With respect to TTM, what seems rathers strange, is that Morningstar calculates TTM in standalone collumn, so it shouldn't be matter of implementation but data access.

Regards,

Sanning

Hi Sanning

I share your impatience. Like most software companies, our roadmap and appetite for improvements and new features (and volume of bugs) outpaces our engineering capacity. It is still in our roadmap and something we've been giving some thought to designing and prototyping. It would be a part of a larger upgrade to our fundamentals infrastructure and refashioning of the API.

All the best,
Josh

Thank you for your reply.

I totally get it and I am not saying anything with respect to other missing features but when you are working with fundamentals not being able to reliably access more than 1 quarter of data puts huge limitation on strategies we can develop. Your answer which indicates that it won't be pushed forward in forseeable future just shows that you are not aware of the opportunity costs. I mean almost every anomaly discovered with respect to data from financial statements are based on 1 financial year and more.

I really appreciate all the work and hours that you put into pipeline but with respect to TTM, FY etc. you seriously did not think it through.

Sorry for sounding cranky, I don't mean it in a bad way.

Good Luck,

Sanning

I've managed to get my fundamentals algorithm implemented in Quantopian with yearly data, but it is pretty useless. Based on actual trading history, the same algorithm in real life should yield 30-60 annually with quarterly data (most figures calculated with TTM and quarterly figures), but the annual figures miss market corrections in mispricings with many months.

This feature would be key for fundamental investors.

Is there any indication on the estimated release timing?

same question as Siim's. Will really appreicate QP team could provide such feature and nice to have estimated release timing.

We are actively working on speeding up fundamentals data loading and exposing TTM data. It's a major project, and has been underway for a few months already. The first milestone we are aiming for is to speed up fundamental data retrieval in pipeline. After that, we will be looking at the TTM fields. Again, the project is actively underway, but it involves a complete re-write of how we load and store the fundamental data, so it has taken some time. I don't have an ETA at this time but I can tell you that it is actively being worked on.

thanks for the update Jamie. QP team is the best.
hopefully it will provide easy access to Last-N-Q data (e.g. EPS) in an array-like, as well as Last-N-Year data.

Pipeline is a great design. However, my concern is such "Factor" based (snapshot of factor) doesn't communicate or allow algo to leverage historical "flow" and context. for sure, it's much easy and clear to recover price-vol context from a dataframe. Financial/accounting history is just as import as price itself, since they explained the underlying reason.

w/o such LNQ, LNY, we have to exclude whole cyclic sectors, failed to capture true and continuous EPS/operating CF growth.

I noticed Jamie provide a pipeline version of retrieving last N Q EPS. thanks for sharing.

@Jamie McCorriston, it is almost 3 years since you posted about work-in-progress to provide TTM fundamental data. How did it go?

Hi @Ken,

Last Twelve Month (LTM) does exist for FactSet Fundamentals. @Jamie had also previously provided a LastFourQuarters CustomFactor which can be used with MorningStar Fundamentals if you prefer that.