def sample_811():
"""
8.1.1 买入因子的实现
:return:
"""
# buy_factors 60日向上突破，42日向上突破两个因子
buy_factors = [{
'xd': 60,
'class': AbuFactorBuyBreak
}, {
'xd': 42,
'class': AbuFactorBuyBreak
}]
benchmark = AbuBenchmark()
capital = AbuCapital(1000000, benchmark)
kl_pd_manager = AbuKLManager(benchmark, capital)
# 获取TSLA的交易数据
kl_pd = kl_pd_manager.get_pick_time_kl_pd('usTSLA')
abu_worker = AbuPickTimeWorker(capital, kl_pd, benchmark, buy_factors,
None)
abu_worker.fit()
orders_pd, action_pd, _ = ABuTradeProxy.trade_summary(abu_worker.orders,
kl_pd,
draw=True)
ABuTradeExecute.apply_action_to_capital(capital, action_pd, kl_pd_manager)
capital.capital_pd.capital_blance.plot()
plt.show()
def sample_811():
"""
8.1.1 买入因子的实现
:return:
"""
# buy_factors 60日向上突破，42日向上突破两个因子
buy_factors = [{'xd': 60, 'class': AbuFactorBuyBreak},
{'xd': 42, 'class': AbuFactorBuyBreak}]
benchmark = AbuBenchmark()
capital = AbuCapital(1000000, benchmark)
kl_pd_manager = AbuKLManager(benchmark, capital)
# 获取TSLA的交易数据
kl_pd = kl_pd_manager.get_pick_time_kl_pd('usTSLA')
abu_worker = AbuPickTimeWorker(capital, kl_pd, benchmark, buy_factors, None)
abu_worker.fit()
orders_pd, action_pd, _ = ABuTradeProxy.trade_summary(abu_worker.orders, kl_pd, draw=True)
ABuTradeExecute.apply_action_to_capital(capital, action_pd, kl_pd_manager)
capital.capital_pd.capital_blance.plot()
plt.show()
benchmark = AbuBenchmark()
# 现金和基准利润
capital = AbuCapital(1000000, benchmark)
# 多线程管理类
kl_pd_manager = AbuKLManager(benchmark, capital)
# 获取TSLA的股票信息
kl_pd = kl_pd_manager.get_pick_time_kl_pd('usTSLA')
# 准备开始工作
abu_worker = AbuPickTimeWorker(capital, kl_pd, benchmark, buy_factors,
None)
abu_worker.fit()
# 画出哪几个点可以买入，以及最终的收益情况
# orders_pd,action_pd,_=ABuTradeProxy.trade_summary(abu_worker.orders,kl_pd,draw=True)
orders_pd, action_pd, _ = ABuTradeProxy.trade_summary(abu_worker.orders,
kl_pd,
draw=False)
# 上面是从股价角度，下面从我们的资金来看
# ABuTradeExecute.apply_action_to_capital(capital, action_pd, kl_pd_manager)
# print(capital.capital_pd.head())
# capital.capital_pd.capital_blance.plot()
# plt.show()
# 上面只是实现了买入突破，下面我们用卖出突破来试试
# 2、这里是卖出突破
sell_factor1 = {'xd': 120, 'class': AbuFactorSellBreak}
sell_factors = [sell_factor1]
capital = AbuCapital(1000000, benchmark)
orders_pd, action_pd, _ = ABuPickTimeExecute.do_symbols_with_same_factors(
['usTSLA'], benchmark, buy_factors, sell_factors, capital, show=False)
capital = AbuCapital(1000000, benchmark)
kl_pd_manager = AbuKLManager(benchmark, capital)
#获取特斯拉择时阶段的走势数据
kl_pd = kl_pd_manager.get_pick_stock_kl_pd('usTSLA')
abu_worker = AbuPickTimeWorker(capital, kl_pd, buy_factors, buy_factors, None)
abu_worker.fit()
"""
下面使用ABuTradeProxy.trade_summary()函数将abu_worker中生成的所有orders对象
进行转换及可视化，由图开发--1所示，由于AbuPickTimeWorker没有设置sell_factors,
所以所有的交易单子都一只保留没有卖出
orders_pd:所有交易的相关数据
action_pd:所有交易的行为数据
"""
from abupy import ABuTradeProxy
order_pd, action_pd, _ = ABuTradeProxy.trade_summary(abu_worker.orders,
kl_pd,
draw=True,
show_info=True)
"""
最后将交易行为作用于资金上进行资金的走势模拟，如图所示为策略资金走势
"""
from abupy import ABuTradeExecute
#将action_pd作用在capital上，即开始涉及资金
ABuTradeExecute.apply_action_to_capital(capital, action_pd, kl_pd_manager)
#绘制资产曲线
capital.capital_pd.capital_blance.plot()
"""
卖出因子的实现
上面所有单子都没有成交的原因是没有卖出因子，下面首先实现类似买入策略的N日趋势突破策略AbuFactorSellBreak
当股价向下突破N日最低价格时卖出股票
"""
#需要继承自AbuFactorSellBase