def handle_bar(context, bar_dict):
'''
交易函数
'''
s1 = history_bars(context.stocks[0], 21, '1d', 'close')
s2 = history_bars(context.stocks[1], 21, '1d', 'close')
logger.debug('s1:' + str(s1))
logger.debug('s2:' + str(s2))
import pdb
pdb.set_trace()
s1delta = (s1[-1] - s1[0]) / s1[0]
s2delta = (s2[-1] - s2[0]) / s2[0]
log_str = '元和 ' + str(s1[0]) + '->' + str(s1[-1]) + ' 涨幅: ' + str(
round(s1delta, 3)) + ' 债券 ' + str(s2[0]) + '->' + str(
s2[-1]) + ' 涨幅: ' + str(round(s2delta, 3))
trading = None
if s1delta is not None and s2delta is not None:
if s1delta < 0 and s2delta < 0:
trading = 'cash'
elif s1delta > s2delta:
trading = context.stocks[0]
else:
trading = context.stocks[1]
if trading is None or trading == context.hold:
return
if context.hold is not None and context.hold != 'cash':
order_target_percent(context.hold, 0)
log_str += ' sell ' + context.hold
if trading != 'cash':
order_target_percent(trading, 1)
log_str += ' buy ' + trading
context.hold = trading
logger.info(log_str)
def handle_bar(context, bar_dict):
#count = context.buyStkCount
context.today = context.now.date()
context.today = str(context.today)
#context.prev_calendar_date = get_prev_trade_date(context,context.today)
for stk in context.portfolio.positions:
percentage_today = get_percentage(context, context.today, stk)
if percentage_today >= 0.099 or percentage_today <= -0.03:
if stk in context.universe:
context.universe.remove(stk)
if stk not in context.universe:
if (bar_dict[stk].close == bar_dict[stk].open == bar_dict[stk].high == bar_dict[stk].low) and \
percentage_today <= - 0.099:
logger.info('跌停无法卖出：' + stk)
else:
order_target_percent(stk, 0)
logger.info('sell:' + str(stk) + ' percent today: %.2f%%' %
(percentage_today * 100))
# 买入新股
for stk in context.universe:
if stk not in context.portfolio.positions:
percentage_today = get_percentage(context, context.today, stk)
if (bar_dict[stk].close == bar_dict[stk].open == bar_dict[stk].high == bar_dict[stk].low) and \
percentage_today >= 0.099:
logger.info('涨停无法买入：' + stk)
else:
if len(context.portfolio.positions) < context.buyStkCount:
percentage_today = get_percentage(context, context.today,
stk)
logger.info('buyin:' + str(stk) +
' percent today: %.2f%%' %
(percentage_today * 100))
order_shares(stk, 500)
def handle_bar(context, bar_dict):
# 根据前一交易日的股票池入市买卖
for order_book_id in context.portfolio.positions:
if order_book_id not in context.universe:
order_target_percent(order_book_id, 0)
for order_book_id in context.universe:
if order_book_id not in context.portfolio.positions:
order_target_percent(order_book_id, 1)
def handle_bar(context, bar_dict):
order_id = order_target_percent(context.s1, 0.02, style=LimitOrder(context.limitprice))
print("after: ", context.portfolio.cash)
order = get_order(order_id)
order_side = SIDE.BUY if order.quantity > 0 else SIDE.SELL
assert order.side == order_side
assert order.order_book_id == context.s1
assert order.price == context.limitprice
def handle_bar(context, bar_dict):
order_id = order_target_percent(context.s1, 0.02, style=LimitOrder(context.limitprice))
print("after: ", context.portfolio.cash)
order = get_order(order_id)
order_side = SIDE.BUY if order.quantity > 0 else SIDE.SELL
assert order.side == order_side
assert order.order_book_id == context.s1
assert order.price == context.limitprice
def position(context, bar_dict):
stocks = set(context.to_buy)
holdings = set(get_holdings(context))
to_buy = stocks - holdings
holdings = set(get_holdings(context))
to_sell = holdings - stocks
for stock in to_sell:
if bar_dict[stock].is_trading:
order_target_percent(stock, 0)
to_buy = get_trading_stocks(to_buy, context, bar_dict)
cash = context.portfolio.cash
average_value = 0
if len(to_buy) > 0:
average_value = 0.98 * cash / len(to_buy)
for stock in to_buy:
if bar_dict[stock].is_trading:
order_value(stock, average_value)
context.marketval = context.portfolio.market_value
def handle_bar(context, bar_dict):
"""
Description : 选择的证券的数据更新将会触发此段逻辑
Arg :
Returns :
Raises :
"""
# 需要买的股票列表
_lst_buy_stock = []
# 遍历所有的股票
for _stock in context.stocks:
# 首先取得前面多少日的收盘价
_data = history_bars(_stock, context.N + 1, '1d', "close")
# 判断是否是前面几天啦
if len(_data) < context.N + 1:
continue
# 取得最小值和最大值
_data_2 = _data[0:context.N]
_min = _data_2.min()
_max = _data_2.max()
_close_1 = _data_2[-1]
_close_2 = _data[-1]
# 先判断是否达到卖出的条件，
# 条件是，达到止损
if _close_2 < _close_1 * (100 + context.min_up):
# 然后判断是否有买入
if _stock in context.portfolio.positions.keys():
order_target_percent(_stock, 0)
# logger.info("清空股票：{}".format(_stock))
# 判断是否是有仓位
if _stock in context.portfolio.positions.keys():
# 如果是有降低，就清仓啦
if _close_2 < _close_1:
order_target_percent(_stock, 0)
# logger.info("清空股票：{}".format(_stock))
# 判断是否满足买的条件
if ((_close_1 > _min * (100 + context.M) / 100) and _close_1 == _max
and (_close_2 - _close_1) / _close_1 * 100 > context.min_up):
# logger.info("买入股票{}".format(_stock))
# order_target_percent(_stock, 0.1)
_lst_buy_stock.append(_stock)
logger.info("{}".format(len(_lst_buy_stock)))
def handle_bar(context, bar_dict):
#count = context.buyStkCount
context.today = context.now.date()
context.today = str(context.today)
#context.prev_calendar_date = get_prev_trade_date(context,context.today)
for stk in context.portfolio.positions:
percentage_today = get_percentage(context, context.today, stk)
# 去除涨幅大于100%并且跌幅大于5%的股票
for stk in context.portfolio.positions:
position_percent = (
context.portfolio.positions[stk].market_value -
context.portfolio.positions[stk].bought_value
) / context.portfolio.positions[stk].bought_value
if position_percent >= 1 or position_percent <= -0.05:
if stk in context.universe:
context.universe.remove(stk)
if stk not in context.universe:
if (bar_dict[stk].close == bar_dict[stk].open == bar_dict[stk].high == bar_dict[stk].low) and \
percentage_today <= - 0.099:
logger.info('跌停无法卖出：' + stk)
else:
order_target_percent(stk, 0)
logger.info('sell:' + str(stk) + ' percent today: %.2f%%' %
(percentage_today * 100))
# 买入新股
for stk in context.universe:
if stk not in context.portfolio.positions:
percentage_today = get_percentage(context, context.today, stk)
if (bar_dict[stk].close == bar_dict[stk].open == bar_dict[stk].high == bar_dict[stk].low) and \
percentage_today >= 0.099:
logger.info('涨停无法买入：' + stk)
else:
if len(context.portfolio.positions) < context.buyStkCount:
percentage_today = get_percentage(context, context.today,
stk)
logger.info('buyin:' + str(stk) +
' percent today: %.2f%%' %
(percentage_today * 100))
order_target_percent(stk, 0.2)
logger.info('portfolio.positions: ' + str(context.portfolio.positions))
def handle_bar(context, bar_dict):
# pass
#
#def handle_bar_weekly(context, bar_dict):
'''
交易函数
'''
hist_s1 = history_bars(context.stocks[0], context.window_size + 1, '1d',
'close')
hist_s2 = history_bars(context.stocks[1], context.window_size + 1, '1d',
'close')
curr_s1 = bar_dict[context.stocks[0]].close
curr_s2 = bar_dict[context.stocks[1]].close
logger.debug('s1:' + str(hist_s1))
logger.debug('s2:' + str(hist_s2))
s1delta = (curr_s1 - hist_s1[0]) / hist_s1[0]
s2delta = (curr_s2 - hist_s2[0]) / hist_s2[0]
log_str = '[' + context.now.isoformat() + ']'
log_str += '沪深300 ' + str(hist_s1[0]) + '->' + str(curr_s1)
log_str += ' 涨幅: ' + str(round(s1delta, 3))
log_str += ' 中证500 ' + str(hist_s2[0]) + '->' + str(curr_s2)
log_str += ' 涨幅: ' + str(round(s2delta, 3))
trading = None
if s1delta is not None and s2delta is not None:
if s1delta < 0 and s2delta < 0:
trading = 'cash'
elif s1delta > s2delta:
trading = context.stocks[0]
else:
trading = context.stocks[1]
if trading is None or trading == context.hold:
return
if context.hold != 'cash':
order_target_percent(context.hold, 0)
log_str += ' sell ' + context.hold
if trading != 'cash':
order_target_percent(trading, 0.99)
log_str += ' buy ' + trading
context.hold = trading
logger.info(log_str)
def handle_bar(context, bar_dict):
#count = context.buyStkCount
#context.today = context.now.date()
#context.today = str(context.today)
#context.prev_calendar_date = get_prev_trade_date(context,context.today)
#for stk in context.A_H_price_compare_result.A_code:
# df = context.A_H_price_compare_result[(context.A_H_price_compare_result.A_code == stk)]
# plot(stk, df.iloc[0,7])
df = context.A_H_price_compare_result[(context.A_H_price_compare_result.A_code == '000002.XSHE')]
plot('000002.XSHE', df.iloc[0,8])
# 买入新股
A_stk = '000002.XSHE'
H_stk = ''
if not context.holding_A:
order_target_percent('000002.XSHE', 1)
context.holding_A = True
if bar_dict[A_stk].is_trading:
if df.iloc[0,8] <= -10:
order_value('000002.XSHE', 20000)
if df.iloc[0,8] >= -5 and A_stk in context.portfolio.positions:
order_value('000002.XSHE', -20000)
def handle_bar(context, bar_dict):
"""
Description : 选择的证券的数据更新将会触发此段逻辑
Arg :
Returns :
Raises :
"""
# 需要买的股票列表
_lst_buy_stock = []
# 遍历所有的股票
for _stock in context.stocks:
# 首先取得前面多少日的收盘价
_data = history_bars(_stock, context.N, '1d', "close")
# 判断是否是前面几天啦
if len(_data) < context.N:
continue
# 取得最小值和最大值
_min = _data.min()
_max = _data.max()
_close = _data[-1]
# 先判断是否达到卖出的条件，
# 条件是，达到止损
if _close < _max * (100 - context.loss)/100:
# 然后判断是否有买入
if _stock in context.portfolio.positions.keys():
order_target_percent(_stock, 0)
logger.info("清空股票：{}".format(_stock))
# 判断是否满足买的条件
if ((_close > _min * (100 + context.M)/100)
and _close ==_max):
logger.info("买入股票{}".format(_stock))
_lst_buy_stock.append(_stock)
# 输出有多少个股票买入
# 因为有时候有很多股票需要买入，这里要判断最值得的。
# 我只买10个股票。
# 这里要判断要买那个股票
_lst_buy_stock_2 = [] # 这个是最终要选择的股票
if (len(_lst_buy_stock) > 10):
# 按照ATX来购买。趋势高的就买喽。
pass
else:
_lst_buy_stock_2 = _lst_buy_stock
# 如果现在持有的股票不在这个最终要选择的股票里边，就卖了吧
if _stock in context.portfolio.positions.keys():
if _stock not in _lst_buy_stock_2:
order_target_percent(_stock, 0)
logger.info("清空股票：{}".format(_stock))
# 然后购买最终持有的股票。
for _stock in _lst_buy_stock_2:
order_target_percent(_stock, 0.1)
logger.info("购买股票：{}".format(_stock))
logger.info("总共买入股票数量:{}".format(len(_lst_buy_stock)))
