GlobalStockPicking 2.0 – Major Portfolio Changes

Before I start this post, I just have to comment on the last months terrible portfolio performance. After being comfortably ahead of the MSCI World benchmark, I’m now behind by almost 5% on the year. The portfolio is down nearly -8% in 1.5 month. Some of it, is company specific stuff, like the gaming halt in China (NetEase). Some of it is just general Emerging Markets and China sell-off, versus how strong USA (which I’m heavily underweight) is in comparison. A picture says more than a 1000 words:

MSCI World_USA outperf

Now over to something more fun than my under-performance, which I’m not too worried about, its bound to happen, especially when you have such large regional tilts.

GlobalStockPicking 2.0

In a recent post I laid out my new and hopefully improved portfolio construction/allocation. I summarize my new portfolio construction in the following three buckets:


Long Term

The idea is to keep the main focus on the long-term portfolio. This bucket contains about 15 stocks and carries the majority weight (65-90%) of my total portfolio . Given a 5+ year holding period, this implies that I should not change more than 3 holdings in a year. I did not put that as a strict requirement, because sometimes more action is needed. But the Target Holding Period defined above is really there to imply that this should be a low turn-over portfolio of great long term holdings.


I have been following stocks and the market so long now, that I see stocks that are miss-priced for one or another reason. When I see the risk/reward as favorable, I now have the flexibility to take part on a more short term basis. The analysis on my side here could be anything from very deep to more shallow.


I’m not sure if this the gambling genes in me that likes this so much, but I just love speculative stocks. I added this investment bucket for two reasons:

1. I spend quite a lot of time researching and reading about these kind of stocks. I think I sometimes actually have an information advantage (that is yet to be proven).

2. Because its fun. Investing is mostly serious business, but it should also be fun and exciting.

Portfolio Changes – Selling 3 holdings

It will take some time to have a portfolio that is fully in line with the above buckets. I think for example the Opportunistic cases I present today are not the strongest ideas ever. Nevertheless I think they are good enough to enter my new and shiny three bucket investing strategy. Below I will go through what has to leave the portfolio. At a later stage there still might be 1-2 long term holdings that needs to be evaluated if I’m really comfortable holding long-term.

Kopparbergs – Sell Full Holding – 5% investment return

Since I bought into Kopparbergs I spent quite a lot of time, Peter Lynch style, looking at cider products in stores around the world. Walking around daily life, like in a supermarket is just full of investment opportunities don’t you think? In fact this is in general something I draw quite a lot of inspiration from. The more important step in that process is both figuring out what you think of the product compare to its competition and more importantly, how other people feel about it. In the case of Kopparbergs, I think that competition has stepped up significantly and consumers are now having choices similar to Kopparbergs. Kopparbergs more or less created a new cider segment, with very sweet cider. From what I see in stores, although less sweet, for example Carlsbergs Sommersby cider is extremely popular. My case was that Kopparbergs cider had a good chance of being a hit in the US, I now changed my mind about that and see it as less likely. Kopparbergs product offering is not strong enough to really stand out in this competition. Another important factor is that selling these products is as much about distribution and network as in having an awesome product. For all the above reasons I decided that the likelihood of Kopparberg continuing a strong growth journey in cider sales, is low.

Original Kopparbergs investment case

ISS – Sell Full Holding – 15% investment loss

A behemoth in property services, mainly related to cleaning with almost ½ million staff is an impressive entity. My investment thesis was a turn-around in free cash flow after paying down debt and after that a significant dividend increase. That didn’t really play out as planned and the stock market has also been as disappointed as I. Selling this holding is for totally different reasons though and that for me is too low growth opportunities. This is a steady (potentially) high dividend paying company. Although high dividend stocks have many nice characteristics, it’s not really what I look for in a long-term investments. There has to be both growth and dividends. Mature businesses which are just fighting with operational efficiencies is not what I believe will generate alpha long term. It might do so in a bear market, given the stability and quality of the company, but I’m not going to hold ISS as a timing play on a bear market.

I will have to expand what I look for later, in my Part 2 of the “Art of Screening”

Original ISS investment case

Radisson Hotel Group – Sell Full Holding – 39% investment return

I’m usually pretty tough on myself and my investments failures. That’s because I’m not here to brag, but to become a better investor. But now I will do a bit of bragging. Damn it feels good when you are spot on in an investment idea. I painted out a investment scenario whereby HNA would be forced to sell it’s position in Rezidor (now renamed to Radisson). On top of that I had listened to a 3.5 hour investor presentation on how the hotel group was going to structure it’s turn-around. So it was a double whammy turn-around + bid case. As it happened the market started to believe the turn-around, especially when it already started to show in the latest results. Then came the bid by a Chinese hotel company: HNA sells Radisson Holdings to Jin Jiang-led consortium.

Unfortunately this bid did not give as much of a stock price bump as I had hoped. There is still some un-clarity around how much Jin Jiang will need to offer the minority holders, but they might low ball investors and keep the stock listed. There still might be more upside here, but my investment case has played out and I’m happy stepping off here, overall a great investment which returned 39% in less than 6 months.

Original Radisson/Rezidor investment case

New Holdings – Adding 5 holdings

I will at end of trading today add 5 new holdings to the portfolio, and after selling the 3 above holdings, this is what my new 3 bucket portfolio will look like:


Short comments on new holdings

Obviously this will need to be expanded over multiple posts, but here is the quick and dirty on these 5 new holdings:

Amer Sports – Opportunistic – 4% position

Since my previous investment in Xtep, I have both researched and followed the Chinese sportswear and sport shoe producers in China. I invested in the one (Xtep) that was trading cheap on all kinds of metrics. If I had taken a more long-term approach, perhaps I should have considered the local champion Anta instead. Anta which is a 13bn USD MCAP company recently showed a tentative interest in bidding for Amer Sports, a Finnish holding company for a long list of attractive brands/assets. The tentative offer was at 40 EUR per share and the stock quickly after repriced from 29 EUR to 36 EUR, but has after that come down to 34 EUR. If one wants to play mathematics on that, one can say the market is pricing about a 50% probability of this bid actually going through.

My investment case is two fold:

  1. I liked Amer Sports already before this bid and had already done a quick due diligence on the stock. Even if the bid falls through, I’m not in panic mode holding this stock, it could convert to the long-term time bucket if I did a deeper due diligence and like what I see even more than I already do. There has already been other speculations that Amer might spin-off parts of its business to unlock value.
  2. The market is way too skeptical on the bidder in this case. I take this as typical “China fear”. This investment, so makes sense for Anta. If and when it goes through I will be very compelled to add Anta to my long-term holding bucket, I think they would do great things with Amers portfolio of companies. We have Winter Olympics coming up in Beijing 2022 and Amer holds several “winter” assets. Anta has the network in China to actually being able to grow these brands in this tricky market, in the past Anta has bought the China rights to the at the time quite poor brand Fila in 2009. They have totally re-positioned the brand in China over these years, growing it into a real success, from 200 to over 1000 stores in the country. I put the probability of Anta being serious with this bid at 90-95% and I take the probability of a successful takeover somewhat lower (85%), since there is some overhang with for example USA wanting to meddle in this, given that many of the brands under Amer are tightly related to USA.

My own expectation is that this should be priced at 85%*40 + 15%*29 = 38.35 EUR, giving about 12.5% upside on current market price of 34.1 EUR. – Opportunistic – 4% position

In this pretty brutal China sell-off I have been scratching my head if and when I should poke my hand in trying to catch any of these “falling knives”. I somewhat randomly felt that now would be a good time to catch one of the stocks I have been looking at for quite some time. is the case of a quickly growing e-commerce company with tremendous revenue growth. The company plows all of the cash back into investments in its own business and other businesses. For example it’s a co-investor in Yonghui Superstores, which my largest holding Dairy Farm owns 19.99% of. For a primer on I kindly refer to Travis Wiedower who presents the case in his investor letter: in LetterEGREGIOUSLY CHEAP blog.

What has taken this fall into another gear, is what happened recently to the CEO of the company: Richard Liu of Was Arrested on a Rape Allegation, Police Say

A pretty disastrous allegation having hanging over you, I will refrain from speculating in the probabilities of this being true. The main point here is that at this stage the company is bigger than Richard. Yes, Richard built this company and yes this will have a negative effect on JD’s perception among the Chinese. What did Richard do in the US when he got arrested? He was actually studying at Carlson School of Management to complete the American residency of a US-China business administration doctorate programme. Having time for these types of studies shows that other people are running the company by now. There is some issues with the governance structure if Richard would be imprisoned, but we very far from that right now, he is not even charged yet. Richard has built a fantastic business in China, in many ways better than Alibaba’s model. My best guess is that these allegations will die out and will on a 1-2 year time horizon trade significantly higher. When/if this allegation overhang is removed, this might move into my long term time bucket.

Irisity – Speculative – 2% position

The company listed in 2013 under the name Mindmancer. The idea was to provide smart camera surveillance systems to construction sites, schools and such. The whole package of software imagine recognition, cameras and installation was provided by Mindmancer. They had some success and have installed this in numerous places over these last ~5 years. The problem was that the business model didn’t scale and it was hard to keep the company profitable. There was also management issues, where one of the founders, a very young an enthusiastic guy was the CEO. He probably had the heart in the right place, but was to inexperienced to run and grow this company. The largest shareholders which is connected to the University in Sweden where the company started, decided to appoint a new CEO, change the name of the company to Irisity and do a rights issue (24 MSEK at 7.8 SEK per share) to strengthen the balance sheet. After that the new CEOs strategy has been to go for scalable sales model, just selling the software they develop. The software is proven in all the live conditions where it has been installed already. They are going for so called Software as a Service (SaaS) model. Somewhat surprisingly this quite quickly has got a lot of interest from market participants, both G4S and several of the worlds largest camera producers.

A somewhat sloppy google translate of one of their press releases recently (Irisity press releases):

“Irisity AB (publ) signs license agreement with Hangzhou Hikvision Digital Technology Co. Ltd.

Hikvision is the world’s largest supplier of innovative video surveillance products and solutions. With 20,000 employees, including nearly 10,000 in R & D, the development of intelligent cameras leads. Hikvision is listed on the Shenzhen Stock Exchange with a valuation of USD 46 billion. The company shows a strong YoY 32% growth, with sales of USD 6.6 billion (2017). In collaboration with Hikvision, Irisity now evaluates embedded integration of IRIS ™ AI software in Hikvision’s camera platform.

–        Hikvision is a wish party to Irisity, we already have our AI with several of their IP cameras, but are also looking forward to creating a Linux embedded solution right in the camera. This is the future, since very few cameras will be delivered without built-in AI! Comments Victor Hagelbäck, CTO on Irisity.”

What is not mentioned in the press release is that Hikvision produces almost 100 million cameras per year, so the potential is gigantic if these companies really like the Irisity software.

So to summarize, the company has a proven product in the Nordic markets. They are currently trying to convince huge players, that its software algorithms are good enough. In a best case they would want to pay Irisity to embedd them in their products. Right now this license agreement is not worth any money, its just shows that Irisity has got to actually showcase their products and on some level for example Hikvision (several other big companies are doing the same) is evaluating their product. I find Irisity (valued at about 35m USD) at a very attractive risk reward right now, even if the probability is very low to see large orders. This is truly speculative, one of these lottery tickets, but with much better odds than playing the lottery.

Scorpio Tankers – Speculative – 2% position

This is a fairly simple case, market analysts seems to think that Day Rates should normalize. They have not done so, so far. Equity markets have given up and stock is tanking (ha ha). Taking the long term view on day rates, its seems plausible that they would increase from these levels. I’m a firm believer in mean reversion. Scorpio has a attractive fleet of new vessels, as long as day rates recovers somewhat, they are highly cash generative. Let’s see if that happens or not.


UR-Energy – Speculative – 2% Position

Canadian listed Uranium miner, that I actually owned already back in 2006-2007. At the time, it was the only junior Uranium prospecting company, that actually came out on the other side of the bull and following bear Uranium market. They are now a small scale Uranium producer, with a large portion of their production hedged at higher levels. I will have to write another time about Uranium, but its a very special market and a strong case can be made for long term increases of as its called yellow cake. I’m choosing UR-Energy as my Uranium proxy, because they have excellent management, a very crucial detail in the mining industry, which is full of crooks and cheaters.

Please comment what you think of my new holdings and I will try to follow up with more details in later posts!


Read More

The Art of Screening – Part 1

This will be an exploration in how to set up stock screenings, if you have a lot of experience of playing around with this, please do comment and help me out.

A stock screening could have many purposes, most screens are not related to finding the “hidden gems”. The screening could be used to list companies with certain characteristics, for example all Bank stocks in Asia. This post will not be about these type of screens. It will be about screening for stocks you otherwise would struggle to find and stocks that hopefully few others have looked at. Later post will explore other angles of screening, for example dive deeper into what stock characteristics I’m looking for. The beauty of being a Global investor is that you work with the widest possible set of publicly traded companies. I think would be a waste if you as a Global investor did not take advantage of having access to all markets. This should be exploited to the largest extend possible. According to Bloomberg there are 61 000 listed companies in the world. Just like my catch-line of this blog, surely among the 61 000 companies there is bull market somewhere? But with 61 000 companies it is like finding a needle in a haystack, the question is, how do we find the needle?

I will divide the challenge of finding the needles in the haystack into two parts:

  1. Where should one look? Meaning what should be filtered away from categorizing metrics. Examples being: Country, Company Size, Industry
  2. What type of metrics? Meaning what company specific criteria are on average delivering out-performance? Examples being: Price to Book, P/E, Growth, Piotroski F-Score, Momentum

What universe?

Obviously in practice as a private investor you do not have access to every single market in the world. Few professional investors do either. So in practice, in my case the Global Universe of stocks is listed on one of these countries exchanges: Australia, Austria, Belgium, Canada, China (Shanghai & Shenzhen), Czech Republic, Denmark, England, Finland, Germany, Greece,  Hong Kong, Hungary, Indonesia, Ireland, Italy, Japan, Malaysia, Netherlands, Norway, Philippines, Poland, Portugal, Singapore, South Africa, South Korea, Spain, Sweden, Switzerland, Taiwan, Thailand, Turkey and USA.

What is the competition?

To understand where we should look to find the hidden gems, we first need to understand the current investment landscape and competition. I’m a firm believer that markets are fairly efficient. One should respect the huge amount of clever highly educated people spending all their efforts trying to find the best investment cases, all with the goal to outperform markets. Lately a lot of money has gone into passive investments but there is still a lot of money sitting with fundamental active managers.

Not only passive investments drive return today, we also need to compete with machines. In the last 10-15 years the competition from computer algorithms have increased significantly. In the beginning it was only hedge funds, like AQR, Renaissance Capital and a few other that were using statistical analysis to find stocks characteristics that on average outperformed the market. They applied much of their strategies in a market neutral or at least hedge manner. Meaning going long the stocks they thought had the right characteristics and short the ones that had the opposite. Today this market has exploded, Smart Beta, Factor/Style investing has gone mainstream and huge amounts of money is invested in it. Also fundamental fund managers use these screens to come up with stock picking ideas and evaluate their fundamental portfolios from a factor/style perspective. When I started this blog my ambition has always been to apply similar screens, but on parts of stock universe which institutional investors can not reach.

On top of that, with internet, cheaper brokerage fees and everyone having all the information in the world at their fingertips, private individuals have entered the space of stock picking in a way never seen before. Just look at the amount investment blogs out there, with young and old trying to dig up new investment cases.

To summarize – Three categories of investors:

  1. Professional investors, most of the money sitting with long only mutual funds, but also hedge funds and family offices has large pools of money to deploy. Through company visits, and deep analysis they find the miss-priced stocks according to a multitude of investment styles and approaches.
  2. Smart Beta / Factor / Risk Premia / Statistical Investing, it has many names, but all of them is based on the idea of sifting through large amounts data, finding patterns in that data that indicates as high probability as possible of out-performance. The styles here are also developing, but having worked in this field, the strategies tend to be more similar. The sophistication is rather related to the type of Quant strategy, the simplest being large smart beta ETFs and Funds and the most sophisticated are still firms like AQR and Renaissance Capital.
  3. Individual investors – everything from total beginners, to very professional individuals, investing mostly their own money. Here many have no idea of what they are doing, but there is also wisdom in crowds and on average they might be right, that’s all that matters. There is also a large group of clever hobby investors or finance professionals who invest their own money.

Where to look

My main thesis is to look where few are looking. Do not look for stocks in the same pool as where one or all three above listed categories of investors are looking. The probability to find something “unique” is pretty low, but at least concentrate your efforts where the above three categories is looking less.

Sabre Capital (John Huber) wrote an excellent piece on this, well worth a read: What is your investing edge?. As is argued, many investors believe that if you just look for small caps you have an edge. You have then solved the problem of competing with the “big fish” in category 1-2 above. That is probably true, but one then forgets the “small fish” in category 1-2, as well as the whole category 3. Meaning just buying small-caps is simplifying it a bit too much. Actually as we all know many private individuals love investing in small caps, penny stocks etc. This is appealing to anyone with some gambling genes in them, the thrill of fast gains is exciting even for the most professional investor. Just like the option market has a volatility smile, meaning investors are willing to pay more for call options with a high return potential. I believe small and micro caps in bull markets could actually on average be overvalued, due to this effect, people love buying a lottery ticket. Again, in bull markets this might be an area to avoid.

Avoiding Category 1 & 2

Professional investors come in all shapes and sizes, but to manage money in today’s world comes with certain levels of costs. If your AUM (Assets Under Management) is too small, those costs become unreasonably large compared to your potential income. Without doing a big deep-dive into this, this is my thinking in a few sentences. I would argue that firms with less than 200-300 million USD in a fund, does not really bear itself long-term. There is definitely a lot of funds smaller than that. But they either do not have the resources to actually do all that research that we are afraid of competing with, or they belong to a larger fund group, where they have some small funds but total AUM is higher. Such a firm usually will focus its research on larger companies, for its larger funds.

What are the smallest companies these funds can then reasonably invest in? Again we want to avoid the stock pickers, small funds that run a 200 stock portfolio, would not worry me. The amount of research spent per company, by a small fund with 200 holdings, will be more like an index fund than actually doing deep research. Let’s say 30 holdings for a small stock picking fund of 250 million AUM. That gives us 8.3 million USD invested per holding. What would such a fund managers requirement on liquidity be for buying position in the 8 million range? Well I don’t think they would be comfortable holding anything more than 10 daily turnovers. Actually if the fund is registered under UCITS or such, this would not be allowed for a daily traded fund, but some funds are not daily, like hedge funds. So let’s stick with the generous assumption to begin with. This means that stocks with daily turnover below about 800 000 USD would be a no-go.

If we look at Quant funds, I would say their requirements on liquidity is much much higher. Having worked on building such quant strategies, in a long/short context, for Europe we would not go outside the Stoxx 600 companies, so anything below that, would be under the radar for our factor strategies. Some other funds do go lower, but not much much lower, meaning there is still a huge chunk of the market where factor strategies is not applied. Again this something we then instead could explore to copy their ideas, but in a stock universe they can not touch.

Avoiding Category 3

So my first idea of avoiding the three types of investor above would be something like this: Avoid category 1-2 by looking at small enough companies so most of the competition is gone. Avoid category 3 by looking at markets where individuals are not participating to a large extend in direct ownership of shares. This idea led me to a fairly lengthy search trying to finding out, what markets have low direct ownership of shares from the local population. The data is somewhat sketchy on this and some of the data is unfortunately old, but I managed from several research papers collect together a fairly good overview of direct ownership:

Country stock market participation rates

The source of this data is 3 different studies: “Participation Matters: Stock Market Participation and the Valuation of National Equity Markets – Journal of Financial and Quantitative Analysis”, “Stock market participation and household characteristics in Europe” and “The Effect of House Price on Stock Market Participation in China: Evidence from the CHFS Micro-Data – Emerging Markets Finance and Trade”.

For the few markets that has data both from 2000 and 2007, one can see stock participation in most developed economies has increased significantly (Sweden, Denmark) over the year. In general if we would have data for 2018, participation it probably higher in most markets. Better data would be great, but if the pattern stays the same the above is still useful.  We can definitely conclude that less people are participating as direct owners of companies in Italy, compared to Sweden. My thesis here is that on average one would have more success looking at smaller companies in Italy, than in Sweden.

From my list on markets that I’m able to trade, data on participation rates are missing in some cases. But a good guess is that also these markets have low participation rates, just because they are not very developed. So adding those back in and making a somewhat arbitrary cut, I come up with these markets as good hunting grounds:

Low participation countries

How many companies are we then left with?

Applying the above Country Filter: 61 000 –> 12 700 companies

Now let’s also define a liquidity filter. Unfortunately my screening does not support a turnover screening, instead I have translated it into a rough estimate in terms of MCAP. After some sample checks a Market Cap below 500 MUSD combined with a free float above 30%, is more or less in line with a daily turnover under 800 000 USD. Another filter I throw in putting floor on MCAP at 15 MUSD. I’m not interested in investing in too small companies.

MCAP < 500 MUSD: 12 700 –> 9400 companies

MCAP >15 MUSD: 9400 –> 7700 companies

Free Float > 30%:  7700 –> 5774 companies

So by trying to look in the right place, where other people are not looking, we are down to 5774 companies. This is how they are distributed country-wise

Hunting Grounds Stocks

Hunting Grounds established – Time for factors

So if these 5774 stocks is our new hunting grounds, what do we do next? It is still too many stocks to read up on, now its time to apply different metrics. These metrics should be something you believe in that your companies should have to be great investments. One such metric is the Piotroski F Score (More about Piotroski).

Applying Piotroski F Score > 8

5774 –> 111 companies

Here are all the 111 companies

Piotroski Screen_20180902


Now we got the universe down to something manageable. From this stage on, its time to go back to the regular due diligence process. This list above contains 111 new companies for me. The screening has helped me with:

  1. Pick out a universe of stocks where few others are looking.
  2. Use a quantitative metric like Piotroski F-Score to within the this universe pick out stocks with good characteristics.

The idea of this is that this selection should on average out-perform the market. For this to be true, one has to believe that these are stocks less covered by the market and that Piotroski F-Score actually works as an indicator for alpha generation. If you start a fund investing according to my steps above, basically you then have a Piotroski Quant Fund. This fund is probably picking stocks where no other Quant-funds are looking. I hope such a Quant fund would outperform the market, and we could back-test this model (if I just had the time). But even if it does not, my idea is to apply my own due intelligence on top of this, to pick the best companies from the above 111. So for me it matters if the above 111 stocks generates alpha, but its not the end of the world if they do not. As long as the stocks I pick from the 111, generate alpha.

Another way which I played with earlier to find certain investments, has been identifying sub-sectors with future great prospects. For example I believe certain type of beverage and brewery companies have a very attractive business profile. Instead of using countries to define the universe, one could combine sub-sectors with metrics to find the for example few undervalued Beverage companies.

This was one example of a screening process. One could endlessly modify how one picks out the first the universe, and then the metrics. A will write more on this topics in a follow-up post, creating especially more metrics. The trick is to figure out what your investment style is, express that in metrics, and the screening will do the rest. Well maybe not the rest, you still need to decide what on the shortlist you want to invest in.

Happy to take any input on what you think would be successful screening methods, preferably backed up by some good reasoning!

Read More