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At The Money: How to Manage Your News & Data Flow · Masters in Business

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  Speaker 1: The following episode of At the Money was recorded July
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  Speaker 1: twenty twenty five. This was before President Trump fired the
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  Speaker 1: Bureau of Labor Statistics Commissioner Erica mcintarfur. Please note the
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  Speaker 1: conversation was recorded before that departure. Newsday Wall Street relies
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  Speaker 1: on data economic releases, quarterly earnings, performance comparisons. But it's
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  Speaker 1: really easy to get tripped up by all of this math.
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  Speaker 1: How should investors manage this fire hose of numbers? To
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  Speaker 1: help us navigate this, let's bring in pulled Surprise winning
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  Speaker 1: reporter Michael Hiltzik. He covers business for the Los Angeles Times.
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  Speaker 1: He's a two time winner of the Gerald Globe Award
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  Speaker 1: and has authored numerous books on business. So, Michael, let's
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  Speaker 1: just start with the basics. How do you manage this
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  Speaker 1: analyst torrent of data that comes our way?
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  Speaker 2: Well, that's a good question. Mostly I try to ignore
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  Speaker 2: most of it, and I curate what I use and
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  Speaker 2: what I rely on. And basically the way I work
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  Speaker 2: is I start with a topic that I want to explore,
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  Speaker 2: a subject I want to explore, and then I go
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  Speaker 2: search out the data that I need. In that way,
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  Speaker 2: I'm not affected. I mean, there are some sources, you know,
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  Speaker 2: come across my emails regularly that I will pay some
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  Speaker 2: attention to, but most of it I don't, And I
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  Speaker 2: know where to go most of the time for what
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  Speaker 2: I need.
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  Speaker 1: So let's talk about that. If you're if you're going
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  Speaker 1: to be writing about or researching a particular subject, what
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  Speaker 1: sources of economic data do you rely on and what
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  Speaker 1: sources do you find troublesome and best ignored?
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  Speaker 2: Yeah, well, I think if I'm writing about, you know,
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  Speaker 2: something that touches on macroeconomics or domestic economics, I think
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  Speaker 2: you can't do better than the BLS, the Bureau of
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  Speaker 2: Labor Statistics or the Bureau of Economic Analysis, And thus
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  Speaker 2: far they haven't been undermined maybe a little bit, but
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  Speaker 2: not too much by by Trump, so their data are
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  Speaker 2: really still reliable. And I also go to FRED that's
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  Speaker 2: the service from the Saint Louis FED that can reduce
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  Speaker 2: a lot of this of the data from BLS and
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  Speaker 2: PA too graphical form, and I've published spread charts. You know,
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  Speaker 2: if there's a month that passes without it, that's that's rare.
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  Speaker 1: So how do you assess the credibility enact you're cy
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  Speaker 1: of any source obviously, BLS, b EA, FREAD have a
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  Speaker 1: very long track record. But what factors do you consider
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  Speaker 1: when you're looking at a source of economic data.
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  Speaker 2: Well, I look at at these sources the way I
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  Speaker 2: look at any sources. You know, I look for consistency.
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  Speaker 2: I look for you know, my father was a CPA
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  Speaker 2: and he used to say, you know, check the arithmetic.
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  Speaker 2: And I do that because you know, over the years
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  Speaker 2: or decades that I've been writing about business and finance,
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  Speaker 2: I look for outliers in the data. And when I
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  Speaker 2: see something like that, it warrants further checking, and it
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  Speaker 2: warrants skepticism. Actually, so you know, I look for trends
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  Speaker 2: to be consistent. I look for the data to be
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  Speaker 2: coherent and cohesive, and you know, if I can, I
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  Speaker 2: check one source against the other and then try to
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  Speaker 2: see if doing that turns up some flaw or flaws
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  Speaker 2: in the in the print.
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  Speaker 1: So so you mentioned check the math. Are there any
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  Speaker 1: other common data quality issues that you encounter that investors
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  Speaker 1: should be aware of?
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  Speaker 2: Well, there are some consistent laws or errors or mistakes
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  Speaker 2: that I find, typically in news reports that use these
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  Speaker 2: data and then try to draw conclusions. I think, you know,
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  Speaker 2: I both probably feel that data that's produced without an
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  Speaker 2: inflation deflator or without an acknowledgment, particularly if it's a
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  Speaker 2: trend line, is something that I try to fix if
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  Speaker 2: I can. But certainly that's a context that is consistent
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  Speaker 2: lacking in reports of the data. I you know, when
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  Speaker 2: I'm reading a report of an economic release, you know,
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  Speaker 2: in almost any newspaper, I will always try to go
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  Speaker 2: back to the original print, not rely on somebody's interpretation.
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  Speaker 2: I've just seen interpretations of data just be all over
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  Speaker 2: the place, particularly if we're talking about government programs that
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  Speaker 2: rely on financial statistics like Social Security, Medicare, Obamacare. I
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  Speaker 2: just see so many problems in reporting on those programs
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  Speaker 2: because reporters don't do the math, or they don't do
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  Speaker 2: their homework, or they come at these programs through a
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  Speaker 2: political perspective that basically allows them to ignore what's really happening.
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  Speaker 1: So you mentioned making sure that data is inflation adjusted.
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  Speaker 1: You and I have spoken about seasonality and how often
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  Speaker 1: that seems to trip up consumers of data. What other
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  Speaker 1: problems tend to arise when you see a commonly used
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  Speaker 1: data source or data series, Well, those.
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  Speaker 2: Are the big those are the big ones, you know,
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  Speaker 2: if I'm looking at a chart, if it if it's
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  Speaker 2: a trend line chart, and it doesn't go to zero,
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  Speaker 2: so that you don't really know, you can't really tell,
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  Speaker 2: you know, if a change is significant or if it's
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  Speaker 2: an artifact of big numbers are small numbers. I want
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  Speaker 2: to be suspicious about that. So and we see the
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  Speaker 2: you know, we see these flaws in reporting all over
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  Speaker 2: the place, the major newspapers, the wire services, cable news.
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  Speaker 2: They are basically winging it, and they're using data. Uh,
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  Speaker 2: they're using numbers that they get, they're misinterpreting them, sometimes wildly.
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  Speaker 1: So you you mentioned fred, which I really think of
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  Speaker 1: as an online software tool to depict data series in
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  Speaker 1: a graph or an image. Any other software or tools
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  Speaker 1: that you find useful.
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  Speaker 2: Well from time to time, we you know, we at
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  Speaker 2: the only times we've used fact set, Uh, we've used
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  Speaker 2: wide charts. I'm not sure. I'm pretty sure that we're
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  Speaker 2: not even subscribers to them anymore, but we use you know,
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  Speaker 2: for raw data and graphical displays. I find, yeahoo, finance
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  Speaker 2: is as good as as anything else. But you know,
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  Speaker 2: when I'm using these these sources, I do want to
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  Speaker 2: go back and double check the numbers, just to make
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  Speaker 2: sure that what what I'm using are the figures that
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  Speaker 2: were produced originally.
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  Speaker 1: What about trade organizations I recall frequently, especially during the
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  Speaker 1: financial crisis, being annoyed by a lot of the spin
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  Speaker 1: from the National Association of Realtors, who are the original
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  Speaker 1: source of a lot of housing sales data.
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  Speaker 2: Yeah, I think I think you're absolutely right about that.
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  Speaker 2: I mean, if I need to turn to an industry
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  Speaker 2: source or a lobbying organization or what have you, like
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  Speaker 2: the national, like the NAM, the franchisees have something, and
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  Speaker 2: they all produce figures. If I'm looking for a figure
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  Speaker 2: that they produce, if I want to say, you know,
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  Speaker 2: the National Association of Manufacturers says this, then I'll use it.
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  Speaker 2: But with the caveat that that's who they are. You
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  Speaker 2: can't always trust them. They are almost always talking their book,
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  Speaker 2: so to speak. And have to keep that in mind,
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  Speaker 2: and it's got to be re elected in what I
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  Speaker 2: write as well, and often look at you know, some
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  Speaker 2: of these outfits are sources that I rely on to debunk.
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  Speaker 2: And it's always a good column if I can say, look,
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  Speaker 2: here's what these guys said, and here's how they got
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  Speaker 2: the numbers. Wrong, and here's why they probably deliberately got
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  Speaker 2: the numbers wrong.
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  Speaker 1: What about thing tanks? They publish analytical data frequently, but
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  Speaker 1: I would hardly consider them objective or disinterested parties.
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  Speaker 2: Yeah, I agree, some are better than others. Some I
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  Speaker 2: will use or quote without too much fear. The Peterson
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  Speaker 2: Institute of International Economics I find consistently pretty good, definitely
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  Speaker 2: useful for trade issues, trade figures, trade commentary. There's another
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  Speaker 2: Peterson funded think tank, the Commission for the Responsible Federal
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  Speaker 2: But I mean sometimes I find them useful. Sometimes their
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  Speaker 2: analysis is so infected by ideology or partisanship that you know,
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  Speaker 2: I have to walk back when I when I see
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  Speaker 2: I have to sort of, you know, recalculate with what
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  Speaker 2: they've used.
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  Speaker 1: So you were a column recently on Tesla. What about
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  Speaker 1: public companies? How do we evaluate things like not just earnings,
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  Speaker 1: but forward guidance and all sorts of Sometimes it's a
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  Speaker 1: little bit of happy talk about what's coming in the future.
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  Speaker 2: Yeah, well, I think, you know, if we're uh, you know,
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  Speaker 2: to the extent they're putting out disclosed financials, you know,
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  Speaker 2: subject to sec oversight, they are, that is what it is. Uh,
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  Speaker 2: you know, you know I can say, this is what
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  Speaker 2: they've disclosed, this is what they've said. Forward guidance, I think,
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  Speaker 2: you know, forward guidance to me is basically, you know,
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  Speaker 2: trying to shoehorn a long term perspective into a snapshot. Uh.
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  Speaker 2: It's it's very rare, rare that it's uh useful at all.
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  Speaker 2: And of course that also depends on who's doing the
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  Speaker 2: forward guidance. When we add elon musk uh you know,
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  Speaker 2: deliver a you know, financial Q and a. Just last night,
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  Speaker 2: I'm not sure. I'm not sure that any of that
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  Speaker 2: uh is useful any more than anything he says it's useful,
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  Speaker 2: and it was. It was very musky, and you know,
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  Speaker 2: it was, uh, you know, we're going to have uh,
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  Speaker 2: you know, we're you know, we're gonna have robots, you know,
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  Speaker 2: cleaning our house and you know, take care of our
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  Speaker 2: children by the end of next year, you know, I
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  Speaker 2: mean is his timelines are always suspect and others. But
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  Speaker 2: a company that's in trouble you want to be uh,
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  Speaker 2: you know, very cautious about uh, you know what they're saying.
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  Speaker 2: You know, a company that's revised me it's forward guidance.
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  Speaker 2: We're dropping its forward guidance. I think we all know
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  Speaker 2: these are red flans.
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  Speaker 1: Yeah, I've been waiting for fully self driving cars now
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  Speaker 1: for ten years and it's always two years away. So
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  Speaker 1: let me ask a slightly offbeat question. Early in my career,
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  Speaker 1: there was this entire group of conspiracy theorists who believed
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  Speaker 1: that the BLS was cooking the data, that you couldn't
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  Speaker 1: trust beea, that all of the government sources of information
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  Speaker 1: were partisan and biased and completely unreliable. That hasn't been
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  Speaker 1: my experience, But what's your experience, like.
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  Speaker 2: Well, no, it hasn't been my experience. And look, you
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  Speaker 2: know the data, the statistics that come out of those agencies. Basically,
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  Speaker 2: you know, these are time trend prints essentially, and they're
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  Speaker 2: the benchmarks. So I think we have to rely on
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  Speaker 2: them as benchmarks. And we know that b l S
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  Speaker 2: and b A I think periodically revise their methodology, but
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  Speaker 2: they're transparent about it. And you know, as long as
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  Speaker 2: we recognize that there's a break in in the in
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  Speaker 2: the trend line, then I think we can deal with
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  Speaker 2: it safely. But but but you know, politicians are always
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  Speaker 2: sort of attacking these sources when they the numbers that
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  Speaker 2: they produce you know, are inimical to their uh, their
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  Speaker 2: partisan goals, and you know, we have to get used
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  Speaker 2: to it. We're certainly seeing that now. I think we'll
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  Speaker 2: see it more. You know, we're going to see an
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  Speaker 2: attack on FED data. Uh, dis intensifying.
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  Speaker 1: So what are the other pitfalls that investors should aware
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  Speaker 1: of when it comes to economic data.
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  Speaker 2: Well, I think investors always have to be sensitive to
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  Speaker 2: the source of the data they're relying on. They have
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  Speaker 2: to be cautious about sort of second order or third
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  Speaker 2: order interpretations. The data, certainly on the macroeconomic or agency level,
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  Speaker 2: is always accessible. But you know, I sympathize with investors
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  Speaker 2: who just don't have the time to go back and look.
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  Speaker 2: I think projections of market activity these are you know,
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  Speaker 2: never of great value. You know, projections are always good
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  Speaker 2: and accurate right up to the point that they're not. So,
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  Speaker 2: you know, at sort of larger, larger issues. You know,
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  Speaker 2: when I when I hear somebody talking about, well, liquidity
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  Speaker 2: is going to drive the market or something like that,
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  Speaker 2: I don't really put much trust really as in that.
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  Speaker 1: So to wrap up, investors who are looking to learn
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  Speaker 1: more from economic data need to go to the original
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  Speaker 1: sources prioritize, make sure you are aware of things like
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  Speaker 1: inflation adjusting and seasonal adjustments. Be wary about trade organizations
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  Speaker 1: and think tanks, not all of them are objective. The
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  Speaker 1: same is true about forward guidance from companies public companies
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  Speaker 1: about what they see in the future, and just generally
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  Speaker 1: use common sense when it comes to analyzing the endless
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  Speaker 1: fire hose of economic data. I'm Barry Ridholts. You're listening
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  Speaker 1: to act the money on bloomber