问答
如何 …
… 获取 PyBroker 的版本？
[1]:
import pybroker
pybroker.__version__
[1]:
'1.1.27'
… 从另外一个标的获取数据？
[2]:
from pybroker import ExecContext, Strategy, YFinance, highest
def exec_fn(ctx: ExecContext):
if ctx.symbol == 'NVDA':
other_bar_data = ctx.foreign('AMD')
other_highest = ctx.indicator('high_10d', 'AMD')
strategy = Strategy(YFinance(), start_date='1/1/2022', end_date='1/1/2023')
strategy.add_execution(
exec_fn, ['NVDA', 'AMD'], indicators=highest('high_10d', 'close', period=10))
result = strategy.backtest()
Backtesting: 2022-01-01 00:00:00 to 2023-01-01 00:00:00
Loading bar data...
[*********************100%***********************] 2 of 2 completed
Loaded bar data: 0:00:00
Computing indicators...
100% (2 of 2) |##########################| Elapsed Time: 0:00:01 Time: 0:00:01
Test split: 2022-01-03 00:00:00 to 2022-12-30 00:00:00
100% (251 of 251) |######################| Elapsed Time: 0:00:00 Time: 0:00:00
Finished backtest: 0:00:02
你还可以检索其他符号的模型、预测和其他数据。有关更多信息，请参阅 ExecContext 参考文档。
… 设置限价
设置 买入限价（buy_limit_price） 或 卖出限价（sell_limit_price）：
[3]:
from pybroker import ExecContext, Strategy, YFinance
def buy_fn(ctx: ExecContext):
if not ctx.long_pos():
ctx.buy_shares = 100
ctx.buy_limit_price = ctx.close[-1] * 0.99
ctx.hold_bars = 10
strategy = Strategy(YFinance(), start_date='3/1/2022', end_date='1/1/2023')
strategy.add_execution(buy_fn, 'SPY')
result = strategy.backtest()
result.orders.head(10)
Backtesting: 2022-03-01 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: 2022-03-01 00:00:00 to 2022-12-30 00:00:00
100% (212 of 212) |######################| Elapsed Time: 0:00:00 Time: 0:00:00
Finished backtest: 0:00:00
[3]:
| type | symbol | date | shares | limit_price | fill_price | fees | |
|---|---|---|---|---|---|---|---|
| id | |||||||
| 1 | buy | SPY | 2022-03-04 | 100 | 431.35 | 430.62 | 0.0 |
| 2 | sell | SPY | 2022-03-18 | 100 | NaN | 441.04 | 0.0 |
| 3 | buy | SPY | 2022-04-06 | 100 | 446.52 | 446.20 | 0.0 |
| 4 | sell | SPY | 2022-04-21 | 100 | NaN | 443.56 | 0.0 |
| 5 | buy | SPY | 2022-04-22 | 100 | 433.68 | 431.76 | 0.0 |
| 6 | sell | SPY | 2022-05-06 | 100 | NaN | 410.26 | 0.0 |
| 7 | buy | SPY | 2022-05-09 | 100 | 407.23 | 401.46 | 0.0 |
| 8 | sell | SPY | 2022-05-23 | 100 | NaN | 394.06 | 0.0 |
| 9 | buy | SPY | 2022-05-24 | 100 | 392.95 | 391.05 | 0.0 |
| 10 | sell | SPY | 2022-06-08 | 100 | NaN | 413.10 | 0.0 |
… 设置成交价格
设置 买入成交价格（buy_fill_price） 和 卖出成交价格（sell_fill_price）。请参阅 PriceType 以查看选项。
[4]:
from pybroker import ExecContext, PriceType, Strategy, YFinance
def exec_fn(ctx: ExecContext):
if ctx.long_pos():
ctx.buy_shares = 100
ctx.buy_fill_price = PriceType.AVERAGE
else:
ctx.sell_shares = 100
ctx.sell_fill_price = PriceType.CLOSE
strategy = Strategy(YFinance(), start_date='3/1/2022', end_date='1/1/2023')
strategy.add_execution(buy_fn, 'SPY')
result = strategy.backtest()
result.orders.head(10)
Backtesting: 2022-03-01 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: 2022-03-01 00:00:00 to 2022-12-30 00:00:00
100% (212 of 212) |######################| Elapsed Time: 0:00:00 Time: 0:00:00
Finished backtest: 0:00:00
[4]:
| type | symbol | date | shares | limit_price | fill_price | fees | |
|---|---|---|---|---|---|---|---|
| id | |||||||
| 1 | buy | SPY | 2022-03-04 | 100 | 431.35 | 430.62 | 0.0 |
| 2 | sell | SPY | 2022-03-18 | 100 | NaN | 441.04 | 0.0 |
| 3 | buy | SPY | 2022-04-06 | 100 | 446.52 | 446.20 | 0.0 |
| 4 | sell | SPY | 2022-04-21 | 100 | NaN | 443.56 | 0.0 |
| 5 | buy | SPY | 2022-04-22 | 100 | 433.68 | 431.76 | 0.0 |
| 6 | sell | SPY | 2022-05-06 | 100 | NaN | 410.26 | 0.0 |
| 7 | buy | SPY | 2022-05-09 | 100 | 407.23 | 401.46 | 0.0 |
| 8 | sell | SPY | 2022-05-23 | 100 | NaN | 394.06 | 0.0 |
| 9 | buy | SPY | 2022-05-24 | 100 | 392.95 | 391.05 | 0.0 |
| 10 | sell | SPY | 2022-06-08 | 100 | NaN | 413.10 | 0.0 |
… 获取当前仓位
[5]:
from pybroker import ExecContext, Strategy, YFinance
def exec_fn(ctx: ExecContext):
# Get all positions.
all_positions = tuple(ctx.positions())
# Get all long positions.
long_positions = tuple(ctx.long_positions())
# Get all short positions.
short_positions = tuple(ctx.short_positions())
# Get long position for current ctx.symbol.
long_position = ctx.long_pos()
# Get short position for a symbol.
short_position = ctx.short_pos('QQQ')
strategy = Strategy(YFinance(), start_date='3/1/2022', end_date='1/1/2023')
strategy.add_execution(exec_fn, ['SPY', 'QQQ'])
result = strategy.backtest()
Backtesting: 2022-03-01 00:00:00 to 2023-01-01 00:00:00
Loading bar data...
[*********************100%***********************] 2 of 2 completed
Loaded bar data: 0:00:00
Test split: 2022-03-01 00:00:00 to 2022-12-30 00:00:00
100% (212 of 212) |######################| Elapsed Time: 0:00:00 Time: 0:00:00
Finished backtest: 0:00:00
… 使用自定义列数据
使用 pybroker.register_columns 注册您的自定义列：
[6]:
import pybroker
from pybroker import ExecContext, Strategy, YFinance
yf = YFinance()
df = yf.query('SPY', start_date='1/1/2022', end_date='1/1/2023')
df['buy_signal'] = 1
def buy_fn(ctx: ExecContext):
if not ctx.long_pos() and ctx.buy_signal[-1] == 1:
ctx.buy_shares = 100
ctx.hold_bars = 1
pybroker.register_columns('buy_signal')
strategy = Strategy(df, start_date='3/1/2022', end_date='1/1/2023')
strategy.add_execution(buy_fn, 'SPY')
result = strategy.backtest()
result.orders.head(10)
Loading bar data...
[*********************100%***********************] 1 of 1 completed
Loaded bar data: 0:00:00
Backtesting: 2022-03-01 00:00:00 to 2023-01-01 00:00:00
Test split: 2022-03-01 00:00:00 to 2022-12-30 00:00:00
100% (212 of 212) |######################| Elapsed Time: 0:00:00 Time: 0:00:00
Finished backtest: 0:00:00
[6]:
| type | symbol | date | shares | limit_price | fill_price | fees | |
|---|---|---|---|---|---|---|---|
| id | |||||||
| 1 | buy | SPY | 2022-03-02 | 100 | NaN | 435.65 | 0.0 |
| 2 | sell | SPY | 2022-03-03 | 100 | NaN | 437.45 | 0.0 |
| 3 | buy | SPY | 2022-03-04 | 100 | NaN | 430.62 | 0.0 |
| 4 | sell | SPY | 2022-03-07 | 100 | NaN | 425.83 | 0.0 |
| 5 | buy | SPY | 2022-03-08 | 100 | NaN | 421.16 | 0.0 |
| 6 | sell | SPY | 2022-03-09 | 100 | NaN | 426.17 | 0.0 |
| 7 | buy | SPY | 2022-03-10 | 100 | NaN | 423.43 | 0.0 |
| 8 | sell | SPY | 2022-03-11 | 100 | NaN | 424.15 | 0.0 |
| 9 | buy | SPY | 2022-03-14 | 100 | NaN | 420.17 | 0.0 |
| 10 | sell | SPY | 2022-03-15 | 100 | NaN | 422.63 | 0.0 |
… 在超过一个K线之后下单
使用 buy_delay 和 sell_delay 配置选项：
[7]:
from pybroker import ExecContext, Strategy, StrategyConfig, YFinance
def buy_fn(ctx: ExecContext):
if not tuple(ctx.pending_orders()) and not ctx.long_pos():
ctx.buy_shares = 100
ctx.hold_bars = 1
config = StrategyConfig(buy_delay=5)
strategy = Strategy(YFinance(), start_date='3/1/2022', end_date='1/1/2023', config=config)
strategy.add_execution(buy_fn, 'SPY')
result = strategy.backtest()
result.orders.head(10)
Backtesting: 2022-03-01 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: 2022-03-01 00:00:00 to 2022-12-30 00:00:00
100% (212 of 212) |######################| Elapsed Time: 0:00:00 Time: 0:00:00
Finished backtest: 0:00:00
[7]:
| type | symbol | date | shares | limit_price | fill_price | fees | |
|---|---|---|---|---|---|---|---|
| id | |||||||
| 1 | buy | SPY | 2022-03-08 | 100 | NaN | 421.16 | 0.0 |
| 2 | sell | SPY | 2022-03-09 | 100 | NaN | 426.17 | 0.0 |
| 3 | buy | SPY | 2022-03-16 | 100 | NaN | 430.24 | 0.0 |
| 4 | sell | SPY | 2022-03-17 | 100 | NaN | 437.13 | 0.0 |
| 5 | buy | SPY | 2022-03-24 | 100 | NaN | 447.63 | 0.0 |
| 6 | sell | SPY | 2022-03-25 | 100 | NaN | 450.71 | 0.0 |
| 7 | buy | SPY | 2022-04-01 | 100 | NaN | 451.30 | 0.0 |
| 8 | sell | SPY | 2022-04-04 | 100 | NaN | 454.59 | 0.0 |
| 9 | buy | SPY | 2022-04-11 | 100 | NaN | 442.20 | 0.0 |
| 10 | sell | SPY | 2022-04-12 | 100 | NaN | 441.20 | 0.0 |
… 取消未完成的订单
请参阅 cancel_pending_order 和 cancel_all_pending_orders 方法。
[8]:
from pybroker import ExecContext, Strategy, StrategyConfig, YFinance
def buy_fn(ctx: ExecContext):
pending = tuple(ctx.pending_orders())
if not pending and not ctx.long_pos():
ctx.buy_shares = 100
ctx.hold_bars = 1
if pending and ctx.close[-1] < 430:
ctx.cancel_all_pending_orders(ctx.symbol)
config = StrategyConfig(buy_delay=5)
strategy = Strategy(YFinance(), start_date='3/1/2022', end_date='1/1/2023', config=config)
strategy.add_execution(buy_fn, 'SPY')
result = strategy.backtest()
result.orders.head(10)
Backtesting: 2022-03-01 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: 2022-03-01 00:00:00 to 2022-12-30 00:00:00
100% (212 of 212) |######################| Elapsed Time: 0:00:00 Time: 0:00:00
Finished backtest: 0:00:00
[8]:
| type | symbol | date | shares | limit_price | fill_price | fees | |
|---|---|---|---|---|---|---|---|
| id | |||||||
| 1 | buy | SPY | 2022-03-23 | 100 | NaN | 446.10 | 0.0 |
| 2 | sell | SPY | 2022-03-24 | 100 | NaN | 447.63 | 0.0 |
| 3 | buy | SPY | 2022-03-31 | 100 | NaN | 454.96 | 0.0 |
| 4 | sell | SPY | 2022-04-01 | 100 | NaN | 451.30 | 0.0 |
| 5 | buy | SPY | 2022-04-08 | 100 | NaN | 448.29 | 0.0 |
| 6 | sell | SPY | 2022-04-11 | 100 | NaN | 442.20 | 0.0 |
| 7 | buy | SPY | 2022-04-19 | 100 | NaN | 441.74 | 0.0 |
| 8 | sell | SPY | 2022-04-20 | 100 | NaN | 445.53 | 0.0 |
… 如何在多个K线之间保持数据？
使用 ExecContext#session 字典：
[9]:
from pybroker import ExecContext, Strategy, YFinance
def buy_fn(ctx: ExecContext):
if not ctx.long_pos():
ctx.buy_shares = 100
ctx.hold_bars = 1
count = ctx.session.get('entry_count', 0)
ctx.session['entry_count'] = count + 1
strategy = Strategy(YFinance(), start_date='1/1/2022', end_date='1/1/2023')
strategy.add_execution(buy_fn, 'SPY')
result = strategy.backtest()
Backtesting: 2022-01-01 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: 2022-01-03 00:00:00 to 2022-12-30 00:00:00
100% (251 of 251) |######################| Elapsed Time: 0:00:00 Time: 0:00:00
Finished backtest: 0:00:00
… 如何平仓？
使用 sell_all_shares() 或 cover_all_shares() 来清空仓位：
[10]:
from pybroker import ExecContext, Strategy, YFinance
def buy_fn(ctx: ExecContext):
pos = ctx.long_pos()
if not pos:
ctx.buy_shares = 100
elif pos.bars > 30:
ctx.sell_all_shares()
strategy = Strategy(YFinance(), start_date='1/1/2022', end_date='1/1/2023')
strategy.add_execution(buy_fn, 'SPY')
result = strategy.backtest()
result.trades
Backtesting: 2022-01-01 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: 2022-01-03 00:00:00 to 2022-12-30 00:00:00
100% (251 of 251) |######################| Elapsed Time: 0:00:00 Time: 0:00:00
Finished backtest: 0:00:00
[10]:
| type | symbol | entry_date | exit_date | entry | exit | shares | pnl | return_pct | agg_pnl | bars | pnl_per_bar | stop | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| id | |||||||||||||
| 1 | long | SPY | 2022-01-04 | 2022-02-18 | 477.78 | 435.24 | 100 | -4254.0 | -8.90 | -4254.0 | 32 | -132.94 | None |
| 2 | long | SPY | 2022-02-22 | 2022-04-07 | 430.68 | 447.11 | 100 | 1643.0 | 3.81 | -2611.0 | 32 | 51.34 | None |
| 3 | long | SPY | 2022-04-08 | 2022-05-25 | 448.29 | 395.67 | 100 | -5262.0 | -11.74 | -7873.0 | 32 | -164.44 | None |
| 4 | long | SPY | 2022-05-26 | 2022-07-14 | 402.75 | 375.04 | 100 | -2771.0 | -6.88 | -10644.0 | 32 | -86.59 | None |
| 5 | long | SPY | 2022-07-15 | 2022-08-30 | 382.90 | 400.05 | 100 | 1715.0 | 4.48 | -8929.0 | 32 | 53.59 | None |
| 6 | long | SPY | 2022-08-31 | 2022-10-17 | 398.14 | 362.63 | 100 | -3551.0 | -8.92 | -12480.0 | 32 | -110.97 | None |
| 7 | long | SPY | 2022-10-18 | 2022-12-02 | 371.49 | 405.00 | 100 | 3351.0 | 9.02 | -9129.0 | 32 | 104.72 | None |
… 如何同时处理多个标的？
使用 set_before_exec 或 set_after_exec：
[11]:
from pybroker import ExecContext, Strategy, YFinance
def long_short_fn(ctxs: dict[str, ExecContext]):
nvda_ctx = ctxs['NVDA']
amd_ctx = ctxs['AMD']
if nvda_ctx.long_pos() or amd_ctx.short_pos():
return
if nvda_ctx.bars >= 2 and nvda_ctx.close[-1] < nvda_ctx.low[-2]:
nvda_ctx.buy_shares = 100
nvda_ctx.hold_bars = 3
amd_ctx.sell_shares = 100
amd_ctx.hold_bars = 3
strategy = Strategy(YFinance(), start_date='1/1/2022', end_date='1/1/2023')
strategy.add_execution(None, ['NVDA', 'AMD'])
strategy.set_after_exec(long_short_fn)
result = strategy.backtest()
result.trades
Backtesting: 2022-01-01 00:00:00 to 2023-01-01 00:00:00
Loading bar data...
[*********************100%***********************] 2 of 2 completed
Loaded bar data: 0:00:00
Test split: 2022-01-03 00:00:00 to 2022-12-30 00:00:00
100% (251 of 251) |######################| Elapsed Time: 0:00:00 Time: 0:00:00
Finished backtest: 0:00:00
[11]:
| type | symbol | entry_date | exit_date | entry | exit | shares | pnl | return_pct | agg_pnl | bars | pnl_per_bar | stop | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| id | |||||||||||||
| 1 | long | NVDA | 2022-01-05 | 2022-01-10 | 284.74 | 265.57 | 100 | -1917.0 | -6.73 | -1917.0 | 3 | -639.00 | bar |
| 2 | short | AMD | 2022-01-05 | 2022-01-10 | 139.52 | 128.72 | 100 | 1080.0 | 8.39 | -837.0 | 3 | 360.00 | bar |
| 3 | long | NVDA | 2022-01-14 | 2022-01-20 | 267.04 | 248.28 | 100 | -1876.0 | -7.03 | -2713.0 | 3 | -625.33 | bar |
| 4 | short | AMD | 2022-01-14 | 2022-01-20 | 134.21 | 124.96 | 100 | 925.0 | 7.40 | -1788.0 | 3 | 308.33 | bar |
| 5 | long | NVDA | 2022-01-21 | 2022-01-26 | 240.43 | 231.79 | 100 | -864.0 | -3.59 | -2652.0 | 3 | -288.00 | bar |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 76 | short | AMD | 2022-12-07 | 2022-12-12 | 70.33 | 69.10 | 100 | 123.0 | 1.78 | 1863.0 | 3 | 41.00 | bar |
| 77 | long | NVDA | 2022-12-15 | 2022-12-20 | 170.10 | 160.81 | 100 | -929.0 | -5.46 | 934.0 | 3 | -309.67 | bar |
| 78 | short | AMD | 2022-12-15 | 2022-12-20 | 67.17 | 64.79 | 100 | 238.0 | 3.67 | 1172.0 | 3 | 79.33 | bar |
| 79 | long | NVDA | 2022-12-21 | 2022-12-27 | 163.65 | 145.78 | 100 | -1787.0 | -10.92 | -615.0 | 3 | -595.67 | bar |
| 80 | short | AMD | 2022-12-21 | 2022-12-27 | 66.53 | 63.62 | 100 | 291.0 | 4.57 | -324.0 | 3 | 97.00 | bar |
80 rows × 13 columns
… 如何对夏普比率进行年化？
设置 bars_per_year 配置选项。例如，设置为 252 的值将用于对每日回报进行年化。
[12]:
from pybroker import ExecContext, Strategy, StrategyConfig, YFinance
def buy_fn(ctx: ExecContext):
if ctx.long_pos() or ctx.bars < 2:
return
if ctx.close[-1] < ctx.high[-2]:
ctx.buy_shares = 100
ctx.hold_bars = 1
config = StrategyConfig(bars_per_year=252)
strategy = Strategy(YFinance(), start_date='1/1/2022', end_date='1/1/2023', config=config)
strategy.add_execution(buy_fn, 'SPY')
result = strategy.backtest()
result.metrics.sharpe
Backtesting: 2022-01-01 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: 2022-01-03 00:00:00 to 2022-12-30 00:00:00
100% (251 of 251) |######################| Elapsed Time: 0:00:00 Time: 0:00:00
Finished backtest: 0:00:00
[12]:
-0.8930247224724036
… 用于卖空的限制保证金
默认情况下，PyBroker 并不限制可以用于卖空的保证金数量。然而，你可以手动限制可用保证金的数量：
[13]:
import pybroker
from pybroker import ExecContext
from decimal import Decimal
def short_fn(ctx: ExecContext):
margin_requirement = Decimal('0.25')
max_margin = ctx.total_equity / margin_requirement - ctx.total_equity
if not ctx.short_pos():
available_margin = max_margin - ctx.total_margin
ctx.sell_shares = ctx.calc_target_shares(0.5, cash=available_margin)
ctx.hold_bars = 1
strategy = Strategy(YFinance(), start_date='1/1/2022', end_date='1/1/2023')
strategy.add_execution(short_fn, ['NVDA', 'AMD'])
result = strategy.backtest()
result.portfolio.head(10)
Backtesting: 2022-01-01 00:00:00 to 2023-01-01 00:00:00
Loading bar data...
[*********************100%***********************] 2 of 2 completed
Loaded bar data: 0:00:00
Test split: 2022-01-03 00:00:00 to 2022-12-30 00:00:00
100% (251 of 251) |######################| Elapsed Time: 0:00:00 Time: 0:00:00
Finished backtest: 0:00:00
[13]:
| cash | equity | margin | market_value | pnl | unrealized_pnl | fees | |
|---|---|---|---|---|---|---|---|
| date | |||||||
| 2022-01-03 | 100000.00 | 100000.00 | 0.00 | 100000.00 | 0.00 | 0.00 | 0.0 |
| 2022-01-04 | 100000.00 | 100000.00 | 289702.46 | 102722.18 | 0.00 | 2722.18 | 0.0 |
| 2022-01-05 | 111667.90 | 111667.90 | 0.00 | 111667.90 | 11667.90 | 0.00 | 0.0 |
| 2022-01-06 | 111667.90 | 111667.90 | 338321.57 | 107432.09 | 11667.90 | -4235.81 | 0.0 |
| 2022-01-07 | 112472.56 | 112472.56 | 0.00 | 112472.56 | 12472.56 | 0.00 | 0.0 |
| 2022-01-10 | 112472.56 | 112472.56 | 338302.00 | 103062.55 | 12472.56 | -9410.01 | 0.0 |
| 2022-01-11 | 98536.05 | 98536.05 | 0.00 | 98536.05 | -1463.95 | 0.00 | 0.0 |
| 2022-01-12 | 98536.05 | 98536.05 | 296592.41 | 99830.87 | -1463.95 | 1294.82 | 0.0 |
| 2022-01-13 | 103550.41 | 103550.41 | 0.00 | 103550.41 | 3550.41 | 0.00 | 0.0 |
| 2022-01-14 | 103550.41 | 103550.41 | 317490.89 | 99036.58 | 3550.41 | -4513.83 | 0.0 |
… 如何获取和设置全局参数？
[14]:
import pybroker
# Set parameter.
pybroker.param('lookback', 100)
# Get parameter.
pybroker.param('lookback')
[14]:
100
… 如何应用随机滑点？
设置一个 RandomSlippageModel：
[15]:
from pybroker import ExecContext, RandomSlippageModel, Strategy, YFinance
def buy_fn(ctx: ExecContext):
if not ctx.long_pos():
ctx.buy_shares = 100
ctx.hold_bars = 1
slippage = RandomSlippageModel(min_pct=1.0, max_pct=5.0) # Slippage of 1-5%
strategy = Strategy(YFinance(), start_date='3/1/2022', end_date='1/1/2023')
strategy.set_slippage_model(slippage)
strategy.add_execution(buy_fn, 'SPY')
result = strategy.backtest()
result.orders.head(10)
Backtesting: 2022-03-01 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: 2022-03-01 00:00:00 to 2022-12-30 00:00:00
100% (212 of 212) |######################| Elapsed Time: 0:00:00 Time: 0:00:00
Finished backtest: 0:00:00
[15]:
| type | symbol | date | shares | limit_price | fill_price | fees | |
|---|---|---|---|---|---|---|---|
| id | |||||||
| 1 | buy | SPY | 2022-03-02 | 98 | NaN | 435.65 | 0.0 |
| 2 | sell | SPY | 2022-03-03 | 98 | NaN | 437.45 | 0.0 |
| 3 | buy | SPY | 2022-03-04 | 98 | NaN | 430.62 | 0.0 |
| 4 | sell | SPY | 2022-03-07 | 98 | NaN | 425.83 | 0.0 |
| 5 | buy | SPY | 2022-03-08 | 98 | NaN | 421.16 | 0.0 |
| 6 | sell | SPY | 2022-03-09 | 98 | NaN | 426.17 | 0.0 |
| 7 | buy | SPY | 2022-03-10 | 97 | NaN | 423.43 | 0.0 |
| 8 | sell | SPY | 2022-03-11 | 97 | NaN | 424.15 | 0.0 |
| 9 | buy | SPY | 2022-03-14 | 97 | NaN | 420.17 | 0.0 |
| 10 | sell | SPY | 2022-03-15 | 97 | NaN | 422.63 | 0.0 |