - timedelta(days=delta_days)
mask = data.index.to_series().between(
Helper.date_to_string(start_day),
Helper.date_to_string(end_day))
closes.append(
data[mask]['Close'][-1]) if len(data[mask]) > 0 else None
if len(closes) == x:
return np.mean(closes)
return None
def get_year_by_time_str(self, str):
return Helper.string_to_datetime(str)
def get_range_time(self, data):
start_time_str, end_time_str = super(IntradayTrader,
self).get_range_time(data)
return Helper.string_to_datetime(
start_time_str), Helper.string_to_datetime(end_time_str)
def trade(self, data):
self.stock_codes = data['daily'].keys()
start_time, end_time = self.get_range_time(data['daily'])
days_count = Helper.days_from_range_time(start_time, end_time)
for days in range(1, days_count):
print 'processing...', round(float(days) / days_count, 5)
date = start_time + timedelta(days=days)
self.new_date_init()
take_position_indicators = {}
for stock_code in self.stock_codes:
stock_data = self.data_to_date(data, date, stock_code)
if len(stock_data['daily']) > 0:
if stock_code in self.holding_stocks:
should_take_profit = self.take_profit_condition(
date, stock_code, stock_data)
should_cut_lost = self.cut_loss_condition(
date, stock_code, stock_data)
if should_take_profit or should_cut_lost:
open_price = self.holding_stocks[stock_code]
del self.holding_stocks[stock_code]
stock_data = data['daily'][stock_code].loc[
data['daily'][stock_code].index >= date]
if len(stock_data) > 0:
close_info = stock_data.iloc[0]
self.close_position(close_info.name,
stock_code, open_price,
close_info['Close'],
self.holding_stocks.keys())
else:
_, criterion = self.take_position_condition(
date, stock_code, stock_data)
take_position_indicators[stock_code] = criterion
else:
should_take_position, criterion = self.take_position_condition(
date, stock_code, stock_data)
if should_take_position:
take_position_indicators[stock_code] = criterion
holding_stocks = self.holding_stocks.keys()
selected_stocks = self.selecting_stocks(date,
take_position_indicators)
candidate_stocks = set(holding_stocks + selected_stocks)
if len(candidate_stocks):
for stock_code in candidate_stocks:
mask = data['daily'][stock_code].index >= date
stock_data = data['daily'][stock_code].loc[mask]
if len(stock_data) > 0:
if stock_code not in selected_stocks:
open_price = self.holding_stocks[stock_code]
close_info = stock_data.iloc[0]
del self.holding_stocks[stock_code]
self.close_position(close_info.name, stock_code,
open_price,
close_info['Close'],
self.holding_stocks.keys())
elif stock_code not in self.holding_stocks:
open_info = stock_data.iloc[0]
self.holding_stocks[stock_code] = open_info['Open']
self.history_orders.append([
open_info.name, stock_code, 'open',
open_info['Open'], '',
', '.join(self.holding_stocks.keys())
])
self.record_take_position(date, stock_code,
open_info['Open'])