A Wealth Creation Journal

Category: Investing Lessons

Another Investment Mistake – AddCN

While it never feels good to write about investment mistakes, I have found that the process of revisiting the initial investment case and evaluating the decision-making process is critical for the advancement of my investing skillset. So let me share the mistakes that I have made with AddCN and why I have sold a big chunk of the position but still kept some. See Live Portfolio Update – 2021 – #17 (AddCN)

I first invested in AddCN (an online classified business in Taiwan) in Jun 2018 and my original investment thesis is based on my conviction in online classified businesses being high-quality businesses with ample pricing power. It was trading around 20x p/e and paying a 5% dividend yield. I believed that it could grow its earnings around 10% per year and hence the 20x P/E valuation is pretty cheap. 3 years on, AddCN is trading on 16x P/E and still paying 5% dividend yield. And its earnings only grew 5% between 2018 and 2020 and hence the multiple derating.

My average purchase price for AddCN is around TWD 261 and if I include all the dividends received, then the investment is flat over the 3 years. For a 10% position to be flat for 3 years, the opportunity cost is huge. Overall the investment performance has been very disappointing!

The biggest mistake that I made is to assume that online classified businesses are high-quality and overestimated the quality of growth derived from price increases. For a very long period of time, successful online classified platforms, such as REA Group in Australia, Rightmove in the UK and Seek in Australia, has been the holy grail of great businesses – high margin, strong pricing power, capital-light and hence very high free cash flow generation. However, price increases of the online classified platforms come at a cost of reduced RoI for the customer and hence the very act of increasing price in my view compromises the long term viability of the business since there is no incremental value created for the customers (typically customers are property agents, used car dealers and corporates posting job vacancies).

The rise of vertically integrated transactional platforms such as Carvana, Opendoor and Beike will slowly replace pure information-based online classified platforms such as AddCN. Though this transition could happen at very different paces in different geographies.

In short, my mistake has been to overpay for AddCN because I did not fully recognise the vulnerabilities of online classified platforms at the time of investment. This is a case of not properly weighing the risks.

In the case of AddCN, the transition from marketplace platforms to transaction platforms will take many years to unfold in Taiwan. At 16x P/E, AddCN is quite fairly valued given its 5-10% growth rate and defensible position as the leading property portal in Taiwan and hence I have not fully exited AddCN. If I found better ideas, I would not hesitate to sell AddCN completely.

Thoughts on the video game business

I am a gamer myself and I am very excited about the future of video game as a great entertainment medium and a “subset of reality”. But I am even more excited about the lucrative prospects of video game businesses as an investor!  I have learnt so much from the great thinkers in this industry – Chris Crawford, Nicole Lazzaro, Satoshi Iwata, Gavin Baker, Shigeru Miyamoto, Matthew Ball and many more. And I have taken their work and organized it in a way that is useful to me as an investor.

Note: While I will use game and video game interchangeably here, I recognise that many great games, such as Magic: the Gathering and Warhammer, share many common features with the video game as described below. For this discussion, I mostly focus on video games

1. Unlike traditional media of TV, books and music, video game is an interactive entertainment media. This is a highly immersive environment where the gamer can interact with the game environment and change the course of events in the game world. Video games, because of this interactivity, are in essence problems for gamers to solve. For example, puzzles in Legend of Zelda, defeat enemies with finite resources in a real-time strategy game, opponents to be killed in a first-person shooting (FPS) game. It is believed that human instinctively derives happiness from solving problems and the harder the problem, the more intense the feeling of happiness when the problem is solved. Using this perspective, a video game is a very cheap and effective medium to create all kind of problems for humans to solve. It would be stupendously expensive to recreate a typical role-playing game that involves 100 characters to act out 100 hours of game-play content in real life! So game worlds simulate problems for gamers to solve and gamers derive happiness from solving the problems. 

2. In this context, the video game industry has tremendous future ahead of it! Beyond its current incarnation as an entertainment media, video games can be used to solve real-world problems such as education and politics. Imagine the value that could be created if job interviews involve the candidate playing a game which simulates the work environment with high fidelity or two countries before engaging in a trade war is required to play a game that simulates the economic consequences of their trade policies in a game! Humans can sometimes only learn from things that they have experienced and games are an efficient way for human to learn from experience albeit in a virtual environment. This is very far into the future but I believe this is the direction that we are heading towards.

3. The most important difference, from a business model perspective, between video games and traditional media is that video games’ interactive nature creates a feedback loop of inputs and rewards. Gamers give up time and effort to create inputs into a game and the game rewards the gamer with some kind of positive emotions. If the gamers feel that they receive more reward from the game than the effort they put in, the gamer is said to be in a positive feedback loop where his/her emotional attachment to the game grows with time. Some game companies exploit this feedback loop (through mechanisms such as loot boxes) in a way similar to gambling. Other game companies create truly beautiful games where the gamers are treated to a rewarding emotional journey similar to watching a well-made movie.

4. There are three main roles in the video game value chain – 1) Game developers (Nintendo / Blizzard) who made the game, 2) Game publishers help to market and distribute the game. Game publishers can either buy the game content from game developers outright and take on the marketing cost to sell the game or more commonly finance part of the game development cost and strike a profit share agreement with the game developers. It is common to see big game developers such as Activision develop and publish their own games, 3) Game distribution platforms. Apple / Google for mobile games. Steam / Epic for PC games. Sony / Xbox / Nintendo for console games. Most game companies are involved in multiple roles across the value chain. E.g. Tencent takes on all three roles – game developer, game publisher and a distribution platform 

5. Game developers and distribution platforms capture the majority of the profit pool in the value chain while the game publishers are increasingly squeezed in the middle. Game publishers’ service, relatively speaking, add less value and least differentiated and hence they take the smallest slice of the cake on thin margins. Tencent is a unique case where it began as a game distribution platform and game publisher and grew to become a very successful game developer. As a content creator, the game developers differentiate themselves through game content. Fans are extremely loyal to great games but the challenge for the game developer is to consistently produce great games.  Game distribution platforms such as Apple App Store through their control of users are extremely profitable. For a typical mobile game on iPhone, the Apple app store clips 40-50% of the total revenue and the game publisher takes 10-20% and the game developer accounts for the rest

6. Why do people pay for virtual items in games? Gamers pay because they receive an emotional reward in exchange for time and money spent on the game. Ultimately, the maximum amount of money people is willing to pay depends on the quantum of emotional reward they receive. There are a couple of ways for people to get an emotional reward – not a comprehensive list. 1) enjoy a good the storytelling (similar to emotional reward from movies) 2) sense of competence as one becomes good at the game 3) social interactions – critical for many online games. E.g. gamer pay for cosmetic appearances for their in-game avatar. When my 15-year-old cousin was asked why she pays for virtual clothes in-game, she said “you don’t walk around naked nor wear the same cloth every day so why shouldn’t I behave any different in-game”.

7. Traditionally (let’s say before the 2000s), in the Game as a Product (GAAP) revenue model, gamers pay a fixed sum in exchange for unlimited gameplay time to get an unknown amount of emotional reward. The traditional distribution model of games is in essence very similar to books. A gamer walks into a physical game store to check out the latest games available and make a purchase decision based on very limited information. Pretty much judging a game by its cover. It is impossible to charge each gamer a different price based on how much each gamer liked the game. For the most part, the gamer cannot try the game before deciding on the purchase. Furthermore, the gamer’s relationship with the game developer is indirect because the game developer does not know who plays the game nor how the game is played. Feedback collection mechanism is chunky and ineffective. The entire experience is sub-par for gamer and game developer.

8. Internet and smartphones herald a new revenue model – Game-as-a-Service (GAAS). GAAS employs a continuous revenue model with free-to-play being the most dominant GAAS model for mobile games. GAAS spreads the revenue across the entire lifecycle of a gamer while GAAP is 100% upfront payment. There are many different manifestations of GAAS such as a game subscription, in-game transactions, in-game economy tax. I am excluding the discussion of cloud gaming here because cloud gaming is more about computation and I want to focus on game monetisation method here. Conceptually, GAAS is a superior revenue model to Game-as-a-Product because 1) game developers can build direct relationships with its gamers and own that relationship; 2) price discrimination of gamers; 3) maximise gamers’ lifetime value. Said in another way, for great games that use the GAAS model as opposed to GAAP model, the gamer’s loyalty is higher, generate higher revenue and play longer while also getting more emotional rewards from the game.

9. We are still exploring what is considered fair and ethical in the GAAS model. Some game developers design GAAS games with feedback loops similar to those that cause gambling addiction or create an unfair advantage to paying gamers.  Other GAAS games, such as League of Legends, sell virtual costumes for purely cosmetic purposes and does not impact the competitive gameplay at all. I believe that GAAS is especially powerful for great games with a fair monetisation mechanism.  Because great games are by definition offering tons of emotional reward, and it is likely to be under-monetised in the GAAP model because great games’ sale price is not too different from the average game price. On a price per unit of emotional reward basis, the great games are arguable under-monetised as a GAAP game. Using a GAAS model, gamers who otherwise cannot afford the game could play the game for free and the most passionate fans can be monetised based on the different amounts of emotional reward they each individually receive.

10. A great example is a Chinese online MMORPG game created by Netease called Fantasy Westward Journey. This game has two monetisation methods – 1) gamers pay an hourly rate of USD 1 to play the game and, 2) Netease charges a 1% commission rate for transactions between gamers. Most passionate fans are willing to spend thousands of US dollar to buy powerful characters from players who committed incredible time and effort to train up the character. Netease charges a 1% commission rate for this kind of transactions. The commission dollars help to keep the hourly rate low which then keeps the players with a lot of time and less money in the game to train up their characters which they can sell to players with more money but less time. Such an in-game economy structure improves the game experience, increase gamer loyalty and maximise gamers’ lifetime value in a continuous game world using a GAAS revenue model

11. Gamers can become incredibly loyal to one game over a long period of time once they become invested in the game. I started playing DOTA when it was just a customized game within Warcraft in 2007. DOTA has inspired League of Legends and the entire MOBA genre. DOTA has a reasonably high barrier to entry because the gamers need to develop a base level of game knowledge and skill to start enjoying the game meaningfully. Given that I have already become a reasonably good DOTA player, I don’t want to commit to another game where I need to build up a base level of competence to play that game. Instead, I prefer to enjoy the joys of playing a game that I am already pretty good at. And DOTA, which is now hosted on Steam, continues to release new game content to enrich the game experience which means it is never boring for me. The point here is gamers become loyal to a game when they become highly invested in the game world and the challenge is for game developers to provide new content to continue to enrich the game experience. Again this is only possible in a continuous game world

12. Finally, let’s think about how to value a game developer. There are two components to the value of a game developers 1) the present value of all free cash flow generated by the existing game franchise and 2) the present value of all free cash flow generated by future game franchises. The total profit generated by the existing game franchise requires one to estimate A) longevity of the game, B) revenue per gamer and C) the ongoing operating cost of the game. A game company’s development capabilities determine the probability of producing successful games in the future. It is much harder to assess the value created by futures games but it can have very real value

13. To assess the existing game franchise, one must understand the drivers for gamer loyalty to a specific game (longevity) and the quantum of emotional reward (revenue per gamer) received by the gamers. One can investigate the strength of the game community to get some sense of the social bond between gamers. The social bond formed through the game can be one of the most powerful retention mechanism. Another neat trick to assess gamer loyalty to the game is to investigate the behaviour of returning players. For example, Warhammer 40K has many gamers who played as a teenager but stopped playing as they got older. However, given a chance, many old Warhammer 40k players readily come back into the game. The “relapse rate” for Warhammer is very high. The revenue per gamer should be proportional to the emotional reward per gamer. However, if the game is fun for a sub-group of gamers at the expense of another group of gamers then the game might not be sustainable. Hence the pay-to-win model is inherently quite risky. Sometimes it is clear that the game is under-monetised. For example, Nintendo’s Animal Crossing is a great example. Many gamers are paying hundreds of dollars to acquire certain items from other gamers which Nintendo is not capturing. Finally, for any game franchise to attain super long longevity, the game developers must continuously innovate and create new game experiences in the game world.

14. There are a few exceptional game franchises that have proven their capacity to sustain themselves for a very long time into the future. Pokemon, League of Legends, Magic the Gathering, Legend of Zelda and the sports franchises are such examples. Pokemon is able to build an incredible IP and continue to generate high-quality game content. While Pokemon has sustained its longevity under the GAAP model, its transition to a GAAS model through Pokemon Go is going to make Pokemon a much more valuable franchise!

15. To assess the game development capabilities of a company, one must understand the game company’s culture, its development process and historical success rate. It is hard to define the commercial success of a game on an absolute basis. Typically, the game industry, just like any other creative industry, is defined by huge but few successes. So it is better to define success through return on investment. For the sake of this discussion, I define a 10x return on investment as a successful game. A great game company tend to have a very strong and unique culture. Some game company care more about making really great games than others who are more concerned about short term commercial success. Some great game companies have well-defined game philosophy, for example, Nintendo is a big believer in hardware and software integration as a source of differentiated game experience. One needs to assess if the game development team’s organizational structure makes sense for the games that they are trying to build. From an investor perspective, the most important method is to study the game development track record. CD Projekt Red is developing a very impressive track record and its future game franchise value makes up the majority of its market value. Nintendo maintains a very impressive game development track record over a long period of time though it is not proven in the mobile game space. Blizzard has a great track record but they are struggling in the mobile era. Netease and Tencent both have impeccable game development track records!

16. Scale matters a lot for game developers. Luck plays an important role in the outcome of any one particular game. Assume a good game developer can expect a 5% success rate and each successful game yield 10x return, then the game developer’s expected return is 50%. However, the game developers need many tries before the expected value can be achieved. Hence the two gamers with the same expected return, the larger of the two is much more likely to realise the expected return. But as game companies grow larger, they tend to become more bureaucratic and hinders the creative process and reduce the expected return. So scale matters only to the degree that the expected return doesn’t decline with scale.

17. GAAP vs GAAS involves very different game development process. Chinese game companies are generally leading in this regard. GAAS requires a game development team that continuously create and improve game experience after the game is launched. However, GAAP game development process pretty much ends after the game is launched. This difference to game development approach is, I think, one of the main reason why traditional console game companies, such as Nintendo and Activision, are not able to be very successful in the mobile game era.  Mobile games almost exclusively adopt GAAS model while console games are still very reliant on GAAP revenue model.

As an investor, I prefer game companies with incredibly strong game franchises and a proven game development track record. There are very few game companies that fulfil both criteria. Netease, Tencent and Nintendo are some examples. Please let me know if you know of any! The goal is to buy such game companies at a discount to its existing game franchise value and future game value is margin of safety.

Baoye Group – a mistake & a lesson

I recently sold my ownership in Baoye and ended the 4-year partnership with the business. I registered a 5% loss, but the real economic loss is much higher after accounting for the opportunity cost of having the capital tied up in an unproductive venue.

This experience changed my view on what constitutes a truly conservative investment. I used to consider securities, such as Baoye, trading below its net asset value as a conservative investment. However, for such an investment to be profitable, the discount to intrinsic value needs to narrow over a reasonable time period. Unless there are clear paths such as activist involvement to value realisation, time may not be your friend in these situations. On the other hand, time is the friend of a great business that can grow its intrinsic value. Mr Market may at any point misprice a great business, but the market value will generally grow alongside intrinsic value. Hence a truly conservative investment is a great business selling at cheap to fair valuation. The lesson is not about avoiding average businesses with dirt-cheap valuations; instead, it is about a better calibration of the relative attractiveness of investment opportunities.

Phil Fisher believed that there are only three reasons to sell the ownership of businesses: 1) “a mistake has been made with the original purchase”, 2) the company’s business quality starts to deteriorate with the passage of time, and 3) a more attractive investment opportunity that is more deserving of the capital. In this case, Baoye was sold because of the first reason as I committed a mistake in my original investment analysis. The most unfortunate part is that it took me four years to recognise and correct this mistake. I promise to learn faster next time!

As a reminder, Baoye Group is a Chinese company that is vertically integrated with construction, residential real estate development and building materials. We became a partner in the business because Baoye offered 1) very attractive valuation, 2) good and well-aligned management team, and 3) potential growth prospect from prefabricated buildings. My biggest analytical mistake was with Baoye‘s growth prospects. I believed that prefabricated buildings would drive growth at Baoye’s building material business. While Baoye did build numerous prefabrication factories, they only contributed 2% to operating profit. Most of the business’s profit is still in residential development.

This is evidenced in the capital allocation decision as well. Over the last four years, management allocated capital in the following manner:

  1. ~RMB 5.7bn in land purchases for residential property development
  2. ~RMB 1bn in capex (mostly for building housing industrialisation related factories)
  3. ~RMB 0.2bn in share buybacks

The vast majority of capital was recycled in residential development. On its balance sheet, Baoye has a book value of RMB 8.7bn as of June 2019. It carries a cost value of ~RMB 9bn land and properties for residential development. While the founder of Baoye, Mr Peng, has been talking about the revolution in construction through prefabrication for many years now, he has not allocated capital according to his vision. Without growth from the prefabricated construction business, Baoye is just a regional residential property developer in China with undifferentiated product offering in an increasingly consolidated sector. I do believe that housing industrialisation will one day revolutionise the construction sector, but I am not sure Baoye will be the main beneficiary of it.

I have misjudged the management team’s desire to profit from the cheap market valuation as it is trading at 0.3x P/B with 50% of its market capitalisation in net cash. Given Hong Kong Stock Exchange’s listing rules, the company is only allowed to buy back 1-2% of total share base each year. So, sizable share buyback is impossible. There is a lot of social status attached with owning a listed company in China that I suspect Baoye management enjoys. I believe they are fully capable of taking advantage of the cheap valuation. But they chose not to because they have other capital allocation priorities.

TC comments

I haven’t sold and have learned at least a few things.

As your partner blogger, I reject the “great biz at fair” vs “fair biz at cheap” argument. This seems only correct in hindsight. As you say, the lesson is not to never do fair biz at cheap, it’s the calibration of correctly trading off these two that needs to be good.

I still believe this is a very “fair” (neither great nor bad, but high conviction of being “average”) business at a *very*  cheap valuation (high conviction of cheapness). So in terms of this calibration it seems fine to me. Rather, if this was a stock listed on US (it isn’t & not saying this is somehow “unfair”), this might have worked in the same ’16-’19 time-frame.

Maybe the already large management ownership together with the steady share buyback is working against minority shareholders, as the stock becomes more illiquid and the market starts discounting a future where a squeeze-out becomes a possibility. A calibration takeaway here might be to prefer management owning 20-40% versus more than 50% from the thesis outset.

Another calibration for me is to lighten up on a similar company when management *that already has high ownership percentage* stops the dividend. If I recall correctly, we could have trimmed our positions at roughly the same price when this happened years ago. In hindsight, the reasoning management gave “housing industrialisation capex” was only a half-truth, as the company still has plenty of cash. The company has only done buybacks since.

Another interesting thing is that we learned (or indeed both have the illusion of having learned) different things.

Maybe it is not as important to the thesis, but the following is an insight for which I have the highest conviction that it is actually a correct insight from this situation:

A few years ago, I became a dogmatic believer in tax-efficient buybacks, always preferring buybacks to dividends because of taxes. Indeed, from a theoretical point of view, when keeping future stock “% discount to NAV” valuations *constant* to the current % NAV discount, buybacks are exactly as accretive as dividends (only difference is taxes).

However, as I outlined above, in situations were minorities might get nervous because liquidity decreases disproportionally (buying 1% of outstanding if float is 30% outstanding is 3% of float, vs buying 1% of 99% of outstanding only 1%) and a squeeze out is getting discounted, this is where practice starts disagreeing with my theory. In other words, % discount to NAV does not remain constant (i.e. “value + return of capital in bb/divi is its own catalyst” argument) but widens. I believe the devil’s advocate argument here is to say that 1 pp buybacks of a very small float should also have a very big boosting effect to the share price when they are carried out.

That is a long-winded way of the hindsight gut feeling “bird in the hand is worth two in the bush” that really teached me the virtue of a dividend. Tax efficiency is NOT the only difference with buybacks in practice.

My last take-away is that I am reinforcing my belief that countries with stock markets that are going sideways or down do *not* tend to become more efficient in the cross-section. In other words, in a rising Chinese stock market, this stock might have gotten discovered by more sophisticated international stock pickers. Instead we got increasing international scepticism vs China / HK, even from the “low base” when we invested in 2016.

A thought I wrestle with: is this truly a safe stock because of its large cash position? Or does it tank when the global economy sinks, as geopolitics typically becomes more muddy (or at least the perception) and international investors lose faith in (1) enforcing property rights in the future (2) values denominated in a currency that has capital controls etc. This is what I will call “cyclicality thru geopolitics”. Is Baoye similar to owning a cash-rich “safe” net net in Georgia or Taiwan (with invasion of neighboring country becoming more probable to please populace when the economy sinks)? That would make its fundamental *conditional* beta higher in black swan situations higher than we might think (i.e. low beta until things really go awry). But yes, I am probably overthinking this, and maybe this is already under-owned by the international investor community.

Investment Decision Log – User Manual

I have recently created a spreadsheet to record all of my investment decisions. The goal is to track decision quality and try to learn from mistakes and reinforce things that I am doing well. This is a long term project to improve my decision-making skills.

Decision-making is inherently statistical in nature. Hence the nature of this assessment should be statistical in nature too. With a sufficiently large sample size, the assessment of the decisions should start to become meaningful as the quality of my decisions will converge with share price performance.

I also included ideas that I have done some work on but not acted on….

Each decision will be given a rating based on two dimensions – 1) share price performance since decision; 2) facts that evolved since the decision to measure the soundness of decision logic e.g. I sold DTG because I think the risk of long term price competition is not sufficiently captured in the valuation.

The second dimension is still subject to my own judgement and hence the risk that it is not sufficiently well captured. The good thing is that I still have share price performance as an objective measure to capture things that clearly look out of place. For example, if the share price is down 90% while I claim the original decision is good then I need to have a very convincing explanation backed by strong evidence. I trust that I can be brutally honest to myself.

To assess the second dimension of decision making:

      1. Did what I predict to happen actually materialise?
      2. Based on the outcome of the events, was the original probabilistic assessment correct?
      3. Was luck involved in the magnitude of the outcome? (added to comments)

If the answer to all three is positive, then it is a good decision. If 1 and 2 are conflicting, need to explain why they are conflicting. Will still need to make a collective judgement. Also need to comment on the role of luck. For example, I expect a positive event to yield a 10% increase in share price but it went up 50% because of extraneous factors. Then luck was responsible to push up the magnitude of the return

There are five possible ratings for each decision:

      • G – Good Decision and Good Outcome
      • U – Good Decision and Bad Outcome
      • L – Bad Decision and Good Outcome
      • E – Bad Decision and Bad Outcome
      • X – Unable to evaluate decision quality regardless of the outcome

The goal is to prevent U decisions to discourage me from making the same decision in the future. Nor should I let L decisions to trick me into over-confidence. And allow for reinforcement by G decisions and learn from E decisions. Rating X is given to decisions where there is insufficient facts and time to evaluate the quality of the decision.

The assessment period for each decision depends on the nature of the underlying decision. For example a special situation investment decision depends on the outcome of a specific event. So even if I sold the position before the event crystallises and make profit on it, I must still wait for the outcome of the decision to determine the quality of my decision. On the other extreme, an investment in Games Workshop requires a longer time to evaluate because the fundamental investment thesis is a long term one. For example, Warhammer IP is a very good one requires continuous assessment. Hence each investment decision should be assigned to different assessment periods.

Ways to analyse my own decision:

      • Based on position size – big vs small – am I good at making big position decision vs small position decisions
      • Value of add and reduces
      • Decision by investment categories – General / Compounder / Workouts
      • The magnitude of mistake of omission
      • The decision over the lifetime of each investment
      • The decision that yield the best returns vs worst returns

Shortcomings of this decision log – it doesn’t capture a lot of passively made decisions such as to do nothing to an existing position when stock prices go up. This is something I need to think about how to capture better.

The HLP Lessons

In the past couple of months, I spent a lot of time and effort researching Hang Lung Properties (HLP). It is a Hong-Kong listed commercial property developer and owner. HLP has a portfolio of prime retail properties in HK and mainland China. My initial interest in the company originated from my belief that despite the threat from eCommerce, well-positioned shopping malls in demographically strong areas should continue to do well.

There is a lot to like about the company at first glance. It was trading at close to 4% dividend yield, a strong development pipeline and have at least 2-3% rent growth from its existing shopping mall portfolio. The shopping malls are relatively high-end and located in some of the biggest cities in China. Most importantly, it seems to have a well-aligned management (HLP is family controlled) and a “legendary” capital allocator at its helm. I recommend you read the Hang Lung’s Chairman Letters where the CEO’s impeccable ability to time the real estate cycle and reluctance to overpay are both well documented.

It was almost too good to be true. You have 1) very competent capital allocator, 2) a high-quality retail properties portfolio, 3) a highly visible development pipeline, and 4) a cheap valuation for this business quality. I allowed myself to become very excited about the company as I devoured the Chairman Letter religiously. I am actively looking for evidence to further support my investment thesis. Sure there are a few problems but as a long-term investor, I can look past these “short-term” issues.

However, as I learnt more about these “short-term” issues, inconvenient evidence began to accumulate. The consumption power of Chinese Tier-2 cities does not grow nearly as fast those implied in Hung Lung’s Chairman Letters. The oversupply of retail space in Tier-2 cities would take so many years to digest that the return on incremental retail properties in these Tier-2 cities is just too low for the level of risk involved. However, the company seems focused on its Tier 2 city strategy in China. Not to mention the first mover advantage of the luxury mall in Tier-2 cities is so entrenched that it is a winner-take-most economics. Most luxury brands will not open two stores in a Tier 2 city in China and luxury brands need to co-tenant together. This means that once the first high-quality mall captures most of the large luxury brands in its mall. It is extremely difficult for the second and third mall to compete. You can build mid-end malls but then you would have so many similar malls that the low rent almost guarantees an unsatisfactory return. Chinese Tier-2 cities retail space is over-supplied from high-end to low-end malls.

At this point, I am just confused. Why would such a smart and rationale capital allocator commit to such an obviously sub-par strategy? As I spoke to people who are close to the Chairman, it became clear that this is an individual who has a huge ego. It would be extremely difficult for him to openly admit the mistake and change course. It is unclear to me if he is just too proud to admit the mistake or that admitting the mistake to something that is so central to his personal identity (he sees himself as the smart guy that never overpays) is just too difficult for him.

In any case, I learn quite a few lessons which I can take along with as I continue my adventure in the investing jungle.

  1. Don’t give too much credit to CEO / Chairman just because they can write fantastic annual letters
  2. When the business’s core operation is transformed in volume or in nature (in Hang Lung’s case from property management to property development), one cannot assume that the company will naturally be able to adapt
  3. Even when the manager is heavily invested in the company, the ego can still get in the way such that mistakes are not corrected
  4. Human irrationality is more powerful than you might think
  5. Past track record does not guarantee future success

Of course, I could just be wrong in thinking that building malls in Chinese Tier 2 cities is a sub-par investment strategy. I hope I am wrong.

MC

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