Chart Fun | A Tale Of Two Companies
“Prediction is very difficult, especially about the future.”
— Niels Bohr.
Most of us are well aware of the Fukushima Nuclear Power Plant disaster. In 2011, an earthquake off the coast of Japan triggered a 14 meter high tsunami wave; which scaled the plant’s seawall and flooded the lower grounds. Coolant losses then precipitated three nuclear meltdowns.
What is not so widely known is the story of the Onagawa Nuclear Power Plant. This plant —closer to the earthquake’s epicenter than Fukushima—had a very different fate. Despite experiencing very high levels of ground shaking, all reactors of the Onagawa Plant successfully withstood the earthquake and the tsunami.
One plant suffered fatal meltdowns. The other emerged unscathed.
One of the primary reasons behind the different outcomes was elevation. The Onagawa plant was built at a higher elevation than the Fukushima plant.
Now consider this. The Fukushima plant was commissioned in 1971. Onagawa plant in 1984. 40 years passed before an extreme event befell Fukushima.
Would it be right to say that the Fukushima plant was inadequately designed? Or, was it a victim of a freak 1-in-40-year event?
The tale points to a more general vexing question we face frequently.
By When?
What if the event we expect never transpires? Or occurs too infrequently?
If we prepare for an extreme event and it doesn’t occur, we would have wasted scarce capital.
Not only do we face the difficult prospect of predicting events, we face the added constraint of predicting their timing.
Financial systems are similar in design. There are potential disasters/winners always lurking around the financial landscape.
Which ones are likely to escalate into a full blown disaster/winner? How likely?
More importantly: By When?
Difficult questions to answer.
A Tale Of Two Companies — I
Here are actual cash flow profiles of two companies.
The cash flow profiles are snapshots from different points in time. Company A is in the Hotels business. Company B is in the Realty business.
In the 5 years leading up to the respective snapshot dates, Company A and B grew revenues at 18% and 9% annually, respectively.
Not only has Company A grown faster, it has generated cash. Company B, on the other hand, has been ‘asset light’. But has required repeated rounds of financing to fill the void left by operating cash flow.
Prediction time.
Which one is more likely to default?
Most would guess Company B.
The business seems to be in worse shape; guzzling capital, requiring journeys to the capital markets for financing.
It was Company A that went on to default within the next few years. The stock was well invested before the bankruptcy.
You have to opine on two questions:
1. Will Company B default?
2. By When?
Company B is a widely regarded, popular name. Would your opinion change if you learnt the name?
During that era, the prevailing market wisdom was to own asset heavy companies (Company A). The prevailing market wisdom today is to own asset light companies (Company B).
Will this change?
By When?
A Tale Of Two Companies — II
Snapshot of two similar sized companies on revenue, but with different operating health profiles. Company A is a cash machine, has better business economics, superior management profile; and yet, is valued at a fraction of Company B.
The markets have been perceiving automobile industry-related companies negatively in recent times.
You have to opine on two questions:
1. If you had to go long on one company, which candidate would you consider?
2. By When, would you expect a correction in mispricing?
A Tale Of Few Countries — Financials Edition
Indian financials are among the most well-owned sectors within the equity landscape. Financials form a lion’s share of the front line indices (35%; similar to China). Financials enjoy a horde of natural buyers — non-economic participants — setting prices.
A look at a select set of US, China and Indian banks.
An overwhelming majority of Indian banks’ source of capital is public deposits. This means that cuts to the base rate by the RBI do not transmit quickly through the system. An average Indian bank’s cost of funds tends to be sticky, as deposits reprice slowly due to depositor behavior. India now wants her banks to link loan rates to base rates. In a soft interest rate regime; falling yields, sticky cost of funds, and bad NPL situation doesn’t sound like an inviting concoction.
Compared to US and Chinese banks, Indian banks employ more leverage, on average (lower Networth/Assets ratio). The higher leverage would be manageable if it was accompanied by vigilant risk management. However, the non-performing loan (NPL) situation paint a different story.
Not only do Indian banks have higher leverage; they also have higher NPL ratios compared to US and Chinese banks (those pointing to under-reporting of NPL by Chinese banks ought to entertain a similar possibility among Indian financials too!). Those least equipped to handle leverage use the most of it.
US banks have the best overall health. Yet, are valued lower than Indian private banks. Chinese banks enjoy relatively better health profile as well. Yet, they are priced on par with far inferior Indian public sector banks.
Is Indian banks’ premium attributable to superior prospects/corporate governance (the numbers/reality indicate otherwise)?
Or, to non-economic participants providing a stream of natural buyers, who own banks at any price?
You have to opine on two questions:
1. Will this situation change? Why?
2. By When?
Predicting potential bankruptcy situations, mispricing situations, or longer-term structural changes in market perception; all share common characteristics.
They all involve predicting:
1. The Event.
2. The Timing.
The shifting sands of prevalent wisdom become a critical characteristic that an investor needs to watch for. Position too soon and run the risk of being fatigued out of the position. Position too late and miss the bus.
I generally prefer to be a little early than late.
However, the mechanics of the shift (when/how will the herd turn?) remain a key factor. Every now and then, through sheer luck, one gets the timing right. That, however, remains the exception to the general rule.
