def test_update_day_k_data_in_local(self):
manager = HistoryDataManager.HistoryDataManager()
local_start_date = datetime.datetime.strptime('2019-05-01',
constant.key_date_format)
local_end_date = datetime.datetime.strptime('2020-05-07',
constant.key_date_format)
rtn = manager._update_day_k_data_in_local('sh.600016',
local_start_date,
local_end_date)
print(rtn)
def plot_stock(title):
# 获取数据
start= '2015-01-01'
end = '2020-07-07'
historyManager = HistoryDataManager.HistoryDataManager()
dd = historyManager.get_day_k_history('sh.600015', start, end)
dd.index = pd.to_datetime(dd.date)
dd.close = dd.close.astype(float)
dd.close.plot(figsize=(14, 6), color='r')
plt.title(title + '价格走势\n' + start + ':' + end, size=15)
plt.annotate(f'期间累计涨幅:{(dd.close[-1]/dd.close[0]-1)*100:.2f}%', xy=(dd.index[-150], dd.close.mean()),
xytext=(dd.index[-500], dd.close.min()), bbox=dict(boxstyle='round,pad=0.5',
fc='yellow', alpha=0.5),
arrowprops=dict(facecolor='green', shrink=0.05), fontsize=12)
plt.savefig("mygraph.png")
def main(code, start, end='', startcash=10000, qts=500, com=0.001):
print('###code:' + code)
# 创建主控制器
cerebro = bt.Cerebro()
# 导入策略参数寻优
cerebro.optstrategy(MyStrategy)
# 获取数据
historyManager = HistoryDataManager.HistoryDataManager()
df = historyManager.get_day_k_history(code, '2016-01-01', '2020-07-07')
if not base.is_df_validate(df):
return startcash
df = df.sort_values(by=['date'], ascending=True)
df = df[df['volume'].astype(float) > 0.0]
if len(df) < 100:
return startcash
df.index = pd.to_datetime(df.date)
df = df[['open', 'high', 'low', 'close', 'volume']].astype(float)
data = bt.feeds.PandasData(dataname=df)
# 初始化cerebro回测系统设置
cerebro = bt.Cerebro()
# 加载数据
cerebro.adddata(data)
# 将交易策略加载到回测系统中
cerebro.addstrategy(MyStrategy)
# 设置初始资本为100,000
cerebro.broker.setcash(100000.0)
# 每次固定交易数量
cerebro.addsizer(bt.sizers.FixedSize, stake=1000)
# 手续费
cerebro.broker.setcommission(commission=0.001)
print(code + '初始资金: %.2f' % cerebro.broker.getvalue())
cerebro.addanalyzer(bt.analyzers.SharpeRatio, _name='SharpeRatio')
cerebro.addanalyzer(bt.analyzers.DrawDown, _name='DW')
results = cerebro.run()
return cerebro.broker.getvalue()
def main(code, start, end='', startcash=10000, qts=500, com=0.001):
# 创建主控制器
cerebro = bt.Cerebro()
# 导入策略参数寻优
cerebro.optstrategy(MyStrategy, maperiod=range(3, 31))
# 获取数据
historyManager = HistoryDataManager.HistoryDataManager()
df = historyManager.get_day_k_history('sh.600015', '2015-01-01', '2020-07-07')
df.index = pd.to_datetime(df.date)
df = df[['open', 'high', 'low', 'close', 'volume']].astype(float)
# 将数据加载至回测系统
data = bt.feeds.PandasData(dataname=df)
cerebro.adddata(data)
# broker设置资金、手续费
cerebro.broker.setcash(startcash)
cerebro.broker.setcommission(commission=com)
# 设置买入设置，策略，数量
cerebro.addsizer(bt.sizers.FixedSize, stake=qts)
print('期初总资金: %.2f' %
cerebro.broker.getvalue())
cerebro.run(maxcpus=1)
print('期末总资金: %.2f' % cerebro.broker.getvalue())
def __init__(self):
self.historyManager = HistoryDataManager.HistoryDataManager()
self.jqDataCrawler = cj.JQDataCrawler()
self.bonusDataManager = BonusDataManager()
def test_get_day_k_history(self):
manager = HistoryDataManager.HistoryDataManager()
rtn = manager.get_day_k_history('sh.600006', '2020-06-8', '2020-06-08')
print(rtn[['code', 'date', 'peTTM', 'psTTM']])
def __init__(self):
self.historyManager = HistoryDataManager.HistoryDataManager()