$WAND.L – Wandisco overbought

Software company WAND (Wandisco) has been performing well. Its 2014Q3 explains why: booking have increased by 56% and 21% on prior year, and announces it has been selected by a Fortune 100 tech company.

I have been bearish on WAND ever since I heard of it. WAND does things like host repositories. I’ve always held that this is a commodity. Places like Github offer free hosting accountings. There are many other similar offerings. The way I see it, the big problem with WAND is that anyone who is technically competent – which is every user (because they’ll all be software developers) – could set up a similar thing on their own infrastructure.

Analysts are forecasting revenues of £12m for 2015, but this may be on the low side given the recent announcement. Typical margins for the sector are about 7%, so you’ve basically got a company that is expected to have an operating profit of less than £1m trading at £92m on the stock exchange. That’s a lot of growth baked into the price.

A lot of growth stocks have come off the boil this year, and WAND is down an eyewatering 69% YTD. It’s difficult to think it will get much interest as a momentum stock. Markets can be fickle beasts, of course, and what was off can suddenly go back on again under the right circumstances. The stock now has an RSI of 70%, which is technically overbought.

So, although there’s no telling how how this will or wont go, let’s just say that I wouldn’t buy in at this point. Some of my readers like trading ideas, so they might want to consider a short.

On 17 October, Investec reiterated a buy rating, with a target price of 1275p. I’ve no idea where they got that price from. It seems laughable to me. Still, kudos to them for going out on a limb.

Conclusion: a speculative AIM company that has yet to prove itself. Their capital requirements and ongoing development seems like it will be substantial. It has yet to demonstrate that it can earn meaningful returns on capital. The company’s valuation is far too high, in my opinion, and its loss of price momentum is unlikely to entice momentum investors into the game. Avoid.

We’ll see. I’ll do a follow-up in 6 months time to see how accurate I was or was not.

384p. ASX 3419

Update 22-Oct-2014: I have a communication from David Richards, CEO, president and co-founder of WAND, (Twitter) advising me that my understanding that the service they offer in terms of git and data availability was a little narrow. What WAND offer is reliability, which is much more difficult to replicate. I’m sure we’ve all had instances where Github went down. David pointed me to a list of patents, which I’ve had a skim read through, but have yet to get my heads around. The gist of at least some of them, as far as my limited reading has lead me, is that it allows machines to communicate as to what the “state” should be. To re-iterate their recent RNS, a Fortune 100 tech company has selected WANdisco’s Big Data technology, so there’s obviously confidence by big players that the company can deliver. WAND is still a small company, and as such, it will be interesting to see how they cope with scaling. The likes of Yahoo and Google are hardly inexperienced when it comes to scaling data.

I have retracted my comment of “typical AIM nonsense”, and replaced it with a more considered opinion.

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Mathematical diversion: the ladder problem

This is a mathematical diversion to while away some time, and stim-
ulate your brain. Try solving it before looking at the paper, as it states
some basic equations and approaches quickly. The problem is stated be-
low.
There is a vertical wall, and a horizontal floor. A box, measuring 1m
x 1m x 1m lies on the floor, and is flush against the wall and the floor.
The problem is actually in 2D, so you can ignore depth. Suppose there
is a ladder, of length c, which is propped so that the top of the ladder
touches the wall, the bottom touches the floor, and somewhere along its
length it touches the corner of the box. The question is: determine
b, the horizontal distance from the bottom of the box to the point at which the
ladder meets the floor. You may assume c= 3 if that helps. There are no
tricks in the statement of this problem.
To read the full article (which has mathy stuff in it so I can’t type it here): http://pdf.markcarter.me.uk/ladder.pdf
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$ASC.L – ASOS – a quick’n’ dirty valuation

ASC (ASOS) finals are out today, prompting Paul Scott to tweet: “Lousy figures from ASOS. Is this co really any good? Have my doubts. Op margin only 5%. Profits down”. The market response was very positive, though, sending the shares up 16.4% to 2263p, as at the time of writing.

The shares are down 62.9% YTD, and down nearly 69% from their all-time high of 7195p. When high growth, high momentum shares stall, they do so with fanfare. I had written in the past that I valued ASC at about £20 per share. To my amazement, the shares actually reached that level. It just goes to show: if you wait long enough, then you will often find that things go your way.

A number of incidents happened to ASC since that valuation, and I said that it would probably need to be revised downwards. I thought it might be worth trying to value ASC again. I am being lazy, so I will use the application that I just published as a two-phase growth model. Here’s what the screenshot looks like:

asc

I have been really sloppy as regards cost of capital, and so-forth. I just simply wanted a quick estimate. As you can see, the company looks to be worth about £1200m, or 1440pps, which is significantly below its current market cap of £1900m.

A better model would use a three-phase growth model, which would make it much more valuable than the figures I have suggested. Work would also need to be done on the assumptions about the cost of capital and terminal figures.

Nevertheless, I think you’d have to put in some pretty wacky assumptions to reach Barclay’s former share target of 8000p. I am completely puzzled as to how they came out with that figure. Even using a three-phase model with robust growth assumptions, I did not come out with anything like their valuation. It’s also difficult to see what pricing models they might have been using. Seriously, I think much of the time analyst’s target prices make no sense. They mostly seem to be anchored on prevailing share prices, tweaked with momentum expectations. I don’t see how else they can do it.

It will be interesting to see what happens from here.

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Two-phase growth model app available

Last week I posted an article of Stocks showing at least 50% upside using a DCF model. I have now made an application which uses the most interesting parts of the model. You can download it using this link. Here is a screenshot:

shot

The application is quite small, and requires no extra libraries, as far as I know. It is for any Windows platform. It’s all pretty self-explanatory, really. You enter in operating profit, dividend cover, etc., press the Calculate button, and out pops the intrinsic value for the value of common stock using DCF.

The model assumes that operating profits grow at a rate of ROCE*(1-1/DCOV), where DCOV is the dividend cover, for the next 5 years. It then assumes market returns for the terminal stage. If you are lazy, then you can leave the terminal cost of capital, terminal growth, cost of capital, and even tax rate, alone.  Operating profit, dividend cover, ROCE and net cash are the numbers you are likely to want to play with first.

Have fun.

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$BLNX.L – the case against it as a Magic Formula stock

I notice that BLNX (Blinkx) has appeared on Stockopedia’s Greenblatt Magic Formula screen, with a ROC of 52.6% and an EY of 27.1%. It also has a QV rank of 93.

BLNX has net cash of £75m, a market cap of £118m, a PE of 7.18. Revenues have increased more than sixfold over the last four years. Its one-year relative strength is -79%. So, OK, how comes a company that’s grown revenues sixfold has a PE of 7 and massively underperformed the indices?

Here is some commentary over at Stockopedia:
* Paul Scott, 30 Jan 2014: calls BLNX’s website an inferior copy of YouTube.
* Paul Scott, 6 May 2014: neutral on Blinkx. Results look impressive. Raised cash. Profits look real. Debtors are modest relative to turnover, Balance Sheet excellent.
* Paul Scott, 2 Jul 2014: suspicious where a share price does not rebound when it should. Trading update is a clear profit warning
* Edmund Shing, 28 Aug 2014: posted a bullish article, highlighting its value. Points to Bloomerg Businessweek article of 7 Feb 2014, alledging that BLNX inflated its traffic stats to boost commissions.
* Paul Scott, 1 Oct 2014: reports profit warning, as he expected. Says he doesn’t really understand the business model. Calls H1 a disaster.

I’ll add my own observations below.

Firstly, as soon as I hear that there are accounting shenanigans from sources I have no particular reason to doubt, it’s Shields Up time. From then on, a company is guilty until proven innocent.

Secondly, look at all that cash. You would think that I would be bullish about that, but I actually take it as a warning sign. If you look at many foreign stocks , you will find that they are awash with cash. Why? Scam after scam Chinese company seems to have plenty of cash. There will be some legitimate exceptions of course. FCCN (French Connection), for example.

Next, I took a look at the cashflow statements. They issued $30m of stock in 2011, $15m in in 2012, and $66m in 2014. That’s a massive amount of equity for a company that is worth only £118m. Clearly, all that money did not translate into shareholder value. The company made acquisitions of £33m in 2012, and £25m in 2014. This is another huge warning sign.

Next, look at Stockopedia’s calculations of Return on Capital: a paltry 6.52%. It’s ROE is 5.98%, a wholly inadequate figure. If a company is growing rapidly, always check these figures. It can alert you as to whether the company is investing sensibly, or not.

Conclusion: despite the PE of 7, this one’s going down. Avoid. IMO, DYOR, yada yada.

BLNX 29.5p. ASX 3369

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Stocks showing at least 50% upside using a DCF model

There are many screens like Greenblatt, that attempt to measure “cheap and good”, or GARP screens that use a combination of “value and growth”, but there are not any scrrens that attempt to measure discount to intrinsic value. Yesterday, I realised that it was possible to actually do this using Stockopedia.

The values I needed were: market cap (MKT), operating profit (OP), ROCE, net cash (NCASH), and dividend cover (DCOV).

Given DCOV, it is easy to calculate an earnings re-investment rate, which, combined with a ROCE, tells me at what rate I expect OP to grow. I then assume OP grows at that rate for 5 years, and then switches to market-expected rates. Those are the basic assumptions of the model, and allows me to compute an intrinsic value for the company. I can then compare it to the market cap, and apply a filter below 50% upside, The model adjusts for NCASH.

Stockopedia only returns 200 qualifying companies, so I have restricted my search to companies with a market cap of at least £250m, have excluded as many AIM-listed shares as possible, and sorted by ROCE descending.

A number of other assumptions were needed. I used a risk-free rate RF=2.95% and an equity risk premiun ERP=4.96%. I don’t have unlevered betas for the companies, so I assumed all the betas were 1. The hurdle rate is therefore 7.91% in all cases, and the perpetual growth rate is RF. I also did not adjust the cost of capital for debt. These assumptions may be disliked by some, but there’s really other no way of producing bulk computations for intrinsic value.

So you should think of the computations as a starting-off point, from which you can do further work. Note, also, that the OPs are taken “as-is”. Some of them will be distorted by exceptional items, and some of them are in USD, which throws off the calculations. There are also no adjustments for operating leases and pension deficits. Like I say, cavaet emptor.

Here is a table of results:

  #  EPIC       Upside  P/E    Name
---  ------  ---------  -----  -------------------------------
  1  GKN       1.54671  10.4   GKN
  2  ITV       1.58682  20.8   ITV
  3  XPP       1.5979   13.2   XP Power
  4  IPO       1.6034   8.33   IP
  5  DLAR      1.64208  6.95   De La Rue
  6  ATK       1.65468  14.6   WS Atkins
  7  SPD       1.65998  19.3   Sports Direct International
  8  HAS       1.66271  18.3   Hays
  9  CRST      1.66439  9.82   Crest Nicholson Holdings
 10  HL.       1.6858   25.5   Hargreaves Lansdown
 11  RDW       1.70098  9.46   Redrow
 12  HFG       1.74224  14.5   Hilton Food
 13  AVV       1.74855  17.2   AVEVA
 14  PFC       1.8086   10.0   Petrofac
 15  FOXT      1.87711  12.8   Foxtons
 16  DNLM      1.91909  18.2   Dunelm
 17  LOOK      1.97206  10.9   Lookers
 18  UKCM      2.01667  6.03   UK Commercial Property Trust
 19  HWDN      2.0205   18.3   Howden Joinery
 20  VZC       2.10285  15.2   Verizon Communications Inc
 21  LSL       2.15945  11.4   LSL Property Services
 22  IBM       2.17893  11.2   International Business Machine…
 23  PDG       2.30425  8.09   Pendragon
 24  HIK       2.34738  17.3   Hikma Pharmaceuticals
 25  FDM       2.40176  34.6   FDM (Holdings)
 26  GMS       2.43112  10.5   Gulf Marine Services
 27  BLT       2.46258  10.0   BHP Billiton
 28  888       2.47652  14.9   888 Holdings
 29  TT.       2.48817  7.37   TUI Travel
 30  TTA       2.52339  9.88   Total SA
 31  EDCL      2.97754  8.05   Eurasia Drilling
 32  HLCL      2.98072  4.42   Helical Bar
 33  SMWH      3.15547  15.1   WH Smith
 34  GPOR      3.17671  5.10   Great Portland Estates
 35  DLN       3.28182  5.08   Derwent London
 36  ITE       3.36212  9.45   ITE
 37  NBPE      3.36623  4.91   NB Private Equity Partners
 38  NOG       3.39358  9.05   Nostrum Oil & Gas LP
 39  NXT       3.44832  17.0   Next
 40  DMC       3.46037  14.3   DAMAC Real Estate Development
 41  REL       3.5027   12.8   Reed Elsevier
 42  AA.       3.67377  13.9   AA
 43  GLTR      3.70754  8.58   Globaltrans Investment
 44  SIA       4.21821  21.3   SOCO International
 45  XCH       4.3057   25.3   Xchanging
 46  OPHR      4.46711  13.3   Ophir Energy
 47  DGO       4.85896  7.02   Dragon Oil
 48  GMD       4.96425  -      Game Digital
 49  WKP       5.49217  3.74   Workspace
 50  BNK       5.90446  11.5   Bankers Petroleum
 51  AFR       6.74221  8.15   Afren
 52  FXPO      7.15282  2.96   Ferrexpo
 53  AEP      12.7208   17.5   Anglo-Eastern Plantations
 54  OKEY     15.5672   15.0   O'Key SA
 55  RMG      17.968    8.19   Royal Mail
 56  SEPL     27.3966   2.21   Seplat Petroleum Development
 57  SSA      28.8468   27.0   Aktsionernaya Finansovaya Korp…
 58  MFON     28.9517   11.3   Megafon OAO
 59  FIVE     35.8363   3.59   X5 Retail NV
 60  CNCT     38.9168   8.44   Connect
 61  GCLA     45.4253   51.3   Grupo Clarin SA
 62  TRCN     98.8475   0.84   TransContainer OAO
 63  NVTK    104.81     94.9   Novatek OAO
 64  ETLN    134.848    5.86   Etalon
 65  MCRO    195.078    19.4   Micro Focus International
 66  PIK     202.902    8.08   Gruppa Kompaniy PIK OAO
 67  ATAD    203.908    32.7   Tatneft' OAO
 68  GAZ     208.782    18.6   Gazprom neft' OAO
 69  KCEL    363.146    7.14   Kcell AO
 70  OGDC    377.114    85.4   Oil and Gas Development Co
 71  PHST    900.156    1.18   Farmstandart OAO

There is obviously going to be suspicious ones amongst them. Clearly, companies are not likely to have an upside of 10X+.By way of example, GKN has an upside of 55%. It currently trades on a PE of 10.4. Note that my computations make no use of PEs. PEs are a pricing statistic, not an intrinsic valuation metric.

You will see that some companies have high P/Es, yet are ostensibly undervalued. This is possible if companies have high re-investment rates and high returns on capital.

Here’s my code:

# -*- coding: latin-1 -*-

import operator
from pprint import pprint as prin

import tabulate

import aswath
import mython.csvmc


def floatm(x):
    x = x.replace(',', '')
    return float(x)

def calc(d):
    #print(d['Name'])
    del d['']

    dcov = d['Div Cover']
    if dcov == '-': dcov = "inf"
    dcov = floatm(dcov)
    roce = floatm(d['ROCE %'])/100
    op = floatm(d['Op Profit'])
    mkt = floatm(d['Mkt Cap £m'])
    ncash = mkt - floatm(d['EV'] )
    vc = aswath.grow2b(op, dcov, roce, ncash)
    d['upside'] = vc/mkt

    return d

def upside(d): return d['upside']

def main():
    inp = mython.csvmc.read_dict('~/Downloads/stocko.csv')
    calcs = map(calc, inp)
    calcs = filter(lambda x: upside(x) > 1.5, calcs)
    calcs = list(calcs)
    calcs.sort(key = upside)
    prin(len(calcs))
    prin(calcs)

    tab =[ [i+1, d['Ticker'], d['upside'], d['P/E'],  d['Name']] for i, d in enumerate(calcs)]
    print(tabulate.tabulate(tab, headers= ['#', 'EPIC', 'Upside', 'P/E', 'Name']))

if __name__ == "__main__" :
    main()

All of the computations are in the aswath module, which can be obtained from github.

Happy investing to you all.

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$NPT.L – NetPlay TV – a Magic Hat disaster

Gaming company NPT (NetPlay TV) issued its Q3 trading update yesterday, in which it said: “Despite the Group’s level of marketing spend, it has not achieved the targeted levels of new customers and net revenue expected from this spend. This situation combined with the current trading environment, and the initiation of POC means that the Board expects current market expectations to be materially lower than forecast.”

The shares closed down 17.7% to 8.12p. NPT was added to the Magic Hat portfolio in early August at 12.25p (http://is.gd/1XlNqw). I warned at the time that “my track record with gaming stocks is atrocious”. With the selection of NPT in the Magic Hat portfolio, my track record continues untarnished. My conclusion is that all gaming stocks are univestable. NPT only has a market cap of £24m, so it is probably more vulnerable than most to business setbacks.

I will keep NPT in the Magic Hat portfolio for its entire year, but I’m not a happy bunny. This was one stock that I should have overridden the mechanical pick, and I have paid the price. If I had to guess, I would say that the price when its year is up in the Magic Hat portfolio will be lower then than it is now. My hunch is that, despite the increases in revenue, the abundance of cash, and low P/FCF, this company is headed to the toilet. We shall see.

Paul Scott commented on the stock at Stockopedia yesterday (http://is.gd/5tsMvu): “the relatively small (£10k & £20k) Director buys in recent months now look to have been done more for PR reasons, to arrest the share price decline, than on fundamentals”. Exactly! That’s why I think we haven’t seen the end of this mess.

Private Punter (http://is.gd/1W9Jah) wrote about the company yesterday, and his full article can be seen on Cambridge News (http://is.gd/qE0og5): “While the growth label has effectively for now at least been cast aside, it is, on a value basis, where the shares may retain appeal, presenting a nice yield via the dividend.”

His post seems fair, and I don’t detect any rampiness in it. It certainly is a quandary. What I will say, though, is that the sentence I quoted sent a chill down my spine. To quote David Einhnorn: “We avoid ‘evolving hypotheses.’ If our investment rationale proves false, we exit the position rather than create a new justification to hold”. In other words, growth shares should not become value shares. If they do, then you are likely wrong twice.

Happy investing to you all.

Edit 20-Oct-2014: Removed stray text that appeared at the end of the post due to posting via email.

Edit 22-Oct-2014: Emboldened share price for ease of identification.

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