def get_signal(signal, aum, balance, EndDate, close_dict):
signal['symbol'] = signal.index
symbol_lst = signal.symbol.tolist()
porfolio = Future()
main_contract_dict = porfolio.get_main_symbol(product=symbol_lst,
date=EndDate)
main_contract = pd.DataFrame(main_contract_dict).T[['main_contract']]
contract_lst = main_contract.main_contract.tolist()
ExchangeID_dict = porfolio.get_ExchangeID(contract_lst=contract_lst)
ExchangeInstID_dict = porfolio.get_ExchangeInstID(
contract_lst=contract_lst)
VolumeMultiple_dict = porfolio.get_VolumeMultiple(contract_lst)
main_contract['symbol'] = main_contract.index
signal_dict = {}
for symbol in symbol_lst:
main_contract = main_contract_dict[symbol]['main_contract']
trading_code = ExchangeID_dict[main_contract][
'ExchangeID'] + '.' + ExchangeInstID_dict[main_contract][
'ExchangeInstID']
signal_dict[symbol] = {
'symbol': symbol,
'trading_code': trading_code,
'weight': signal.loc[symbol]['weight'],
'last_price': close_dict[symbol],
'VolumeMultiple':
VolumeMultiple_dict[main_contract]['VolumeMultiple']
}
trading_info = pd.DataFrame(signal_dict).T
trading_info['position'] = aum * balance / len(symbol_lst) * trading_info[
'weight'] / trading_info['last_price'] / trading_info['VolumeMultiple']
# trading_info['position'] = trading_info['position'].apply(lambda x: int(np.around(x, 0)))
print(trading_info)
return trading_info
profit_df['date_time'] = profit_df.index
profit_df = profit_df.assign(
date_time=lambda df: df.date_time.apply(lambda x: str(
x)[:10]))
profit_df = profit_df.reset_index(drop=True)
hq = pd.read_csv('e:/data/future_index/' + code.upper() +
'_' + 'daily' + '_index.csv')[[
'date_time', 'close'
]].assign(
date_time=lambda df: df.date_time.
apply(lambda x: str(x)[:10]))
hq = hq[(hq['date_time'] > s_date)
& (hq['date_time'] < e_date)]
contract_lst = [code.upper()]
VolumeMultiple = porfolio.get_VolumeMultiple(contract_lst)[
code.upper()]['VolumeMultiple']
aum_ini = hq.close.tolist()[0] * VolumeMultiple * 2 * level
profit_df = hq.merge(profit_df,
on=['date_time'],
how='left').sort_values(['date_time'])
# profit_df = profit_df.fillna(0)
profit_df['chg'] = (
profit_df['profit'] - profit_df['close'].shift(1) *
profit_df['count'] * VolumeMultiple * fee
) * level / profit_df['close'].shift(1) / (VolumeMultiple *
2)
profit_df = profit_df.fillna(0)
if method == 'sum':
profit_df['net'] = 1 + profit_df['chg'].cumsum()
else:
profit_df['net'] = (1 + profit_df['chg']).cumprod()
# close_dict = {}
# for index_code in symbol_lst:
# code = code_dic[index_code]
# index_hq = stock_price(code, hq_last_date, hq_last_date, 'daily')
# close_dict[index_code] = index_hq.close.tolist()[-1]
# print(close_dict)
porfolio = Future()
main_contract_dict = porfolio.get_main_symbol(product=symbol_lst, date=hq_last_date)
main_contract = pd.DataFrame(main_contract_dict).T[['main_contract']]
print(main_contract)
PriceTick_dict = porfolio.get_PriceTick(symbol_lst)
contract_lst = main_contract.main_contract.tolist()
ExchangeID_dict = porfolio.get_ExchangeID(contract_lst=contract_lst)
ExchangeInstID_dict = porfolio.get_ExchangeInstID(contract_lst=contract_lst)
VolumeMultiple_dict = porfolio.get_VolumeMultiple(contract_lst)
LongMarginRatio_dict = porfolio.get_LongMarginRatio(contract_lst)
ShortMarginRatio_dict = porfolio.get_ShortMarginRatio(contract_lst)
main_contract['symbol'] = main_contract.index
print(main_contract)
signal_dict = {}
for symbol in symbol_lst:
main_contract = main_contract_dict[symbol]['main_contract']
price_tick = PriceTick_dict[symbol]['PriceTick']
trading_code = ExchangeID_dict[main_contract]['ExchangeID'] + '.' + ExchangeInstID_dict[main_contract][
'ExchangeInstID']
signal_dict[symbol] = {
'symbol': symbol, 'trading_code': trading_code, 'price_tick': price_tick,
'last_price': api.get_quote(trading_code).pre_close,
'VolumeMultiple': VolumeMultiple_dict[main_contract]['VolumeMultiple'],