Please check new version at https://github.com/ysdede/jesse-tk
cd into project
pip install -e .You can use ewoexit2rt strategy to test this tool.
We already have a ~4500 lines optimization log file located at
storage/genetics/ewoexit-Binance Futures-ETH-USDT-15m-2021-02-01-2021-08-25.txt
Running jesse-picker with pick parameter selects and sorts dna strings with given options.
jesse-picker pick log_file_name sort_criteria n1 n2
pnl1: Sort by PNL1, optimization phase pnl
pnl2: Sort by PNL2, test (short) phase pnl
wr1: Sort by winrate1, optimization phase winrate
wr2: Sort by winrate2, test (short) phase winrate
n1, n2: pick best performing n dnas from lists. Enter huge numbers to get all dnas. TODO: it should be improved.
eg:
G:\ewoexit2>jesse-picker pick "storage/genetics/ewoexit-Binance Futures-ETH-USDT-15m-2021-02-01-2021-08-25.txt" pnl2 100 500Output:
Strategy name: ewoexitRestore Strat Class: <class 'strategies.ewoexitRestore.ewoexitRestore'>
Total 403 unique dnas found.
Picked dnas count: 403
Validated dna file. 403/403This will create a python file containing selected dnas at jessepickerdata\dnafiles\strategyname+dnas.py
eg: 'jessepickerdata\dnafiles\ewoexitRestorednas.py'
[dna_string, win_rate1, total_trades_1, pnl_1, win_rate_2, total_trades_2, pnl_2, dict {optimization parameters as name: value pairs}],
dnas = [
['*qDIIT)@q', 35, 115, 437.73, 36, 22, 4.13, {'stop': 12, 'treshold': 47, 'ewoshort': 13, 'ewolong': 37, 'chop_rsi': 14, 'chop_band_width': 84, 'trend_ema_len': 5, 'exit_ema_fast': 4, 'exit_ema_slow': 233}],
['(UDD0p)vq', 29, 133, 394.14, 17, 29, 10.99, {'stop': 10, 'treshold': 33, 'ewoshort': 13, 'ewolong': 34, 'chop_rsi': 5, 'chop_band_width': 137, 'trend_ema_len': 5, 'exit_ema_fast': 10, 'exit_ema_slow': 233}],
['(qDIIT)5q', 31, 134, 380.21, 33, 24, 2.96, {'stop': 10, 'treshold': 47, 'ewoshort': 13, 'ewolong': 37, 'chop_rsi': 14, 'chop_band_width': 84, 'trend_ema_len': 5, 'exit_ema_fast': 3, 'exit_ema_slow': 233}],
['(UDDIN)vq', 30, 120, 372.69, 35, 20, 29.32, {'stop': 10, 'treshold': 33, 'ewoshort': 13, 'ewolong': 34, 'chop_rsi': 14, 'chop_band_width': 73, 'trend_ema_len': 5, 'exit_ema_fast': 10, 'exit_ema_slow': 233}],
# .
# .
['PU4aB^[6v', 34, 63, 166.92, 72, 11, 27.0, {'stop': 45, 'treshold': 33, 'ewoshort': 7, 'ewolong': 49, 'chop_rsi': 11, 'chop_band_width': 103, 'trend_ema_len': 106, 'exit_ema_fast': 3, 'exit_ema_slow': 247}],
['(<Xt;@vYv', 24, 79, 161.85, 38, 13, 28.08, {'stop': 10, 'treshold': 20, 'ewoshort': 19, 'ewolong': 58, 'chop_rsi': 9, 'chop_band_width': 46, 'trend_ema_len': 161, 'exit_ema_fast': 7, 'exit_ema_slow': 247}],
['(nX[;@vYv', 20, 97, 152.71, 43, 16, 32.89, {'stop': 10, 'treshold': 45, 'ewoshort': 19, 'ewolong': 46, 'chop_rsi': 9, 'chop_band_width': 46, 'trend_ema_len': 161, 'exit_ema_fast': 7, 'exit_ema_slow': 247}],
['r42OV8u?a', 46, 89, 103.59, 57, 21, 9.33, {'stop': 76, 'treshold': 16, 'ewoshort': 6, 'ewolong': 40, 'chop_rsi': 18, 'chop_band_width': 31, 'trend_ema_len': 159, 'exit_ema_fast': 4, 'exit_ema_slow': 186}],
]We've created a general-purpose dna file that we can use to find the best dnas fit for a given pair.
Replace the dna strings in routes.py with anchor. (don't search for table flipping emoji online, it will print it out with error a message at first run.
routes.py example:
routes = [
('FTX Futures', 'ETH-USD', '15m', 'ewoexitRestore', '(╯°□°)╯︵ ┻━┻'),
]
extra_candles = [
('FTX Futures', 'ETH-USD', '1h'),
]run
G:\ewoexit2>jesse-picker refine jessepickerdata/dnafiles/ewoexitRestorednas.py 2021-06-01 2021-09-0335/403
Pair TF Dna Total Total Net Max. Annual Win Sharpe Calmar Winning Losing Largest Largest Winning Losing Market
Trades Profit % DD % Return % Rate % Ratio Ratio Streak Streak Win. Trade Los. Trade Trades Trades Change %
ETH-USD 15m AQTB<3v2v 56 38.83 -6.0 178 45 3.08 29.7 5 6 1138 -234 25 31 8.78
ETH-USD 15m A`TB<3v2v 56 38.83 -6.0 178 45 3.08 29.7 5 6 1138 -234 25 31 8.78
ETH-USD 15m fDTG<3v2v 50 43.5 -7.63 209 50 3.47 27.35 5 5 1126 -283 25 25 8.78
ETH-USD 15m YUT@;>t6v 52 39.97 -7.12 185 48 3.12 26.05 5 5 1138 -370 25 27 8.78
ETH-USD 15m YDTB;3q2v 53 38.36 -6.8 175 45 3.03 25.77 5 6 1120 -366 24 29 8.78
ETH-USD 15m pqGI(Ca@v 47 38.13 -6.83 174 51 2.98 25.48 5 6 1090 -270 24 23 8.78
ETH-USD 15m ?UTD<<vvv 47 40.0 -7.38 186 49 3.1 25.16 8 7 1147 -222 23 24 8.78
ETH-USD 15m =UTD<<vvv 48 38.29 -7.18 175 48 2.99 24.36 8 7 1153 -212 23 25 8.78
ETH-USD 15m VbT?<;vGv 49 38.39 -7.28 176 49 3.0 24.13 5 5 1114 -353 24 25 8.78
ETH-USD 15m rqTI<Tv0v 45 41.96 -8.79 198 49 3.46 22.57 5 7 1108 -283 22 23 8.78
ETH-USD 15m VbT?<;v,v 56 34.44 -6.78 152 45 2.79 22.39 4 6 990 -342 25 31 8.78
ETH-USD 15m 1bT?<;vuv 57 35.82 -7.46 160 42 2.83 21.42 5 8 1141 -132 24 33 8.78
ETH-USD 15m pqGIFCi@v 47 39.08 -8.52 180 51 3.09 21.12 5 6 1073 -275 24 23 8.78
ETH-USD 15m YDYB;3r2v 50 35.31 -7.5 157 50 3.02 20.92 5 5 722 -270 25 25 8.78
ETH-USD 15m YDYB;3l2v 51 35.07 -7.5 155 49 3.0 20.74 5 6 722 -270 25 26 8.78
ETH-USD 15m mqTW;Cv@r 48 32.84 -7.07 143 46 2.8 20.16 5 5 1067 -283 22 26 8.78
ETH-USD 15m f^TB<3v2v 52 37.55 -8.69 170 46 2.95 19.6 5 6 1120 -447 24 28 8.78
It will test all dnas given in dna file with routes.
It will create a new dna file sorted by Calmar at jessepickerdata/dnafiles/ETH-USD 2021-09-01 2021-09-25.py
You can use this as input dna file in the future refinements.
I chose =bdOSb@l3 because I made a bunch of refinements in past with a lot of symbols and find out that they have this dna in common.
It's not number one in performance lists but appears in the top of most pair's backtests. And it performs well on random period tests.
G:\ewoexit2>jesse backtest 2021-06-01 2021-09-25 period | 116 days (3.87 months)
starting-ending date | 2021-06-01 => 2021-09-25
exchange | symbol | timeframe | strategy | DNA
-------------+-----------+-------------+----------------+-----------
FTX Futures | ADA-USD | 15m | ewoexitRestore | =bdOSb@l3
FTX Futures | AAVE-USD | 15m | ewoexitRestore | =bdOSb@l3
FTX Futures | FIL-USD | 15m | ewoexitRestore | =bdOSb@l3
FTX Futures | DOT-USD | 15m | ewoexitRestore | =bdOSb@l3
FTX Futures | IOTA-USD | 15m | ewoexitRestore | =bdOSb@l3
FTX Futures | LINK-USD | 15m | ewoexitRestore | =bdOSb@l3
FTX Futures | BCH-USD | 15m | ewoexitRestore | =bdOSb@l3
FTX Futures | 1INCH-USD | 15m | ewoexitRestore | =bdOSb@l3
FTX Futures | UNI-USD | 15m | ewoexitRestore | =bdOSb@l3
FTX Futures | TRX-USD | 15m | ewoexitRestore | =bdOSb@l3
FTX Futures | ETH-USD | 15m | ewoexitRestore | =bdOSb@l3
FTX Futures | NEO-USD | 15m | ewoexitRestore | =bdOSb@l3
METRICS |
---------------------------------+---------------------------------
Total Closed Trades | 596
Total Net Profit | 14,778.2788 (147.78%)
Starting => Finishing Balance | 10,000 => 24,778.28
Total Open Trades | 1
Open PL | -47.74
Total Paid Fees | 1,234.45
Max Drawdown | -3.35%
Annual Return | 1595.77%
Expectancy | 24.8 (0.25%)
Avg Win | Avg Loss | 93.91 | 32.83
Ratio Avg Win / Avg Loss | 2.86
Percent Profitable | 45%
Longs | Shorts | 47% | 53%
Avg Holding Time | 15 hours, 18 minutes, 5 seconds
Winning Trades Avg Holding Time | 1 day, 56 minutes, 24 seconds
Losing Trades Avg Holding Time | 7 hours, 15 minutes, 52 seconds
Sharpe Ratio | 5.88
Calmar Ratio | 476.15
Sortino Ratio | 22.34
Winning Streak | 10
Losing Streak | 16
Largest Winning Trade | 1,017.61
Largest Losing Trade | -78.65
Total Winning Trades | 271
Total Losing Trades | 325
Market Change | -5.14%
Backtests all pairs given in pairs.py with current dna.
Replace symbol field with keyword 'ANCHOR!'
Routes file template for mass backtest:
routes = [
('FTX Futures', 'ANCHOR!', '15m', 'ewoexit2', '=bdOSb@l3'),
]
extra_candles = [
('FTX Futures', 'ANCHOR!', '1h'),
]run
jesse-picker testpairs 2021-06-01 2021-09-25It will print out backtest results per symbol sorted by performance and create a report file:
jessepickerdata/results/Pairs-FTX Futures-15m--2021-06-01--2021-09-25--20210927 024722.csv
Naming convention: Pairs-{exchange}-{timeframe}--{startDate}--{finishDate}--{testTime}.csv
Console output:
18/156 2021-06-01 2021-09-25
Pair TF Total Total Net Max. Annual Win Sharpe Calmar Winning Losing Largest Largest Winning Losing Market
Trades Profit % DD % Return % Rate % Ratio Ratio Streak Streak Win. Trade Los. Trade Trades Trades Change %
ADA-USD 15m 44 49.63 -3.37 252 66 4.75 74.55 12 4 1285 -229 29 15 31.89
DOT-USD 15m 54 51.61 -6.98 266 44 3.26 38.18 4 5 1213 -238 24 30 32.94
LINK-USD 15m 45 42.8 -7.25 204 53 4.06 28.11 3 7 870 -192 24 21 -26.84
ETH-USD 15m 44 24.98 -5.32 100 45 3.07 18.9 3 7 691 -190 20 24 8.78
AVAX-USD 15m 49 26.5 -7.96 108 41 2.11 13.6 3 4 1048 -194 20 29 300.83
BTC-USD 15m 40 14.11 -3.87 51 50 2.33 13.16 4 3 491 -165 20 20 15.3
FTM-USD 15m 51 19.77 -9.32 76 39 1.68 8.1 4 6 1152 -183 20 31 277.26
XRP-USD 15m 45 13.35 -8.21 48 38 1.71 5.82 3 6 1082 -184 17 28 -8.62
SOL-USD 15m 51 13.64 -11.7 49 37 1.35 4.19 3 8 887 -185 19 32 327.25
MATIC-USD 15m 41 8.84 -11.1 30 39 1.14 2.72 3 6 923 -178 16 25 -39.38
ATOM-USD 15m 56 7.05 -16.38 24 38 0.71 1.44 3 5 956 -180 21 35 205.99
XTZ-USD 15m 67 3.35 -19.77 11 33 0.46 0.55 2 14 935 -176 22 45 95.31
FTT-USD 15m 0 0 0 0 0 0 0 0 0 0 0 0 0 0
AXS-USD 15m 0 0 0 0 0 0 0 0 0 0 0 0 0 0
DOGE-USD 15m 0 0 0 0 0 0 0 0 0 0 0 0 0 0
SRM-USD 15m 49 -6.31 -22.15 -18 22 -0.48 -0.83 4 11 1089 -176 11 38 65.42
ALGO-USD 15m 47 -7.15 -18.09 -21 30 -0.68 -1.14 3 6 694 -151 14 33 92.32
LUNA-USD 15m 58 -19.59 -23.85 -49 24 -2.01 -2.07 3 19 1057 -156 14 44 519.87I've picked some of them and created a routes file:
routes = [
('Binance Futures', 'ADA-USDT', '15m', 'ewoexitRestore', '=bdOSb@l3'),
('Binance Futures', 'AAVE-USDT', '15m', 'ewoexitRestore', '=bdOSb@l3'),
('Binance Futures', 'FIL-USDT', '15m', 'ewoexitRestore', '=bdOSb@l3'),
('Binance Futures', 'DOT-USDT', '15m', 'ewoexitRestore', '=bdOSb@l3'),
('Binance Futures', 'IOTA-USDT', '15m', 'ewoexitRestore', '=bdOSb@l3'),
('Binance Futures', 'LINK-USDT', '15m', 'ewoexitRestore', '=bdOSb@l3'),
('Binance Futures', 'BCH-USDT', '15m', 'ewoexitRestore', '=bdOSb@l3'),
('Binance Futures', '1INCH-USDT', '15m', 'ewoexitRestore', '=bdOSb@l3'),
('Binance Futures', 'UNI-USDT', '15m', 'ewoexitRestore', '=bdOSb@l3'),
('Binance Futures', 'TRX-USDT', '15m', 'ewoexitRestore', '=bdOSb@l3'),
# .
('Binance Futures', 'ETH-USDT', '15m', 'ewoexitRestore', '=bdOSb@l3'),
('Binance Futures', 'NEO-USDT', '15m', 'ewoexitRestore', '=bdOSb@l3'),
]
extra_candles = [
('Binance Futures', 'ADA-USDT', '1h'),
('Binance Futures', 'AAVE-USDT', '1h'),
('Binance Futures', 'FIL-USDT', '1h'),
('Binance Futures', 'DOT-USDT', '1h'),
('Binance Futures', 'IOTA-USDT', '1h'),
('Binance Futures', 'LINK-USDT', '1h'),
('Binance Futures', 'BCH-USDT', '1h'),
('Binance Futures', '1INCH-USDT', '1h'),
('Binance Futures', 'UNI-USDT', '1h'),
('Binance Futures', 'TRX-USDT', '1h'),
('Binance Futures', 'ETH-USDT', '1h'),
('Binance Futures', 'NEO-USDT', '1h'),
]In addition, I realized that FTX does not have sufficient candle data for some symbols, so I switched to Binance Futures. The strategy will be tested on Binance after being trained with FTX data. It'll be fun.
----------------------+--------------------------
period | 224 days (7.47 months)
starting-ending date | 2021-02-15 => 2021-09-27
exchange | symbol | timeframe | strategy | DNA
-----------------+------------+-------------+----------------+-----------
Binance Futures | ADA-USDT | 15m | ewoexitRestore | =bdOSb@l3
Binance Futures | AAVE-USDT | 15m | ewoexitRestore | =bdOSb@l3
Binance Futures | FIL-USDT | 15m | ewoexitRestore | =bdOSb@l3
Binance Futures | DOT-USDT | 15m | ewoexitRestore | =bdOSb@l3
Binance Futures | IOTA-USDT | 15m | ewoexitRestore | =bdOSb@l3
Binance Futures | LINK-USDT | 15m | ewoexitRestore | =bdOSb@l3
Binance Futures | BCH-USDT | 15m | ewoexitRestore | =bdOSb@l3
Binance Futures | 1INCH-USDT | 15m | ewoexitRestore | =bdOSb@l3
Binance Futures | UNI-USDT | 15m | ewoexitRestore | =bdOSb@l3
Binance Futures | TRX-USDT | 15m | ewoexitRestore | =bdOSb@l3
Binance Futures | ETH-USDT | 15m | ewoexitRestore | =bdOSb@l3
Binance Futures | NEO-USDT | 15m | ewoexitRestore | =bdOSb@l3
Executing simulation... [####################################] 100%
Executed backtest simulation in: 270.46 seconds
METRICS |
---------------------------------+----------------------------------
Total Closed Trades | 1122
Total Net Profit | 98,024.3456 (980.24%)
Starting => Finishing Balance | 10,000 => 108,024.35
Total Open Trades | 6
Open PL | 2,715.6
Total Paid Fees | 9,017.45
Max Drawdown | -18.53%
Annual Return | 4649.0%
Expectancy | 87.37 (0.87%)
Avg Win | Avg Loss | 396.51 | 126.66
Ratio Avg Win / Avg Loss | 3.13
Percent Profitable | 41%
Longs | Shorts | 46% | 54%
Avg Holding Time | 13 hours, 50 minutes, 12 seconds
Winning Trades Avg Holding Time | 1 day, 34 minutes, 24 seconds
Losing Trades Avg Holding Time | 6 hours, 24 minutes, 13 seconds
Sharpe Ratio | 4.58
Calmar Ratio | 250.91
Sortino Ratio | 13.85
Winning Streak | 10
Losing Streak | 17
Largest Winning Trade | 6,628.67
Largest Losing Trade | -678.52
Total Winning Trades | 459
Total Losing Trades | 663
Market Change | 13.67%Perform 50 rounds of random backtests for a 14-day period between 2021-02-15 and 2021-09-27. I am aware that the random sample duration is as short as 14 days, yet we trade 12 pairs in parallel and have 80 trades every sample. A short-term stress test can assist us understand the performance of the strategy and parameters. By the way, don't be deceived by samples that has very high sharpe ratio.
jesse-picker random 2021-02-15 2021-09-27 50 1450/50 Remaining Time: 00:00:00
Pair TF Start Date End Date Total Total Net Max. Annual Win Sharpe Calmar Winning Losing Largest Largest Winning Losing Market
Trades Profit % DD % Return % Rate % Ratio Ratio Streak Streak Win. Trade Los. Trade Trades Trades Change %
ADA-USDT 15m 2021-06-12 2021-06-26 73 82.11 -3.87 216049410 63 9.12 55816700.84 10 11 649 -103 46 27 -23.58
ADA-USDT 15m 2021-06-13 2021-06-27 73 80.0 -3.87 162875149 63 8.92 42079047.78 10 11 649 -103 46 27 -22.52
ADA-USDT 15m 2021-06-10 2021-06-24 72 75.82 -3.87 91896586 62 8.61 23731410.93 11 11 684 -80 45 27 -27.79
ADA-USDT 15m 2021-06-14 2021-06-28 71 67.83 -3.47 29632681 68 7.93 8532991.15 11 7 600 -103 48 23 -23.9
ADA-USDT 15m 2021-06-20 2021-07-04 74 58.62 -6.27 7510169 54 7.14 1198076.17 10 11 610 -98 40 34 -8.03
ADA-USDT 15m 2021-08-25 2021-09-08 90 49.14 -5.28 1675994 39 8.74 317439.61 7 15 1053 -77 35 55 4.33
ADA-USDT 15m 2021-06-05 2021-06-19 87 43.18 -5.59 620470 55 9.44 110925.37 12 11 645 -80 48 39 -18.76
ADA-USDT 15m 2021-05-18 2021-06-01 52 40.02 -5.71 360672 42 6.13 63143.86 9 10 662 -77 22 30 -28.25
ADA-USDT 15m 2021-08-30 2021-09-13 90 38.44 -4.51 273449 30 7.55 60632.38 7 15 1027 -90 27 63 9.04
ADA-USDT 15m 2021-05-09 2021-05-23 57 38.07 -6.11 256222 40 5.97 41963.87 6 10 745 -87 23 34 -46.07
ADA-USDT 15m 2021-05-11 2021-05-25 48 36.16 -6.1 182666 40 5.79 29950.37 6 10 734 -86 19 29 -36.37
ADA-USDT 15m 2021-05-16 2021-05-30 47 35.23 -6.11 154491 43 5.8 25277.87 6 10 720 -84 20 27 -43.3
ADA-USDT 15m 2021-07-23 2021-08-06 84 29.45 -2.85 53340 50 10.87 18716.32 10 8 550 -77 42 42 34.4
ADA-USDT 15m 2021-08-03 2021-08-17 80 26.93 -2.17 33014 57 11.03 15232.85 7 5 480 -72 46 34 31.26
ADA-USDT 15m 2021-06-04 2021-06-18 92 31.79 -5.6 82518 55 7.9 14744.73 10 11 657 -81 51 41 -18.34
ADA-USDT 15m 2021-05-26 2021-06-09 70 31.75 -6.62 81980 59 6.98 12391.06 9 6 490 -72 41 29 -5.07
ADA-USDT 15m 2021-08-04 2021-08-18 80 25.71 -2.17 26075 52 10.31 12042.34 7 5 485 -73 42 38 26.15
ADA-USDT 15m 2021-05-30 2021-06-13 74 29.88 -6.62 57834 55 6.57 8737.7 9 11 488 -82 41 33 -1.74
ADA-USDT 15m 2021-05-30 2021-06-13 74 29.88 -6.62 57834 55 6.57 8737.7 9 11 488 -82 41 33 -1.74
ADA-USDT 15m 2021-05-15 2021-05-29 47 27.97 -6.1 40297 36 4.85 6606.41 6 10 713 -83 17 30 -43.5
ADA-USDT 15m 2021-08-23 2021-09-06 91 26.53 -5.28 30563 40 9.58 5783.94 6 15 1073 -72 36 55 20.59
ADA-USDT 15m 2021-07-19 2021-08-02 72 22.88 -2.73 14931 47 9.4 5465.99 10 7 542 -73 34 38 27.45
ADA-USDT 15m 2021-05-27 2021-06-10 79 25.22 -6.61 23711 52 5.6 3586.1 9 10 493 -82 41 38 -11.02
ADA-USDT 15m 2021-09-08 2021-09-22 61 20.59 -4.18 9423 46 5.08 2252.74 8 7 296 -72 28 33 -18.35
ADA-USDT 15m 2021-05-17 2021-05-31 40 22.64 -6.63 14234 32 4.11 2146.96 4 12 655 -76 13 27 -39.67
ADA-USDT 15m 2021-07-21 2021-08-04 80 18.45 -2.86 6053 45 7.31 2114.43 10 8 538 -76 36 44 43.22
ADA-USDT 15m 2021-08-22 2021-09-05 95 21.14 -5.28 10537 39 7.88 1994.59 6 15 1070 -72 37 58 16.76
ADA-USDT 15m 2021-09-11 2021-09-25 59 17.82 -4.72 5308 44 4.42 1125.67 8 7 303 -74 26 33 -10.9
ADA-USDT 15m 2021-08-21 2021-09-04 92 18.03 -5.29 5547 40 6.81 1049.17 6 15 1066 -66 37 55 10.96
ADA-USDT 15m 2021-05-23 2021-06-06 60 19.1 -6.61 6929 60 5.59 1047.83 10 6 493 -70 36 24 14.84
ADA-USDT 15m 2021-07-01 2021-07-15 69 13.7 -3.48 2175 51 8.06 625.71 7 9 329 -67 35 34 -9.97
ADA-USDT 15m 2021-07-02 2021-07-16 62 12.54 -3.48 1674 47 7.51 480.61 6 9 322 -65 29 33 -8.08
ADA-USDT 15m 2021-07-10 2021-07-24 61 10.37 -2.22 1004 52 6.77 452.37 12 6 239 -68 32 29 -11.21
ADA-USDT 15m 2021-03-18 2021-04-01 70 13.53 -6.5 2095 37 4.36 322.16 6 8 356 -69 26 44 14.38
ADA-USDT 15m 2021-07-07 2021-07-21 49 9.0 -3.02 714 43 6.23 236.28 6 5 238 -63 21 28 -29.04
ADA-USDT 15m 2021-04-15 2021-04-29 63 9.88 -6.04 890 38 4.31 147.3 6 17 288 -68 24 39 0.92
ADA-USDT 15m 2021-04-22 2021-05-06 76 9.88 -6.19 889 41 4.37 143.69 6 14 299 -70 31 45 25.36
ADA-USDT 15m 2021-07-03 2021-07-17 62 6.29 -3.55 341 45 3.97 96.03 6 9 234 -62 28 34 -14.42
ADA-USDT 15m 2021-04-29 2021-05-13 74 7.04 -6.34 423 32 2.76 66.78 5 14 309 -62 24 50 6.07
ADA-USDT 15m 2021-08-17 2021-08-31 74 5.14 -5.25 239 42 2.54 45.43 6 7 256 -67 31 43 -2.11
Random test will create a report file at: jessepickerdata/results/Binance Futures-15m--20210927 182519--20210927 182519.csv
This is the average of 50 tests:
Total Total Max. Annual Win Sharpe Calmar Winning Losing Largest Largest Num .of Num. of Market
Trades Profit DD % Profit Rate % Ratio Ratio Strike Strike Winning Losing Wins Loses Change
71.28 23.48 -5.27 10241168 43.78 5.30 2642679 7.00 10.24 500.98 -74.32 31.30 39.98 -0.68
Chart: Results sorted by date, Market Change scaled to right axis.
As seen on the chart strategy performs too bad at March 2021, we can isolate routes and perform single backtests to find out what's happening.
The simple strategies presented here are solely for educational purposes. They are insufficient for live trading.
Please remember that the past performance of a strategy is not a guarantee of future results. USE THEM AT YOUR OWN RISK.
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.