def __init__(self):
super(CereborAGE, self).__init__()
dataframe_AUTD = FinanceDataSource.get_data(
FinanceDataSource.str_tonghuashun,
FinanceDataSource.tonghuashun_AUTD)
dataframe_AGTD = FinanceDataSource.get_data(
FinanceDataSource.str_tonghuashun,
FinanceDataSource.tonghuashun_AGTD)
dataframe_AUTD['openinterest'] = 0
dataframe_AGTD['openinterest'] = 0
data_AUTD = bt.feeds.PandasData(dataname=dataframe_AUTD)
data_AGTD = bt.feeds.PandasData(dataname=dataframe_AGTD)
self.adddata(data_AUTD, name="AUTD")
self.adddata(data_AGTD, name="AGTD")
# 如下是佣金
self.cerebro.broker.setcommission(
# automargin=0.15, # 保证金比例
commission=0.0008, # 手续费，记得是万分之8
leverage = 100/15, # 这个才是真正的杠杆，15%的保证金相当于100 / 15的杠杆
interest=0.073, # 递延费，记得是万分之8， * 365 = 0.073
# mult = 100, # 这个应该是一手是多少克吧, 但是却不成功。
# automargin = -1, # Use param mult * price if automargin < 0 , 不能实现一手是100克。
)
def init_data(self):
"""封装上数据"""
dataframe = FinanceDataSource.get_data(
FinanceDataSource.str_tonghuashun,
FinanceDataSource.tonghuashun_AGUSDO)
dataframe['openinterest'] = 0
data = bt.feeds.PandasData(dataname=dataframe)
self.adddata(data)
def __init__(self):
super(CerebroAGTD, self).__init__()
dataframe = FinanceDataSource.get_data(
FinanceDataSource.str_tonghuashun,
FinanceDataSource.tonghuashun_AGTD)
dataframe['openinterest'] = 0
data = bt.feeds.PandasData(dataname=dataframe)
self.adddata(data)
# 如下是佣金
self.cerebro.broker.setcommission(
# automargin=0.15, # 保证金比例
commission=0.0008, # 手续费，记得是万分之8
leverage = 100/15, # 这个才是真正的杠杆，15%的保证金相当于100 / 15的杠杆
interest=0.073 # 递延费，记得是万分之8， * 365 = 0.073
)
@Last Change: 2017-12-29 21:27:51
@Description : 看看AUTD的zip转向
"""
import sys
import os
sys.path.append(
os.path.join(os.path.dirname(os.path.realpath(__file__)),
"../../FinanceDataSource"))
import FinanceDataSource
from zip import get_zip
from zip import get_zip_ratio
from zip import get_zip_all
_data = FinanceDataSource.get_data(FinanceDataSource.str_tonghuashun,
FinanceDataSource.tonghuashun_AUTD)
_lst = get_zip_all(_data, FinanceDataSource.str_close, 2)
print("get_zip_all(_data, FinanceDataSource.str_close, 2)")
print(_lst)
print(sum(_lst))
print(sum(_lst) / len(_lst))
_lst = get_zip_all(_data, FinanceDataSource.str_close, 1)
print("get_zip_all(_data, FinanceDataSource.str_close, 1)")
print(_lst)
print(sum(_lst))
print(sum(_lst) / len(_lst))
"""
得到如下结果：
get_zip_all(_data, FinanceDataSource.str_close, 2)
"""@File Name: ADX_1.py @Author: [email protected] @Created Time:2018-01-13 15:21:48 @Last Change: 2018-01-13 15:21:48 @Description : """ import sys import os sys.path.append( os.path.join(os.path.dirname(os.path.realpath(__file__)), "../../FinanceDataSource")) sys.path.append("../../FinanceDataSource") import FinanceDataSource sys.path.append( os.path.join(os.path.dirname(os.path.realpath(__file__)), "../../CandlestickOhlc")) sys.path.append("../../CandlestickOhlc") from CandlestickOhlc import candlestickohlc import datetime import talib _book_id = "600469.XSHG" _data = FinanceDataSource.get_data(FinanceDataSource.str_cn_stock, _book_id) _data["ADX"] = talib.ADX(_data["High"].as_matrix(), _data["Low"].as_matrix(), _data['Close'].as_matrix()) candlestickohlc(_data, otherseries=["ADX"])
ax.xaxis_date()
ax.autoscale_view()
plt.setp(plt.gca().get_xticklabels(), rotation=45, horizontalalignment='right')
plt.show()
if __name__ == "__main__":
# We will look at stock prices over the past year, starting at January 1, 2016
start = datetime.datetime(2016, 1, 1)
end = datetime.date.today()
# Let's get Apple stock data; Apple's ticker symbol is AAPL
# First argument is the series we want, second is the source ("yahoo" for Yahoo! Finance), third is the start date, fourth is the end date
# apple = web.DataReader("AAPL", "yahoo", start, end)
import sys, os
sys.path.append(
os.path.join(
os.path.dirname(
os.path.realpath(__file__)),
"../FinanceDataSource"))
# sys.path.append("../../FinanceDataSource")
import FinanceDataSource
# yahoo_s_p_500 = init_data.get_data(init_data.str_pandas_datareader, init_data.yahoo_s_p_500)
# pandas_candlestick_ohlc(yahoo_s_p_500)
data = FinanceDataSource.get_tonghuashun_data(FinanceDataSource.tonghuashun_AGUSDO)
import talib
data["20d"] = talib.MA(data["Close"].as_matrix(), 20)
data["120d"] = talib.MA(data["Close"].as_matrix(), 120)
candlestickohlc(data , shareseries=["20d"], otherseries=["20d", "120d"])
def get_tonghuashun_AGUSDO_data():
"""取得同花顺上的白银数据"""
return FinanceDataSource.get_tonghuashun_data(
FinanceDataSource.tonghuashun_AGUSDO)