Double 7's (Short Term Trading Strategies that Work)

1. The SPY is above its 200-day moving average or X-day ma
2. The SPY closes at a 7-day low, buy.
3. If the SPY closes at a 7-day high, sell your long position.



In [1]:

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

import pinkfish as pf
import strategy

# 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)

Some global data



In [3]:

    
#symbol = '^GSPC'
symbol = 'SPY'
#symbol = 'DIA'
#symbol = 'QQQ'
#symbol = 'IWM'
#symbol = 'TLT'
#symbol = 'GLD'
#symbol = 'AAPL'
#symbol = 'BBRY'
#symbol = 'GDX'
#symbol = 'OIH'
capital = 10000
start = datetime.datetime(1900, 1, 1)
start = datetime.datetime.strptime(pf.SP500_BEGIN, '%Y-%m-%d')
end = datetime.datetime.now()

Define high low trade periods



In [4]:

    
period = 7

Run Strategy



In [5]:

    
s = strategy.Strategy(symbol, capital, start, end, period, sma=70, stop_loss_pct=85, margin=1.5)
s.run()

Retrieve log DataFrames



In [6]:

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



In [7]:

    
tlog.tail()









    Out[7]:







  
    
      
      entry_date
      entry_price
      exit_date
      exit_price
      pl_points
      pl_cash
      qty
      cumul_total
      direction
      symbol
    
  
  
    
      285
      2019-12-03
      304.89
      2019-12-12
      312.36
      7.47
      10235.89
      1371
      278999.14
      LONG
      SPY
    
    
      286
      2020-01-27
      320.20
      2020-02-04
      325.70
      5.50
      7445.92
      1353
      286445.06
      LONG
      SPY
    
    
      287
      2020-02-21
      330.08
      2020-03-04
      309.67
      -20.41
      -27491.82
      1347
      258953.24
      LONG
      SPY
    
    
      288
      2020-06-11
      299.29
      2020-06-23
      312.05
      12.76
      17183.75
      1347
      276136.99
      LONG
      SPY
    
    
      289
      2020-06-24
      304.09
      2020-07-02
      312.23
      8.14
      11485.56
      1411
      287622.55
      LONG
      SPY



In [8]:

    
dbal.tail()

Generate strategy stats - display all available stats



In [9]:

    
pf.print_full(stats)









    



start                                                  1993-11-11
end                                                    2020-07-15
beginning_balance                                           10000
ending_balance                                          297622.55
total_net_profit                                        287622.55
gross_profit                                            517448.86
gross_loss                                             -229826.31
profit_factor                                                2.25
return_on_initial_capital                                 2876.23
annual_return_rate                                          13.56
trading_period                           26 years 8 months 4 days
pct_time_in_market                                          32.00
margin                                                       1.50
avg_leverage                                                 1.16
max_leverage                                                 1.63
min_leverage                                                 1.00
total_num_trades                                              290
trades_per_year                                             10.87
num_winning_trades                                            229
num_losing_trades                                              60
num_even_trades                                                 1
pct_profitable_trades                                       78.97
avg_profit_per_trade                                       991.80
avg_profit_per_winning_trade                              2259.60
avg_loss_per_losing_trade                                -3830.44
ratio_avg_profit_win_loss                                    0.59
largest_profit_winning_trade                             17183.75
largest_loss_losing_trade                               -27491.82
num_winning_points                                         400.80
num_losing_points                                         -169.49
total_net_points                                           231.30
avg_points                                                   0.80
largest_points_winning_trade                                12.76
largest_points_losing_trade                                -20.41
avg_pct_gain_per_trade                                       0.82
largest_pct_winning_trade                                    6.92
largest_pct_losing_trade                                   -10.05
max_consecutive_winning_trades                                 20
max_consecutive_losing_trades                                   2
avg_bars_winning_trades                                      6.66
avg_bars_losing_trades                                      15.10
max_closed_out_drawdown                                    -22.82
max_closed_out_drawdown_start_date                     2011-05-10
max_closed_out_drawdown_end_date                       2011-08-08
max_closed_out_drawdown_recovery_date                  2012-06-29
drawdown_recovery                                           -0.25
drawdown_annualized_return                                  -1.68
max_intra_day_drawdown                                     -24.87
avg_yearly_closed_out_drawdown                             -10.18
max_yearly_closed_out_drawdown                             -22.82
avg_monthly_closed_out_drawdown                             -2.40
max_monthly_closed_out_drawdown                            -21.06
avg_weekly_closed_out_drawdown                              -0.79
max_weekly_closed_out_drawdown                             -19.38
avg_yearly_closed_out_runup                                 22.49
max_yearly_closed_out_runup                                 68.15
avg_monthly_closed_out_runup                                 3.27
max_monthly_closed_out_runup                                20.13
avg_weekly_closed_out_runup                                  1.07
max_weekly_closed_out_runup                                 12.18
pct_profitable_years                                        86.46
best_year                                                   66.86
worst_year                                                 -17.67
avg_year                                                    14.52
annual_std                                                  13.75
pct_profitable_months                                       58.29
best_month                                                  20.13
worst_month                                                -20.38
avg_month                                                    1.07
monthly_std                                                  3.36
pct_profitable_weeks                                        31.99
best_week                                                   12.18
worst_week                                                 -19.38
avg_week                                                     0.27
weekly_std                                                   1.93
sharpe_ratio                                                 0.89
sortino_ratio                                                0.70
dtype: object

Equity curve

Run Benchmark, Retrieve benchmark logs, and Generate benchmark stats



In [10]:

    
benchmark = pf.Benchmark(symbol, capital, s._start, s._end)
benchmark.run()
benchmark.tlog, benchmark.dbal = benchmark.get_logs()
benchmark.stats = benchmark.get_stats()









    



1993-11-11 00:00:00 BUY  215 SPY @ 46.38
2020-07-15 00:00:00 SELL 215 SPY @ 321.85

Plot Equity Curves: Strategy vs Benchmark



In [11]:

    
pf.plot_equity_curve(dbal, benchmark=benchmark.dbal)

Plot Trades



In [12]:

    
pf.plot_trades(dbal, benchmark=benchmark.dbal)

Bar Graph: Strategy vs Benchmark



In [13]:

    
df = pf.plot_bar_graph(stats, benchmark.stats)
df









    Out[13]:







  
    
      
      strategy
      benchmark
    
  
  
    
      annual_return_rate
      13.56
      7.52
    
    
      max_closed_out_drawdown
      -22.82
      -56.42
    
    
      drawdown_annualized_return
      -1.68
      -7.50
    
    
      drawdown_recovery
      -0.25
      -1.42
    
    
      best_month
      20.13
      23.06
    
    
      worst_month
      -20.38
      -31.38
    
    
      sharpe_ratio
      0.89
      0.48
    
    
      sortino_ratio
      0.70
      0.60
    
    
      monthly_std
      3.36
      4.54



In [14]:

    
returns = dbal['close']
returns.tail()









    Out[14]:





date
2020-07-09   297622.55
2020-07-10   297622.55
2020-07-13   297622.55
2020-07-14   297622.55
2020-07-15   297622.55
Name: close, dtype: float64



In [15]:

    
benchmark_returns = benchmark.dbal['close']
benchmark_returns.tail()









    Out[15]:





date
2020-07-09   67621.08
2020-07-10   68311.22
2020-07-13   67719.97
2020-07-14   68597.18
2020-07-15   69227.13
Name: close, dtype: float64



In [16]:

    
pf.prettier_graphs(returns, benchmark_returns, label1='Strategy', label2='Benchmark', points_to_plot=5000)

	entry_date	entry_price	exit_date	exit_price	pl_points	pl_cash	qty	cumul_total	direction	symbol
285	2019-12-03	304.89	2019-12-12	312.36	7.47	10235.89	1371	278999.14	LONG	SPY
286	2020-01-27	320.20	2020-02-04	325.70	5.50	7445.92	1353	286445.06	LONG	SPY
287	2020-02-21	330.08	2020-03-04	309.67	-20.41	-27491.82	1347	258953.24	LONG	SPY
288	2020-06-11	299.29	2020-06-23	312.05	12.76	17183.75	1347	276136.99	LONG	SPY
289	2020-06-24	304.09	2020-07-02	312.23	8.14	11485.56	1411	287622.55	LONG	SPY

	high	low	close	shares	cash	leverage	state
date
2020-07-09	297622.55	297622.55	297622.55	0	297622.55	1.00	-
2020-07-10	297622.55	297622.55	297622.55	0	297622.55	1.00	-
2020-07-13	297622.55	297622.55	297622.55	0	297622.55	1.00	-
2020-07-14	297622.55	297622.55	297622.55	0	297622.55	1.00	-
2020-07-15	297622.55	297622.55	297622.55	0	297622.55	1.00	-

	strategy	benchmark
annual_return_rate	13.56	7.52
max_closed_out_drawdown	-22.82	-56.42
drawdown_annualized_return	-1.68	-7.50
drawdown_recovery	-0.25	-1.42
best_month	20.13	23.06
worst_month	-20.38	-31.38
sharpe_ratio	0.89	0.48
sortino_ratio	0.70	0.60
monthly_std	3.36	4.54