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_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 formatAxticks(ax):
days = DayLocator() # every month
months = MonthLocator() # every month
months.MAXTICKS = 3000
yearsFmt = DateFormatter('%d/%m/%Y')
ax.xaxis.set_major_locator(months)
ax.xaxis.set_minor_locator(days)
ax.xaxis.set_major_formatter(yearsFmt)
ax.autoscale_view()
ticks = ax.get_xticks()
n = len(ticks)/4
ax.set_xticks(ticks[::n])
return ax
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')
