Upticks / Downticks

Let’s mark each trade as an uptick if its price is above the last trade’s price and as a downtick if it’s below.

import onetick.py as otp

def uptick(t):
    if t['PRICE'] == otp.nan or t['PRICE'][-1] == otp.nan:
        return otp.nan
    if t['PRICE'] > t['PRICE'][-1]:
        return 1
    elif t['PRICE'] < t['PRICE'][-1]:
        return -1
    else:
        return 0

trd = otp.DataSource('US_COMP_SAMPLE', tick_type='TRD')
trd = trd[['PRICE']]
trd['UPTICK'] = trd.apply(uptick)
otp.run(
    trd,
    symbols=['AAPL'],
    start=otp.dt(2024, 2, 1, 9, 30),
    end=otp.dt(2024, 2, 1, 9, 30, 1),
)

	Time	PRICE	UPTICK
0	2024-02-01 09:30:00.000961260	184.010	NaN
1	2024-02-01 09:30:00.000961491	184.000	-1.0
2	2024-02-01 09:30:00.000961701	184.000	0.0
3	2024-02-01 09:30:00.000973163	184.000	0.0
4	2024-02-01 09:30:00.000973355	184.000	0.0
...	...	...	...
574	2024-02-01 09:30:00.987184691	183.900	0.0
575	2024-02-01 09:30:00.990378350	183.920	1.0
576	2024-02-01 09:30:00.991941892	183.935	1.0
577	2024-02-01 09:30:00.993785116	183.905	-1.0
578	2024-02-01 09:30:00.996512511	183.934	1.0

579 rows × 3 columns