Speaker 1: Hello, and welcome to another episode of the Odd Blots podcast.
Speaker 1: I'm Tracy Allaway and I'm Joe wisntal Joe. I don't
Speaker 1: know if you've been following what's going on in Hong
Speaker 1: Kong markets lately, but there is a very very big
Speaker 1: event coming up. Well it's only a few weeks away now,
Speaker 1: although I have to say I'm not exactly sure when
Speaker 1: we're at leasing this episode, but in theory, there is
Speaker 1: a very big event coming up, so much to choose from.
Speaker 1: I feel like, you know, when you say something like, oh,
Speaker 1: I'm not sure if you're following what's going on in
Speaker 1: Hong Kong lately, my mind darts to, like, uh ten
Speaker 1: different things. Yeah, okay, But in the market, there is
Speaker 1: just one thing I think that everyone is focused on
Speaker 1: at the moment, and that is the I p O
Speaker 1: of Ant Group, which is the sort of offshoot of
Speaker 1: Jack Ma's Ali Baba. The big thing about this particular
Speaker 1: I p O is that I think they're aiming for
Speaker 1: evaluation of something like at least two hundred eighty billion dollars,
Speaker 1: which would easily make it the biggest I p O ever,
Speaker 1: and the whole transaction again, it hasn't actually taken place yet,
Speaker 1: but the whole transaction is so big that we're actually
Speaker 1: seeing it affect things like demand for Hong Kong dollars.
Speaker 1: We've seen liquidity in that market Titan. The demand for
Speaker 1: ant shares is expected to be so high that they
Speaker 1: haven't even bothered with Cornerstone investors, which is really unusual
Speaker 1: for an I p O. We're also seeing brokers in
Speaker 1: Hong Kong offer retail investors twenty times leverage on the
Speaker 1: ant shares because they're so certain there's going to be
Speaker 1: a pop on the first day of trading, and everyone
Speaker 1: wants to get an allocation of the equity when it
Speaker 1: first comes out. So it's a really really big deal,
Speaker 1: and you can see that there's a lot of excitement
Speaker 1: around at at the moment. Wow, those are some great stats.
Speaker 1: And I knew it was a big deal, and I
Speaker 1: knew it was a big company, but actually you sort
Speaker 1: of just blew me away with all that stuff. I mean,
Speaker 1: two quick questions for you. A what does AUNT do?
Speaker 1: I mean, I know it's like this big finance thing,
Speaker 1: but I actually have no concept of what the company
Speaker 1: actually does. And be two billion dollars, I mean that's
Speaker 1: got to make it. Whether you know, it's bigger than
Speaker 1: any US financial institution by a laun shot, right, Yeah,
Speaker 1: I think that's right. And if you think think back
Speaker 1: to Saudi Aramco. I mean, there was so much talk
Speaker 1: about Saudi Aramco when they listed on public markets for
Speaker 1: the first time. I think we even did one or
Speaker 1: two episodes about it that ended up being something like
Speaker 1: twenty eight billion dollars raised, so much smaller than what
Speaker 1: we're talking about now. Aunt grew Group. I'm sure I'm
Speaker 1: not going to describe it right, and I'm sure some
Speaker 1: people are going to take issue, but it's basically the
Speaker 1: sort of um I think it's the fintech portion of
Speaker 1: Ali Baba, including Alley Pay, which is one of the
Speaker 1: big big payments providers in China along with we Chat.
Speaker 1: So if you've ever visited China, you know that cash
Speaker 1: is almost non existent at this point, and anywhere you go,
Speaker 1: be it a Starbucks or a street side vendor, you
Speaker 1: can pay using a digital wallet like ally Pay or
Speaker 1: wee Chat. So that's one of the reasons people are
Speaker 1: really excited about it. And of course it's a big
Speaker 1: fintech giant in a very very large market in one
Speaker 1: of the few markets that is really growing at the moment,
Speaker 1: given China's purported economic strength. But of course when it
Speaker 1: comes to this type of growth, particularly in China, there's
Speaker 1: always a question mark over how you're actually measuring that
Speaker 1: and whether those measurements or those numbers are accurate or not,
Speaker 1: you know what I mean, absolutely so, So just to
Speaker 1: step back, just to sort of conceptualize the company, um,
Speaker 1: Ali Baba is this sort of right e commerce powerhouse,
Speaker 1: extraordinary company doing all kinds of things, And so I
Speaker 1: guess you could sort of imagine it is like say,
Speaker 1: like Facebook or some of the US megacap internet companies,
Speaker 1: they have their own like sort of payments apps and
Speaker 1: payments messaging and stuff like that, and so this would
Speaker 1: be this is Ali Baba's. It's gigantic, and they're essentially
Speaker 1: spinning it out into its own publicly traded company that's
Speaker 1: worth the insane amount of money. But as you say,
Speaker 1: you know, with with so many of these UH companies,
Speaker 1: I mean, they produce financials, but all kinds of um
Speaker 1: difficulty really gating from the outside like a true like
Speaker 1: size and scope of the business. Yeah, I guess you
Speaker 1: could think about it as jen if Amazon also owned
Speaker 1: Venmo or something like that, and everyone used Venmo to
Speaker 1: pay for virtually everything in the US. Oh, and also
Speaker 1: that Amazon had a gigantic money market fund that people
Speaker 1: using Venmo could also invest in. That's that's kind of
Speaker 1: Alley Pay in a nutshell. I'm excited now. Okay, So
Speaker 1: for today's episode, we're going to do a deep dive
Speaker 1: onto Chinese internet companies. We're going to get a better
Speaker 1: sense of how they're actually accounting for the growth that
Speaker 1: I just described, and I think we're going to get
Speaker 1: a better idea of whether or not all that excitement
Speaker 1: over future growth is necessarily justified. And to do that,
Speaker 1: we're going to be speaking to Stephen Clapham. He's the
Speaker 1: founder of Behind the balance Sheet and also runs an
Speaker 1: investment and research training consultancy. He recently published a very
Speaker 1: very detailed and expensive report into Chinese internet stocks, looking
Speaker 1: at them from a forensic accounting perspective. So really the
Speaker 1: perfect person to discuss all this with. I think, alright,
Speaker 1: I can't wait. You got me super excited. Okay, all right, Steven,
Speaker 1: welcome to the show. Thanks so much for coming on. Well,
Speaker 1: thank you for having me. So I guess to begin with,
Speaker 1: I'm curious what piqued your interest in Chinese internet stocks
Speaker 1: in particular, because there's no shortage of companies that you
Speaker 1: could be looking at with a forensic accounting background, and
Speaker 1: you chose to look at these ones in particular. I
Speaker 1: think you looked at five of the biggest ones. What
Speaker 1: sparked your interest? Well, Tracy, you said that this report
Speaker 1: was expensive, and in fact, I want to disagree articly
Speaker 1: because I think this report is very cheap and the
Speaker 1: reason I allude at these is five thousand dollars, right, honestly, Tracy,
Speaker 1: five thousand dollars is a argon for this report. And
Speaker 1: before you laugh, and let me explain why. So the
Speaker 1: reason that I looked at this I was commissioned to
Speaker 1: produce this report by a client, and one of my
Speaker 1: training clients is particularly interested in the Chinese um internet
Speaker 1: companies and was concerned that they hadn't been able to
Speaker 1: get to the bottom of the way they were accounting
Speaker 1: in various aspects when we talked about what those aspects were,
Speaker 1: so they asked me if I could help, and I said, yeah,
Speaker 1: of course, and foolishly I completely underestimated how long it
Speaker 1: would take to to do the work. And when I
Speaker 1: tell you that Ali Baba's accounts were a thousand and
Speaker 1: seventy seven pages long, you can probably understand why it's
Speaker 1: quite easy to underestimate how long it would take. And
Speaker 1: so I went back to the clients halfway through the
Speaker 1: work and I said, look, I'm having a better problems
Speaker 1: here because it's taken me far, far longer than than
Speaker 1: I was anticipating. I knew that it would be complicated,
Speaker 1: but I didn't quite understand how much work would be involved.
Speaker 1: And the clients, I know, look, no problem at all.
Speaker 1: I said, Look, the best way around this is I
Speaker 1: don't want to do a bad job for you, but
Speaker 1: equally I don't want to spend a huge amount of
Speaker 1: time and I'm not getting rewarded for so the best compromises,
Speaker 1: why don't I just sell the report once you were
Speaker 1: finished with it and once you've done everything that you
Speaker 1: want to do in the in the stocks. And they
Speaker 1: said that's fine, and so we um, we just put
Speaker 1: the report up on the website a few weeks ago.
Speaker 1: There's been quite a bit of interesting we haven't actually
Speaker 1: started to advertise it yet. Obviously, these are very, very
Speaker 1: big companies, and they are incredibly complicated, and if you
Speaker 1: think about a set of accounts, it's over a thousand
Speaker 1: pages long. The most recent accounts are about half that,
Speaker 1: but it's still a huge amount of time to go through.
Speaker 1: And what we do is we go through word by words,
Speaker 1: number by number, dissecting every element of it. And if
Speaker 1: you're the average institutional investor, you just not have time
Speaker 1: to do this detail work. So that's why five dollars
Speaker 1: is Actually it's not nearly it's not nearly as much
Speaker 1: as it sounds, because it's saved people a huge amount
Speaker 1: of effort and there's a huge amount of effort involved
Speaker 1: on our side and producing it. Okay, So setting aside
Speaker 1: whether five thousand dollars is a fair value or not,
Speaker 1: stepping back a little background, tell us your sort of
Speaker 1: general work. You mentioned that this was originally produced for
Speaker 1: a training client. What do you do for clients when
Speaker 1: you say training clients? And what was the sort of
Speaker 1: request that came in that ultimately led to this research? Oh? Sure,
Speaker 1: so we I mean, our business has got three parts
Speaker 1: to it. We've got our retail side, so we've got
Speaker 1: an online training school for retail investors. So you can
Speaker 1: go there and you can buy one of our courses
Speaker 1: which helps you understand how to invest. And then on
Speaker 1: the institutional side, which two things we do bespoke research
Speaker 1: for people and we run training courses. So we've got
Speaker 1: a forensic accounting course which we started in June and
Speaker 1: we've done I think three hundred people have been through
Speaker 1: that course in the last two and a bit years.
Speaker 1: Obviously fewer people this year because it's a physical in
Speaker 1: perison course, although we've been doing a little bit of
Speaker 1: it on on Zoom. And on the bespoke research side,
Speaker 1: people typically will come to us when they've got a problem,
Speaker 1: they've got a piece of research that is either too
Speaker 1: difficult for them to do in house, or too time
Speaker 1: consuming for them to do in house, or sometimes too
Speaker 1: controversial for them to do in has. Often what happens
Speaker 1: is you own a stock and it goes down, and
Speaker 1: the analyst that's involved in in looking after that position,
Speaker 1: we'll do one of two things while they say he
Speaker 1: or she, while they say, you know what, I think,
Speaker 1: we think I'm in a mistake. We should just get out,
Speaker 1: or they'll say I'm right, We've just got to be patient.
Speaker 1: And often what happens is the portfolio manager doesn't feel
Speaker 1: that the analyst is being able to make the decision
Speaker 1: rationally without emotion, and he doesn't have enough time to
Speaker 1: do the working staff, so they bring me in as
Speaker 1: a sort of independent third party without any emotion attached
Speaker 1: to the holding that can make a rational assessment of
Speaker 1: where the risk and reward lies at this point after
Speaker 1: the shares have fallen. And that's what we do. It
Speaker 1: a little bit of that. And the other thing we
Speaker 1: do is we do forensic accounting research. So people will say,
Speaker 1: you know, I'm thinking of I'm thinking of buying a
Speaker 1: stock and can you please have a look at it?
Speaker 1: Or they'll say we own this stock, can you please
Speaker 1: have look at it? In fact, it won't be a
Speaker 1: surprise to you, Tracy sitting in Hong Kong that Hong
Speaker 1: Kong listed or Chinese based companies are quite a popular
Speaker 1: area for people to ask us to get involved. One
Speaker 1: we did quite recently it was Hutchinson, so a client. Again,
Speaker 1: I mean I do this obviously exclusively for Trump for
Speaker 1: clients that our clients on the training side. I don't
Speaker 1: get random people coming in off the street asked me
Speaker 1: to do fends and accounting reports for them. I do
Speaker 1: it for the people that know me and like my work.
Speaker 1: And this particular client, very big two billion asset manager.
Speaker 1: We're interested in Hutchson because it looked very cheap, and
Speaker 1: he said, can you go and have a deeper dive
Speaker 1: and tell us if it really is cheaper not? And
Speaker 1: that's typically what we do, and this is exactly what
Speaker 1: we did in the case of the fire Chinese internet
Speaker 1: companies Ali Baba, ten Cent, JD, dot Com, Buy Do
Speaker 1: and made To and Ding Dan King. There are those
Speaker 1: five stocks we were asked to look at and to
Speaker 1: look at on a series of I think it was
Speaker 1: a dozen different elements, and there were things like is
Speaker 1: the company flattering at sarnings? Is the company using investment
Speaker 1: gains to boost tarnings? Is it carrying the value of
Speaker 1: enlisted investments? Are they being carried at the correct values?
Speaker 1: So it's a whole string of things that we were
Speaker 1: that we were asked to the camp. That's a really
Speaker 1: helpful description of what you do. I'm curious when it
Speaker 1: comes to Chinese stocks though, are there particular challenges that
Speaker 1: investors face when it comes to things like transparency or
Speaker 1: you know, realistic accounts. I guess this is a criticism
Speaker 1: that we hear about Chinese accounting and Chinese companies quite
Speaker 1: a lot. There's all sorts of issues you face. I mean, clearly,
Speaker 1: the first problem you've got is that the first of
Speaker 1: all I've got is that I don't speak the language.
Speaker 1: I can't read the language. So you're at a massive
Speaker 1: disadvantage relative to looking at a company in the United States.
Speaker 1: Are in the UK, where you've got that sort of
Speaker 1: home country advantage and where you've got local pools of knowledge,
Speaker 1: local sources of intelligence. And we've got some contacts in China.
Speaker 1: But for example, one of the things that the client
Speaker 1: asked us to look into was the role of the
Speaker 1: audit firm and any connections between the partner involved in
Speaker 1: the audit and the companies. And you know, we had
Speaker 1: to say to them, look, we can't really do that
Speaker 1: because we just don't have sufficient knowledge. We don't have
Speaker 1: any feet on the ground in China um to be
Speaker 1: able to assess if there are any hidden links between
Speaker 1: the company and the auditor, whereas in the UK, for example,
Speaker 1: that would be it wouldn't be easy to do. But
Speaker 1: we've got various tools and techniques that we deploy in
Speaker 1: order to make an assessment if that there, if there
Speaker 1: could be that sort of connection. But it would be
Speaker 1: impossible for us to look at something like that in China,
Speaker 1: and we don't we just so we don't. We don't,
Speaker 1: We don't even try. But there's there's a number of
Speaker 1: issues with Chinese companies in general. Obviously the use of
Speaker 1: these variable interest entities is a very common that these
Speaker 1: companies are said, uh and these you know, that has
Speaker 1: a whole set of other issues which we which we
Speaker 1: don't go into detail in this report because they're generic.
Speaker 1: You know, that's a generic thing. What are you buying
Speaker 1: when you buy one of these businesses? And you know,
Speaker 1: there's lots been been written about that, and people I
Speaker 1: think have made their own judgments about whether they find
Speaker 1: that an acceptable risk or an unacceptable risk. Instead, what
Speaker 1: we did here was we drilled down into some of
Speaker 1: the specifics. And many of the specifics are related to
Speaker 1: the nature of these businesses, the fact that they are
Speaker 1: internet businesses and that they're heavily involved in a whole
Speaker 1: investment ecosystem, and so a lot of our work was
Speaker 1: dedicated to that area that part of them. So to
Speaker 1: do some compare and contrast. Obviously, we have our internet
Speaker 1: giants here in the US, Facebook, Amazon, etcetera. Talk to
Speaker 1: us about some of the general differences that are required
Speaker 1: for someone to do serious accounting analysis of the books
Speaker 1: or of the statements of US based Internet companies first
Speaker 1: Chinese ones. Well, I mean some of these companies report
Speaker 1: under US GAP. So there's you know that counting rules
Speaker 1: are the same, um right, ten Cent reports sunder I
Speaker 1: f r S, which I think is quite unusual because
Speaker 1: ordinarily companies that are listed in the US generally have
Speaker 1: gaps as their main language, mean accounting language, but that
Speaker 1: counting rules are exactly the same. But what you've got
Speaker 1: here is if you if you think of Ali Baba
Speaker 1: and Amazon, they're being they're they're kind of similar in
Speaker 1: in concept. I mean they're obviously they do different things
Speaker 1: and their different score ten Cent, gd dot com you
Speaker 1: would think of those in the same light as thinking
Speaker 1: of an Amazon. But if I told you that the
Speaker 1: Ali Baba cants went from over a thousand pages to
Speaker 1: just under five hundred pages, do you know how long
Speaker 1: that counts are for Amazon? Do you want to make
Speaker 1: a guess? A good guess? So you're You're obviously practiced
Speaker 1: at this game, because the Amazon accounts in twenty nineteen,
Speaker 1: including Jeff Bezos's letter at the front, which is an
Speaker 1: addendum to the actual pen K filing, was only eighty
Speaker 1: seven pages, so their cants are much much simpler there
Speaker 1: and an Amazon um I think, although I disagree with
Speaker 1: some of it's some of the way it presents its numbers.
Speaker 1: You know, I wrote a blog a little while ago
Speaker 1: about the fact that it presents its free cash flow
Speaker 1: in three different ways, all of them wrong in my view.
Speaker 1: I've got a different definition, but at least it is
Speaker 1: quite helpful in the way it presents its numbers. Some
Speaker 1: of these Chinese companies are I would open it they're
Speaker 1: less helpful than ANALYSM. Sorry, can you just dive into
Speaker 1: that point? So how are the numbers less helpful? And
Speaker 1: I'm aware that, you know, one of the criticisms of
Speaker 1: tech companies all over the world is flattering their growth figures,
Speaker 1: you know, how many users they have on their platform.
Speaker 1: There's also, I guess, the use of non gap metrics,
Speaker 1: the most famous being uh we work and community adjusted EBITDA.
Speaker 1: Is that the kind of thing that you're that you
Speaker 1: found in your report. Yeah, absolutely, I mean the use
Speaker 1: of non gap. I mean this isn't a criticism solely
Speaker 1: of these and Neese companies. I mean it's that it's
Speaker 1: very prevalent throughout Less and Pole hundred as well. Um.
Speaker 1: But you know these companies, the non gap numbers and
Speaker 1: the gap numbers are there often miles apart, not so
Speaker 1: much in the case of ten cents, but in the
Speaker 1: case of all there for they're very significant differences. And
Speaker 1: you know one of the main differences, which isn't a
Speaker 1: criticism of the Chinese companies, more a criticism of the
Speaker 1: way the South Side community treats the reporting these days.
Speaker 1: But they all make huge adjustments for stock based compensation.
Speaker 1: So I think in the case of Ali Baba, but
Speaker 1: I remember correctly, it was something like five billion dollars
Speaker 1: um and that obviously stock based compensation is a real
Speaker 1: expense because if you didn't give people stock, you'd have
Speaker 1: to pay them real money. And it's a real expense
Speaker 1: because it comes at the expense of shareholders, shield shareholders
Speaker 1: lucid to the extent that these shares are issued. So
Speaker 1: it's daft. I think that analysts ignore this number when
Speaker 1: they're calculating earnings because if they weren't, it wasn't stock based,
Speaker 1: it'd be cash and they wouldn't ignore it. So I
Speaker 1: think this is just you know, one aspect. But the
Speaker 1: one of the big elements in the Chinese group which
Speaker 1: is different from the US peers is the use of
Speaker 1: investment gains to flatter profits. Do you see a lot
Speaker 1: of gains on either the sale of investments or on
Speaker 1: the revaluation of investments. And this isn't to say that
Speaker 1: these companies are doing anything wrong because the counting rules
Speaker 1: I think are slightly daft in in in this in
Speaker 1: this respect, because what happens here is that I've got
Speaker 1: an investment in company X. Company X is a young,
Speaker 1: fast growing Chinese internet company. It's hungry for capital, so
Speaker 1: it needs more capital, and it decides to bring in
Speaker 1: an outside shareholder. When outside shareholder makes an investment, it's
Speaker 1: likely to be at a higher price than the price
Speaker 1: which I have invested, And accounting rules require you to
Speaker 1: revalue the investment and book the game through the p now,
Speaker 1: which it's obviously ludicrous. I mean, whoever thought up this
Speaker 1: accounting standard, I don't know what planet they were that
Speaker 1: they were wrong but I think it's a I think
Speaker 1: it's a silly system. And I'm not saying that the
Speaker 1: companies are doing anything wrong by adopting this. This is
Speaker 1: what they're required to do, but it gives a misleading
Speaker 1: representation of their profitability. So this should be a balance
Speaker 1: sheet item as opposed to something that would flow down
Speaker 1: to the bottom line basically, if we're trying to get
Speaker 1: a true understanding of the company. Yeah, well, I mean
Speaker 1: I would argue that it shouldn't even be adopted in
Speaker 1: the balance sheet. You might want to note what the
Speaker 1: what most recent valuation was, because obviously it's helpful for investors.
Speaker 1: But to give you an example, in the case of
Speaker 1: Ali Baba mean Ali Baba and had an investment in
Speaker 1: a business and the investment was being reorganized and these
Speaker 1: are almost invariably very complicated structuring. So this particular investment
Speaker 1: was an investment that they held jointly without financial and
Speaker 1: the business was restructured by being merged with another business.
Speaker 1: And who should come in to make an investment in it?
Speaker 1: But soft Bank. Now we all know that soft Bank
Speaker 1: is not the most disciplined purchaser of assets, and that
Speaker 1: they've been prepared to invest on the basis of a
Speaker 1: longer term vision than most other more ordinary shareholders would
Speaker 1: be prepared to say so, being prepared to pay very
Speaker 1: high prices for some assets that I think are quite questionable.
Speaker 1: So Ali Baba also owns it is also partly owned
Speaker 1: by soft Bank, So soft Bank owns a big steak
Speaker 1: in Ali Baba. So what you have is SoftBank coming
Speaker 1: in paying a very high price for one of Alabama's assets,
Speaker 1: and Ali Baba then revaluing the value of that asset
Speaker 1: in its books and taking a difference to profit loss account.
Speaker 1: What could go wrong? Well, um, just on that note,
Speaker 1: could you maybe talk a little bit more about related
Speaker 1: party transactions because this is something that also crops up
Speaker 1: quite a bit with Chinese companies, where you often have
Speaker 1: this sort of shadowy network of companies that are tangentially
Speaker 1: related to each other and are sometimes, if not self dealing,
Speaker 1: lending each other helping hand when it comes to things
Speaker 1: like funding. What examples of that did you find? There
Speaker 1: are a lot of related party transactions in in in
Speaker 1: these companies. Ali Baba is actually not the not the
Speaker 1: main culprit here. I think it was g D dot
Speaker 1: Com had the largest exposure it's related party transactions and
Speaker 1: the problem with the lated party transactions, and that we
Speaker 1: we cover this in our forensic accounting course for our
Speaker 1: institutional clients. We also cover it in online courses for
Speaker 1: retail investors to say, look, one of the first things
Speaker 1: that we look at when we open this out of accounts,
Speaker 1: we look at the related parties, not because if there
Speaker 1: are a string of related party transactions, you then have
Speaker 1: to ask yourself, well, who's who's verifying this? How do
Speaker 1: we know that these numbers are accurate? How do we
Speaker 1: know that we're not being disadvantaged? And it's almost impossible
Speaker 1: for the outside investor to make a rational judgment of this,
Speaker 1: and equally, it's probably pretty difficult for the auditor to
Speaker 1: make a real assessment of have the related party transaction
Speaker 1: has been booked correctly in their cants? And so many
Speaker 1: of the frauds that I studied when I was originally
Speaker 1: building the forensic accounting course, I went to spent time
Speaker 1: in the British Library and I poured through all sorts
Speaker 1: of academic studies. I poured through lots of accounts. I
Speaker 1: looked back at past frauds, and many of them. One
Speaker 1: of the one of the key signals in advance was
Speaker 1: related party transactions. And where you've got related party transaction,
Speaker 1: you just don't know what the motivation is and you
Speaker 1: don't know whether you are being fairly treated, and that's
Speaker 1: a huge it's always a huge risk. So what I
Speaker 1: say to the to my retail clients is that if
Speaker 1: you open their hands and there's a page related party transactions,
Speaker 1: it's probably it's probably not worthwhile pursuing that as a
Speaker 1: potential investment because it could take you a huge amount
Speaker 1: of time to verify, and even then you may not
Speaker 1: know that you've got the right answer. So what else
Speaker 1: is in there? I mean, you mentioned that the ali
Speaker 1: Baba accounts are five hundred pages, the Amazon accounts are
Speaker 1: eighty seven pages. What else is found in that four
Speaker 1: hundred and thirteen page gap that fundamentally makes the analysis
Speaker 1: of an Ali Baba more complicated and more work than
Speaker 1: the analysis of Amazon. But I mean, it's just this
Speaker 1: year's scale volume, number of transactions that they're doing, apart
Speaker 1: from anything else. You know, when we when we look
Speaker 1: at companies that are doing a lot of acquisitions and disposals,
Speaker 1: it's very difficult to determine what's actually going on, because
Speaker 1: where you've got a lot of acquisitions, and even where
Speaker 1: you've got disposals, the underlying cash flows can be obscured.
Speaker 1: Just they explain what I mean using perhaps a simpler
Speaker 1: example would be you know, you often see rolloups platform
Speaker 1: companies where they're making acquisition after acquisition. One of the
Speaker 1: things that we worry about when we see these is
Speaker 1: when you look at the operating cash flow in any year,
Speaker 1: you don't know how much of the cash flow has
Speaker 1: been generated from the business itself and how much of
Speaker 1: the cash flow has been generated from improving, for example,
Speaker 1: the working capital in the businesses you acquired last year.
Speaker 1: And you often see this in rollouts where they'll do
Speaker 1: a lot of acquisitions of of mom and pop businesses.
Speaker 1: They buy the mom and pop businesses which maybe didn't
Speaker 1: have an independent credit controller, and they'll enforce very strict
Speaker 1: terms and their customers, and immediately they get a cash
Speaker 1: return in that they're working capital shrinks, so they're operating
Speaker 1: cash flow looks much better than it really would would
Speaker 1: do were it not continuing to make acquisitions. And that's
Speaker 1: fine as long as you carry on making more and
Speaker 1: more acquisitions and and repeating the formula, But as soon
Speaker 1: as you stop, what often happens with these businesses is
Speaker 1: the cash flow on wines and it's the exact same
Speaker 1: thing is true, but on a different scale for these
Speaker 1: Chinese companies because they're making loads and laws of acquisitions
Speaker 1: and disposals each year, and so trying to divorce what's
Speaker 1: going on in their core business with what's going on
Speaker 1: as a result of acquisitions is extremely difficult. Now, they
Speaker 1: would probably argue that they're investing in young, immature businesses,
Speaker 1: and to the extent that they're making acquisitions, they're probably
Speaker 1: having to invest in the working capital, so that the
Speaker 1: actual cash flows are worse than they would otherwise be.
Speaker 1: But you're seeing um also a change in the coversation
Speaker 1: of the businesses. So more of these businesses are going
Speaker 1: to subscription type models in which customers are paying in advance.
Speaker 1: So obviously the opposite is true, and their cash flows
Speaker 1: would then be enhanced relative to what they would have
Speaker 1: been if they hadn't been making acquisitions. So the most
Speaker 1: complicated part of this is the fact that there's lots
Speaker 1: and lots of moving parts and they're all moving very quickly,
Speaker 1: and that's what makes the makes the job of understanding
Speaker 1: the business much much more complicated. So your description of
Speaker 1: add backs just reminded me very much of Valiance roll
Speaker 1: up strategy back in the day, and I remember one
Speaker 1: of the issues with the roller was that you ended
Speaker 1: up getting a lot of add backs where the company
Speaker 1: would add back line items for acquisitions. So, for instance,
Speaker 1: if it expected a transformational m and a deal to
Speaker 1: really add to its bottom line, it would add back
Speaker 1: extra revenue or extra profit into its accounts. Is that
Speaker 1: something that you see with Chinese companies and does that
Speaker 1: also impact they're funding because again going back to the
Speaker 1: Valiant example, I remember that the ad backs basically made
Speaker 1: Valiant appear a lot less leverage than it otherwise would
Speaker 1: have appeared, which allowed it to tap the debt market
Speaker 1: relatively cheaply for a very long time and keep buying
Speaker 1: extra companies. Yeah. I mean Valiant is a very curious
Speaker 1: example because there was such a massive difference between the
Speaker 1: numbers that analysts were focusing on and the numbers which
Speaker 1: were being report that you would have imagined that people
Speaker 1: would have spent more time focusing on that. I think
Speaker 1: the case of these Chinese companies is slightly different. If
Speaker 1: I told you that if you looked at the last
Speaker 1: five years for these five companies, um and I told
Speaker 1: you that they had made investments in the Chinese, predominantly Chinese,
Speaker 1: and they made a very small number of acquisitions, very
Speaker 1: small volume of acquisitions overseas. But they basically they've invested
Speaker 1: in a huge range of Chinese venture capital. And if
Speaker 1: I told you that they had spent nearly three trillion,
Speaker 1: that's trillion, remember in the last five years. So what's
Speaker 1: that that's like five vision funds, these five companies in
Speaker 1: five years. I like, how we measure everything in vision
Speaker 1: funds nowadays? Yeah, it's a great it's a great unit
Speaker 1: of I think it's a useful it's a useful unity.
Speaker 1: It's absolutely great. You want to look at you want
Speaker 1: to scale something ridiculous, And that's so you know, on average,
Speaker 1: there's a vision fund every year, or a vision fund
Speaker 1: every company to any how you look at it. But
Speaker 1: that's basically what we're saying. And you then have to decide, okay,
Speaker 1: unlike perhaps the vision fund, have they made sensible investments
Speaker 1: and that the issue here then becomes, okay, well, what
Speaker 1: is the carrying value that they're that they're showing in
Speaker 1: their in their books for these investments, and to be
Speaker 1: fair to them, they vary. The disclosures do vary from
Speaker 1: company to companies. Some are better, some are worse. But
Speaker 1: you know, there are so there are enough disclosures at
Speaker 1: some of the companies that you can do some quite
Speaker 1: detailed analysis and you can come up within assessments that
Speaker 1: whether you think the numbers are sensible, and that's and
Speaker 1: that's what we've done. A little spoiler for you. They're
Speaker 1: not all sensible. So there are some you know, there's
Speaker 1: some numbers in there that if we were the finance
Speaker 1: director we would be rather uncomfortable about the carrying values
Speaker 1: of those businesses. But the real point here isn't that
Speaker 1: you know, I can sit here in London trying to
Speaker 1: value an investment in an unimportant, unlisted, no public information
Speaker 1: Chinese venture. I mean, obviously that's extremely difficult and would
Speaker 1: be impossible for me to do, to do the whole thing.
Speaker 1: But the question I've got is how can the auditors
Speaker 1: do that? Because it's not easy, right, and I mean
Speaker 1: just the scale of these investments is phenomenal. So what
Speaker 1: you would have to ask yourself is how likely is
Speaker 1: it that the auditors would have found all the right
Speaker 1: bands that were required and made the companies take those
Speaker 1: right nows. And I can tell you that there right
Speaker 1: there are There have been right gunds, not saying that
Speaker 1: haven't there's never been any right downds, but the right
Speaker 1: bunds are on a somewhat lower scale than division funds.
Speaker 1: So what does that tell you, Well, it tells you
Speaker 1: either that they're phenomenally successful at making these investments or
Speaker 1: that they can justify carrying values because they found somebody
Speaker 1: else to come in at a higher price. Which that
Speaker 1: doesn't mean to say that the values are accurately disclosed
Speaker 1: in the balance sheet, but it does mean to say
Speaker 1: that they've conformed with their counting rules right. Or it
Speaker 1: could be that they've invested a lot of money and
Speaker 1: obviously the value valuations of these stocks has gone through
Speaker 1: the roof in the last few years, and they've carried
Speaker 1: on investing throughout. So is it possible that these companies
Speaker 1: will be forced to take some significant right hands in
Speaker 1: the next few years if the valuations don't hold firm
Speaker 1: and they've invested in a range of I mean, you know,
Speaker 1: a very wide range of products. It's not like they're can,
Speaker 1: you know, confined to a single vertical. They're all trying
Speaker 1: to expand across a whole range of different activities, many
Speaker 1: of them completely divorced from their core business. So we
Speaker 1: started this conversation talking a little bit about ant Financial
Speaker 1: and the upcoming I p O valuation target is something
Speaker 1: like two billion dollars. If someone is buying a share
Speaker 1: of ant Financial, what do you think they're buying exactly?
Speaker 1: And Financial wasn't one of the stocks that we were
Speaker 1: asked to look at because when we were asked to
Speaker 1: do this work, the filings weren't available, and you know,
Speaker 1: perhaps the client will ask us to come back and
Speaker 1: and have another look at at that one. The difficulty
Speaker 1: with these sorts of flotations, and you know, it's particularly
Speaker 1: true in emerging markets, and I've seen a number of
Speaker 1: times in Asia, is that when there's a buzz, and
Speaker 1: particularly when there's a large retail component to the deal,
Speaker 1: the institutions will just follow in because it be that
Speaker 1: not too so these things. You can create your own
Speaker 1: success by producing a big enough buzz about the story
Speaker 1: and then as long as the numbers appear to be
Speaker 1: going in the right direction, everything everything is fine. It's
Speaker 1: only if things stop and you find that they've been
Speaker 1: sold for more than their otherwise worth. I always think
Speaker 1: with with I p O s, I used to specialize
Speaker 1: one of my specialties when I was at the hedge funds.
Speaker 1: One of the things that I used to do is
Speaker 1: I used to look for I p o s that
Speaker 1: were either really unpopular. So a company coming to the
Speaker 1: market which was deemed unattractive for whatever reason, needed to
Speaker 1: come to the market, needed to raise the capital, would
Speaker 1: often come at a ridiculously cheap price. And on the
Speaker 1: other side, what we used to do was we used
Speaker 1: to look for these overhyped stocks coming to the market
Speaker 1: and we used to shore them. And it was an
Speaker 1: incredibly profitable strategy because the issue with an I p
Speaker 1: O is that you've got very level playing field. Very
Speaker 1: very few people in the stock market have got history
Speaker 1: with the company, so everybody's equal, and if you spend
Speaker 1: more time than your competitors and understand the company better,
Speaker 1: there's It's one of the few areas in the stock
Speaker 1: market where you can deploy an information advantage legally. You know,
Speaker 1: sometimes there's an information advantage, but you've got inside information.
Speaker 1: Obviously you can't deploy that. But this is one of
Speaker 1: the few areas where a fund with a bigger research
Speaker 1: department with more resources can effectively deploy these resources to
Speaker 1: gain an information advantage. Actually, I have a sort of
Speaker 1: curveball question. Here's something I've wondered about, but you mentioned
Speaker 1: earlier on that. You know, you give advice to people
Speaker 1: that if they see a whole page of related party
Speaker 1: transactions and a filing, that's probably a red flag to
Speaker 1: steer clear. Are there any you know, when you when
Speaker 1: people think about forensic accounting, they think about uncovering a
Speaker 1: good short or maybe sort of justifying long position. Have
Speaker 1: you done or a people doing any work on sort
Speaker 1: of quantitative uses of this stuff? So for example, just
Speaker 1: you know, short all the companies with lots of related
Speaker 1: party transactions go along all of the parties all of
Speaker 1: the companies that don't have them to some sort of
Speaker 1: market neutral strategy. Are there any sort of approaches to
Speaker 1: investing in the work that you do that don't try
Speaker 1: to drill down in one company, but just take a
Speaker 1: few accounting rules and then do a big balance diversified
Speaker 1: portfolio based on these items. Yeah, I mean, I think
Speaker 1: it's a very good question, Joe, and I think that
Speaker 1: actually most of the popular tools have been all gold
Speaker 1: out of existence. So there's a very good paper by
Speaker 1: research affiliates looking at gross profitability, which was a subject
Speaker 1: of an academic paper in came up with some very
Speaker 1: very good results. The fact is that all the algorithms
Speaker 1: have been using the findings of that paper. And what's
Speaker 1: happened is those stocks have been re rated, um, and
Speaker 1: they've done well, but they've done well because they've been rerated.
Speaker 1: And I think most of these most of these issues
Speaker 1: are most of the accounting issues have been arbitraged away.
Speaker 1: And in fact, in my book which comes out next month, UM,
Speaker 1: we talk about the fact that algorithms have been kind
Speaker 1: of the enemy of the the analysts because algorithms can
Speaker 1: do all this stuff much better than the analyst. And
Speaker 1: the one area which I'm I'm quite intrigued about but
Speaker 1: slightly helpless about is is natural language processing. So we've
Speaker 1: on some basic textual analysis in this report, looking at
Speaker 1: the words and trying to interpret whether there has been
Speaker 1: an unusual amount of obfuscation but by these companies relative
Speaker 1: to an Amazon, for example. And you can't do this
Speaker 1: without a computer and there's all sorts of things areas
Speaker 1: in the in the area of understanding text, understanding words
Speaker 1: that computers can do much better. To my knowledge, there
Speaker 1: isn't anybody that can analyze dissect a computer that can
Speaker 1: analyze and dissect the related parties notes, because obviously they're
Speaker 1: very complicated, very specific, and I think that's one of
Speaker 1: the area's what you do need a human being. Fortunately,
Speaker 1: it's still some areas what you do need humans, just
Speaker 1: on the subject of natural language text. Looking at Chinese accounts,
Speaker 1: one of the surprising things, or one of the things
Speaker 1: that I think is surprising to people who aren't familiar
Speaker 1: with this particular market, is sometimes you read the accounts
Speaker 1: and you get a lot of mentions of what the
Speaker 1: company is doing to benefit China or to benefit the
Speaker 1: Communist Party and president she and things like that. I
Speaker 1: remember one of the I guess the most amusing examples
Speaker 1: that I found it that recently was there was I
Speaker 1: think it was a bank and someone, probably an old
Speaker 1: lady in China, had microwaved her bank notes in order
Speaker 1: to get rid of the virus um on them. She
Speaker 1: thought COVID might be transmitted through banknotes, and she brought
Speaker 1: these destroyed banknotes into the bank and they had helped
Speaker 1: her piece them back together or salvage them in some way.
Speaker 1: And the bank had written a footnote in its accounts
Speaker 1: about this particular incident, and it went into a lot
Speaker 1: of detail just to say that it was doing its
Speaker 1: part to help people during the coronavirus outbreak. So that's
Speaker 1: a long winded way of me asking you how much
Speaker 1: does politics enter into Chinese accounting corporate accounting? Well, and
Speaker 1: for these companies, I think their main they're looking westward. Really,
Speaker 1: they're looking at the investors in all right. Maybe it's
Speaker 1: not so true today, but going back a few months,
Speaker 1: they were looking at Western investment. And I think, you know,
Speaker 1: talking too much about how they're engineering themselves to help
Speaker 1: the Chinese government doesn't endear them to the average marginal
Speaker 1: investor in New York. So I don't think there was
Speaker 1: as much of that as you might see in a
Speaker 1: domestic Chinese issuer. But there's some interesting I mean, some
Speaker 1: of them have got some quite interesting observations about what
Speaker 1: they're doing to help the Chinese consumer, what they're doing
Speaker 1: to help their employees, and and and those sorts of
Speaker 1: sorts of things. I don't think we saw too many,
Speaker 1: too much discussion about microwave banknotes or anything along those lines.
Speaker 1: I don't I don't recall recall one of those. One
Speaker 1: last question for you, Stephen, what's your I guess your
Speaker 1: number one tip to any investor who's trying to survey
Speaker 1: the accounts of a company that they're considering putting money in,
Speaker 1: whether it's Chinese or from somewhere else in the world.
Speaker 1: But I'm glad you I'm glad you asked asked me that.
Speaker 1: And if I can just put in a plug for
Speaker 1: my book The Smart Money Method where you got where
Speaker 1: you talking about three pillars. So there's three things you
Speaker 1: should do when you look at a stock to make
Speaker 1: sure you're not buying a fraud. And you might not
Speaker 1: be looking to avoid a fraud. You might just be
Speaker 1: looking to avoid a company that's not going to perform well.
Speaker 1: And you know all the studies tell you that the
Speaker 1: majority of stocks do badly, the majority of stocks underperform.
Speaker 1: So if you do these three simple checks, then you
Speaker 1: will protect yourself and reduce the odds that you're buying
Speaker 1: a loser. The first check is to look at the
Speaker 1: working capital ratios companies that have rising days of receivables
Speaker 1: rising days of inventory tend to be well. They can
Speaker 1: be frauds, but they tend not to be as good investment.
Speaker 1: And the reason is very simple. If your customers aren't
Speaker 1: paying you, that probably isn't a good thing. If your
Speaker 1: stocks are rising, it usually means your customers don't want
Speaker 1: what you're trying to sell. The second tip is always
Speaker 1: do a comparison of the margins today with the past
Speaker 1: and with the peer group. Every single fraud I studied
Speaker 1: for my freensic handing course had margins which were higher
Speaker 1: than peers and usually unexplainable. And the third thing is
Speaker 1: don't just look at the earnings, look at the cash flow.
Speaker 1: Is the company generating as much cash as it's reporting
Speaker 1: in earnings, And if there is a trend in which
Speaker 1: earnings have carried on going up and cash hasn't, that's
Speaker 1: usually assigned to stay away. So those three simple tricks
Speaker 1: working capital, margin comparisons and cash persus earnings will keep
Speaker 1: you out of trouble. That was really great. Thank you
Speaker 1: so much for coming on our boots of great conversation.
Speaker 1: Oh thank you so much for having me. I mean,
Speaker 1: I'm absolutely you want to do. That was fantastic. I'm
Speaker 1: really excited about reading the book now. Thank you so much,
Speaker 1: ye Joe. I really enjoyed that conversation. I think it
Speaker 1: was a useful bit of critical analysis to offset some
Speaker 1: of the optimism and excitement that we've seen lately, not
Speaker 1: just around the AT I p O, but around tech
Speaker 1: stocks really all over the world. I feel like we
Speaker 1: could just do episode after episode with UM with accountants
Speaker 1: and particularly forensic accounts. It's just like it's always so
Speaker 1: interesting and every time we do or like we got
Speaker 1: to do more accounting episodes and then we forget. But
Speaker 1: I always remember after these conversations, like why they're like
Speaker 1: so interesting and uh, he was like a great sort
Speaker 1: of articulator of some of the issues that make corporate
Speaker 1: analysis so difficult and interesting. Yeah, I can't even imagine
Speaker 1: going through a thousand pages of accounts, but I thought
Speaker 1: the point about, for instance, related party transactions was a
Speaker 1: really good one. If there are pages and pages of
Speaker 1: complex footnotes and related party transactions, then that's probably a
Speaker 1: red flag right there, or at least I don't know.
Speaker 1: I kind of I wonder how many investors are actually
Speaker 1: going through all of those I can't imagine it's many.
Speaker 1: You know, it's interesting. I thought your question was really
Speaker 1: great at the end about politics and the connection between
Speaker 1: the corporate leadership, particularly these big Chinese companies, and the
Speaker 1: government in China. Just in general, it feels like that
Speaker 1: is such a sort of factor in understanding both like
Speaker 1: how the economy works and how specific businesses work. I
Speaker 1: was thinking back to our our conversation with Tom Rlick,
Speaker 1: the Bloomberg economist who has the book about the China
Speaker 1: bubble and so much so many misconceptions of analyzing China,
Speaker 1: at least in or leaks view, sort of stemmed from
Speaker 1: the idea that Chinese, the Chinese government by control of
Speaker 1: the banks, can sort of get any outcome at wants,
Speaker 1: and it can forestall a bubble or constall bubbles from
Speaker 1: crashing as long as it wants, And so thinking about
Speaker 1: like some of these sort of the non financial companies
Speaker 1: and the investments they make, and how they mark their
Speaker 1: investments and whether they get whether they have a um,
Speaker 1: whether they can find an entity to invest in an
Speaker 1: investment that will continue to increase the value, it just
Speaker 1: seems like it's got to be pretty tough to analyze
Speaker 1: that from any sort of like outside sort of like
Speaker 1: typical Western standards, when you have so much of the
Speaker 1: large industrial leadership of a country so tightened with the government. Yeah,
Speaker 1: I think that's absolutely right, and that's probably why Chinese
Speaker 1: political analysis is probably a growing area of opportunity in finance.
Speaker 1: I mean it is one of the benefits of a
Speaker 1: command economy, right, you can direct capital and control industries
Speaker 1: to some degree. And there are examples in China of
Speaker 1: companies that have basically based their entire business model on
Speaker 1: figuring out what it is the Chinese leadership wants. So
Speaker 1: the best example of that is China Evergrand, which I
Speaker 1: don't even know how to describe it. It's a Chinese
Speaker 1: property company, but it also makes electric cars because the
Speaker 1: Chinese government was really into that, and it also runs
Speaker 1: some hospitals because healthcare is important. At one point, it
Speaker 1: got into soccer teams or football because she was really
Speaker 1: into sports. It's a it's a that's probably the most
Speaker 1: extreme example of companies trying to tow the party line,
Speaker 1: but it's one of the most interesting. Let's do a
Speaker 1: ever Grand episode. Yeah, you know what I love, like, Hey,
Speaker 1: we should do an ever Grand episode. But also I
Speaker 1: love how many times I feel like when it comes
Speaker 1: to a Chinese, big Chinese company, like there's a really
Speaker 1: big challenge with how to describe it, right, It's always like, Okay,
Speaker 1: it's good. There's it's almost like there's no analog that
Speaker 1: we can think of, at least among Western companies, for
Speaker 1: the sort of the range of business lines that some
Speaker 1: of these you know, Chinese giants are in. Yeah. I
Speaker 1: always find myself reaching for American parallels and then saying
Speaker 1: like Amazon but much bigger, or like Apple but much bigger,
Speaker 1: or like Google but also with a random money market
Speaker 1: fund and things like that. I love it. Well. One
Speaker 1: other things, Um, we gotta start using vision fund as
Speaker 1: a unit of Yeah, the U s economy by too
Speaker 1: soft bank vision funds this year. Yeah? Perfect, All right,
Speaker 1: should we leave it there? Let's leave it there. Okay.
Speaker 1: This has been another episode of the All Thoughts podcast.
Speaker 1: I'm Tracy Alloway. You can follow me on Twitter at
Speaker 1: Tracy Alloway and I'm Joe Why Isn't All? You could
Speaker 1: follow me on Twitter at the Stalwart. Follow our guest
Speaker 1: on Twitter. He's Steve Clapham and his handle is at
Speaker 1: Steve Clapham and follow our producer, Laura Carlson at Laura M. Carlson,
Speaker 1: followed the Bloomberg head of podcast, Francesco Levie at Francesca
Speaker 1: Today and check out all of our podcasts under the
Speaker 1: handle add podcast and check out Steven's new book, The
Speaker 1: Smart Money Method. Thanks for listening to to