def init(context):
# 在context中保存全局变量
context.s1 = "同花顺.AGUSDO"
# 实时打印日志
logger.info("RunInfo: {}".format(context.run_info))
# 设置这个策略当中会用到的参数，在策略中可以随时调用，这个策略使用长短均线，我们在这里设定长线和短线的区间，在调试寻找最佳区间的时候只需要在这里进行数值改动
context.SHORTPERIOD = 20
context.LONGPERIOD = 120
def deposit_withdraw(self, account_type, amount):
"""出入金"""
# 入金 现金增加，份额增加，总权益增加，单位净值不变
# 出金 现金减少，份额减少，总权益减少，单位净值不变
if account_type not in self._accounts:
raise ValueError(_("invalid account type {}, choose in {}".format(account_type, list(self._accounts.keys()))))
unit_net_value = self.unit_net_value
self._accounts[account_type].deposit_withdraw(amount)
_units = self.total_value / unit_net_value
user_log.info(_("Cash add {}. units {} become to {}".format(amount, self._units ,_units)))
self._units = _units
def get_stock_data_from_mongo(self, code, cyc_type):
"""
:param str code: WindCode
:param cyc_type: Type from CycType
:return: numpy.ndarray
"""
logger.info('Load data from MongoDB: Code = {}, CycType = {}'.format(
code, cyc_type))
cursor = self.db[get_col_name(code)].find({
'cycType': cyc_type
}, {
'_id': False,
'date': True,
'open': True,
'close': True,
'high': True,
'low': True,
'volume': True,
'amount': True
}).sort("date", pymongo.ASCENDING)
pre_close = np.round(cursor.next()['close'], CONVERTER['close'].round)
data_num = cursor.count()
dtype = np.dtype([(f, FIELDS[f]) for f in FIELDS.keys()])
bars = np.zeros(shape=(data_num, ), dtype=dtype)
i = 0
for doc in cursor:
if cyc_type == CycType.CYC_DAY:
bars[i]['datetime'] = convert_date_to_int(doc['date'])
bars[i]['limit_up'] = np.round(
np.floor(pre_close * 11000) / 10000,
CONVERTER['limit_up'].round)
bars[i]['limit_down'] = np.round(
np.ceil(pre_close * 9000) / 10000,
CONVERTER['limit_down'].round)
elif cyc_type == CycType.CYC_MINUTE:
bars[i]['datetime'] = convert_dt_to_int(doc['date'])
else:
raise NotImplementedError
bars[i]['open'] = np.round(doc['open'], CONVERTER['open'].round)
bars[i]['close'] = np.round(doc['close'], CONVERTER['close'].round)
bars[i]['high'] = np.round(doc['high'], CONVERTER['high'].round)
bars[i]['low'] = np.round(doc['low'], CONVERTER['low'].round)
bars[i]['volume'] = doc['volume']
bars[i]['total_turnover'] = doc['amount']
pre_close = doc['close']
i += 1
logger.info(
'Load data from MongoDB finished: Code = {}, CycType = {}'.format(
code, cyc_type))
return bars
def _submit_by_trade(self, trade):
if self._is_expired(trade):
user_log.info('[实盘易] 委托已过期，忽略下单请求')
return
try:
price_type = 0 if trade.order.type == ORDER_TYPE.LIMIT else 4
order = trade.order
actual_order = self._shipane_client.execute(
self._mod_config.client,
action=order.side.name,
symbol=order.order_book_id,
type=order.type.name,
priceType=price_type,
price=order.price,
amount=trade.last_quantity)
return actual_order
except Exception as e:
user_log.error("[实盘易] 下单异常：" + str(e))
def handle_bar(context, bar_dict):
close = FinanceDataMining_DataSource.get_bar(context.s1, bar_dict.dt,
"1d")['Close']
# 因为策略需要用到均线，所以需要读取历史数据
prices = FinanceDataMining_DataSource.history_bars(context.s1, "1d",
"Close", bar_dict.dt)
if prices is None:
return
# 使用talib计算长短两根均线，均线以array的格式表达
short_avg = talib.SMA(prices, context.SHORTPERIOD)
long_avg = talib.SMA(prices, context.LONGPERIOD)
# 计算现在portfolio中股票的仓位
# 要有一个判断是否存在这个股票的
cur_position = 0
if context.s1 in context.portfolio.positions:
cur_position = context.portfolio.positions[context.s1].quantity
# 计算现在portfolio中的现金可以购买多少股票
shares = context.portfolio.cash / close
# 如果短均线从上往下跌破长均线，也就是在目前的bar短线平均值低于长线平均值，而上一个bar的短线平均值高于长线平均值
if short_avg[-1] - long_avg[-1] < 0 and short_avg[-2] - long_avg[
-2] > 0 and cur_position > 0:
# 进行清仓
logger.info("进行清仓")
order_target_value(context.s1, 0)
# 如果短均线从下往上突破长均线，为入场信号
if short_avg[-1] - long_avg[-1] > 0 and short_avg[-2] - long_avg[-2] < 0:
# 满仓入股
logger.info("10分之一仓入股")
import ipdb
ipdb.set_trace() # XXX BREAKPOINT
order_shares(context.s1, int(shares / 10), close)
def _submit_by_order(self, order):
"""
对于 响应 ORDER_CREATION_PASS 事件，已经经过了事前风控，所以比如资金不足，下单手数为0等无效订单已经排除，这里不需要额外处理。
:param order:
:return:
"""
if self._is_expired(order):
user_log.info('[实盘易] 委托已过期，忽略下单请求')
return
try:
price_type = 0 if order.type == ORDER_TYPE.LIMIT else 4
actual_order = self._shipane_client.execute(
self._mod_config.client,
action=order.side.name,
symbol=order.order_book_id,
type=order.type.name,
priceType=price_type,
price=order.price,
amount=order.quantity)
self._order_id_map[order.order_id] = actual_order['id']
return actual_order
except Exception as e:
user_log.error("[实盘易] 下单异常：" + str(e))
def after_trading(context):
logger.info("开盘前执行after_trading函数")
def before_trading(context):
logger.info("开盘前执行before_trading函数")