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Data mining – finding cheap and un-loved stocks using IG filters


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In this article I will go through a quick set of criteria, build a filter and see what comes out the other end.

 

With the FTSE100 at all time highs, let’s look through that selection (the UK 100 stocks) and try and find potential trade opportunities.

The overall index has moved up over the preceding months but how does that resonate with particular stocks.

Which have been left behind, and

Can we find any hidden gems  that may be worth further inspection?

 

To help answer these questions we will use IG’s own tools designed to help investors filter through the vast population of stocks and hone in on those that meet a set of criteria: Data mining.

 

From the classic IG trading platform, go to the ‘Research’ button and click on Market Screener (or simply click on this link for our market screener), a new tab will open.dm_screening1.JPG

 

From here the first thing I have done is clicked ‘Reset’ to clear any pre-existing filters: we have a blank canvas now.

Scroll down to the bottom of the list and you will see there are 10+ pages of stocks, this is too many to review, so let’s focus on refining that list.

dm_screening2.JPG

 

From the left-hand-side I selected the group we are interested in. In this piece I want to look at those within the overall 100 index. So I click this selector on the left-hand side under ‘Index’

dm_screening3.JPG

 

 – the screener tells us we have limited to 102 stocks (not sure why its 102, I’d expect 100, but its close enough for now)

dm_screening4.JPG

 

Now let’s dig a bit deeper. I am looking for those unloved stocks that have not benefited from the moves encountered by the FTSE over the last month or so. We click ‘Select Fundamentals’.

dm_screening5.JPG

 

First thing we’ll add is a screen to identify shares that have not moved positively in price over the last two or so months. This suggests they have not moved in step with the index through November and December '17. So I select the criteria shown

dm_screening6.JPG

 

We use the tolerance sliders to set our criteria. I want to select shares that have not realised good gains over the last 13 weeks – I set my maximum to 5% (gain) and minimum to -15% (suggests share has actually fallen in price)

dm_screening7.JPG

 

I am also going to retrieve shares that have a lowly PE rating. With the Cyclically Adjusted PE (CAPE) now standing above 30 (source: SCSW Jan-18) setting our PE ratio threshold to a maximum of 13 means we are excluding the highly rated stocks that are up on a par with the CAPE, and looking for those that are less favourably rated. Same again, 'Select fundamentals' and pick our criteria...

dm_screening8.JPG

 

Lastly, I want to obtain some form of 'comfort' in the stock I am buying. We can add in the ratio Price/Tangible Book, and this at least gives us the certainly that the stocks will be backed by some form of physical asset (store, stock, merchandise, fittings, cash etc) There is no hard-and-fast rule here, but let’s set the maximum slider to 2.5 = that is to say the stocks we are screening for will have a share price that is no more than 2.5 x tangible assets per share. The lower this value, the nearer the shares are in comparison to their book value (the assets as recognised on the balance sheet)

dm_screening9.JPG

 

Right, let’s recap.

  • We know the FTSE 100 is at an all time high, or thereabouts
  • We know CAPE sits above 30 (read this as average PE of 30 across the market)
  • We are looking for FTSE100 shares that have not risen in step with the FTSE index over the 2017 Christmas period- as we hope there will be some anomalies
  • We are looking for lowly rated shares – those not trading on high multiples, and certainly less than CAPE
  • Also we want some kind of asset backed security, so will ensure the shares are no more expensive than 2.5x the tangible asset value.

 

Our results are below. We get 7 shares returned from this screen:

  • MKS
  • SBRY
  • UU.
  • BDEV
  • 3i.
  • SSE
  • LGEN

dm_screening10.JPG

Interestingly, I have positions in two of these shares already and am betting exactly that the shares are under-rated and due a positive correction in the near term. We also talked about LGEN in another thread, where our contributor,  has an interest

 

Of these 7 there are a few things to note:

  • MKS is down 10% over the prior 13 weeks
  • SBRY is strongly asset backed at only 0.86 of its tangible asset value
  • Both 3i and SSE are on strikingly low PE ratios

 

  • I think this provides an opportunity for further investor research:
  • What PE ratios do the competitors of 3i and SSE trade on, is there a sector anomaly that could be exploited?
  • Is MKS set for an easy 10% gain in the coming weeks (results imminent for Christmas period)
  • Is SBRY offering a quick 15% trade whilst its share price is selling for less than the per share asset backing?

 

Let me know any thoughts you might have – again, this is not advice but a chance to look into some techniques for valuing unloved shares and potentially exploiting anomalies in solid FTSE100 companies..

Is this useful? 

What would you do differently?

We could follow this on and look at mining for solid dividends another time..

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Well the news is starting to flow, so we can look at our trade ideas and establish if the calls made were indeed fortuitous.

 

Today (10 Jan 18) sees the release of SBRY trading statement Q3 covering the 15 weeks to 6 January 2018.

 

My assertion was SBRY had not benefited from the overall index move in the run-up to Christmas, but it was nonetheless a quality company and I was expecting positive news.

 

https://www.investegate.co.uk/sainsbury-j--plc--sbry-/rns/third-quarter-trading-statement/201801100700034219B/

 

I quite like the way this reads - especially for a retailer in the current climate of increased competition (Aldi, Lidl on the scene), inflation and rising input costs due to exchange rate movements.

The headline reads 

'strong Christmas week, with record sales, over 340,000 online grocery orders and stellar growth in Argos Fast Track delivery and collection. Online accounted for 20% of the Group's sales during the quarter'

 

SBRY is integrating the Argos acquisition and synergies from the Argos deal seem to be driving the benefits to the bottom line. EBITDA related synergies are expected to rise to £80m-£85m, and in turn this will result in 2017/18 underlying profit to be moderately ahead of published consensus. E.G. ahead of forecasts. Note 1 of the RNS tells us: 2017/18 UPBT consensus estimate of £559m, as published on 5 January 2018 on j.sainsbury.co.uk/investors/analyst.consensus

 

If PBT is expected to be 'moderately ahead' of £559m, I'll assume 'moderate' means 4%, raising the profit target for 17/18 to £581m.

 

This resets our EPS estimate to: 26-27p and at 251p gives a PE of 9.6.


Additionally, SBRYs three-year cost savings target of £500m is on track to achieve £185m  this year, exceeding our three-year target and forecast to exceed £500m by £40m, so their could yet be more surprises to the upside for this share.

 

Thoughts?

 

So the strategy seems to be working and the RNS reiterates four key areas of the business where [we] can differentiate ourselves

 

 

 

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On 7/12/2018 at 5:16 PM, Guest TinkerTrader said:

this is incredibly useful!

why doesn't this have a billion likes?

Thanks @TinkerTrader. I appreciate you reading my article. I get quite busy at times, however I will create something similar soon for dividend paying ideas. With the markets undergoing (potentially) a bit of turbulence then we might want to look at stocks that provide some level of income to switch into to ride out the storm! I might get chance this week..

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  • 6 months later...
  • 4 weeks later...

Example of a volume screener. 

@LoneStockTrader

Instead of looking for the next stock tip or subscribing to an expensive stock watchlist service, simply scan daily for stocks up on unusually high volume. Not all of those stocks will be big winners. But almost all big winners will appear in that list on the day they break out.

 

image.thumb.png.6d277ff6910f6369101c43ae1212feb7.png

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