August 2014 artwork

 

Untitled

Darker than Black.

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$TSCO.L – Tesco – a 200p valuation

BLUF: Share price 230p, estimated value 200p, implied downside 13%

In light of Tesco’s announcement to reduce their dividend, I thought it would be worthwhile having a stab at a possible valuation for Tesco. My previous valuation in March (http://wp.me/p2eZvw-Ck) put a value of 360p at a time when the share price was 291p, with an implied upside of 24%.

My new estimate of value, 200p, is a significant reduction from 360p, and pushes the share price from being undervalued to overvalued, despite a reduction in the share price. Such a radical shift should not normally be expected, as it is more usual to make only minor tweaks to the model in the light of new information.

However, the recent announcement by Tesco signals a large downward movement in the overall dividend – a basic input to the valuation model.

It is difficult to decide what the new rebased dividend should be – but that’s what makes the game so interesting. I outline the valuation below.

Let me start off with an earnings estimate. Analysts have an EPS of 23.61p for 2015, and 21.23p for 2016. These will probably need to be reducted, so I will estimate an EPS of 20p. Next, I will apply a dividend cover of 2.46 – which is the highest covering it has had over the last decade. So I am estimating a dividend next year as 8.13p.

Recall our Gordon Dividend Growth Model:
P = D/ (k-G) … [1]
where
P = stock value
D = expected dividend per share one year from now
k = required rate of return for equity investor
G = growth rate in dividends (in perpetuity)

I am now going to assume that the growth rate in dividends, G, is the risk-free rate. This is a general default assumption. However, you might want to assume that their dividends will never grow, and set G=0.

Sticking with the former assumption, though, gives me a simplification k-G = beta * erp
where
beta is the stock’s beta
erp is the equity risk premium

Using my values from last time, I will set
beta = 0.82
erp = 4.96%

So, plugging those numbers into equation [1] gives
P = 8.13 /(0.82 * 0.0496) ~= 200p

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Should You Buy ASOS plc On Takeover Speculation?

BLUF: No

“Should You Buy ASOS plc On Takeover Speculation?”. That was the question posed over at Motley Fool today (http://is.gd/xWIMrp). Uncharacteristically for them, they actually answered the question posed in the headline. Their answer is: “Maybe”. Hmmm, I think I can award only half marks at best.

Readers may recall that I valued ASC (ASOS) at about £20 per share (http://wp.me/p2eZvw-Dt) in late March. The shares were 5528p when I first wrote the article, and they stand at 2686p now. There’s obviously been a rather big decline since I last wrote, and the shares now trade far below the 7000p+ targets that some analysts had given. The look rather silly in hindsight. In June, Barclays reduced its price target from 8000p to 5000p. Seriously, these guys must be pulling price targets out of a hat.

The ASC share price is up 14% today on bid rumours. Motley Fool report that the trade buyers are rumoured to be eBay and Amazon.

From my limited experience, bid rumours have a less than even chance of materialising. Even when negotiations are actually announced, your chances are less than fair.

I’ve never really understood where rumours come from. The companies themselves are going to keep quiet, and their bankers and other professional advisors are going to be at least as keen to keep a lid on their inside information. Their reputation depends on it.

ASC is a share that I should take a look at revaluing some time. The developments that have occurred since I last did a valuation suggests that I need to bring down their margins, and hence the valuation.

I do not expect a bidder to materialise. If that’s the case, then I expect the shares to go lower from here.

We shall see. It’s all just my opinion.

2686p

 

Update 27-Aug-2014 Redrut posted an article on Seeking Alpha today, “ASOS: Growth At A Reasonable(Ish) Price”, arguing for a valuation of £30 – £34.

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Twitch: was it worth $970M to Amazon?

BLUF: it might be!

The BBC reported recently that Amazon buys video-game streaming site Twitch for $970M. The question is, of course, how can a game clips company be worth $1b? Has Amazon lost its mind in a fit of hubris and tech-euphoria, or might there actually be some grounded basis in their valuation logic.

Twitch is clearly a “growth” story, and value investors will no doubt scoff at the numbers I am about to throw out there. But here goes anyway.

Over a 1-year period, Siteanalytics reported that the number of unique visitors to twitch.tv went from 1.85M to 3.57M (http://is.gd/y1nai6). That’s a growth rate of 93%. Starting from a small base, one might argue that it could double its unique visitors every year for the next five years, especially now that Amazon is on board.

But let’s be modest, and say that it can grow revenues at 50% pa for the next five years, and that revenue growth will taper linearly to a risk-free rate of 2.5% over the subsequent five years. So its revenues will be up about 15X over that 10-year period.

Sounds implausible? Not necessarily. Google’s revenues went from $3189m in Dec 04 to $63,126m TTM, an increase of nearly 20X
(http://is.gd/Fq6eGw). These are actual revenues, not projections. Twitch is starting from a smaller base. So I think the 50% pa over 5 years that I am using for Twitch will turn out to be conservative.

Next up, how much revenue is Twitch generating? Well, I couldn’t find an answer to that, but I’ll take a stab at some numbers. The reports on number of users vary, but I will use the figure of 45M
(http://is.gd/e81yn9). What’s the revenue per user? I don’t know, but Facebook has an ARPU (Annual Revenue Per User) of $1.63, LinkedIn $1.53, Yahoo $1.81 and Google a massive $10.09 (source:
http://is.gs/nHOLe0). Assuming Google is an outlier, let me ignore it an take an average. So maybe Twitch is generating $1.60 per user. A complete guess on my part, admittedly. So it’s probably generating revenues of $72m, which will be expected to grow to over $1.4b over a decade, if you use my assumptions about revenue growth.

Next, we need to make some assumptions about operating margins. It’s very tricky this one. They could be making a loss, they could be making a profit. I don’t know. I’m going to assume that the operating margin is 0%, and will ramp up linearly to a “sector norm” in a decade. I’ll use a terminal operating margin of 20%. Some tech companies are reporting 15%, some 25%. So I’ll take 20%. The intermediate operating margins I have used are probably fairly low for an extended period, so I suspect that Twitch will be able to generate better EBITs than I have put into my computations.

Producing that revenue growth will require capital. How much? Well LinkedIn has an SCR (Sales Capital Ratio) of 2.14, and Twitter is 2.50. So let me use 2.30. I might be being too generous here, as Twitch uses a lot of bandwidth so their SCR might well be much lower than most tech companies.

I have made some assumptions about tax rates. I don’t know how much capital has already been invested in Twitch, or how much cash or debt they have. So I have swept this under the carpet.

Cost of capital needs to be estimated. I just used the figures that Aswath Damodaran did in his recent valuation of Twitter – which is 10.9% tapering down to 8%. People might take issue with that, especially seeings as it is not a public quoted company.

I think I’ve covered most assumptions, now.

When you grind the numbers, you actually come up with a valuation of Twitch of $950m – remarkably similar to the price that Amazon paid. Most of the value is tied up in the PV of the terminal value: $956m. The PV of the cashflows over the next 10 years I estimate as negative $6m. It is not until year 8 that Twitch goes cashflow positive. A lot of investment is required to fuel growth.

So there we have it. $970m for a company that is possibly generating only $72m in revenues might actually be worth it. Arguably, my assumptions about revenue growth rate and EBIT operating margins are too low, at least intially, meaning that the company is actually worth a lot more. The Sales to capital ratio might be too high, in which case you would need to moderate the value.

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A simple value strategy using Stockopedia

A mechanical strategy that I’ve been using lately, with good effect, is to hunt on Stockopedia for the following criteria:
* Value >= 70
* Quality >=70
* 14-day oversold in last 5 days
(http://www.stockopedia.com/chart-signals/14-day-rsi-oversold-5195/5/)

I’m looking for sufficient value and quality that is being dumped by the market. My reasoning behind not ratchetting up the Value level to, say, 90, is that good results can be had even from companies that aren’t ridiculously cheap (see my post on Perfect, Putrid and Mediocre portfolios http://wp.me/p2eZvw-MH)

The strategy would have worked well if you had bought housebuilder TEF.L (Telford Homes), like I did, on 11 August at 277p. By an amazing coincidence, it was tipped by Jim Slater shortly thereafter, and has now sky-rocketed to 342p. That’s a gain of over 20% in a couple of weeks.

It was luck on my part, to be sure, but I think it is the right principle to follow.

By way of another example, consider telecomm equipment manufacturer VLK (Visilink). It is having a great surge today on the back of a tip by Simon Thompson. I had bought in January at 45p. After yoyo-ing around, it currently trades at 47.15p. A bit of a gain, but nothing to write home about. My mistake was that I bought when the RSI was well above 30. If I had waited until the RSI was below 30, I could have picked up the shares at 40.8p in March or 41.8p in late July. In August, another oversold opportunity was available at similar prices. If you were really lucky, you would have bought at the bottom at 39.8p. If you weren’t so lucky, you might have picked them up at 45.06p in June. That is, admittedly, slightly higher than my entry price. On the other hand, you could have done something more productive with your money in the meantime. Also, you would have likely increased your odds of getting a good entry point.

It’s hardly a perfect system. It’s more about odds than guarantees.

A good time to sell is when the company is looking overbought. TEF and VLK are at that point.

Another desirable property of the company is good
liquidity. If you look at the charts of the 14d RSI oversold, you will see that some companies have jerking jumps. Avoid those. An example of such a company is THRL (Target Healthcare REIT):

www.stockopedia.com

See how the the company swings from under- to over- sold violently, and it has big intraday movements? Avoid the micro caps. Some small-caps (£50m-£350m) are OK, some not. Most of them look unsuitable, although the higher cap ones should be OK. You may want to set a threshold, like £200m.

Currently, there are no large-cap (>£2.5b) stocks that qualify under this screen. TSCO (Tesco) come close, but their quality is just shy of the quality threshold. The same applies to mid-caps (£350m – £2.5b) and small-caps. I’m not even considering the micros.

So it looks like a case of sitting on the sidelines with any cash that you have until an opportunity comes along.

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“How to Read a Book”. tl;dr

“How to Read a Book: The Classic Guide to Intelligent Reading”, by Mortimer Adler and Charles van Doren.

Regarded as a classic, and receiving high praise. Amazon readers rate it 4.5 out of 5. Praiseworthy, indeed.

Weighing in at 426 pages, I am currently on page 168. Think about that for a moment. Do we really need 426 pages to explain how to read a book? I have put the book down for now. I hope to return to it later; but for now, I feel I have more important things to read. My reading interests are extensive, so it’s a question of prioritising.

In other words: “tl;dr” – too long, didn’t read. Don’t waste your time.

My main beef with the book is that it is too academic in its approach. It is nice in theory, but that’s not how I would want to read a book in practise. One reviewer summed up the problem succinctly: the books tells you how to analyse a book to within an inch of its life.

In nearly every case, that’s unnecessary. Even for someone performing a literature review as part of their PhD will find his description overblown, at least for science-based PhDs. I have never heard of anyone writing a PhD thesis trying to obtain a “complete” understanding of a book. The effort goes into UNDERSTANDING the RELEVANT parts of a book or paper (although for a paper, the whole, or none, of its contents are likely to be relevant), and then constructing a COHESIVE framework of those ideas from several sources.

The easy part of the equation is “relevance”. PhD supervisors know up-front what will be relevant for a student. Even for non-academics, find relevant material is not a big problem, thanks to Google. Do you want to know about Fuzzy Logic? Then Google for Fuzzy Logic. Simples. Looking at the page, you will gain a good idea as to whether it is worth reading, or not.

Actually, one thing I did notice when I was giving computer workshops is that undergraduates failed to look at the table of contents or indices of a book if they had any problems. The index is your friend when you want to search for specific information.

The hardest part of reading a book is the actual understanding. Mathematics and science are challenging intellectually, so this is where the greatest hurdles are likely to be faced. Structuring ideas is also difficult, especially when you’re trying to write a literature review. Most people wont be writing literature reviews, so that wont present a large-scale problem. Having said that, I think that structuring and understanding go hand-in-hand. All understanding is, in some sense, structured understanding. Otherwise, there is no real understanding, merely rote learning.

Adler’s fourth dimension to reading, “syntopical”, is, I consider, a peripheral aspect of most reading endeavours. Syntopic reading is about “how to read two or more books on the same subject” (giving rise to the joke about someone publishing a book called “How to Read Two Books”). It may be important for literature degrees, where you’re comparing Shakespeare with Orwell, for example, but of limited use elsewhere. Even in science PhDs, I don’t think there is any secret skill that needs to be mastered. A science thesis literature review is not really about comparing and critiquing. A mathematical proof, is, after all, either right or wrong; and one is only interested in reviewing the correct ones. Style is also unimportant. We don’t care how the author writes a proof, just so long as we understand it. So whilst it may be relevant to talk about whether Shakespeare was a “better” or “more important” writer than Orwell, it’s not the kind of conversation one has about Gauss versus Newton.

So, from my point of view, I found HtRaB to be disappointing. Your Mileage May Vary. If you want to be able to analyse a book to within an inch of its life, then it is the book you. If you want to be able to understand very complex material from within a vast sea of information, as I do, then you might be better off looking elsewhere.

For my money, reading is about learning. And learning is about how get understanding into a slightly-larger monkey brain. It’s about psychology and human cognition. It’s about the “5+/-2 rule”, which says that the human mind is capable of retaining only five things in short-term memory at once, plus or minus two. It may interest you know that it is the way that computer programmers think, sometimes explicitly, sometimes implicitly. A program of a thousand lines or more of code is impossible to fit into a programmer’s head, even if they did write it themselves. It is amazing how much you forget, and how the program is structured. Programmers cope with this complexity by isolating what they look at. Coding is not just about instructing a computer, it’s about instructing a computer in a way that limited human intelligence can understand.

Reading, and understanding, is also largely about building conceptual models. Given the limitations of human cognition imposed by the “5+/-2 rule”, it means that complex models are formed by aggregating simpler concepts together into a network. The way you learn is to build on what you already know.

Research also shows that humans have an attention span of about 10 minutes. Your comprehension abilities will start to decline after that. After about 25 minutes, you’re starting to push water up a hill.

So, when all is said and done, reading a book is about respecting the limits of human cognition, and maximising efficiency of learning within those boundaries. HtRaB did not address those problems at all. For this reason, I think it will disappoint many readers, who will be presented with different material than they were expecting.

If you are interested in the drawbacks of current learning paradigms, then you will be interested in the Youtube video by Donald Clark “Don’t lecture me”: http://youtu.be/9e4iFx2Gm0A

I would also like to point to an interesting blog article by Dan Kois,”Easy ‘Reading': Just Take It One Page At A Time”
http://is.gd/WPTJ4h. In the article, he reviews the book “The Pleasures of Reading in an Age of Distraction”, by Alan Jacobs. “The solution? ‘Don’t turn reading into the intellectual equivalent of eating organic greens;, he urges. Read at whim, without shame and for pleasure”.

“Many of them say that they used to be able to read but since becoming habituated to online reading and the short bursts of attention it encourages – or demands – simply can’t sit down with a book anymore. They fidget; they check their iPhones for email and Twitter updates … ‘I miss my old brain'”.

I wonder, though, if the whole argument shouldn’t be flipped 180. The 10-minute attention span is something we should work WITH, not AGAINST. Consider The Feynman Technique, for example, named after the famous physicist Richard Feynman. It involves writing down a topic on a single sheet of paper, and takes about that amount of time. You can see a video by Scott Young, “Learn Faster with The Feynman Technique”, to learn more: http://youtu.be/FrNqSLPaZLc. There may be great wisdom in breaking conceptually difficult topics into self-contained chunks. Those chunks are aggregated until you have a complete understanding of a subject. Perhaps we’ve been doing it wrong all this time, and the youth are uncovering a new way of knowledge acquisition.

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Magic Formula selection from a year ago

On 14-Aug-2014 I blogged an example Magic Formula portfolio consisting of 8 shares: http://wp.me/p2eZvw-tc

The current share prices are, in pence, for the record:
RNK 167, IRV 648, SPT 99, LSC 2450, KENZ, HRG 60, AZN 4202, BA 438

The percentage returns are:
RNK 3.7, IRV 21.1, SPT -27.7, LSC 44.1, KENZ 107.6, HRG -21.1, AZN 26.9, BA -2.4
Mean: 19.0%
1-year return for All-Share: -0.1%, for FTSE 250: 6.5%

So, the Magic Formula has beaten the indices by a large margin.

The picks a year before that showed what appeared to be a
market-beating return. I downplayed its outperformance, saying that it could be due to a “killer pick”. I might have been wrong to be so dismissive, though. As you can see from the performance of KENZ, “killer picks” do happen when you have a portoflio.

It was an interesting exercise, and to some extent validates the Magic Formula. It is difficult to know for sure, of course, as the selections have only been going for a comparatively short period. I think one has to accept the fact that one will have periods of outperformance, and periods of underperformance.

I wont be making a similar selection for the forthcoming year; otherwise I become too busy. I can barely keep pace with my other interests as it is. However, I am still making Magic Formula picks at my Stockopedia Fantasy Fund:
http://www.stockopedia.com/fantasy-funds/magic-hat-463/
You can follow that if you are interested in Magic Formula picks. Over the past six months, my hand-selected picks have trounced the purely mechanical screen. Whether that proves anything, I’m unsure.

A pattern that I have seen with cheap micro-caps in my aforementioned blog post was that they can perform very badly. Some really bad stocks are selected. Setting a floor on the market cap, say £200m – maybe £100m – seems to improve the quality. There is such a lot of dross at the micro- end of the scale.

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