buy-and-hold (monthly and holding period returns)

In [1]:

    

import pandas as pd
import matplotlib.pyplot as plt
import datetime
from talib.abstract import *

import pinkfish as pf

# format price data
pd.options.display.float_format = '{:0.2f}'.format

%matplotlib inline


    

In [2]:

    

# set size of inline plots
'''note: rcParams can't be in same cell as import matplotlib
   or %matplotlib inline
   
   %matplotlib notebook: will lead to interactive plots embedded within
   the notebook, you can zoom and resize the figure
   
   %matplotlib inline: only draw static images in the notebook
'''
plt.rcParams["figure.figsize"] = (10, 7)


    

In [3]:

    

pf.DEBUG = True


    

In [4]:

    

symbol = '^GSPC'
#symbol = 'SPY'
capital = 10000
start = datetime.datetime(1900, 1, 1)
end = datetime.datetime.now()


    

In [5]:

    

class Strategy:

    def __init__(self, symbol, capital, start, end):
        self._symbol = symbol
        self._capital = capital
        self._start = start
        self._end = end

    def _algo(self):
        pf.TradeLog.cash = self._capital

        for i, row in enumerate(self._ts.itertuples()):

            date = row.Index.to_pydatetime()
            high = row.high; low = row.low; close = row.close 
            end_flag = pf.is_last_row(self._ts, i)
            shares = 0

            # buy
            if self._tlog.shares == 0:
                shares = self._tlog.buy(date, close)
            # sell
            elif end_flag:
                shares = self._tlog.sell(date, close)

            if shares > 0:
                pf.DBG("{0} BUY  {1} {2} @ {3:.2f}".format(
                       date, shares, self._symbol, close))
            elif shares < 0:
                pf.DBG("{0} SELL {1} {2} @ {3:.2f}".format(
                       date, -shares, self._symbol, close))

            # record daily balance
            self._dbal.append(date, high, low, close)

    def run(self):
        self._ts = pf.fetch_timeseries(self._symbol)
        self._ts = pf.select_tradeperiod(self._ts, self._start, self._end,
                                         use_adj=True)
        self._ts, self._start = pf.finalize_timeseries(self._ts, self._start)
        self._tlog = pf.TradeLog(self._symbol)
        self._dbal = pf.DailyBal()

        self._algo()

    def get_logs(self):
        """ return DataFrames """
        self.tlog = self._tlog.get_log()
        self.dbal = self._dbal.get_log(self.tlog)
        return self.tlog, self.dbal

    def get_stats(self):
        stats = pf.stats(self._ts, self.tlog, self.dbal, self._capital)
        return stats


    

In [6]:

    

s = Strategy(symbol, capital, start, end)
s.run()


    

    




1927-12-30 00:00:00 BUY  566 ^GSPC @ 17.66
2020-07-17 00:00:00 SELL 566 ^GSPC @ 3224.73

In [7]:

    

tlog, dbal = s.get_logs()
stats = s.get_stats()


    

In [8]:

    

tlog.tail()


    

    
Out[8]:







  

    

      

      
entry_date
      
entry_price
      
exit_date
      
exit_price
      
pl_points
      
pl_cash
      
qty
      
cumul_total
      
direction
      
symbol
    
  
  

    

      
0
      
1927-12-30
      
17.66
      
2020-07-17
      
3224.73
      
3207.07
      
1815201.61
      
566
      
1815201.61
      
LONG
      
^GSPC
    
  

In [9]:

    

dbal.tail()


    

    
Out[9]:







  

    

      

      
high
      
low
      
close
      
shares
      
cash
      
leverage
      
state
    
    

      
date
      

      

      

      

      

      

      

    
  
  

    

      
2020-07-13
      
1831195.60
      
1782581.78
      
1785858.94
      
566
      
4.44
      
1.00
      
-
    
    

      
2020-07-14
      
1811742.11
      
1770259.95
      
1809800.77
      
566
      
4.44
      
1.00
      
-
    
    

      
2020-07-15
      
1832870.94
      
1811634.61
      
1826237.43
      
566
      
4.44
      
1.00
      
-
    
    

      
2020-07-16
      
1822745.12
      
1810406.43
      
1820017.10
      
566
      
4.44
      
1.00
      
-
    
    

      
2020-07-17
      
1825201.61
      
1825201.61
      
1825201.61
      
0
      
1825201.61
      
1.00
      
X
    
  

In [10]:

    

pf.print_full(stats)


    

    




start                                                   1927-12-30
end                                                     2020-07-17
beginning_balance                                            10000
ending_balance                                          1825201.61
total_net_profit                                        1815201.61
gross_profit                                            1815201.61
gross_loss                                                    0.00
profit_factor                                                 1000
return_on_initial_capital                                 18152.02
annual_return_rate                                            5.79
trading_period                           92 years 6 months 17 days
pct_time_in_market                                          100.00
margin                                                           1
avg_leverage                                                  1.00
max_leverage                                                  1.00
min_leverage                                                  1.00
total_num_trades                                                 1
trades_per_year                                               0.01
num_winning_trades                                               1
num_losing_trades                                                0
num_even_trades                                                  0
pct_profitable_trades                                       100.00
avg_profit_per_trade                                    1815201.61
avg_profit_per_winning_trade                            1815201.61
avg_loss_per_losing_trade                                        0
ratio_avg_profit_win_loss                                     1000
largest_profit_winning_trade                            1815201.61
largest_loss_losing_trade                                        0
num_winning_points                                         3207.07
num_losing_points                                                0
total_net_points                                           3207.07
avg_points                                                 3207.07
largest_points_winning_trade                               3207.07
largest_points_losing_trade                                      0
avg_pct_gain_per_trade                                    18160.08
largest_pct_winning_trade                                 18160.08
largest_pct_losing_trade                                         0
max_consecutive_winning_trades                                   1
max_consecutive_losing_trades                                    0
avg_bars_winning_trades                                   23246.00
avg_bars_losing_trades                                           0
max_closed_out_drawdown                                     -86.17
max_closed_out_drawdown_start_date                      1929-09-16
max_closed_out_drawdown_end_date                        1932-06-01
max_closed_out_drawdown_recovery_date                   1954-09-22
drawdown_recovery                                            -2.71
drawdown_annualized_return                                  -14.89
max_intra_day_drawdown                                      -86.17
avg_yearly_closed_out_drawdown                              -15.98
max_yearly_closed_out_drawdown                              -71.30
avg_monthly_closed_out_drawdown                              -4.21
max_monthly_closed_out_drawdown                             -42.18
avg_weekly_closed_out_drawdown                               -1.62
max_weekly_closed_out_drawdown                              -28.51
avg_yearly_closed_out_runup                                  26.39
max_yearly_closed_out_runup                                 176.33
avg_monthly_closed_out_runup                                  4.91
max_monthly_closed_out_runup                                 61.42
avg_weekly_closed_out_runup                                   1.79
max_weekly_closed_out_runup                                  26.54
pct_profitable_years                                         68.94
best_year                                                   170.81
worst_year                                                  -71.04
avg_year                                                      7.68
annual_std                                                   20.14
pct_profitable_months                                        59.75
best_month                                                   61.42
worst_month                                                 -42.18
avg_month                                                     0.59
monthly_std                                                   5.35
pct_profitable_weeks                                         56.03
best_week                                                    25.86
worst_week                                                  -27.72
avg_week                                                      0.15
weekly_std                                                    2.62
sharpe_ratio                                                  0.39
sortino_ratio                                                 0.49
dtype: object

In [11]:

    

pf.summary(stats)


    

    
Out[11]:







  

    

      

      
strategy
    
  
  

    

      
annual_return_rate
      
5.79
    
    

      
max_closed_out_drawdown
      
-86.17
    
    

      
best_month
      
61.42
    
    

      
worst_month
      
-42.18
    
    

      
sharpe_ratio
      
0.39
    
    

      
sortino_ratio
      
0.49
    
    

      
monthly_std
      
5.35
    
  

In [12]:

    

returns = dbal['close']
pf.monthly_returns_map(returns['1990':])


    

    






    

    

    

    
Year
    
Jan
    
Feb
    
Mar
    
Apr
    
May
    
Jun
    
Jul
    
Aug
    
Sep
    
Oct
    
Nov
    
Dec
    
Year
    
    
    

    
1990
-8.5
0.9
2.4
-2.7
9.2
-0.9
-0.5
-9.4
-5.1
-0.7
6.0
2.5
-8.2

 
 
1991
4.2
6.7
2.2
0.0
3.9
-4.8
4.5
2.0
-1.9
1.2
-4.4
11.2
26.3

 
 
1992
-2.0
1.0
-2.2
2.8
0.1
-1.7
3.9
-2.4
0.9
0.2
3.0
1.0
4.5

 
 
1993
0.7
1.0
1.9
-2.5
2.3
0.1
-0.5
3.4
-1.0
1.9
-1.3
1.0
7.1

 
 
1994
3.3
-3.0
-4.6
1.2
1.2
-2.7
3.1
3.8
-2.7
2.1
-4.0
1.2
-1.5

 
 
1995
2.4
3.6
2.7
2.8
3.6
2.1
3.2
-0.0
4.0
-0.5
4.1
1.7
34.1

 
 
1996
3.3
0.7
0.8
1.3
2.3
0.2
-4.6
1.9
5.4
2.6
7.3
-2.2
20.3

 
 
1997
6.1
0.6
-4.3
5.8
5.9
4.3
7.8
-5.7
5.3
-3.4
4.5
1.6
31.0

 
 
1998
1.0
7.0
5.0
0.9
-1.9
3.9
-1.2
-14.6
6.2
8.0
5.9
5.6
26.7

 
 
1999
4.1
-3.2
3.9
3.8
-2.5
5.4
-3.2
-0.6
-2.9
6.3
1.9
5.8
19.5

 
 
2000
-5.1
-2.0
9.7
-3.1
-2.2
2.4
-1.6
6.1
-5.3
-0.5
-8.0
0.4
-10.1

 
 
2001
3.5
-9.2
-6.4
7.7
0.5
-2.5
-1.1
-6.4
-8.2
1.8
7.5
0.8
-13.0

 
 
2002
-1.6
-2.1
3.7
-6.1
-0.9
-7.2
-7.9
0.5
-11.0
8.6
5.7
-6.0
-23.4

 
 
2003
-2.7
-1.7
0.8
8.1
5.1
1.1
1.6
1.8
-1.2
5.5
0.7
5.1
26.4

 
 
2004
1.7
1.2
-1.6
-1.7
1.2
1.8
-3.4
0.2
0.9
1.4
3.9
3.2
9.0

 
 

    

    

    

    
Year
    
Jan
    
Feb
    
Mar
    
Apr
    
May
    
Jun
    
Jul
    
Aug
    
Sep
    
Oct
    
Nov
    
Dec
    
Year
    
    
    

    
2005
-2.5
1.9
-1.9
-2.0
3.0
-0.0
3.6
-1.1
0.7
-1.8
3.5
-0.1
3.0

 
 
2006
2.5
0.0
1.1
1.2
-3.1
0.0
0.5
2.1
2.5
3.2
1.6
1.3
13.6

 
 
2007
1.4
-2.2
1.0
4.3
3.3
-1.8
-3.2
1.3
3.6
1.5
-4.4
-0.9
3.5

 
 
2008
-6.1
-3.5
-0.6
4.8
1.1
-8.6
-1.0
1.2
-9.1
-16.9
-7.5
0.8
-38.5

 
 
2009
-8.6
-11.0
8.5
9.4
5.3
0.0
7.4
3.4
3.6
-2.0
5.7
1.8
23.5

 
 
2010
-3.7
2.9
5.9
1.5
-8.2
-5.4
6.9
-4.7
8.8
3.7
-0.2
6.5
12.8

 
 
2011
2.3
3.2
-0.1
2.8
-1.4
-1.8
-2.1
-5.7
-7.2
10.8
-0.5
0.9
-0.0

 
 
2012
4.4
4.1
3.1
-0.7
-6.3
4.0
1.3
2.0
2.4
-2.0
0.3
0.7
13.4

 
 
2013
5.0
1.1
3.6
1.8
2.1
-1.5
4.9
-3.1
3.0
4.5
2.8
2.4
29.6

 
 
2014
-3.6
4.3
0.7
0.6
2.1
1.9
-1.5
3.8
-1.6
2.3
2.5
-0.4
11.4

 
 
2015
-3.1
5.5
-1.7
0.9
1.0
-2.1
2.0
-6.3
-2.6
8.3
0.1
-1.8
-0.7

 
 
2016
-5.1
-0.4
6.6
0.3
1.5
0.1
3.6
-0.1
-0.1
-1.9
3.4
1.8
9.5

 
 
2017
1.8
3.7
-0.0
0.9
1.2
0.5
1.9
0.1
1.9
2.2
2.8
1.0
19.4

 
 
2018
5.6
-3.9
-2.7
0.3
2.2
0.5
3.6
3.0
0.4
-6.9
1.8
-9.2
-6.2

 
 
2019
7.9
3.0
1.8
3.9
-6.6
6.9
1.3
-1.8
1.7
2.0
3.4
2.9
28.9

 
 

    

    

    

    
Year
    
Jan
    
Feb
    
Mar
    
Apr
    
May
    
Jun
    
Jul
    
Aug
    
Sep
    
Oct
    
Nov
    
Dec
    
Year
    
    
    

    
2020
-0.2
-8.4
-12.5
12.7
4.5
1.8
4.0
-
-
-
-
-
-0.2

 
 

 
 
 

In [13]:

    

returns = dbal['close']
pf.holding_period_map(returns['1990':])


    

    





Years
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
1990
-8
8
7
7
5
9
11
13
15
15
13
10
7
8
8
8
8
8
5
6
6
6
6
7
7
7
7
7
7
8
7
1991
26
15
12
9
13
14
17
18
18
15
12
9
10
10
9
10
9
6
7
7
7
7
8
8
8
8
8
8
8
8
1992
4
6
3
10
12
15
17
17
14
11
7
9
9
8
9
8
5
6
6
6
6
7
7
7
7
7
7
8
7
1993
7
3
12
14
17
19
19
15
11
7
9
9
8
9
8
5
6
6
6
6
7
7
7
7
8
7
8
7
1994
-2
15
17
20
21
21
16
12
7
9
9
9
9
9
5
6
6
6
6
7
7
7
7
8
7
8
7
1995
34
27
28
28
26
19
14
8
10
10
10
10
9
5
6
6
6
6
8
8
7
7
8
7
8
8
1996
20
26
26
24
16
11
5
8
8
7
8
8
3
4
5
5
5
6
7
6
6
7
6
7
7
1997
31
29
26
16
9
3
6
6
6
7
6
2
3
4
4
4
6
6
5
6
6
6
7
6
1998
27
23
11
4
-2
2
3
3
4
4
-1
1
2
2
3
4
5
4
4
5
5
6
5
1999
20
4
-2
-8
-2
-0
0
2
2
-3
-1
0
0
1
3
3
3
3
4
4
5
4
2000
-10
-12
-16
-7
-4
-3
-1
-0
-5
-3
-1
-1
-0
2
2
2
3
3
3
4
4
2001
-13
-18
-6
-2
-1
1
2
-5
-2
-0
-0
1
3
3
3
3
4
4
5
5
2002
-23
-2
2
2
4
4
-3
-0
1
1
2
4
5
4
5
5
5
6
6
2003
26
17
12
13
11
0
3
5
4
5
7
7
7
7
8
7
8
7
2004
9
6
8
7
-4
0
2
2
3
5
6
5
6
6
6
7
6
2005
3
8
7
-7
-2
1
1
2
5
5
5
5
6
5
7
6
2006
14
8
-10
-3
0
0
2
5
6
5
5
7
6
7
7
2007
4
-20
-8
-3
-2
0
4
5
4
5
6
5
7
6
2008
-38
-13
-5
-4
-1
4
5
4
5
6
5
7
6
2009
23
18
12
12
15
15
12
12
13
11
12
11
2010
13
6
9
13
13
11
10
12
9
11
10
2011
-0
6
14
13
10
10
11
9
11
10
2012
13
21
18
13
12
13
10
13
11
2013
30
20
13
12
13
10
12
11
2014
11
5
7
10
6
10
8
2015
-1
4
9
5
9
8
2016
10
14
7
12
10
2017
19
6
13
10
2018
-6
10
6
2019
29
13
2020
-0