Commercially available order flow data and exchange rate movements : Caveat emptor

Research suggests that customer order flow should help predict exchange rates. We make two contributions. First, we provide a review of the recent literature on order flow and exchange rate movements. Second, we critically evaluate the practical value of customer order flow data that are commercially available to the wider market, as well as the forecasting properties of inter-dealer order flow. In line with microstructure theory, we find little evidence that the latter can forecast exchange rates, but our results also cast considerable doubt on the practical value to market practitioners of commercially available customer order flow data

Non-Standard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

Non-Standard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants