def ShowAll(self):
df = pd.DataFrame({
'EURUSD': self.pairList['EURUSD']['Close'],
'EURJPY': self.pairList['EURJPY']['Close'],
'USDJPY': self.pairList['USDJPY']['Close']
})
display_charts(df, chart_type="stock", title="MA cross", grid=True)
def PositionChart(Open, long, short, tech):
df = pd.DataFrame(({"Open": Open, "Long": long, "Short": short}))
position_chart = display_charts(df,
title=tech + "_position",
figsize=(560, 400),
chart_type="stock",
grid=True)
return
def ModelChart(df, tech):
df = pd.DataFrame(df)
chart = display_charts(df,
title=tech + "_cross",
figsize=(560, 400),
chart_type="stock",
grid=True)
return
def ShowVersusCurrency(self, currency):
versusList = {}
for key in self.pairList.keys():
forward = key[:3]
backward = key[3:6]
strVs = 'VS. '
if forward == currency:
# 前半がキー
versusList[strVs + backward] = self.pairList[key]['Close']
elif backward == currency:
# 後半がキー
# 反転して格納
versusList[strVs + forward] = self.pairList[key]['Close'] * -1
df = pd.DataFrame(versusList)
display_charts(df,
chart_type="stock",
title=currency + ' ' + strVs,
grid=True)
return df
# Ensure we're in the correct directory
import os
# Import Data
# ===========
#
# Load data from Google Trends.
data = pd.read_csv('data/GoogleTrendsData.csv',
index_col='Date',
parse_dates=True)
data.head()
# Show DJIA vs. debt related query volume.
display_charts(data,
chart_type="stock",
title="DJIA vs. Debt Query Volume",
secondary_y="debt")
seaborn.lmplot("debt", "djia", data=data, size=7)
# Detect if search volume is increasing or decreasing in
# any given week by forming a moving average and testing if the current value
# crosses the moving average of the past 3 weeks.
#
# Let's first compute the moving average.
data['debt_mavg'] = data.debt.rolling(window=3, center=False).mean()
data.head()
# Since we want to see if the current value is above the moving average of the
# *preceeding* weeks, we have to shift the moving average timeseries forward by one.
if trade[i] > 0:
Position = True
elif Position:
PosPeriod += 1 # ポジションの期間をカウント
if trade[i] < 0:
if PosPeriod > 0:
Line[i] = -trade[i]
diff = (Line[i] - Line[i - PosPeriod]) / PosPeriod
for j in range(i - 1, i - PosPeriod, -1):
Line[j] = Line[j + 1] - diff # ポジションの期間を補間
PosPeriod = 0
Position = False
if trade[i] == 0 and not Position:
Line[i] = 'NaN'
return Line
long1 = Trade["Long"]
long = Position(long1)
#Chart
position = pd.DataFrame({
"Close": Close[1:],
"Long": long[1:]
}) #"Short":short, "UpSigma":UpSigma, "LowSigma":LowSigma
position = position[88000:89000]
display_charts(position,
title="Position",
figsize=(600, 400),
chart_type="stock",
grid=True)
if PosPeriod > 0:
Line[i] = -trade[i]
diff = (Line[i] - Line[i - PosPeriod]) / PosPeriod
for j in range(i - 1, i - PosPeriod, -1):
Line[j] = Line[j + 1] - diff # ポジションの期間を補間
PosPeriod = 0
Position = False
if trade[i] == 0 and not Position:
Line[i] = 'NaN'
return Line
plot = pd.DataFrame({'Equity': Equity + Initial})
display_charts(plot[:1000],
chart_type="stock",
title="Position",
figsize=(640, 480),
grid=True)
long1 = Trade["Long"]
short1 = Trade["Short"]
long = PositionLine(long1)
short = PositionLine(short1)
#Chart
position = pd.DataFrame({
"Open": Open,
"Long": long
}) #"Short":short, position = position[:1000]
display_charts(position,
title="Position",
figsize=(600, 400),
def BacktestReport(Trade, PL, HoldPro, Initial):
LongPL = PL['Long']
LongPLResult = LongPL.sum()
LongTrades = np.count_nonzero(Trade['Long']) // 2
LongWinTrades = np.count_nonzero(LongPL.clip_lower(0))
LongLoseTrades = np.count_nonzero(LongPL.clip_upper(0))
try:
AveProLong = LongPLResult / LongTrades
except:
print("Error")
ShortPL = PL['Short']
ShortPLResult = ShortPL.sum()
ShortTrades = np.count_nonzero(Trade['Short']) // 2
ShortWinTrades = np.count_nonzero(ShortPL.clip_lower(0))
ShortLoseTrades = np.count_nonzero(ShortPL.clip_upper(0))
try:
AveProShort = ShortPLResult / ShortTrades
except:
print("Error")
Trades = LongTrades + ShortTrades
WinTrades = LongWinTrades + ShortWinTrades
LoseTrades = LongLoseTrades + ShortLoseTrades
AssetChart = (LongPL + ShortPL).cumsum()
GrossProfit = LongPL.clip_lower(0).sum() + ShortPL.clip_lower(0).sum()
GrossLoss = LongPL.clip_upper(0).sum() + ShortPL.clip_upper(0).sum()
Profit = GrossProfit + GrossLoss
AvePro = Profit / Trades
Equity = (LongPL + ShortPL).cumsum()
Asset = Initial + Profit
ROI = (Asset - Initial) / Initial * 100
MDD = (Equity.cummax() - Equity).max()
vs = HoldPro - Profit
HoldIni = HoldPro + Initial
HoldROI = (HoldIni - Initial) / Initial * 100
print("Long")
print('買い数 :', LongTrades)
print('勝数 :', LongWinTrades)
print('最大勝 ￥:', LongPL.max())
try:
print('平均勝 ￥:', round(LongPL.clip_lower(0).sum() / LongWinTrades, 2))
except:
print("Error")
print('負数 :', LongLoseTrades)
print('最大負 ￥:', LongPL.min())
try:
print('平均負 ￥:', round(LongPL.clip_upper(0).sum() / LongLoseTrades, 2))
except:
print("Error")
print('損益 ￥:', round((LongPLResult), 2))
print('平均損益 ￥:', round((AveProLong), 2))
try:
print('勝率 :', round(LongWinTrades / LongTrades * 100, 2), '%\n')
except:
print("Error")
print("Short")
print('売り数 :', ShortTrades)
print('勝数 :', ShortWinTrades)
print('最大勝 ￥:', ShortPL.max())
try:
print('平均勝 ￥:', round(ShortPL.clip_lower(0).sum() / ShortWinTrades, 2))
except:
print("Error")
print('負数 :', ShortLoseTrades)
print('最大負 ￥:', ShortPL.min())
try:
print('平均負 ￥:',
round(ShortPL.clip_upper(0).sum() / ShortLoseTrades, 2))
except:
print("Error")
print('損益 ￥:', round((ShortPLResult), 2))
print('平均損益 ￥:', round((AveProShort), 2))
try:
print('勝率 :', round(ShortWinTrades / ShortTrades * 100, 2), '%\n')
except:
print("Error")
print("Total")
print('総数 :', Trades)
print('総勝数 :', WinTrades)
print('最大勝 ￥:', max(LongPL.max(), ShortPL.max()))
try:
print(
'平均勝 ￥:',
round((LongPL.clip_lower(0).sum() + ShortPL.clip_lower(0).sum()) /
WinTrades, 2))
except:
print("Error")
print('負数 :', LoseTrades)
print('最大負 ￥:', min(LongPL.min(), ShortPL.min()))
try:
print(
'平均負 ￥:',
round((LongPL.clip_upper(0).sum() + ShortPL.clip_upper(0).sum()) /
LoseTrades, 2))
except:
print("Error")
print('平均損益 ￥', round(AvePro, 2))
try:
print('勝率 :', round(WinTrades / Trades * 100, 2), '%\n')
except:
print("Error")
print("結果")
print('総損益 :', round(Profit, 2))
print('資産 :￥', Asset)
print('ROI :', round(ROI, 2), '%')
print('総利益 :', round(GrossProfit, 2))
print('総損失 :', round(GrossLoss, 2))
print('\n' '指標')
try:
print('Profit Factor :', round(-GrossProfit / GrossLoss, 2))
except:
print("Error")
print('最大ドローダウン :', round(MDD, 2))
print('Recovery Factor :', round(Profit / MDD, 2))
print("\n" "Hold Position")
print("Hold 損益 :￥", round(HoldPro, 2))
print("Hold 資産 :￥", round(HoldIni, 2))
print("Hold ROI :", round(HoldROI, 2), '%')
print("Hold vs Technical :￥", round(vs, 2))
display_charts(pd.DataFrame({"Assets": AssetChart + Initial}),
chart_type="stock",
title="資産_Chart",
figsize=(560, 400),
grid=True)
return
import json
data = pd.read_csv("G://gongxiang//busyZones.csv",
header=None,
names=("area", "counts"))
pre = pd.read_csv("G://gongxiang//kmresult2.csv",
header=None,
names=("lon", "lat"))
pre["area"] = pre.index
df = pd.merge(data, pre, on="area", how="left")
def foundloc(lon, lat):
url = "http://api.map.baidu.com/geocoder/v2/?location=%f,%f&output=json&ak=Yrf32LVk9DEHOYchZAQlG9nFICRTst5V" % (
lat, lon)
req = urllib.request.urlopen(url)
res = req.read().decode("utf-8")
temp = json.loads(res)
return temp["result"]["formatted_address"]
lon = list(df["lon"])
lat = list(df["lat"])
situation = zip(lon, lat)
situa = []
for i in situation:
situa.append(foundloc(i[0], i[1])[6:-1])
df["name"] = situa
df1 = df[["counts", "name"]]
df1 = df1.set_index("name")
display_charts(df1, title="区域打车次数")
def Show(self, pair):
df = pd.DataFrame({pair: self.pairList[pair]['Close']})
display_charts(df, chart_type="stock", title="MA cross", grid=True)
