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TurtleTrading.py
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# -*- coding:utf-8 -*-
from CloudQuant import MiniSimulator
import numpy as np
import pandas as pd
username = 'Harvey_Sun'
password = 'P948894dgmcsy'
Strategy_Name = 'TurtleTrading_20_10_mean_season'
INIT_CAP = 100000000
START_DATE = '20130101'
END_DATE = '20161231'
fee_rate = 0.001
D1 = 20 # 短线系统，20日ATR，买入均线为D1日最高
Ds = 10 # 短线系统，卖出均线为Ds日最低
D2 = 55 # 长线系统
num = 50 # 买入多少只股票
unit_limit = 4.
def initial(sdk):
# 获取每季度开始的交易日=============================================================================================
trade_days = pd.Series(sdk.getDayList())
day_list = trade_days[np.logical_and(START_DATE <= trade_days, trade_days <= END_DATE)]
day_list.index = pd.to_datetime(day_list)
month_first = day_list.resample('M', label='left', closed='right').first()
season_start = list(month_first.ix[range(0, 48, 3)])
sdk.setGlobal('season_start', season_start)
sdk.prepareData(['LZ_GPA_QUOTE_THIGH', 'LZ_GPA_QUOTE_TLOW', 'LZ_GPA_QUOTE_TCLOSE',
'LZ_GPA_VAL_A_TCAP', 'LZ_GPA_SLCIND_STOP_FLAG', 'LZ_GPA_SLCIND_ST_FLAG'])
# 选取市值最小的50只非新非ST股票=====================================================================================
stock_list = sdk.getStockList()
close = pd.DataFrame(sdk.getFieldData('LZ_GPA_QUOTE_TCLOSE')[-63:], columns=stock_list)
not_new = pd.notnull(close).all(axis=0)
st = pd.Series(sdk.getFieldData('LZ_GPA_SLCIND_ST_FLAG')[-1], index=stock_list)
not_st = pd.isnull(st)
not_new_stocks = list(close.columns[not_new])
not_st_stocks = list(st.index[not_st])
not_new_not_st = list(set(not_new_stocks) & set(not_st_stocks))
cap = pd.Series(sdk.getFieldData('LZ_GPA_VAL_A_TCAP')[-1], index=stock_list)[not_new_not_st]
cap.sort_values(inplace=True)
stock_pool = list(cap[:num].index)
sdk.setGlobal('stock_pool', stock_pool)
# 计算ATR=========================================================================================================
high = pd.DataFrame(sdk.getFieldData('LZ_GPA_QUOTE_THIGH')[-(D1 + 2):-1], columns=stock_list)[stock_pool]
low = pd.DataFrame(sdk.getFieldData('LZ_GPA_QUOTE_TLOW')[-(D1 + 2):-1], columns=stock_list)[stock_pool]
close = pd.DataFrame(sdk.getFieldData('LZ_GPA_QUOTE_TCLOSE')[-(D1 + 2):-1], columns=stock_list)[stock_pool]
x1 = (high - low)[1:]
x2 = np.abs(high - close.shift(1))[1:]
x3 = np.abs(low - close.shift(1))[1:]
max23 = np.where(x2 > x3, x2, x3)
tr = np.where(x1 > max23, x1, max23)
atr = pd.Series(tr.mean(axis=0), index=stock_pool)
sdk.setGlobal('atr', atr)
# 设置其他全局变量=================================================================================================
stock_position = dict([i, 0] for i in stock_pool)
buy_prices = dict([i, 0] for i in stock_pool)
sdk.setGlobal('stock_position', stock_position)
sdk.setGlobal('buy_prices', buy_prices)
out_stocks = []
sdk.setGlobal('out_stocks', out_stocks)
def strategy(sdk):
today = sdk.getNowDate()
sdk.sdklog(today, '================================')
positions = sdk.getPositions()
position_dict = dict([i.code, i.optPosition] for i in positions)
stock_position = sdk.getGlobal('stock_position')
buy_prices = sdk.getGlobal('buy_prices')
season_start = sdk.getGlobal('season_start')
if today in season_start[1:]: # 第一个季度的股票池已经计算出来，这里从第二个季度开始运行
# 选取市值最小的50只非新非ST股票=================================================================================
stock_list = sdk.getStockList()
close = pd.DataFrame(sdk.getFieldData('LZ_GPA_QUOTE_TCLOSE')[-63:], columns=stock_list)
not_new = pd.notnull(close).all(axis=0)
st = pd.Series(sdk.getFieldData('LZ_GPA_SLCIND_ST_FLAG')[-1], index=stock_list)
not_st = pd.isnull(st)
not_new_stocks = list(close.columns[not_new])
not_st_stocks = list(st.index[not_st])
not_new_not_st = list(set(not_new_stocks) & set(not_st_stocks))
cap = pd.Series(sdk.getFieldData('LZ_GPA_VAL_A_TCAP')[-1], index=stock_list)[not_new_not_st]
cap.sort_values(inplace=True)
stock_pool = list(cap[:num].index)
sdk.setGlobal('stock_pool', stock_pool)
# 找到新加入的股票和被踢出的股票=================================================================================
out_stocks = list(set(position_dict.keys()) - set(stock_pool))
sdk.setGlobal('out_stocks', out_stocks)
atr_pre = sdk.getGlobal('atr')
stocks_to_cal_atr = list(set(stock_pool + out_stocks) -set(atr_pre.index))
high = pd.DataFrame(sdk.getFieldData('LZ_GPA_QUOTE_THIGH')[-(D1 + 2):-1], columns=stock_list)[stocks_to_cal_atr]
low = pd.DataFrame(sdk.getFieldData('LZ_GPA_QUOTE_TLOW')[-(D1 + 2):-1], columns=stock_list)[stocks_to_cal_atr]
close = pd.DataFrame(sdk.getFieldData('LZ_GPA_QUOTE_TCLOSE')[-(D1 + 2):-1], columns=stock_list)[stocks_to_cal_atr]
x1 = (high - low)[1:]
x2 = np.abs(high - close.shift(1))[1:]
x3 = np.abs(low - close.shift(1))[1:]
max23 = np.where(x2 > x3, x2, x3)
tr = np.where(x1 > max23, x1, max23)
atr_new = pd.Series(tr.mean(axis=0), index=stocks_to_cal_atr)
atr = pd.concat([atr_pre, atr_new], axis=0)[stock_pool + out_stocks]
sdk.setGlobal('atr', atr)
for stock in stocks_to_cal_atr:
stock_position[stock] = 0
buy_prices[stock] = 0
sdk.setGlobal('stock_position', stock_position)
sdk.setGlobal('buy_prices', buy_prices)
atr_pre = sdk.getGlobal('atr')
stock_list = sdk.getStockList()
not_stop_stocks = pd.Series(stock_list)[pd.isnull(sdk.getFieldData('LZ_GPA_SLCIND_STOP_FLAG')[-(D1 + 1):]).all(axis=0)]
# not_stop_stocks排除了前D1日有过停牌的股票，这样不影响atr的准确性
stock_pool = sdk.getGlobal('stock_pool') # 50只市值最小的股票
out_stocks = sdk.getGlobal('out_stocks') # 被踢出的股票
all_stocks = stock_pool + out_stocks # 所有需要盯着日线的股票
tradable_stocks = set(all_stocks) & set(not_stop_stocks) # 当日可以交易的股票
stock_pool_tradable = set(stock_pool) & set(not_stop_stocks) # 50只小市值股其中可交易的股票
out_stocks_tradable = set(out_stocks) & set(not_stop_stocks) & set(position_dict.keys()) # 小市值外的股票其中可清仓的股票
quotes = sdk.getQuotes(tradable_stocks)
high = pd.DataFrame(sdk.getFieldData('LZ_GPA_QUOTE_THIGH')[-(D1 + 1):], columns=stock_list)[all_stocks]
low = pd.DataFrame(sdk.getFieldData('LZ_GPA_QUOTE_TLOW')[-(D1 + 1):], columns=stock_list)[all_stocks]
close = pd.DataFrame(sdk.getFieldData('LZ_GPA_QUOTE_TCLOSE')[-(D1 + 1):], columns=stock_list)[all_stocks]
x1 = (high - low).iloc[-1]
x2 = np.abs(high - close.shift(1)).iloc[-1]
x3 = np.abs(low - close.shift(1)).iloc[-1]
max23 = np.where(x2 > x3, x2, x3)
tr = pd.Series(np.where(x1 > max23, x1, max23), index=all_stocks)
atr = ((D1 - 1) * atr_pre + tr) / D1
# 计算出来的atr可能为0，原因是有股票长期停牌。
# 也有可能为空，股票退市了没有high、low等数据，这会导致后面的相关计算也为空。为了避免空值对策略的影响，在交易前，先判断股票当日是否是quote
max_high = high[:-1].max()
min_low = (low[-(Ds + 1):-1].min() + max_high) / 2
net_value = sdk.getAccountInfo().previousAsset
unit = np.floor((net_value / num) * 0.01 / (atr * 100)) # 一单位，手
available_cash = sdk.getAccountInfo().availableCash
available_cash_one_stock = available_cash / (num - sum(stock_position.values()) / unit_limit)
orders = []
for stock in stock_pool_tradable:
if stock not in quotes.keys(): # 交易前判断当日该股的quote是否为空
continue
today_open = quotes[stock].open
buy_volume = unit[stock] * 100
money_needed = buy_volume * today_open * (1 + fee_rate)
if (stock_position[stock] == 0) & (close.iloc[-1][stock] > max_high[stock]) & (money_needed <= available_cash_one_stock):
order = [stock, today_open, buy_volume, 1]
orders.append(order)
stock_position[stock] = 1
buy_prices[stock] = today_open
elif (0 < stock_position[stock] < 4) & (close.iloc[-1][stock] > buy_prices[stock] + 0.5 * atr[stock]) & (money_needed <= available_cash_one_stock):
order = [stock, today_open, buy_volume, 1]
orders.append(order)
stock_position[stock] += 1
buy_prices[stock] = today_open
elif (stock_position[stock] > 0) & ((close.iloc[-1][stock] < min_low[stock]) | (close.iloc[-1][stock] < buy_prices[stock] - 2 * atr[stock])):
sell_volume = position_dict[stock]
order = [stock, today_open, sell_volume, -1]
orders.append(order)
stock_position[stock] = 0
else:
pass
sdk.makeOrders(orders)
sdk.sdklog('50只小市值股的下单')
sdk.sdklog(np.array(orders))
clear_orders = []
for stock in out_stocks_tradable:
today_open = quotes[stock].open
if (stock_position[stock] > 0) & ((close.iloc[-1][stock] < min_low[stock]) | (close.iloc[-1][stock] < buy_prices[stock] - 2 * atr[stock])):
sell_volume = position_dict[stock]
order = [stock, today_open, sell_volume, -1]
clear_orders.append(order)
stock_position[stock] = 0
buy_prices[stock] = 0
else:
pass
sdk.makeOrders(clear_orders)
sdk.sdklog('小市值之外的股票的下单')
sdk.sdklog(np.array(clear_orders))
sdk.setGlobal('atr', atr)
sdk.setGlobal('stock_position', stock_position)
sdk.setGlobal('buy_prices', buy_prices)
config = {
'username': username,
'password': password,
'initCapital': INIT_CAP,
'startDate': START_DATE,
'endDate': END_DATE,
'strategy': strategy,
'initial': initial,
'feeRate': fee_rate,
'strategyName': Strategy_Name,
'logfile': '%s.log' % Strategy_Name,
'rootpath': 'C:/cStrategy/',
'executeMode': 'D',
'feeLimit': 5,
'cycle': 1,
'dealByVolume': True,
'allowForTodayFactors': ['LZ_GPA_SLCIND_STOP_FLAG']
}
if __name__ == "__main__":
# 在线运行所需代码
import os
config['strategyID'] = os.path.splitext(os.path.split(__file__)[1])[0]
MiniSimulator(**config).run()