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('NYSE_TAQ', tick_type='TRD')
trd = trd[['PRICE']]
trd['UPTICK'] = trd.apply(uptick)
otp.run(
    trd,
    symbols=['SPY'],
    start=otp.dt(2023, 5, 15, 9, 30), 
    end=otp.dt(2023, 5, 15, 9, 30, 1),
)

	Time	PRICE	UPTICK
0	2023-05-15 09:30:00.000178688	412.22	NaN
1	2023-05-15 09:30:00.000776704	412.22	0.0
2	2023-05-15 09:30:00.003603456	412.22	0.0
3	2023-05-15 09:30:00.006352128	412.24	1.0
4	2023-05-15 09:30:00.007128064	412.24	0.0
...	...	...	...
310	2023-05-15 09:30:00.934032640	412.27	0.0
311	2023-05-15 09:30:00.975609344	412.24	-1.0
312	2023-05-15 09:30:00.980264448	412.27	1.0
313	2023-05-15 09:30:00.985391616	412.28	1.0
314	2023-05-15 09:30:00.985394944	412.28	0.0

315 rows × 3 columns