def stdev(close, length=None, ddof=None, offset=None, **kwargs):
"""Indicator: Standard Deviation"""
# Validate Arguments
length = int(length) if length and length > 0 else 30
ddof = int(ddof) if ddof and ddof >= 0 and ddof < length else 1
close = verify_series(close, length)
offset = get_offset(offset)
if close is None: return
# Calculate Result
if Imports["talib"]:
from talib import STDDEV
stdev = STDDEV(close, length)
else:
stdev = variance(close=close, length=length, ddof=ddof).apply(npsqrt)
# Offset
if offset != 0:
stdev = stdev.shift(offset)
# Handle fills
if "fillna" in kwargs:
stdev.fillna(kwargs["fillna"], inplace=True)
if "fill_method" in kwargs:
stdev.fillna(method=kwargs["fill_method"], inplace=True)
# Name & Category
stdev.name = f"STDEV_{length}"
stdev.category = "statistics"
return stdev
def refresh(self, df):
df = df[-(MAX_ROWS + 1):-1]
open = df.open.astype("f8").values
high = df.high.astype("f8").values
low = df.low.astype("f8").values
close = df.close.astype("f8").values
volume = df.volume.astype("f8").values
df["price"] = WCLPRICE(high, low, close) #Weighted Close Price
df["obv"] = OBV(close, volume)
df["ad"] = AD(high, low, close, volume)
df["macd"], df["signal"], df["histogram"] = MACD(close)
df["rsi"] = RSI(close) #relative strong index
#df["willr"] = WILLR(high, low, close) + 100 #will index
df["roc"] = ROC(close)
#統計
df["beta"] = BETA(high, low)
df["linearR"] = LINEARREG(close) #線形回帰
df["linearA"] = LINEARREG_ANGLE(close) ##線形回帰 角度
df["linearI"] = LINEARREG_INTERCEPT(close) #線形回帰 JIEJU
df["linearS"] = LINEARREG_SLOPE(close) #線形回帰 坂
df["stddev"] = STDDEV(close) #標準偏差
df["tsf"] = TSF(close) #Time Series Forecast
df["var"] = VAR(close) #方差
df["wramount"] = 0
df["amount"] = 0
df["memo"] = 0
# -*- coding: UTF-8 -*- # 載入函數 from function import getKbar import datetime from talib import SMA,STDDEV import numpy as np # 取得資料 KBar=getKbar() # 計算移動平均線 、 標準差 、 低點 KBar['MA'] = SMA(KBar['close'], timeperiod= 120) KBar['STD'] = STDDEV(KBar['close'], timeperiod= 120) KBar['BD'] = KBar['MA']-0.75*KBar['STD'] # 初始資金 InitCapital=1000000 # 進場價格 、 進場數量 OrderPrice = None OrderQty = 0 # 出場價格 CoverPrice = None # 停損 、 停利價 StopLoss = None TakeProfit = None # 總獲利 、 交易次數 TotalProfit = [] TotalTreadeNum = 0 for i in range(1,len(KBar['date'])):
def StopProfitLoss(self, ui, KBar):
self.ui = ui
#from function import getKbar
import datetime
from talib import SMA, STDDEV
import numpy as np
# 計算移動平均線 、 標準差 、 低點
KBar['MA'] = SMA(KBar['close'], timeperiod=120)
KBar['STD'] = STDDEV(KBar['close'], timeperiod=120)
KBar['BD'] = KBar['MA'] - 0.75 * KBar['STD']
# 初始資金
InitCapital = 1000000
# 進場價格 、 進場數量
OrderPrice = None
OrderQty = 0
# 出場價格
CoverPrice = None
# 停損 、 停利價
StopLoss = None
TakeProfit = None
# 總獲利 、 交易次數
TotalProfit = []
TotalTreadeNum = 0
data = {
'買進時間': [],
'買進原因': [],
'買進價格': [],
'售出時間': [],
'售出價格': [],
'售出原因': [],
'數量': [],
'獲利': [] #[(CoverPrice-OrderPrice)*OrderQty*1000],
}
for i in range(1, len(KBar['date'])):
Date = KBar['date'][i]
Close = KBar['close'][i]
LastClose = KBar['close'][i - 1]
BD = KBar['BD'][i]
LastBD = KBar['BD'][i - 1]
status = []
# 進場條件
if LastClose < LastBD and Close >= BD and OrderQty == 0:
# 進場時間、價格、數量
OrderDate = KBar['date'][i + 1]
OrderPrice = KBar['open'][i + 1]
OrderQty = int(InitCapital / (Close) / 1000)
# 停損價、停利價
StopLoss = OrderPrice * 0.8
TakeProfit = OrderPrice * 1.6
status = ' 低點 '
print('買進時間:', OrderDate.strftime('%Y/%m/%d'), '買進價格:',
OrderPrice, '買進數量:', OrderQty)
data['買進時間'].append(OrderDate.strftime('%Y/%m/%d'))
data['買進原因'].append(status)
data['買進價格'].append(OrderPrice)
data['數量'].append(OrderQty)
# 停損判斷
elif OrderQty != 0 and Close < StopLoss:
# 出場時間、價格
CoverDate = KBar['date'][i + 1]
CoverPrice = KBar['open'][i + 1]
# 績效紀錄
Profit = (CoverPrice - OrderPrice) * OrderQty * 1000
TotalProfit += [Profit]
TotalTreadeNum += 1
# InitCapital += Profit
# 下單數量歸零，重新進場
OrderQty = 0
status = ' 停損 '
print('售出時間:', CoverDate.strftime('%Y/%m/%d'), '售出價格:',
CoverPrice, '虧損:', Profit)
data['售出時間'].append(CoverDate.strftime('%Y/%m/%d'))
data['售出原因'].append(status)
data['售出價格'].append(CoverPrice)
data['獲利'].append(Profit)
# 停利判斷
elif OrderQty != 0 and Close > TakeProfit:
# 出場時間、價格
CoverDate = KBar['date'][i + 1]
CoverPrice = KBar['open'][i + 1]
# 績效紀錄
Profit = (CoverPrice - OrderPrice) * OrderQty * 1000
TotalProfit += [Profit]
TotalTreadeNum += 1
# InitCapital += Profit
# 下單數量歸零，重新進場
OrderQty = 0
status = ' 停利 '
print('售出時間:', CoverDate.strftime('%Y/%m/%d'), '售出價格:',
CoverPrice, '獲利:', Profit)
data['售出時間'].append(CoverDate.strftime('%Y/%m/%d'))
data['售出原因'].append(status)
data['售出價格'].append(CoverPrice)
data['獲利'].append(Profit)
# 回測時間結束，則出場
elif OrderQty != 0 and i == len(KBar['date']) - 1:
# 出場時間、價格
CoverDate = Date
CoverPrice = Close
# 績效紀錄
Profit = (CoverPrice - OrderPrice) * OrderQty * 1000
TotalProfit += [Profit]
TotalTreadeNum += 1
# InitCapital += Profit
# 下單數量歸零，重新進場
OrderQty = 0
status = ' 結束 '
print('售出時間:', CoverDate.strftime('%Y/%m/%d'), '售出價格:',
CoverPrice, '盈虧:', Profit)
data['售出時間'].append(CoverDate.strftime('%Y/%m/%d'))
data['售出原因'].append(status)
data['售出價格'].append(CoverPrice)
data['獲利'].append(Profit)
print('交易次數:', TotalTreadeNum, '總盈虧:', sum(TotalProfit))
result = pd.DataFrame(data)
print(result)
self.change_data(result)
import matplotlib.pyplot as plt # 匯出績效圖表
plot_X = list(range(0, len(TotalProfit)))
ax = plt.subplot(111) # 新增繪圖圖片
ax.bar(plot_X, np.cumsum(TotalProfit)) # 繪製圖案 ( X軸物件, Y軸物件, 線風格 )
plt.show()
def StopProfitLoss(self, ui, KBar):
self.ui = ui
#from function import getKbar
import datetime
from talib import SMA, STDDEV
import numpy as np
# 計算移動平均線 、 標準差 、 低點
KBar['MA'] = SMA(KBar['close'], timeperiod=120)
KBar['STD'] = STDDEV(KBar['close'], timeperiod=120)
KBar['BD'] = KBar['MA'] - 0.75 * KBar['STD']
# 初始資金
InitCapital = 1000000
# 進場價格 、 進場數量
OrderPrice = None
OrderQty = 0
# 出場價格
CoverPrice = None
# 停損 、 停利價
StopLoss = None
TakeProfit = None
# 總獲利 、 交易次數
TotalProfit = []
TotalTreadeNum = 0
data = {
'買進時間': [],
'買進原因': [],
'買進價格': [],
'售出時間': [],
'售出價格': [],
'售出原因': [],
'數量': [],
'獲利': [] # [(CoverPrice-OrderPrice)*OrderQty*1000],
}
for i in range(1, len(KBar['date'])):
Date = KBar['date'][i]
Close = KBar['close'][i]
LastClose = KBar['close'][i - 1]
BD = KBar['BD'][i]
LastBD = KBar['BD'][i - 1]
status = []
# 進場條件
if LastClose < LastBD and Close >= BD and OrderQty == 0:
# 進場時間、價格、數量
OrderDate = KBar['date'][i + 1]
OrderPrice = KBar['open'][i + 1]
OrderQty = int(InitCapital / (Close) / 1000)
# 停損價、停利價
StopLoss = OrderPrice * 0.8
TakeProfit = OrderPrice * 1.6
status = ' 低點 '
print('買進時間:', OrderDate.strftime('%Y/%m/%d'), '買進價格:',
OrderPrice, '買進數量:', OrderQty)
data['買進時間'].append(OrderDate.strftime('%Y/%m/%d'))
data['買進原因'].append(status)
data['買進價格'].append(OrderPrice)
data['數量'].append(OrderQty)
# 停損判斷
elif OrderQty != 0 and Close < StopLoss:
# 出場時間、價格
CoverDate = KBar['date'][i + 1]
CoverPrice = KBar['open'][i + 1]
# 績效紀錄
Profit = (CoverPrice - OrderPrice) * OrderQty * 1000
TotalProfit += [Profit]
TotalTreadeNum += 1
# InitCapital += Profit
# 下單數量歸零，重新進場
OrderQty = 0
status = ' 停損 '
print('售出時間:', CoverDate.strftime('%Y/%m/%d'), '售出價格:',
CoverPrice, '虧損:', Profit)
data['售出時間'].append(CoverDate.strftime('%Y/%m/%d'))
data['售出原因'].append(status)
data['售出價格'].append(CoverPrice)
data['獲利'].append(Profit)
# 停利判斷
elif OrderQty != 0 and Close > TakeProfit:
# 出場時間、價格
CoverDate = KBar['date'][i + 1]
CoverPrice = KBar['open'][i + 1]
# 績效紀錄
Profit = (CoverPrice - OrderPrice) * OrderQty * 1000
TotalProfit += [Profit]
TotalTreadeNum += 1
# InitCapital += Profit
# 下單數量歸零，重新進場
OrderQty = 0
status = ' 停利 '
print('售出時間:', CoverDate.strftime('%Y/%m/%d'), '售出價格:',
CoverPrice, '獲利:', Profit)
data['售出時間'].append(CoverDate.strftime('%Y/%m/%d'))
data['售出原因'].append(status)
data['售出價格'].append(CoverPrice)
data['獲利'].append(Profit)
# 回測時間結束，則出場
elif OrderQty != 0 and i == len(KBar['date']) - 1:
# 出場時間、價格
CoverDate = Date
CoverPrice = Close
# 績效紀錄
Profit = (CoverPrice - OrderPrice) * OrderQty * 1000
TotalProfit += [Profit]
TotalTreadeNum += 1
# InitCapital += Profit
# 下單數量歸零，重新進場
OrderQty = 0
status = ' 結束 '
print('售出時間:', CoverDate.strftime('%Y/%m/%d'), '售出價格:',
CoverPrice, '盈虧:', Profit)
data['售出時間'].append(CoverDate.strftime('%Y/%m/%d'))
data['售出原因'].append(status)
data['售出價格'].append(CoverPrice)
data['獲利'].append(Profit)
result = pd.DataFrame(data) # 把字典轉成DataFrame
self.change_data(result, self.ui.tableWidget)
print('交易次數:', TotalTreadeNum, '總盈虧:', sum(TotalProfit))
#result = pd.DataFrame(data)
# print(result)
#self.change_data(result, self.ui.tableWidget)
KPI_dict = {'交易次數': [TotalTreadeNum], '總盈虧': [sum(TotalProfit)]}
KPI_df = pd.DataFrame(KPI_dict)
self.change_data(KPI_df, self.ui.tableWidget_2)
import matplotlib.pyplot as plt # 匯出績效圖表
import matplotlib.ticker as plticker
plot_X = list(range(1, len(TotalProfit) + 1))
plot_Y = np.cumsum(TotalProfit)
ax = plt.subplot(111) # 新增繪圖圖片
ax.bar(plot_X, plot_Y) # 繪製圖案 ( X軸物件, Y軸物件 )
ax.ticklabel_format(style="plain") # 設定Y軸為實數顯示，否則預設顯示為科學符號
# 設定X軸間隔為1
# this locator puts ticks at regular intervals
loc = plticker.MultipleLocator(base=1.0)
ax.xaxis.set_major_locator(loc)
# 設定文字
for x, y in zip(plot_X, plot_Y):
text_show = int(y)
# plt.text(X座標, Y座標, 顯示內容, 水平對齊方式, 垂直對齊方式)
if y > 0:
plt.text(x, y, text_show, ha="center", va="bottom")
else:
plt.text(x, y, text_show, ha="center", va="top")
plt.savefig("bar_chart.png")
self.change_plot("bar_chart.png")
def let_it_be(self, ui, KBar):
self.ui = ui
import datetime
from talib import SMA, STDDEV
import numpy as np
# 計算移動平均線 、 標準差 、 低點 、 高點
KBar['MA'] = SMA(KBar['close'], timeperiod=120)
KBar['STD'] = STDDEV(KBar['close'], timeperiod=120)
KBar['BD'] = KBar['MA'] - 0.75 * KBar['STD']
KBar['BU'] = KBar['MA'] + 0.75 * KBar['STD']
# 初始資金
InitCapital = 1000000
# 進場價格 、 進場數量
OrderPrice = None
OrderQty = 0
# 出場價格
CoverPrice = None
# 停損 、 停利價
StopLoss = None
TakeProfit = None
# 總獲利 、 交易次數
TotalProfit = []
TotalTreadeNum = 0
data = {
'買進時間': [],
'買進原因': [],
'買進價格': [],
'售出時間': [],
'售出價格': [],
'售出原因': [],
'數量': [],
'獲利': [] #[(CoverPrice-OrderPrice)*OrderQty*1000],
}
for i in range(len(KBar['date'])):
Date = KBar['date'][i]
Close = KBar['close'][i]
LastClose = KBar['close'][i - 1]
MA = KBar['MA'][i]
LastMA = KBar['MA'][i - 1]
BD = KBar['BD'][i]
LastBD = KBar['BD'][i - 1]
BU = KBar['BU'][i]
LastBU = KBar['BU'][i - 1]
status = []
# 進場條件
if LastClose < LastBD and Close >= BD and OrderQty == 0:
# 進場時間、價格、數量
OrderDate = KBar['date'][i + 1]
OrderPrice = KBar['open'][i + 1]
OrderQty = int(InitCapital / (Close) / 1000)
# 停損價、停利價
StopLoss = OrderPrice * 0.8
TakeProfit = OrderPrice * 1.6
status = ' 低點 '
print('買進時間:', OrderDate.strftime('%Y/%m/%d'), '買進價格:', OrderPrice,
'買進數量:', OrderQty)
data['買進時間'].append(OrderDate.strftime('%Y/%m/%d'))
data['買進原因'].append(status)
data['買進價格'].append(OrderPrice)
data['數量'].append(OrderQty)
# 順勢 進場條件
if LastClose < LastMA and Close >= MA * 1.01 and OrderQty == 0:
# 進場時間、價格、數量
OrderDate = KBar['date'][i + 1]
OrderPrice = KBar['open'][i + 1]
OrderQty = int(InitCapital / (Close) / 1000)
# 停損價、停利價
StopLoss = OrderPrice * 0.8
TakeProfit = OrderPrice * 1.6
status = ' 順勢 '
print('買進時間:', OrderDate.strftime('%Y/%m/%d'), '買進價格:', OrderPrice,
'買進數量:', OrderQty)
data['買進時間'].append(OrderDate.strftime('%Y/%m/%d'))
data['買進原因'].append(status)
data['買進價格'].append(OrderPrice)
data['數量'].append(OrderQty)
# 高點賣出
elif OrderQty != 0 and LastClose > LastBU and Close <= BU:
# 出場時間、價格
CoverDate = KBar['date'][i + 1]
CoverPrice = KBar['open'][i + 1]
# 績效紀錄
Profit = (CoverPrice - OrderPrice) * OrderQty * 1000
TotalProfit += [Profit]
TotalTreadeNum += 1
# InitCapital += Profit
# 下單數量歸零，重新進場
OrderQty = 0
status = ' 高點 '
print('售出時間:', CoverDate.strftime('%Y/%m/%d'), '售出價格:', CoverPrice,
'獲利:', Profit)
data['售出時間'].append(CoverDate.strftime('%Y/%m/%d'))
data['售出原因'].append(status)
data['售出價格'].append(CoverPrice)
data['獲利'].append(Profit)
# 停損判斷
elif OrderQty != 0 and Close < StopLoss:
# 出場時間、價格
CoverDate = KBar['date'][i + 1]
CoverPrice = KBar['open'][i + 1]
# 績效紀錄
Profit = (CoverPrice - OrderPrice) * OrderQty * 1000
TotalProfit += [Profit]
TotalTreadeNum += 1
# InitCapital += Profit
# 下單數量歸零，重新進場
OrderQty = 0
status = ' 停損 '
print('售出時間:', CoverDate.strftime('%Y/%m/%d'), '售出價格:', CoverPrice,
'虧損:', Profit)
data['售出時間'].append(CoverDate.strftime('%Y/%m/%d'))
data['售出原因'].append(status)
data['售出價格'].append(CoverPrice)
data['獲利'].append(Profit)
# 停利判斷
elif OrderQty != 0 and Close > TakeProfit:
# 出場時間、價格
CoverDate = KBar['date'][i + 1]
CoverPrice = KBar['open'][i + 1]
# 績效紀錄
Profit = (CoverPrice - OrderPrice) * OrderQty * 1000
TotalProfit += [Profit]
TotalTreadeNum += 1
# InitCapital += Profit
# 下單數量歸零，重新進場
OrderQty = 0
status = ' 停利 '
print('售出時間:', CoverDate.strftime('%Y/%m/%d'), '售出價格:', CoverPrice,
'獲利:', Profit)
data['售出時間'].append(CoverDate.strftime('%Y/%m/%d'))
data['售出原因'].append(status)
data['售出價格'].append(CoverPrice)
data['獲利'].append(Profit)
# 回測時間結束，則出場
elif OrderQty != 0 and i == len(KBar['date']) - 1:
# 出場時間、價格
CoverDate = Date
CoverPrice = Close
# 績效紀錄
Profit = (CoverPrice - OrderPrice) * OrderQty * 1000
TotalProfit += [Profit]
TotalTreadeNum += 1
# InitCapital += Profit
# 下單數量歸零，重新進場
OrderQty = 0
status = ' 結束 '
print('售出時間:', CoverDate.strftime('%Y/%m/%d'), '售出價格:', CoverPrice,
'盈虧:', Profit)
data['售出時間'].append(CoverDate.strftime('%Y/%m/%d'))
data['售出原因'].append(status)
data['售出價格'].append(CoverPrice)
data['獲利'].append(Profit)
