How to get daily returns from irregularly spaced price time-series? I have a timeseries that has irregularly spaced time indices as below
data
>>>
Timestamp             price
2017-08-18 15:52:54   762.45
2017-08-18 15:59:27   762.98
2017-08-18 16:00:02   763.04

Usually a simple return (percent change in price) from regularly spaced (hourly, daily) prices can be calculated as
$$
\frac{P_t}{P_{t-1}} - 1
$$
But that assumes that $\Delta t = const$ for all time.
How do we calculate a daily return given prices and timestamps spaced out irregularly (in this case down to seconds), where $\Delta t \neq const$?

Take the closing price of each day and treat these as daily prices. From there on, the usual formulas such as $\frac{P_t-P_{t-1}}{P_{t-1}}$ or $\log(P_t)-\log(P_{t-1})$ apply.
