I always have had interesting conversations around the assumption and concept of terminal value (TV) in my valuation and financial modelling classes.
The above formula is an extension of the Gordon Growth Model - an economic model developed by Myron Gordon, a professor from the University of Toronto, a key assumption being that a company lasts forever.
Corporate life cycles and the secondary market
The ecosystem of companies and their life-cycles today are very different from 40-50 years ago. Nokia came and went in 7 years. BlackBerry (RIM) lasted for no more than two decades. GE is probably one of the more closely relevant examples of how a company lifecycle could run its course for a relatively longer time before being dismantled into three separate segments in 2021. But I think most companies today don't enjoy that kind of legacy.
Many corporate decisions are made using five and ten year plans. While founders may even have a longer term view of how they envision the business to be, these are mostly aspirational, some might even say fluffy. To make a call on a business over a 20-year horizon is almost unfathomable. Most human minds can't handle outcomes beyond a few decades, and as a result, economists try and simplify this scientifically, and in the process, disregard the cyclical nature of businesses - which is a practical consideration for most investors with a finite professional life. After all, the terminal value is only as tangible as the ability to monetise the underlying asset at the right time.
The perpetual growth model also ignores the effects from secondary markets - investors and individuals that are prone to speculating on a company's value, taking positions both on the stock and derivative instruments such as CFDs and options.
This opens up an alternative scenario: Instead of holding on to a share to perpetuity, there is a choice to flip their position for a quick profit, as long as the equity story continues to hold up. This makes both the use of market multiples and communicating the right narrative even more relevant.
The 2% perpetual growth rate
Besides, as we all know, casting the remaining cashflows into terminal value after the forecast period usually implies that you are basing 60-80% of the total firm value on the discount rate and the perpetual growth rate, which to me seems very paradoxical given that we spend a significant amount of time working out the company's revenue and free cash flows, only to chuck it into a mathematical black box.
Interestingly, the so-called 2% rate widely used in our perpetual growth models originated from New Zealand in 1989 when the reserve bank codified its monetary policy.
According to the then central bank chief, he said that this was “a chance remark" and that the figure was "plucked out of the air to influence the public’s expectations”. The US would later on reference and incorporate this into their policy goals to balance economic growth, wages and unemployment among other things. If you try and communicate this with someone sitting in China or parts of emerging Asia, no one would have a clue what you were talking about. Most people in Asia simply don't care about what long-term growth rate you use for arriving at the terminal value.
Don't get so caught up in economic and finance theories
We used get into hours of academic discussions over the WACC and terminal value during my earlier days in banking. Some of it was deemed as a test of your corporate finance knowledge. Other times it was because a valuation report required the loose ends to be tied in order to arrive at a fair value, or that we needed to demonstrate some form of credibility in the delivery of our report.
The reality is: In the M&A world, there is no such thing as a fair value. No correct answer for the WACC. There are only astute decision makers and those who are afraid to get caught on the wrong side of the outcome. Calculating the cost of capital or terminal growth rate with precision is only crucial either from a financial reporting point of view or only if you expect someone important to be challenging these assumptions specifically.
"What is then the right discount rate to use?" Perhaps the more appropriate question is: What kind of returns are you expecting? If you are evaluating a start-up, this could be anywhere north of 35%. For private equity firms, the rates could range between 15-25%. Institutional investors of public equities could expect 9-15% with zero tolerance for failure.
Simply put: The discount rate is mostly investor-driven - which if you think about it, very similar to the CAPM (Capital Asset Pricing Model), only that the CAPM assumes the investors to be fully diversified. Investors who use their own yardstick for the discount rate and can't get to the valuation they want, generally try to manipulate the cash flows or find ways to "create value" in order to establish a case for the investment.
Don't get so caught up with economic and valuation theories. They are only as important as much as you can use them in the real world. As the dynamics of the real world change, so must our understanding and application of finance.
Whenever I approached the close of my financial modelling course, I always did a simple roll-call to call for feedback from everyone in the class. This time, instead of recycling this common practice, I decided to try out a different approach by using Mentimeter and getting everyone to input three keywords on how they felt about the last two days, and this was the result:
A million followers can't be wrong.
One of the key aspects of financial modelling is being able to accurately project cash flows. This has consistently been a perennial question that comes up - "how do we do it?", "How do we know that the numbers are reliable?", and of course the occasional remark from the seasoned industry veteran: "the assumptions are too conservative, I think it should be much higher!"
Subject matter experts and experienced professionals who have been in the game for a long time play an influential role in terms of how we rely on an estimation of the future. In today's context - given the speed and digital pervasiveness of information - the loudest person in the room can also sometimes be easily misconstrued an industry thought leader.
“Facts can be so misleading, but rumors, true or false, are often revealing."
Before we had the TV, email and newspaper, people relied on word-of-mouth as their primary source of information. Casual banter amongst households within proximity was how we passed the word around.
There was usually nothing lost in translation and no one usually questioned its legitimacy. That playground of information is so different today. Part of how we receive information today has evolved to include social media channels, such as Twitter and LinkedIn. We no longer need to hear information directly from the proverbial horse’s mouth. It is incredibly easy to be swayed by the opinions of the majority, albeit online or offline. After all a thought leader with a million followers can't be wrong right?
“Be wary of self-proclaimed and crowd-proclaimed experts. It’s less likely that experts will be mimetically chosen in the hard sciences (physics, math, chemistry) because people have to show their work. But it’s easy for someone to become an overnight expert on “productivity” merely because they got published in the right place. Scientism fools people because it is a mimetic game dressed up as science."
"The key is carefully curating our sources of knowledge so that we are able to get down to what is true regardless of how many other people want to believe it. And that means doing the work.”
Projecting cash flows is a work of art.
You would be almost be certainly wrong if you think that the ability to project cash flows requires hard core quantitative and technical skills. Valuation and financial modelling is really part art part science. In fact I would even go further to say that a large part of it is art, since the desired outcome is almost always based on creatively imagining what the future beholds.
The narrative, so to speak, is as important as the numbers. As Yuval Harari puts it in his book:
"A person who wishes to influence the decisions of governments, organizations, and companies must learn to speak in numbers. Experts do their best to translate every idea into numbers."
And so, the process of constructing a financial model tries to achieve this.
I often get asked if I could provide excel templates for a variety of sectors that people could use to just work off, punching in the inputs to generate the valuation output. Unfortunately, I don’t think it works that way.
The real value in any financial modelling exercise is not the result it produces, but the mental exercise that you have to go through in order to produce a functional three-statement spreadsheet of intricately connected moving parts.
This is probably the same parallel why people run marathons - not to get from point A to point B but more so the journey, the process of having gone through first hand and pain of completing 42.195km and that personal feeling of having achieved something at the finish line. That sensation means something different to everyone.
The financial model is a representation of what you think of the business and possibly how you see it evolving over time. In the hands of another person, the model assumptions and outputs might look very different.
As Warren Buffet once famously said:
"The forecasts may tell you a great deal about the forecaster but they tell you nothing about the future."
Whatever someone wants has value.
Going back to the narrative, the valuation exercise is always all about that magic number and the story behind that number.
It is easy to play around with numbers, crunch the numbers and as a lot of bankers say - massage the numbers. Numbers are freely available nowadays with the Internet and relatively cheap access to that information.
Stories on the other hand are a reflection of the CEO’s ambition and the company’s vision of the future. In the modern and evolving digital world, social media has increasingly found its role as a facilitator of information (both true and fake), and does an incredibly good job of amplifying stories.
Just look at GME.
The boring brick and mortar retailer was reportedly shuttering stores in 2019 and went into a semi-crisis when revenues plunged in 2020. Yet, its share price defied everything the numbers were saying, becoming a cultural sensation on social media.
If you looked at Lehman Brothers' balance sheet back in 2008 they actually had "one of the strongest capital and liquidity positions the Firm has ever had". But the story unfortunately went sideways, souring sentiments very quickly, resulting in its shocking collapse, disregarding whatever the fundamentals and numbers were showing.
Cryptocurrencies and NFTs are also classic examples of how story-telling has manifested in valuation.
There is almost no means of proving why a digital image of a monkey could be worth thousands of dollars. There is also no real use for a digital monkey, and therefore, no way of doing a meaningful DCF valuation.
NFTs are simply worth what they are because people say so and because people want it.
You can’t model sentiment and emotion in a spreadsheet. You also can't do an analysis of the cost-benefits on waging war for national security. Neither can you put a price tag on human relationships. The numbers simply won’t stack up.
"The concept of economic value is easy: whatever someone wants has value, regardless of the reason (if any), and its value is higher the more it is wanted and the less there is of it."
Storytelling for what it is, is a persuasion exercise to galvanise interest and to sell something - an idea, a product, a call to action. But it remains effective only to the extent others believe and identify with it. Any story becomes instantly more believable if there is sufficient information and that the anecdotal evidence provided is relatable by the other party - which explains also why investor targeting strategies are different for retail punters and large institutional buyers.
Without connecting the numbers to a story, projecting cash flows simply becomes an emotionless exercise of numbers.
So, none of this makes sense anymore.
For a long time, offshore financing - which was predominantly priced off the LIBOR or overnight rates - had always been significantly lower than the benchmark rates in China. For years, raising offshore money at a lower cost had always been the de facto fundraise strategy. Today, it is obvious that the tables had turned, quite abruptly as well. After you account for taxes, hedging costs (which is somewhat upside down now) and geopolitical risk, raising offshore money in China doesn’t seem to make much sense at all, not at least in the near term.
While the rest of the world is hiking interest rates, China is going in the opposite direction, encouraging credit activity to boost growth and revive the economy. Earlier on, a consultation paper was also released, outlining guidelines towards formalising and further regulating the approval of offshore debt, on the pretext of promoting the healthy and orderly development of overseas financing by enterprises. Putting aside its over-leveraged property market and inflation in the rest of the world, it is almost as if the policy is indirectly encouraging Chinese companies to source for capital domestically rather than look elsewhere for financing.
The combination of all of the above, coupled with no end in sight of travel opening up, seems to hint that China is closing up from the rest of the world.
With the largest manufacturing engine closed from the world and the severe shortage of oil due to the war, you can hike all the rates you want but I don’t think that is going to meaningfully bring prices down.