163 lines
5.7 KiB
Python
163 lines
5.7 KiB
Python
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# -*- coding:utf-8 -*-
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from CloudQuant import MiniSimulator
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import numpy as np
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import pandas as pd
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username = 'Harvey_Sun'
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password = 'P948894dgmcsy'
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Strategy_Name = 'WQ_alpha#MF_05_100'
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INIT_CAP = 100000000
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START_DATE = '20130101'
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END_DATE = '20161231'
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Fee_Rate = 0.001
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program_path = 'C:/cStrategy/'
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buy_number = 100
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period = 5
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s_or_b = False # true表示选因子较小的股票，false表示选因子较大的股票
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def correlation(x, y):
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upside = ((x - x.mean()) * (y - y.mean())).sum(skipna=False)
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dnside = x.std() * y.std()
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result = upside / dnside
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return result
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def winsorize(x):
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sigma = x.std()
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m = x.mean()
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x[x > m + 3 * sigma] = x + 3 * sigma
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x[x < m - 3 * sigma] = x - 3 * sigma
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return x
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def standardize(x):
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return (x - x.mean()) / x.std()
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def initial(sdk):
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sdk.prepareData(['LZ_GPA_QUOTE_THIGH', 'LZ_GPA_QUOTE_TVOLUME',
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'LZ_GPA_QUOTE_TLOW', 'LZ_GPA_QUOTE_TCLOSE', 'LZ_GPA_QUOTE_TVALUE',
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'LZ_GPA_CMFTR_CUM_FACTOR', 'LZ_GPA_SLCIND_STOP_FLAG'])
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stock_pool = []
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sdk.setGlobal('stock_pool', stock_pool)
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step = period
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sdk.setGlobal('step', step)
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def init_per_day(sdk):
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step = sdk.getGlobal('step')
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if step == period:
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stock_list = sdk.getStockList()
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high = pd.DataFrame(sdk.getFieldData('LZ_GPA_QUOTE_THIGH')[-7:], columns=stock_list)
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low = pd.DataFrame(sdk.getFieldData('LZ_GPA_QUOTE_TLOW')[-7:], columns=stock_list)
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close = pd.DataFrame(sdk.getFieldData('LZ_GPA_QUOTE_TCLOSE')[-7:], columns=stock_list)
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volume = pd.DataFrame(sdk.getFieldData('LZ_GPA_QUOTE_TVOLUME')[-7:], columns=stock_list)
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value = pd.DataFrame(sdk.getFieldData('LZ_GPA_QUOTE_TVALUE')[-7:], columns=stock_list)
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adj_f = pd.DataFrame(sdk.getFieldData('LZ_GPA_CMFTR_CUM_FACTOR')[-7:], columns=stock_list)
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stop = pd.DataFrame(sdk.getFieldData('LZ_GPA_SLCIND_STOP_FLAG')[-8:], columns=stock_list)
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volume.replace(0, np.nan, inplace=True)
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adj_high = high * adj_f
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adj_low = low * adj_f
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adj_close = close * adj_f
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adj_volume = volume / adj_f
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# 计算昨天的#83号factor
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temp = (adj_high - adj_low) / adj_close.rolling(window=5).mean()
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volume_rank = adj_volume.rank(axis=1, pct=True)
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vwap = value / adj_volume
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upside = temp.diff(2).rank(axis=1, pct=True).iloc[-1] * volume_rank.iloc[-1]
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dnside = (temp / (vwap - adj_close)).iloc[-1]
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factor83 = upside / dnside
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factor83[adj_close.isnull().any()] = np.nan
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factor83.replace([np.inf, -np.inf], 0, inplace=True)
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# 计算昨日的#41号factor
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factor41 = (((adj_high * adj_low) ** 0.5 - (value / adj_volume) * 10) / adj_close).iloc[-1] # 计算昨天的alpha41
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factor41 = -1 * np.abs(factor41 - factor41.mean())
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# 处理因子并组合
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factor = standardize(winsorize(factor83)) + standardize(winsorize(factor41))
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# 选出排序靠前的股票
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factor[stop.notnull().any()] = np.nan # 剔除停牌的股票
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factor.sort_values(ascending=s_or_b, inplace=True)
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stock_pool = factor.index[:buy_number]
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# 选出当天应该调仓的股票
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position = sdk.getPositions()
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position_dict = dict([i.code, i.optPosition] for i in position)
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stock_to_buy = set(stock_pool) - set(position_dict.keys())
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stock_to_sell = set(position_dict.keys()) - set(stock_pool)
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sdk.setGlobal('position_dict', position_dict)
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sdk.setGlobal('stock_to_buy', stock_to_buy)
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sdk.setGlobal('stock_to_sell', stock_to_sell)
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else:
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pass
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def strategy(sdk):
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step = sdk.getGlobal('step')
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if step == period:
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step = 1
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today = sdk.getNowDate()
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sdk.sdklog(today, '====================')
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position_dict = sdk.getGlobal('position_dict')
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stock_to_buy = sdk.getGlobal('stock_to_buy')
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stock_to_sell = sdk.getGlobal('stock_to_sell')
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quotes = sdk.getQuotes(list(stock_to_buy | stock_to_sell))
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sell_orders = []
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for stock in stock_to_sell:
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if stock in quotes.keys():
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price = quotes[stock].open
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volume = position_dict[stock]
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order = [stock, price, volume, -1]
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sell_orders.append(order)
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if sell_orders:
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sdk.makeOrders(sell_orders)
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sdk.sdklog('===sell orders===')
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sdk.sdklog(np.array(sell_orders))
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available_cash = sdk.getAccountInfo().availableCash
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available_cash_one_stock = available_cash / len(stock_to_buy)
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buy_orders = []
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for stock in stock_to_buy:
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if stock in quotes.keys():
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price = quotes[stock].open
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volume = int(available_cash_one_stock / (price * 100)) * 100
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if volume > 0:
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order = [stock, price, volume, 1]
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buy_orders.append(order)
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if buy_orders:
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sdk.makeOrders(buy_orders)
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sdk.sdklog('===buy orders===')
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sdk.sdklog(np.array(buy_orders))
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else:
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step += 1
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sdk.setGlobal('step', step)
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config = {
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'username': username,
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'password': password,
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'initCapital': INIT_CAP,
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'startDate': START_DATE,
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'endDate': END_DATE,
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'strategy': strategy,
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'initial': initial,
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'preparePerDay': init_per_day,
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'feeRate': Fee_Rate,
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'strategyName': Strategy_Name,
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'logfile': '%s.log' % Strategy_Name,
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'rootpath': program_path,
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'executeMode': 'D',
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'feeLimit': 5,
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'cycle': 10,
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'dealByVolume': True,
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'allowForTodayFactors': ['LZ_GPA_SLCIND_STOP_FLAG']
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}
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if __name__ == "__main__":
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# 在线运行所需代码
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import os
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config['strategyID'] = os.path.splitext(os.path.split(__file__)[1])[0]
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MiniSimulator(**config).run()
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