def run(self, *args, **kwargs):
while True:
df = LoadNet().get_QVIX()
self.update_qvix.emit(df)
df_north = LoadNet().get_north()
self.update_north.emit(df_north)
df_vol, cha = Volume().update()
data, last = LoadNet().get_50_163()
ser = (data['current'] - last) / last
self.update_vol.emit(df_vol, ser)
if not self.data_model.df_op.empty:
df_month = self.data_model.iv_month_50300()
self.update_month.emit(df_month)
df_iv50, df_iv300 = self.data_model.get_iv()
self.update_iv.emit(df_iv50, df_iv300)
hp = HoldPositions()
greek = hp.update(self.data_model.df_op)
self.update_greek.emit(greek)
time.sleep(3)
def __init__(self):
self.load = LoadNet()
self.months = self.load.check_month()
self.day_later = self.load.get_op_expire_day('2019')
#print(self.day_later)
self.etf_price = 2.95
self.data_price = pd.DataFrame()
self.data_iv = pd.DataFrame()
self.histroy_high = 300
def __init__(self):
self.ln = LoadNet()
self.stock_info_50 = self.ln.get_sz50_price()
self.stock_info_300 = self.ln.get_sz300_price()
self.stock_price_50etf = 0.0
self.stock_price_300etf = 0.0
self.df_op = pd.DataFrame()
self.df_codes = self.init_allcodes()
t = threading.Thread(target=self.loop)
t.start()
def update(self):
#ax.cla()
a = LoadNet().get_sz50_price()
#a.cumsum(axis=0)
str_time = a[31]
str_time_end = "15:00:00"
str_volume = a[9]
tomorrow = float(a[2])
current = float(a[3])
#print(str_time,str_volume)
time = pd.datetime.strptime(str_time, '%H:%M:%S')
min_1 = pd.Timedelta(minutes=1)
time_end = time + min_1
#mean_data['current'][mean_data.index>time.time()] = int(str_volume)/10000
self.mean_data.loc[self.mean_data.index > time.time(),
'current'] = int(str_volume) / 10000
self.diff_data = self.mean_data.copy()
self.diff_data['current'] = pd.to_numeric(self.diff_data['current'])
self.diff_data['current'] = self.diff_data['current'].diff(1)
self.diff_data.iloc[0, 1] = float(self.mean_data.iloc[0, 1])
self.mean_data['mean'] = self.mean_data['current'] / self.mean_data[
'VOL-TDX.VOLUME']
self.cha = (current - tomorrow) / tomorrow * 100
self.res = self.mean_data['mean'][
self.mean_data.index <= time_end.time()]
return self.mean_data['mean'][
self.mean_data.index <= time_end.time()], self.cha
def __init__(self):
self.loadsina = LoadNet()
self.month = self.loadsina.check_month()
self.interestRate = 3.00
self.stockPrice = float(self.loadsina.get_50etf_price()[3])
self.stockPrice_future = self.stockPrice
self.iv_future = 0
self.dayLater = 0
super(Windows, self).__init__()
self.setGeometry(20, 50, 1800, 1200)
self.currentItem = None
self.create_ui()
self.fill_dayWidget()
def draw_qvix(self):
self.ax_QVIX.cla()
#print (LoadNet().get_QVIX())
df =LoadNet().get_QVIX()
# iv = df['QVIX'].astype(float)
# time =df.index.values
# print(iv,time)
# self.ax_QVIX.plot(time,iv)
pd.to_datetime(df['Time'])
df.index = df['Time']
#print(df.columns)
df = df.drop(['Time','Pre','max','min'],axis=1)
df.plot(ax=self.ax_QVIX)
import pandas as pd import numpy as np import matplotlib.pyplot as plt from get_day_histroy import history import matplotlib.font_manager as font_manager from load_sina import LoadNet his = history() mean_data = his.get_dayMean() ln = LoadNet() mean_data['current'] = 0 mean_data['mean'] = 0 POINTS = 100 sin_list = [0] * POINTS indx = 0 zx_index = [] fig, ax = plt.subplots() # ax.set_ylim([-2, 2]) # ax.set_xlim([0, POINTS]) # ax.set_autoscale_on(False) #ax.set_xticks(range(0, 100, 10)) # ax.set_yticks(range(-2, 3, 1)) #ax.grid(True) #line_sin, = ax.plot(mean_data, label='volume', color='cornflowerblue') ax.legend(loc='upper center', ncol=4, prop=font_manager.FontProperties(size=8)) print(mean_data) diff_data = pd.DataFrame()
class Windows(QMainWindow):
def __init__(self):
self.loadsina = LoadNet()
self.month = self.loadsina.check_month()
self.interestRate = 3.00
self.stockPrice = float(self.loadsina.get_50etf_price()[3])
self.stockPrice_future = self.stockPrice
self.iv_future = 0
self.dayLater = 0
super(Windows, self).__init__()
self.setGeometry(20, 50, 1800, 1200)
self.currentItem = None
self.create_ui()
self.fill_dayWidget()
#self.fill_wight_out()
def create_ui(self):
wight = QWidget(self)
wight.setGeometry(10, 10, 1400, 300)
self.listWidget = QtWidgets.QListWidget(self)
self.listWidget.setGeometry(QtCore.QRect(20, 40, 1000, 1000))
self.listWidget.setObjectName("listWidget")
self.listWidget.itemClicked.connect(self.check_in_item)
btn_jian = QPushButton(self)
btn_jian.move(1020, 360)
btn_jian.resize(15, 30)
btn_jian.setText('>')
btn_jian.clicked.connect(self.del_item)
wight_call = QWidget(self)
wight_call.setGeometry(1035, 70, 100, 670)
self.layout_call = QVBoxLayout()
self.layout_call.setContentsMargins(0, 0, 0, 0)
wight_call.setLayout(self.layout_call)
wight_mid = QWidget(self)
wight_mid.setGeometry(1135, 70, 100, 670)
self.layout_mid = QVBoxLayout()
self.layout_mid.setContentsMargins(0, 0, 0, 0)
wight_mid.setLayout(self.layout_mid)
wight_put = QWidget(self)
wight_put.setGeometry(1235, 70, 100, 670)
self.layout_put = QVBoxLayout()
self.layout_put.setContentsMargins(0, 0, 0, 0)
wight_put.setLayout(self.layout_put)
wight_right = QWidget(self)
wight_right.setGeometry(1355, 40, 200, 650)
#wight_right.setStyleSheet('background-color:gray')
layout_r = QVBoxLayout()
self.labelr_currentstock_prince = QLabel()
self.labelr_currentstock_prince.setText(
self.loadsina.get_50etf_price()[3])
labelr_2 = QLabel('利率')
self.spin_lilv = QDoubleSpinBox()
self.spin_lilv.setValue(self.interestRate)
self.spin_lilv.valueChanged.connect(
lambda val: self.set_interestRate(val))
labelr_3 = QLabel('50etf未来价格:')
self.spin_future = QDoubleSpinBox()
self.spin_future.setDecimals(3)
self.spin_future.setSingleStep(0.005)
self.spin_future.setValue(float(
self.labelr_currentstock_prince.text()))
self.spin_future.valueChanged.connect(
lambda val: self.set_stockPricefuture(val))
self.labelr_iv_future = QLabel('未来波动:')
# self.spin_future_iv = QDoubleSpinBox()
# self.spin_future_iv.setDecimals(2)
# self.spin_future_iv.setSingleStep(0.05)
# self.spin_future_iv.setValue(self.iv_future)
#self.spin_future_iv.valueChanged.connect(lambda val:self.set_ivFuture(val))
self.sp = QSlider(Qt.Horizontal)
self.sp.setMinimum(-100)
self.sp.setMaximum(100)
self.sp.setSingleStep(0.01)
self.sp.setValue(self.iv_future)
self.sp.setTickPosition(QSlider.TicksBelow)
self.sp.setTickInterval(5)
self.sp.valueChanged.connect(lambda val: self.set_ivFuture(val))
labelr_daylater = QLabel('几天以后:')
self.spin_daylater = QSpinBox()
self.spin_daylater.setRange(0, 300)
self.spin_daylater.setValue(self.dayLater)
self.spin_daylater.valueChanged.connect(
lambda val: self.set_daylater(val))
btn_calculated = QPushButton('计算收益')
btn_calculated.clicked.connect(self.Show_Profit)
self.labelr_4 = QLabel('收益')
btn_draw = QPushButton('画图')
btn_draw.clicked.connect(self.draw)
layout_r.addWidget(self.labelr_currentstock_prince)
layout_r.addWidget(labelr_2)
layout_r.addWidget(self.spin_lilv)
layout_r.addWidget(labelr_3)
layout_r.addWidget(self.spin_future)
layout_r.addWidget(self.labelr_iv_future)
layout_r.addWidget(self.sp)
layout_r.addWidget(labelr_daylater)
layout_r.addWidget(self.spin_daylater)
layout_r.addWidget(btn_calculated)
layout_r.addWidget(self.labelr_4)
layout_r.addWidget(btn_draw)
wight_right.setLayout(layout_r)
menubar = self.menuBar()
fileMenu = menubar.addMenu('File')
newAct = QAction('load', self)
saveAct = QAction('save', self)
csvAct = QAction('load_csv', self)
fileMenu.addAction(newAct)
fileMenu.addAction(saveAct)
fileMenu.addAction(csvAct)
fileMenu.triggered[QAction].connect(self.processtrigger)
def rest(self):
pass
def processtrigger(self, q):
#保存和读取
if q.text() == 'load':
fname, _ = QFileDialog.getOpenFileName(self, '读取')
data = np.load(fname)
print(data)
self.listWidget.clear()
for i in range(0, data.shape[0]):
code = str(data[i, 0])[0:8]
ls = data[i, 1]
count = data[i, 2]
self.add_listwidget(code, lonshort=ls, count=count)
elif q.text() == 'save':
filename = QFileDialog.getSaveFileName(self, 'save file')
count = self.listWidget.count()
data = np.zeros((count, 3))
for j in range(self.listWidget.count()):
item = self.listWidget.item(j)
code, callput, longshort, eprice, price, count, time, iv, iv_h = self.get_itemInfo(
item)
data[j, :] = [code, longshort, count]
#print (data)
np.save(filename[0], data)
else:
fname, _ = QFileDialog.getOpenFileName(self, '读取')
csv_data = pd.read_csv(fname,
usecols=['代码', '买卖', '持仓'],
encoding='GB2312')
positionList = csv_data.values.tolist()
print(positionList)
self.listWidget.clear()
for option in positionList:
code = str(option[0])
bs = option[1]
if bs == '买':
ls = 1
else:
ls = -1
count = option[2]
self.add_listwidget(code, lonshort=ls, count=count)
def set_interestRate(self, value):
self.interestRate = value
def set_stockPricefuture(self, value):
self.stockPrice_future = value
def set_ivFuture(self, value):
print(value)
self.iv_future = value
self.labelr_iv_future.setText('未来波动： ' + str(value))
def set_daylater(self, value):
self.dayLater = value
def Show_Profit(self):
pass
def draw(self):
pass
def fill_dayWidget(self):
# for i in self.layout_call.count():
# self.layout_call.remove(self.layout_call.children().at(i)i)
wight_out_tt = QWidget(self)
wight_out_tt.setGeometry(1035, 40, 300, 25)
layout_out_tt = QHBoxLayout()
layout_out_tt.setContentsMargins(0, 0, 0, 0)
#wight_out_tt.setStyleSheet('background-color:red')
for month in self.month:
btm = QPushButton(month)
btm.clicked.connect(self.on_monthbtm_click)
layout_out_tt.addWidget(btm)
wight_out_tt.setLayout(layout_out_tt)
def check_in_item(self, item):
self.currentItem = item
self.get_itemInfo(item)
def check_out_item(self):
pass
def on_monthbtm_click(self):
btm = self.sender()
month = btm.text()
print(month)
self.fill_wight_out(month)
def fill_wight_out(self, month):
for i in range(self.layout_call.count()):
self.layout_call.itemAt(i).widget().deleteLater()
for i in range(self.layout_mid.count()):
self.layout_mid.itemAt(i).widget().deleteLater()
for i in range(self.layout_put.count()):
self.layout_put.itemAt(i).widget().deleteLater()
callop, putop = self.loadsina.get_op_codes(month)
for op in callop:
opprice = self.loadsina.get_op_info(op)
btm = QPushButton(opprice[2])
btm.setObjectName(op)
btm.clicked.connect(self.outBtm_click)
self.layout_call.addWidget(btm)
for op in callop:
opprice = self.loadsina.get_op_info(op)
btm = QPushButton(opprice[37][-4:])
btm.setEnabled(False)
self.layout_mid.addWidget(btm)
for op in putop:
opprice = self.loadsina.get_op_info(op)
btm = QPushButton(opprice[2])
btm.setObjectName(op)
btm.clicked.connect(self.outBtm_click)
self.layout_put.addWidget(btm)
def outBtm_click(self):
btm = self.sender()
print(btm.objectName())
self.add_listwidget(btm.objectName())
def add_listwidget(self, opcode, lonshort=0, count=0):
print('addlist_opcode:::' + opcode)
greek = self.loadsina.get_op_greek_alphabet(opcode)
print(greek)
data = '20' + greek[12][7:11]
#data表示是几月的合约
expire_day = self.loadsina.get_op_expire_day(data)[1]
callput_text = greek[0][5] #“购”或“沽”
eprice = greek[13] #行权价，如c2.95
price = greek[14] #当前期权价格
callput = 1
if callput_text == '购':
callput = 1
else:
callput = -1
currentOption = Option(stockPrice=self.stockPrice,
strikePrice=float(eprice),
interestRate=self.interestRate,
daysToExpiration=float(expire_day),
callput=callput,
optionPrice=float(price))
impliedVolatility = currentOption.impliedVolatility
#print(impliedVolatility,"iv_")
#iv_h=impliedVolatility+ self.iv_future*impliedVolatility*0.01
#print(iv_h,"iv_h")
delta = currentOption.delta
gamma = currentOption.gamma
theta = currentOption.theta
vega = currentOption.vega
item = QListWidgetItem()
item.setToolTip(opcode)
item.setSizeHint(QSize(600, 60))
wight = QWidget()
layout_main = QHBoxLayout()
# label_code = QLabel('id')
# label_code.setText(opcode)
# layout_main.addWidget(label_code)
spin_longshort = QSpinBox()
spin_longshort.setMaximum(1)
spin_longshort.setMinimum(-1)
spin_longshort.setValue(lonshort)
spin_longshort.setObjectName('longshort')
layout_main.addWidget(spin_longshort)
label_callput = QLabel('callput')
label_callput.setObjectName('callput')
label_callput.setText(callput_text)
layout_main.addWidget(label_callput)
label_eprice = QLabel('eprice')
label_eprice.setObjectName('eprice')
label_eprice.setText(eprice)
layout_main.addWidget(label_eprice)
label_price = QLabel('price')
label_price.setObjectName('price')
label_price.setText(price)
layout_main.addWidget(label_price)
Delta = QLabel('Delta')
Delta.setText(str(delta)[0:5])
layout_main.addWidget(Delta)
Gamma = QLabel('Gamma')
Gamma.setText(str(gamma)[0:5])
layout_main.addWidget(Gamma)
Theta = QLabel('Theta')
Theta.setText(str(theta)[0:8])
layout_main.addWidget(Theta)
Vega = QLabel('Vega')
Vega.setText(str(vega)[0:8])
layout_main.addWidget(Vega)
iv = QLabel('iv')
iv.setObjectName('iv')
iv_value = round(impliedVolatility, 4)
iv.setText(str(iv_value)[0:5])
#iv.setText(greek[9])
layout_main.addWidget(iv)
spin_count = QSpinBox()
spin_count.setMinimum(0)
spin_count.setValue(count)
spin_count.setObjectName('count')
layout_main.addWidget(spin_count)
label_expire_day = QLabel('label_expire_day')
label_expire_day.setObjectName('label_expire_day')
label_expire_day.setText(str(expire_day))
layout_main.addWidget(label_expire_day)
wight.setLayout(layout_main)
self.listWidget.addItem(item)
self.listWidget.setItemWidget(item, wight)
def del_item(self):
if self.currentItem == None:
return
index = self.listWidget.row(self.currentItem)
self.listWidget.takeItem(index)
def get_itemInfo(self, item):
widget = self.listWidget.itemWidget(item)
code = item.toolTip()
longshort = widget.findChild(QSpinBox, 'longshort').value()
count = widget.findChild(QSpinBox, 'count').value()
callput_text = widget.findChild(QLabel, 'callput').text()
callput = 0
if callput_text == '购':
callput = 1
else:
callput = -1
eprice = widget.findChild(QLabel, 'eprice').text()
price = widget.findChild(QLabel, 'price').text()
expire_day = widget.findChild(QLabel, 'label_expire_day').text()
#iv =widget.findChild(QLabel,'iv').text()
currentOption = Option(stockPrice=self.stockPrice,
strikePrice=float(eprice),
interestRate=self.interestRate,
daysToExpiration=float(expire_day),
callput=callput,
optionPrice=float(price))
impliedVolatility = currentOption.impliedVolatility
iv_h = impliedVolatility + self.iv_future * impliedVolatility * 0.01
return code, callput, longshort, eprice, price, count, expire_day, impliedVolatility, iv_h
def getAllListInfo(self):
count = self.listWidget.count()
data = np.zeros((count, 8))
for j in range(self.listWidget.count()):
item = self.listWidget.item(j)
code, callput, longshort, eprice, price, count, time, iv, iv_h = self.get_itemInfo(
item)
data[j, :] = [
callput, longshort, eprice, price, count, time, iv, iv_h
]
return data
def Calculation_pointMoney(self, pricefuture, iscal_greeks=False):
#print(pricefuture)
data = self.getAllListInfo()
#print(data)
alreadPay = 0
price_sametime = 0
delta = 0
gamma = 0
vega = 0
theta = 0
for i in range(0, data.shape[0]):
#data[i,5]是合约距到期有多少天
expire_day = data[i, 5]
#day表示以新的日期算，距到期还有多少天
day = expire_day - self.dayLater
#print('data? ',data)
callput = data[i, 0]
strikePrice = data[i, 2]
longShort = data[i, 1]
optionPrice = data[i, 3]
amount = data[i, 4]
new_iv = data[i, 7]
if day < 1:
day = 1
futureOption = Option(stockPrice=pricefuture,
strikePrice=strikePrice,
interestRate=self.interestRate,
daysToExpiration=day,
callput=callput,
impliedVolatility=new_iv)
if self.dayLater < expire_day:
futureOptionPrice = futureOption.optionPrice
if iscal_greeks:
delta = amount * longShort * futureOption.delta + delta
print("futureOption.delta=", futureOption.delta)
print("delta=", delta)
gamma = amount * longShort * futureOption.gamma + gamma
vega = amount * longShort * futureOption.vega + vega
theta = amount * longShort * futureOption.theta + theta
else:
print('tianshuchaoguole')
if callput == 1:
if pricefuture < strikePrice:
futureOptionPrice = 0
else:
futureOptionPrice = pricefuture - strikePrice
else:
if pricefuture > strikePrice:
futureOptionPrice = 0
else:
futureOptionPrice = strikePrice - pricefuture
if True:
alreadPay = alreadPay + longShort * optionPrice * amount * 10000
futureOptionPrice = longShort * futureOptionPrice * amount * 10000
else:
futureOptionPrice = 0
price_sametime = price_sametime + futureOptionPrice
if iscal_greeks:
print(delta, gamma, vega, theta)
self.statusBar().showMessage('delta=' + str(delta) + ' gamma=' +
str(gamma) + ' vega=' + str(vega) +
' theta=' + str(theta))
return price_sametime - alreadPay
def Show_Profit(self):
profit = self.Calculation_pointMoney(self.stockPrice_future,
iscal_greeks=True)
#print(profit)
self.labelr_4.setText(str(profit))
def draw(self):
longth = np.linspace(-0.2, 0.2, 48)
profits = np.zeros(longth.shape[0])
plt.figure(figsize=(16, 7.5))
ax = plt.gca()
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
ax.spines['bottom'].set_position(('data', 0))
#x =longth+self.stockPrice_future
x = longth + self.stockPrice
for row in range(longth.shape[0]):
#pricefuture =longth[row]+self.stockPrice_future
pricefuture = longth[row] + self.stockPrice
profits[row] = self.Calculation_pointMoney(pricefuture)
if row % 4 == 0:
#xx =longth[row]+self.stockPrice_future
xx = longth[row] + self.stockPrice
plt.annotate("%s" % np.trunc(profits[row]),
xy=(xx, profits[row]),
xytext=(-20, 10),
xycoords='data',
textcoords='offset points')
plt.plot([xx, xx], [0, profits[row]],
color='blue',
linewidth=1,
linestyle="--")
y = profits
plt.plot(x, y, color='red', linewidth=2.5)
plt.show()
class scan():
def __init__(self):
self.load = LoadNet()
self.months = self.load.check_month()
self.day_later = self.load.get_op_expire_day('2019')
#print(self.day_later)
self.etf_price = 2.95
self.data_price = pd.DataFrame()
self.data_iv = pd.DataFrame()
self.histroy_high = 300
# self.data_panel = pd.DataFrame()
# self.fig = plt.figure()
# self.tmp =0.0
# self.ax = self.fig.gca(projection='3d')
# timer = self.fig.canvas.new_timer(interval=1000)
# timer.add_callback(self.draw)
# timer.start()
# plt.show()
def get_df(self):
self.etf_price = float(self.load.get_50etf_price()[3])
self.data_price = pd.DataFrame()
self.data_iv = pd.DataFrame()
for month in self.months:
up, down = self.load.get_op_codes(month)
xqj_list = []
iv_list = []
p_list = []
for code in up:
data = self.load.get_op_greek_alphabet(code)
xqj_list.append(float(data[13]))
iv_list.append(float(data[9]))
p_list.append(float(data[14]))
df_p = pd.DataFrame(p_list,
index=xqj_list,
columns=[month + '_call'])
self.data_price = pd.concat([self.data_price, df_p], axis=1)
df_iv = pd.DataFrame(iv_list,
index=xqj_list,
columns=[month + '_call'])
self.data_iv = pd.concat([self.data_iv, df_iv], axis=1)
xqj_list = []
iv_list = []
p_list = []
for code in down:
data = self.load.get_op_greek_alphabet(code)
xqj_list.append(float(data[13]))
iv_list.append(float(data[9]))
p_list.append(float(data[14]))
df_p = pd.DataFrame(p_list,
index=xqj_list,
columns=[month + '_put'])
self.data_price = pd.concat([self.data_price, df_p], axis=1)
df_iv = pd.DataFrame(iv_list,
index=xqj_list,
columns=[month + '_put'])
self.data_iv = pd.concat([self.data_iv, df_iv], axis=1)
self.data_price = self.data_price[self.data_price != 0]
#print(self.data_price)
#print(self.data_iv)
def find_pd_diff(self):
df_diff = pd.DataFrame() #期权价格偏离 越大越偏离便宜 只适用于实值
for month in self.months:
#列出看涨现货差价
long_diff =self.etf_price - \
(self.data_price.index + self.data_price[month+'_call'])
df_diff[month + 'call_p'] = long_diff
short_diff =self.data_price.index - \
(self.etf_price + self.data_price[month+'_put'])
df_diff[month + 'put_p'] = short_diff
for index, row in df_diff.iterrows():
for i, v in row.items():
if v > 0.01:
print(df_diff)
return df_diff
# def find_most_cheapset(self,data):
# cheapest_op =data.idxmax()
# most_op =data.idxmin()
# print(cheapest_op,most_op)
def find_combination_pd(self):
#买一个现货赚多少钱 卖一个现货赚-多少钱
pd_combination = pd.DataFrame()
for month in self.months:
good_price =self.data_price[month+'_call']- self.data_price[month+'_put']\
-(self.etf_price-self.data_price.index)
pd_combination[month] = -good_price * 10000
#print(pd_combination)
return pd_combination
def find_good_combination(self, pd_data):
# short_ = pd_data[pd_data.columns].min()
# long_ = pd_data[pd_data.columns].max()
# print(long_,short_)
# money = long_ - short_
long_ = 0
short_ = 0
money = 1
long_date = 'none'
short_data = 'none'
long_right = 0
short_right = 0
for index, row in pd_data.iterrows():
for i, v in row.items():
if (v > long_):
long_ = v
long_date = i
long_right = index
if (v < short_):
short_ = v
short_data = i
short_right = index
money = long_ - short_
long_ = ("%.1f" % long_)
short_ = ("%.1f" % short_)
#money=("%.1f" % money)
return long_date, long_right, long_, short_data, short_right, short_, money
def get_histroy_high(self, h):
if h > self.histroy_high:
self.histroy_high = h
return self.histroy_high
def save_excel(self):
data = QDateTime.currentDateTime()
currTime = data.toString("yyyy-MM-dd-hh-mm-ss")
writer = pd.ExcelWriter('./save_file/' + currTime + '.xlsx')
self.data_price.to_excel(writer, sheet_name='price')
self.data_iv.to_excel(writer, sheet_name='iv')
self.find_combination_pd().to_excel(writer, sheet_name='longshort')
writer.save()
class DataModel:
def __init__(self):
self.ln = LoadNet()
self.stock_info_50 = self.ln.get_sz50_price()
self.stock_info_300 = self.ln.get_sz300_price()
self.stock_price_50etf = 0.0
self.stock_price_300etf = 0.0
self.df_op = pd.DataFrame()
self.df_codes = self.init_allcodes()
t = threading.Thread(target=self.loop)
t.start()
def init_allcodes(self):
mouths = self.ln.check_month()
codes = self.ln.get_allop_codes(mouths)
return codes
def update_alldf(self):
'''
get 50etf 300etf
'''
stock_price_50_allinfo = self.ln.get_50etf_price()
time = stock_price_50_allinfo[31]
self.stock_price_50etf = stock_price_50_allinfo[3]
self.stock_price_300etf = self.ln.get_300etf_price()[3]
self.stock_info_50 = self.ln.get_sz50_price()
self.stock_info_300 = self.ln.get_sz300_price()
'''
get sina info all
'''
codes, names, prices, eprices, edays, days = self.ln.get_allop_info(
self.df_codes)
df_all = pd.DataFrame()
df_all['code'] = codes
df_all['name'] = names
df_all['price'] = prices
df_all['eprice'] = eprices
df_all['eday'] = edays
df_all['day'] = days
'''
get my count discountlist
'''
discountlist = []
for date, row in df_all.T.iteritems():
discount = 0
if '50ETF购' in row['name']:
discount = float(self.stock_price_50etf) - float(
row['eprice']) - float(row['price'])
if '50ETF沽' in row['name']:
discount = float(row['eprice']) - float(
self.stock_price_50etf) - float(row['price'])
if '300ETF购' in row['name']:
discount = float(self.stock_price_300etf) - float(
row['eprice']) - float(row['price'])
if '300ETF沽' in row['name']:
discount = float(row['eprice']) - float(
self.stock_price_300etf) - float(row['price'])
discountlist.append(discount)
df_all['discount'] = discountlist
'''
count iv
'''
ivlist = []
deltalist = []
gammalist = []
thetalist = []
vegalist = []
timelist = []
for date, row in df_all.T.iteritems():
if row['day'] == 0.0:
impliedVolatility = 0
delta = 0
gamma = 0
theta = 0
vega = 0
#row['price'] = float(row['price']) + discount*1.5
else:
op_price = float(row['price'])
eprice = float(row['eprice'])
day = float(row['day'])
callput = 1
if '沽' in row['name']:
callput = -1
stock_price = self.stock_price_50etf
if '300ETF' in row['name']:
stock_price = self.stock_price_300etf
#print (stock_price,eprice,INTERESTRate,day,callput,op_price)
currentOption = Option(stockPrice= stock_price, strikePrice = eprice, interestRate=INTERESTRate, daysToExpiration=day,\
callput = callput, optionPrice=op_price)
impliedVolatility = currentOption.impliedVolatility
delta = currentOption.delta
gamma = currentOption.gamma
theta = currentOption.theta
vega = currentOption.vega
ivlist.append(impliedVolatility)
deltalist.append(delta)
gammalist.append(gamma)
thetalist.append(theta)
vegalist.append(vega)
timelist.append(time)
#print(row['month'],callput, eprice,impliedVolatility,delta,gamma,theta,vega)
#print(impliedVolatility)
df_all['delta'] = deltalist
df_all['gamma'] = gammalist
df_all['vega'] = vegalist
df_all['theta'] = thetalist
df_all['iv'] = ivlist
df_all['time'] = timelist
self.df_op = df_all.copy()
#print (self.df_op)
#self.df_op.to_csv('./Result1.csv',index=0)
def get_iv(self):
'''
50
'''
df_50 = self.df_op[self.df_op['name'].str.contains('50ETF购')]
mindex = df_50['eprice'].drop_duplicates()
eday = df_50['eday'].drop_duplicates()
df_50call_res = pd.DataFrame(index=mindex, columns=eday)
for date, row in df_50.T.iteritems():
df_50call_res.loc[row['eprice'], row['eday']] = row['iv']
df_50call_res['x'] = df_50call_res.index
df_50_put = self.df_op[self.df_op['name'].str.contains('50ETF沽')]
mindex = df_50_put['eprice'].drop_duplicates()
eday = df_50_put['eday'].drop_duplicates()
df_50put_res = pd.DataFrame(index=mindex, columns=eday)
for date, row in df_50_put.T.iteritems():
df_50put_res.loc[row['eprice'], row['eday']] = row['iv']
df_50put_res['x'] = df_50put_res.index
df_50res = pd.concat([df_50call_res, df_50put_res], axis=1)
#df_50res['x'] =df_50res.index
'''
300
'''
df_300 = self.df_op[self.df_op['name'].str.contains('300ETF购')]
mindex = df_300['eprice'].drop_duplicates()
eday = df_300['eday'].drop_duplicates()
df_300call_res = pd.DataFrame(index=mindex, columns=eday)
for date, row in df_300.T.iteritems():
df_300call_res.loc[row['eprice'], row['eday']] = row['iv']
df_300call_res['x'] = df_300call_res.index
df_300_put = self.df_op[self.df_op['name'].str.contains('300ETF沽')]
mindex = df_300_put['eprice'].drop_duplicates()
eday = df_300_put['eday'].drop_duplicates()
df_300put_res = pd.DataFrame(index=mindex, columns=eday)
for date, row in df_300_put.T.iteritems():
df_300put_res.loc[row['eprice'], row['eday']] = row['iv']
df_300put_res['x'] = df_300put_res.index
df_300res = pd.concat([df_300call_res, df_300put_res], axis=1)
return df_50res, df_300res
def iv_month_50300(self):
if self.df_op.empty:
return
df_50 = self.df_op[self.df_op['name'].str.contains('50ETF')]
df_50 = df_50[df_50['iv'] > 0.1]
months = df_50['eday'].drop_duplicates()
meanlist = []
for month in months:
iv_month = df_50[df_50['eday'] == month]
meanlist.append(iv_month.mean(axis=0)['iv'])
df_res50 = pd.DataFrame()
df_res50['date'] = months
df_res50['iv'] = meanlist
df_res50.index = months
df_300 = self.df_op[self.df_op['name'].str.contains('300ETF')]
df_300 = df_300[df_300['iv'] > 0.1]
months = df_300['eday'].drop_duplicates()
meanlist = []
for month in months:
iv_month = df_300[df_300['eday'] == month]
meanlist.append(iv_month.mean(axis=0)['iv'])
df_res300 = pd.DataFrame()
df_res300['date'] = months
df_res300['iv'] = meanlist
df_res300.index = months
df_res = pd.concat([df_res50, df_res300], axis=1)
#print(df_res)
return df_res
def loop(self):
while True:
self.update_alldf()
#self.iv_month_50300()
time.sleep(RATE)