# Irregularly spaced time-series in finance/economics research

In financial econometrics research, it is very common to investigate relationships between financial time series that take the form of daily data. The variable will often be made $I(0)$ by taking the log difference, for example; $\ln(P_t)-\ln(P_{t-1})$.

However, daily data means that there's $5$ data points each week, and Saturday and Sunday are missing. This seems to get no mention in the applied literature that I'm aware of. Here's some closely related questions that I have that come from this observation:

• Does this qualify as irregularly spaced data, even though financial markets are closed over the weekend?

• If so, what are the consequences for the validity of extant empirical results garnered thus far in the gigantic number of papers that ignore this issue?

• Regarding your first question, this problem is sometimes called weekend effect. In my opinion, the answer is context-dependent. For instance, this question makes a lot of sense in the case of stock returns. See for instance here, here, here and here. But I am not sure if this effect applies to other contexts.
– user10525
Dec 15, 2012 at 15:52
• @Procrastinator Submit answer it's very good!!
– Jase
Dec 15, 2012 at 16:19
• There is a quantitative finance SE that may be more suited to get meaningfull answers. There are actualy a lot more problems than weekends: nights, bank holidays... etc. which get worse with multiple price sources. Jul 22, 2019 at 9:41