Asia review: cycles, and cycles

Metacognition: is cognition about cognition, thinking about thinking, knowing about knowing, becoming aware of your awareness and higher order thinking skills.

Not a week goes by without a constant reminder of advancements in artificial intelligence (AI), robotics, smart machines and automation. I find this pace of change dizzying. It creates a sense of wonder that can morph into a feeling of enveloping dread. According to some futurists, almost every industry is likely to be transformed by big data analytics combined with AI and automation. That topic is too weighty for me at this point in time; hence I will leave it for another missive to delve on the implications as we understand it for businesses in Asia.

Enough, for the moment at least, of robots. I want to look back briefly at the fund‘s performance in 2016. I underperformed the benchmark in what certainly was a difficult year on many fronts. That’s not an excuse; it is just stating the obvious. China felt the brunt of a slowdown early in 2016 and fears of capital outflows spooked markets. I bought some cyclicals as the China-related sell-down presented opportunities. Brexit, ironically, led to a surge in liquidity towards risk assets, and I managed to stay ahead of the benchmark until late October. But the US presidential election result and India’s demonetisation exercise (‘a bazooka to kill a fly’, as I referred to it at the time) hit the fund hard in November and December, and I gave back all of the outperformance and more. That was bruising, but I took it on the chin. 

Desperately seeking sustainability 

The portfolio consists of two distinct silos. The core, usually around 75-80% of the portfolio, comprises long-term sustainable businesses. I look for certain financial characteristics in those businesses, but it’s the long-term sustainability – the inherent resilience of the business during tough times, or the ability of management to deal with adverse conditions to ensure long-term success – that matters most to us. The rest of the portfolio, usually no more than 25% of the fund, resides in cyclicals, a contrarian approach to risk perceptions in the market. In this case, I like to own stocks (not businesses) that are cheap and expect to see a return to mean valuations as risk perceptions subside. 

Over time, this approach typically results in a better downside/upside capture, lower portfolio turnover, lower volatility and a lower beta for the fund. I do, of course, need to mention the usual caveat about past performance being no guide to future returns.

That sounds good, but there are two distinct scenarios when you should expect this strategy to underperform. The first is when we experience a negative macroeconomic or policy shock. In such cases, it is almost impossible for the fund to avoid being hurt. Partly this is a result of a high active share, benchmark-agnostic approach, which means the portfolio’s currency exposures are very different from the benchmark. I do not hedge currencies.

For a historical example, you could look back to August 2013, when the ‘tapering’ comment by then Federal Reserve Chairman Mr Bernanke led to a sell-off in several Asian markets (the so-called Taper Tantrum). The fund did not escape the sell-off, and I would characterise November-December 2016 as being in a similar vein. For the record, every such shake-up prompts me to revisit all my core as well as cyclical holdings to assess if any were affected adversely. I find it’s good practice.

The second scenario where my strategy could underperform is when we have a very strong cyclical rally. As noted above, the percentage of cyclicals in the fund is low relative to benchmark. During those rallies, share prices of well-managed businesses will typically lag the market. 

Giant slayed

As I mentioned, any big sell-down in markets necessitates a portfolio revisit. This time around I found myself dealing with three distinct situations. Firstly, India’s surprise demonetisation exercise led Cho-Yu and I to make two separate trips to the country in November 2016 and March 2017, and I’ve written about my impressions from those trips. I did trim some Indian holdings to right-size them but decided not make any drastic changes. My core holdings have remained resilient, some dealing with that episode better than others. In my opinion, the long-term future does not look compromised for any of our Indian holdings. 

The second situation arose from the sharp rise in interest rates as the ‘Trump reflation’ mantra gathered pace. Two of my holdings are low growth but very cheap, cash-generating businesses. They sold off as the markets rightly treated them as bond proxies. One of them is starting to recover its valuation as the initial euphoria of reflation has moderated a bit. The other faces some business challenges, and I am in the process of determining whether this means it’s stayed in the portfolio longer that it should have. 

Finally, there were two stock mistakes which I had to recognise and have exited in the past couple of months. Giant Manufacturing (GM), one of my Taiwanese holdings, was one such mistake. Giant makes bicycles sold under its own brand around the world. Apart from meeting the criteria that we look for, the attraction of the business was twofold. No young entrepreneur today wants to start a business to manufacture bicycles. Most are interested in ‘changing the world’, which effectively means building a new app. I thought this angle to be a good one, meaning a likelihood of fewer threats due to few competitors. Apart from that, a growing interest in health and fitness was driving up bicycle sales across the world. As the sport and habit grew, the average selling price of bikes rose. But, in 2016, two things went very wrong for GM.

The first was a squeeze on margins. After the euro depreciated close to 25% over 2015-16, Giant was unable to raise average selling prices yet faced a rising commodity price environment. Not good, but the bigger impact upon the company’s fortunes sprang from a disruption that I did not think would hit the bicycle industry.

When I mentioned that young entrepreneurs today would rather build apps than bikes, I should have had the intelligence to put the two together. In China, at the last count at least, there were 19 privately-funded, unlisted app-based firms that facilitate bicycle-sharing for hire. Two of those are very large in scale and by far the market leaders. Somewhat similar to Uber, their apps allow you to hire a bicycle. It’s a GPS-enabled locator app that allows you to unlock the bike through a code generated by the app. Unlike ‘Boris bikes’ in London and similar schemes in the West, you can leave the bike anywhere you like – and people do (see this report from UK newspaper The Guardian). The cost of hire is US$0.15 to $0.40 per hour, depending on city and bike type. The largest firm recently raised US$450m and was valued at a staggering US$2bn. Just like Uber, they are all bleeding money but the concept is so appealing – ‘change the world and make a difference’. The big negative effect on GM has come from the simple fact that if bikes are so ubiquitous at such a cheap price, why would anyone want to own a bicycle? A technological disruption brought about by cheap money has forced me to acknowledge that my investment in GM turned out to be a mistake. 

This manic approach to private investments in China is taking on bubble-like characteristics on a grand scale. As several China-based PE/venture capital investors were quoted recently: “Raising money is so easy, it’s finding investments that is a struggle”.

I do realise that AI, robotics and smart machines are likely to take over the world. But some argue that humans still have instinct, gut, consciousness and some intelligence. When it comes to investing in start-ups, particularly in China, I do seriously wonder. Am I the only one that feels this is not going to end well? Or do some of us need a serious introspection in metacognition?

 

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