Point-in-time benchmarks: BBO at different markouts#
Find the prevailing quote at different time intervals (markouts) before/after each trade.
import onetick.py as otp
markouts = [-1, 0, 1, 5, 60, 600]
trd = otp.DataSource('NYSE_TAQ', tick_type='TRD')
trd = trd[['PRICE', 'SIZE']]
qte_by_markout = []
for m in markouts:
mr = str(m).replace('-', 'm')
qte = otp.DataSource('TAQ_NBBO',
tick_type='NBBO',
back_to_first_tick=otp.Hour(24))
qte = qte[['ASK_PRICE', 'BID_PRICE']]
qte = qte.rename({'ASK_PRICE': f'ASK_PRICE_{mr}',
'BID_PRICE': f'BID_PRICE_{mr}'})
qte[f'quote_time_{mr}'] = qte['Time']
# shift the data by m seconds
qte = qte.time_interval_shift(m * 1000)
qte_by_markout.append(qte)
trd = otp.join_by_time([trd] + qte_by_markout)
otp.run(
trd,
symbols=['SPY'],
start=otp.dt(2023, 5, 15, 9, 30),
end=otp.dt(2023, 5, 15, 9, 30, 1),
timezone='EST5EDT',
)
| Time | PRICE | SIZE | ASK_PRICE_m1 | BID_PRICE_m1 | quote_time_m1 | ASK_PRICE_0 | BID_PRICE_0 | quote_time_0 | ASK_PRICE_1 | BID_PRICE_1 | quote_time_1 | ASK_PRICE_5 | BID_PRICE_5 | quote_time_5 | ASK_PRICE_60 | BID_PRICE_60 | quote_time_60 | ASK_PRICE_600 | BID_PRICE_600 | quote_time_600 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2023-05-15 09:30:00.000178688 | 412.22 | 100 | 412.26 | 412.23 | 2023-05-15 09:29:59.000000000 | 412.25 | 412.22 | 2023-05-15 09:30:00.000174080 | 412.28 | 412.27 | 2023-05-15 09:30:01.000000000 | 412.23 | 412.21 | 2023-05-15 09:30:05.000000000 | 412.06 | 412.05 | 2023-05-15 09:31:00.000105984 | 411.45 | 411.44 | 2023-05-15 09:40:00.000000000 |
| 1 | 2023-05-15 09:30:00.000776704 | 412.22 | 247 | 412.26 | 412.23 | 2023-05-15 09:29:59.000000000 | 412.24 | 412.21 | 2023-05-15 09:30:00.000715520 | 412.28 | 412.27 | 2023-05-15 09:30:01.000000000 | 412.23 | 412.21 | 2023-05-15 09:30:05.000000000 | 412.06 | 412.05 | 2023-05-15 09:31:00.000772608 | 411.45 | 411.44 | 2023-05-15 09:40:00.000000000 |
| 2 | 2023-05-15 09:30:00.003603456 | 412.22 | 100 | 412.26 | 412.23 | 2023-05-15 09:29:59.000000000 | 412.24 | 412.22 | 2023-05-15 09:30:00.003562496 | 412.28 | 412.27 | 2023-05-15 09:30:01.002818816 | 412.23 | 412.21 | 2023-05-15 09:30:05.000000000 | 412.06 | 412.05 | 2023-05-15 09:31:00.001634816 | 411.45 | 411.44 | 2023-05-15 09:40:00.000000000 |
| 3 | 2023-05-15 09:30:00.006352128 | 412.24 | 1 | 412.26 | 412.23 | 2023-05-15 09:29:59.005259520 | 412.25 | 412.22 | 2023-05-15 09:30:00.006343936 | 412.28 | 412.27 | 2023-05-15 09:30:01.004251904 | 412.23 | 412.21 | 2023-05-15 09:30:05.000000000 | 412.06 | 412.05 | 2023-05-15 09:31:00.005624320 | 411.45 | 411.44 | 2023-05-15 09:40:00.006328576 |
| 4 | 2023-05-15 09:30:00.007128064 | 412.24 | 3 | 412.26 | 412.23 | 2023-05-15 09:29:59.007053824 | 412.25 | 412.22 | 2023-05-15 09:30:00.007110656 | 412.28 | 412.27 | 2023-05-15 09:30:01.004251904 | 412.23 | 412.21 | 2023-05-15 09:30:05.000000000 | 412.05 | 412.04 | 2023-05-15 09:31:00.007117824 | 411.45 | 411.44 | 2023-05-15 09:40:00.007125760 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 310 | 2023-05-15 09:30:00.934032640 | 412.27 | 160 | 412.26 | 412.22 | 2023-05-15 09:29:59.837682688 | 412.28 | 412.26 | 2023-05-15 09:30:00.934030080 | 412.28 | 412.26 | 2023-05-15 09:30:01.931170560 | 412.25 | 412.23 | 2023-05-15 09:30:05.898093824 | 412.07 | 412.06 | 2023-05-15 09:31:00.927816448 | 411.44 | 411.43 | 2023-05-15 09:40:00.928655104 |
| 311 | 2023-05-15 09:30:00.975609344 | 412.24 | 2 | 412.25 | 412.22 | 2023-05-15 09:29:59.970543872 | 412.28 | 412.27 | 2023-05-15 09:30:00.970691840 | 412.29 | 412.26 | 2023-05-15 09:30:01.972468480 | 412.25 | 412.24 | 2023-05-15 09:30:05.973397760 | 412.07 | 412.06 | 2023-05-15 09:31:00.972016640 | 411.44 | 411.43 | 2023-05-15 09:40:00.954621952 |
| 312 | 2023-05-15 09:30:00.980264448 | 412.27 | 1 | 412.25 | 412.22 | 2023-05-15 09:29:59.970543872 | 412.28 | 412.27 | 2023-05-15 09:30:00.979763456 | 412.29 | 412.27 | 2023-05-15 09:30:01.978472704 | 412.26 | 412.24 | 2023-05-15 09:30:05.978229504 | 412.07 | 412.06 | 2023-05-15 09:31:00.972016640 | 411.44 | 411.43 | 2023-05-15 09:40:00.954621952 |
| 313 | 2023-05-15 09:30:00.985391616 | 412.28 | 100 | 412.25 | 412.22 | 2023-05-15 09:29:59.970543872 | 412.28 | 412.27 | 2023-05-15 09:30:00.985296640 | 412.29 | 412.27 | 2023-05-15 09:30:01.985324032 | 412.26 | 412.24 | 2023-05-15 09:30:05.978229504 | 412.07 | 412.06 | 2023-05-15 09:31:00.972016640 | 411.44 | 411.43 | 2023-05-15 09:40:00.954621952 |
| 314 | 2023-05-15 09:30:00.985394944 | 412.28 | 100 | 412.25 | 412.22 | 2023-05-15 09:29:59.970543872 | 412.28 | 412.27 | 2023-05-15 09:30:00.985296640 | 412.29 | 412.27 | 2023-05-15 09:30:01.985324032 | 412.26 | 412.24 | 2023-05-15 09:30:05.978229504 | 412.07 | 412.06 | 2023-05-15 09:31:00.972016640 | 411.44 | 411.43 | 2023-05-15 09:40:00.954621952 |
315 rows × 21 columns