Applying Stops

Stops are used to automatically buy or sell a security once it reaches a specified price level. They can be useful for limiting potential losses by allowing traders to exit bad trades automatically, as well as for taking profits by selling a security automatically when it reaches a certain price level.

PyBroker supports the simulation of stops, which is explained in detail in this notebook:

[1]:

import pybroker
from pybroker import Strategy, YFinance

pybroker.enable_data_source_cache('stops')

strategy = Strategy(YFinance(), '1/1/2018', '1/1/2023')

Stop Loss

A stop loss order is used to automatically exit a trade once the security’s price reaches or falls below a specified level. For example, the following code shows an example of a stop loss order set at 20% below the entry price:

[2]:

def buy_with_stop_loss(ctx):
    if not ctx.long_pos():
        ctx.buy_shares = ctx.calc_target_shares(1)
        ctx.stop_loss_pct = 20

strategy.add_execution(buy_with_stop_loss, ['TSLA'])
result = strategy.backtest()
result.trades

Backtesting: 2018-01-01 00:00:00 to 2023-01-01 00:00:00

Loading bar data...
[*********************100%***********************]  1 of 1 completed
Loaded bar data: 0:00:00

Test split: 2018-01-02 00:00:00 to 2022-12-30 00:00:00

100% (1259 of 1259) |####################| Elapsed Time: 0:00:00 Time:  0:00:00


Finished backtest: 0:00:02

[2]:

	type	symbol	entry_date	exit_date	entry	exit	shares	pnl	return_pct	agg_pnl	bars	pnl_per_bar	stop
id
1	long	TSLA	2018-01-03	2018-03-28	21.36	17.09	4679	-19988.69	-20.00	-19988.69	58	-344.63	loss
2	long	TSLA	2018-03-29	2019-05-20	17.31	13.73	4622	-16531.36	-20.66	-36520.04	286	-57.80	loss

Take Profit

Similarly, a take profit order can be used to lock in profits on a trade. The following code adds a take profit order at 10% above the entry price:

[3]:

def buy_with_stop_loss_and_profit(ctx):
    if not ctx.long_pos():
        ctx.buy_shares = ctx.calc_target_shares(1)
        ctx.stop_loss_pct = 20
        ctx.stop_profit_pct = 10

strategy.clear_executions()
strategy.add_execution(buy_with_stop_loss_and_profit, ['TSLA'])
result = strategy.backtest()
result.trades

Backtesting: 2018-01-01 00:00:00 to 2023-01-01 00:00:00

Loaded cached bar data.

Test split: 2018-01-02 00:00:00 to 2022-12-30 00:00:00

100% (1259 of 1259) |####################| Elapsed Time: 0:00:00 Time:  0:00:00


Finished backtest: 0:00:00

[3]:

	type	symbol	entry_date	exit_date	entry	exit	shares	pnl	return_pct	agg_pnl	bars	pnl_per_bar	stop
id
1	long	TSLA	2018-01-03	2018-01-22	21.36	23.50	4679	9994.34	10.0	9994.34	12	832.86	profit
2	long	TSLA	2018-01-23	2018-03-27	23.72	18.98	4637	-21997.93	-20.0	-12003.58	44	-499.95	loss
3	long	TSLA	2018-03-28	2018-04-04	17.36	19.10	4727	8206.07	10.0	-3797.51	4	2051.52	profit
4	long	TSLA	2018-04-05	2018-06-07	19.82	21.80	4853	9618.65	10.0	5821.13	44	218.61	profit
5	long	TSLA	2018-06-08	2018-06-12	21.39	23.53	4947	10581.63	10.0	16402.77	2	5290.82	profit
...	...	...	...	...	...	...	...	...	...	...	...	...	...
85	long	TSLA	2022-07-29	2022-10-07	288.71	230.97	1010	-58319.42	-20.0	133480.29	49	-1190.19	loss
86	long	TSLA	2022-10-10	2022-11-09	222.68	178.14	1046	-46584.66	-20.0	86895.63	22	-2117.48	loss
87	long	TSLA	2022-11-10	2022-12-19	185.51	148.41	1007	-37361.71	-20.0	49533.92	26	-1436.99	loss
88	long	TSLA	2022-12-20	2022-12-27	143.07	114.46	997	-28528.16	-20.0	21005.76	4	-7132.04	loss
89	long	TSLA	2022-12-28	2022-12-29	112.25	123.48	1078	12100.55	10.0	33106.31	1	12100.55	profit

89 rows × 13 columns

Trailing Stop

A trailing stop is an order that is used to exit a trade once the instrument’s price falls a certain percentage or cash amount below its highest market price. Here is an example of setting a trailing stop at 20% below the highest market price:

[4]:

def buy_with_trailing_stop_loss_and_profit(ctx):
    if not ctx.long_pos():
        ctx.buy_shares = ctx.calc_target_shares(1)
        ctx.stop_trailing_pct = 20
        ctx.stop_profit_pct = 10

strategy.clear_executions()
strategy.add_execution(buy_with_trailing_stop_loss_and_profit, ['TSLA'])
result = strategy.backtest()
result.trades

Backtesting: 2018-01-01 00:00:00 to 2023-01-01 00:00:00

Loaded cached bar data.

Test split: 2018-01-02 00:00:00 to 2022-12-30 00:00:00

100% (1259 of 1259) |####################| Elapsed Time: 0:00:00 Time:  0:00:00


Finished backtest: 0:00:00

[4]:

	type	symbol	entry_date	exit_date	entry	exit	shares	pnl	return_pct	agg_pnl	bars	pnl_per_bar	stop
id
1	long	TSLA	2018-01-03	2018-01-22	21.36	23.50	4679	9994.34	10.00	9994.34	12	832.86	profit
2	long	TSLA	2018-01-23	2018-03-27	23.72	19.20	4637	-20961.72	-19.06	-10967.37	44	-476.40	trailing
3	long	TSLA	2018-03-28	2018-04-04	17.36	19.10	4783	8303.29	10.00	-2664.08	4	2075.82	profit
4	long	TSLA	2018-04-05	2018-06-07	19.82	21.80	4910	9731.62	10.00	7067.54	44	221.17	profit
5	long	TSLA	2018-06-08	2018-06-12	21.39	23.53	5005	10705.70	10.00	17773.23	2	5352.85	profit
...	...	...	...	...	...	...	...	...	...	...	...	...	...
102	long	TSLA	2022-08-02	2022-10-03	300.25	251.73	1095	-53125.76	-16.16	175768.16	43	-1235.48	trailing
103	long	TSLA	2022-10-04	2022-10-24	249.75	199.80	1104	-55144.80	-20.00	120623.36	14	-3938.91	trailing
104	long	TSLA	2022-10-25	2022-11-08	217.18	189.92	1015	-27668.90	-12.55	92954.46	10	-2766.89	trailing
105	long	TSLA	2022-11-09	2022-12-13	186.50	160.66	1008	-26050.75	-13.86	66903.71	23	-1132.64	trailing
106	long	TSLA	2022-12-14	2022-12-22	158.46	128.79	1036	-30736.04	-18.72	36167.67	6	-5122.67	trailing

106 rows × 13 columns

Setting a Limit Price

A stop order can be combined with a limit price to ensure that the order is executed only at a specific price level. Below shows an example of placing a limit price on a stop order:

[5]:

def buy_with_trailing_stop_loss_and_profit(ctx):
    if not ctx.long_pos():
        ctx.buy_shares = ctx.calc_target_shares(1)
        ctx.stop_trailing_pct = 20
        ctx.stop_trailing_limit = ctx.close[-1] + 1
        ctx.stop_profit_pct = 10
        ctx.stop_profit_limit = ctx.close[-1] - 1

strategy.clear_executions()
strategy.add_execution(buy_with_trailing_stop_loss_and_profit, ['TSLA'])
result = strategy.backtest()
result.trades.head()

Backtesting: 2018-01-01 00:00:00 to 2023-01-01 00:00:00

Loaded cached bar data.

Test split: 2018-01-02 00:00:00 to 2022-12-30 00:00:00

100% (1259 of 1259) |####################| Elapsed Time: 0:00:00 Time:  0:00:00


Finished backtest: 0:00:00

[5]:

	type	symbol	entry_date	exit_date	entry	exit	shares	pnl	return_pct	agg_pnl	bars	pnl_per_bar	stop
id
1	long	TSLA	2018-01-03	2018-01-22	21.36	23.50	4679	9994.34	10.0	9994.34	12	832.86	profit
2	long	TSLA	2018-01-23	2019-12-18	23.72	26.09	4637	10998.96	10.0	20993.31	480	22.91	profit
3	long	TSLA	2019-12-19	2020-01-03	26.78	29.46	4518	12099.20	10.0	33092.51	9	1344.36	profit
4	long	TSLA	2020-01-06	2020-01-08	29.72	32.69	4478	13308.62	10.0	46401.13	2	6654.31	profit
5	long	TSLA	2020-01-09	2020-01-14	32.39	35.63	4462	14452.42	10.0	60853.55	3	4817.47	profit

Canceling a Stop

The following code shows an example of canceling a stop order:

[6]:

def buy_with_stop_trailing_and_cancel(ctx):
    pos = ctx.long_pos()
    if not pos:
        ctx.buy_shares = ctx.calc_target_shares(1)
        ctx.stop_trailing_pct = 20
    elif pos.bars > 60:
        ctx.cancel_stops(ctx.symbol)

strategy.clear_executions()
strategy.add_execution(buy_with_stop_trailing_and_cancel, ['TSLA'])
result = strategy.backtest()
result.trades

Backtesting: 2018-01-01 00:00:00 to 2023-01-01 00:00:00

Loaded cached bar data.

Test split: 2018-01-02 00:00:00 to 2022-12-30 00:00:00

100% (1259 of 1259) |####################| Elapsed Time: 0:00:00 Time:  0:00:00


Finished backtest: 0:00:00

[6]:

	type	symbol	entry_date	exit_date	entry	exit	shares	pnl	return_pct	agg_pnl	bars	pnl_per_bar	stop
id
1	long	TSLA	2018-01-03	2018-03-27	21.36	19.23	4679	-9981.87	-9.99	-9981.87	57	-175.12	trailing

Setting the Stop Exit Price

By default, stops are checked against the bar’s low and high prices, and they are exited at the stop’s threshold (e.g., -2%) on the same bar when the stop is triggered.

To set a custom exit price, the “exit_price” fields for each stop type can be used. When these fields are set, the stop will be checked against the exit_price, and it will exit at the exit_price when triggered. For example, the code below sets the stop_trailing_exit_price to the open price on the bar that triggers the stop:

[7]:

from pybroker import PriceType

def buy_with_stop_trailing_and_exit_price(ctx):
    pos = ctx.long_pos()
    if not pos:
        ctx.buy_shares = ctx.calc_target_shares(1)
        ctx.stop_trailing_pct = 20
        ctx.stop_trailing_exit_price = PriceType.OPEN

strategy.clear_executions()
strategy.add_execution(buy_with_stop_trailing_and_exit_price, ['TSLA'])
result = strategy.backtest()
result.trades.head()

Backtesting: 2018-01-01 00:00:00 to 2023-01-01 00:00:00

Loaded cached bar data.

Test split: 2018-01-02 00:00:00 to 2022-12-30 00:00:00

100% (1259 of 1259) |####################| Elapsed Time: 0:00:00 Time:  0:00:00


Finished backtest: 0:00:00

[7]:

	type	symbol	entry_date	exit_date	entry	exit	shares	pnl	return_pct	agg_pnl	bars	pnl_per_bar	stop
id
1	long	TSLA	2018-01-03	2018-03-28	21.36	17.64	4679	-17412.12	-17.42	-17412.12	58	-300.21	trailing
2	long	TSLA	2018-03-29	2018-07-25	17.31	19.78	4771	11797.10	14.28	-5615.03	81	145.64	trailing
3	long	TSLA	2018-07-26	2018-08-20	20.48	19.45	4585	-4737.83	-5.05	-10352.86	17	-278.70	trailing
4	long	TSLA	2018-08-21	2018-09-07	21.13	17.34	4242	-16077.18	-17.94	-26430.04	12	-1339.76	trailing
5	long	TSLA	2018-09-10	2018-12-26	18.57	20.00	3961	5664.23	7.70	-20765.81	74	76.54	trailing

For more information on the various attributes that can be used to set stops in PyBroker, you can refer to the ExecContext reference documentation.