def plot_contrast(self, moneyrecord1, moneyrecord2, date_ls, startdate,
enddate):
startdate = self.datetransfer(startdate)
date_ls_change = []
for i in date_ls:
if int(i) >= int(startdate) and int(i) <= int(enddate):
date_ls_change.append(i)
mondays = WeekdayLocator(MONDAY)
months = MonthLocator(range(1, 13), bymonthday=1, interval=3)
monthsFmt = DateFormatter("%b '%y")
print(date_ls_change)
#print(date_ls)
date = [str(e) for e in date_ls_change]
date_ls = [
datetime.datetime.strptime(d, '%Y%m%d').date() for d in date
]
algo_pv = moneyrecord1['money'].tolist()
print(algo_pv)
bench_pv = moneyrecord2['moneybenchmark'].tolist()
fig, ax = plt.subplots()
plt.gca().set_color_cycle(['blue', 'red'])
ax.plot_date(date_ls, algo_pv, '-')
ax.plot_date(date_ls, bench_pv, '-')
months.MAXTICKS = 5000
mondays.MAXTICKS = 5000
ax.xaxis.set_major_locator(months)
ax.xaxis.set_major_formatter(monthsFmt)
ax.xaxis.set_minor_locator(mondays)
ax.autoscale_view()
ax.grid(True)
fig.autofmt_xdate()
plt.title('P&L')
plt.legend(['strategy', 'benchmark'], loc='upper left')
plt.show()
def plot(outright_index, fly_index, hedged_index):
date = m["DateTime"].tolist()
outright_prices = m[outright_index].values.tolist()
fly_prices = m[fly_index].values.tolist()
hedged_prices = m[hedged_index].values.tolist()
upper_band = (m[hedged_index+"_mean"]+EntryStd*m[hedged_index+"_std"]).values.tolist()
lower_band = (m[hedged_index+"_mean"]-EntryStd*m[hedged_index+"_std"]).values.tolist()
buy_dates = [x[0] for x in trade_recorder[hedged_index].trades if x[2]>0]
buy_prices = [x[1] for x in trade_recorder[hedged_index].trades if x[2]>0]
sell_dates = [x[0] for x in trade_recorder[hedged_index].trades if x[2]<0]
sell_prices = [x[1] for x in trade_recorder[hedged_index].trades if x[2]<0]
fig, (ax1, ax2, ax3) = plt.subplots(3, sharex = True)
mondays = WeekdayLocator(MONDAY)
mondays.MAXTICKS = 2000
alldays = DayLocator() # minor ticks on the days
alldays.MAXTICKS = 2000
weekFormatter = DateFormatter('%b %d') # e.g., Jan 12
dayFormatter = DateFormatter('%d') # e.g., 12
ax1.xaxis.set_major_locator(mondays)
ax1.xaxis.set_minor_locator(alldays)
ax1.xaxis.set_major_formatter(weekFormatter)
ax1.plot(date, outright_prices)
ax2.plot(date, fly_prices)
ax3.plot(date, hedged_prices)
ax3.plot(date, upper_band, color='k')
ax3.plot(date, lower_band, color='k')
ax3.plot(buy_dates, buy_prices, "^", markersize = 5, color='m')
ax3.plot(sell_dates, sell_prices, "v", markersize = 5, color='k')
ax1.xaxis_date()
ax1.autoscale_view()
def plot_contrast(self,moneyrecord1,moneyrecord2,date_ls,startdate,enddate):
startdate=self.datetransfer(startdate)
date_ls_change=[]
for i in date_ls:
if int(i)>=int(startdate) and int(i)<=int(enddate):
date_ls_change.append(i)
mondays = WeekdayLocator(MONDAY)
months = MonthLocator(range(1, 13), bymonthday=1, interval=3)
monthsFmt = DateFormatter("%b '%y")
print(date_ls_change)
#print(date_ls)
date = [str(e) for e in date_ls_change]
date_ls = [datetime.datetime.strptime(d,'%Y%m%d').date() for d in date]
algo_pv=moneyrecord1['money'].tolist()
print(algo_pv)
bench_pv=moneyrecord2['moneybenchmark'].tolist()
fig, ax = plt.subplots()
plt.gca().set_color_cycle(['blue', 'red'])
ax.plot_date(date_ls, algo_pv,'-')
ax.plot_date(date_ls, bench_pv,'-')
months.MAXTICKS=5000
mondays.MAXTICKS=5000
ax.xaxis.set_major_locator(months)
ax.xaxis.set_major_formatter(monthsFmt)
ax.xaxis.set_minor_locator(mondays)
ax.autoscale_view()
ax.grid(True)
fig.autofmt_xdate()
plt.title('P&L')
plt.legend(['strategy', 'benchmark'], loc='upper left')
plt.show()
def plot_trade(self, symbol, init_index = None, end_index=None, PnL=False, ATR=False):
if init_index == None:
init_index = 0
init_date = b.bars[symbol][init_index]["D"]
if end_index == None:
end_index = len(b.bars[symbol])
end_date = b.bars[symbol][end_index-1]["D"]
mondays = WeekdayLocator(MONDAY)
mondays.MAXTICKS = 2000
alldays = DayLocator() # minor ticks on the days
alldays.MAXTICKS = 2000
weekFormatter = DateFormatter('%b %d') # e.g., Jan 12
dayFormatter = DateFormatter('%d') # e.g., 12
history = [(date2num(x["D"]), x["O"], x["H"], x["L"], x["C"]) for x in b.bars[symbol][init_index:end_index]]
if PnL or ATR:
fig, (ax, ax2) = plt.subplots(2, sharex = True)
else:
fig, ax = plt.subplots()
ax.xaxis.set_major_locator(mondays)
ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_formatter(weekFormatter)
candlestick_ohlc(ax, history)
buys = [(x["Date"], x["Price"]) for x in self.trades[symbol] if (x["Lots"] > 0 and x["Date"] > init_date and x["Date"]<end_date) ]
buy_dates, buy_values = zip(*buys)
ax.plot(buy_dates, buy_values, "^", markersize = 5, color='m')
sells = [(x["Date"], x["Price"]) for x in self.trades[symbol] if (x["Lots"] < 0 and x["Date"] > init_date and x["Date"]<end_date)]
sell_dates, sell_values = zip(*sells)
ax.plot(sell_dates, sell_values, "v", markersize = 5, color='k')
ax.xaxis_date()
ax.autoscale_view()
if PnL:
equity_history = [(date, record["equity"], record["drawdown"]) for date, record in self.history.items()]
dates, values, drawdowns = zip(*equity_history)
ax2 = fig.add_subplot(212)
ax2.plot(dates, values, 'b-')
elif ATR:
equity_history = [(x["D"], x["ATR"]) for x in self.bars[symbol][init_index:end_index]]
dates, values = zip(*equity_history)
ax2 = fig.add_subplot(212)
ax2.plot(dates, values, 'b-')
## ax3 = ax2.twinx()
## ax3.plot(dates, drawdowns, 'r-')
plt.show()
def plot_alpha(self, alpha, date_ls, startdate, enddate):
startdate = self.datetransfer(startdate)
date_ls_change = []
for i in date_ls:
if int(i) >= int(startdate) and int(i) <= int(enddate):
date_ls_change.append(i)
mondays = WeekdayLocator(MONDAY)
months = MonthLocator(range(1, 13), bymonthday=1, interval=3)
monthsFmt = DateFormatter("%b '%y")
#print(date_ls)
date = [str(e) for e in date_ls_change]
date_ls = [
datetime.datetime.strptime(d, '%Y%m%d').date() for d in date
]
algo_pv = alpha['alpha'].tolist()
#print(algo_pv)
fig, ax = plt.subplots()
plt.gca().set_color_cycle(['blue', 'red'])
ax.plot_date(date_ls, algo_pv, '-')
months.MAXTICKS = 5000
mondays.MAXTICKS = 5000
ax.xaxis.set_major_locator(months)
ax.xaxis.set_major_formatter(monthsFmt)
ax.xaxis.set_minor_locator(mondays)
ax.autoscale_view()
ax.grid(True)
fig.autofmt_xdate()
plt.title('Alpha')
plt.legend(['alpha'], loc='upper left')
plt.show()
#KJ_profit_df=pd.DataFrame(columns=[i/10 for i in range(1,121)])
#for K in list_K:
#for J in list_J:
#KJ=B(cash,account,startdate,enddate,K,J)
#KJ_total_portfolio=KJ.test(startdate,enddate,K,J,cash)
#KJ_profit_df.loc[10*J-1,K]=KJ_total_portfolio
#KJ_profit_df.to_csv('KJ_finalprofit.csv')
def plot_alpha(self,alpha,date_ls,startdate,enddate):
startdate=self.datetransfer(startdate)
date_ls_change=[]
for i in date_ls:
if int(i)>=int(startdate) and int(i)<=int(enddate):
date_ls_change.append(i)
mondays = WeekdayLocator(MONDAY)
months = MonthLocator(range(1, 13), bymonthday=1, interval=3)
monthsFmt = DateFormatter("%b '%y")
#print(date_ls)
date = [str(e) for e in date_ls_change]
date_ls = [datetime.datetime.strptime(d,'%Y%m%d').date() for d in date]
algo_pv=alpha['alpha'].tolist()
#print(algo_pv)
fig, ax = plt.subplots()
plt.gca().set_color_cycle(['blue', 'red'])
ax.plot_date(date_ls, algo_pv,'-')
months.MAXTICKS=5000
mondays.MAXTICKS=5000
ax.xaxis.set_major_locator(months)
ax.xaxis.set_major_formatter(monthsFmt)
ax.xaxis.set_minor_locator(mondays)
ax.autoscale_view()
ax.grid(True)
fig.autofmt_xdate()
plt.title('Alpha')
plt.legend(['alpha'], loc='upper left')
plt.show()
#KJ_profit_df=pd.DataFrame(columns=[i/10 for i in range(1,121)])
#for K in list_K:
#for J in list_J:
#KJ=B(cash,account,startdate,enddate,K,J)
#KJ_total_portfolio=KJ.test(startdate,enddate,K,J,cash)
#KJ_profit_df.loc[10*J-1,K]=KJ_total_portfolio
#KJ_profit_df.to_csv('KJ_finalprofit.csv')