Data Update 4 for 2022: Risk = Danger + Opportunity!

 

 

 In the first few weeks of 2022, we have
had repeated reminders from the market that risk never goes away for
good, even in the most buoyant markets, and that when it returns,
investors still seem to be surprised that it is there. Investors all
talk about risk, but there seems to be little consensus on what it is,
how it should be measured, and how it plays out in the short and long
term. In this post, I will start with a working definition of riskt that
we can get some degree of agreement about, and then look at multiple
measures of risk, both at the company and country level. In closing, I
will talk about some of the more dangerous delusions that undercut good
risk taking.

What is risk?

In
the four decades that I have been teaching finance, I have always
started my discussion of risk with a Chinese symbols for crisis, as a
combination of danger plus opportunity:

Over
the decades, though, I have been corrected dozens of times on how the
symbols should be written, with each correction being challenged by a
new reader. That said, thinking about risk as a combination of danger
and opportunity is both healthy and all encompassing. It also brings
home some self-evident truths about risk that we all tend to forget:

1. Opportunity, without danger, is a delusion:
   If you seek out high returns (great opportunities), you have to be
   willing to live with risk (great danger). In fact, almost every
   investment scam in history, from the South Sea Bubble to Bernie Madoff,
   has offered investors the alluring combination of great opportunities
   with no or low danger, and induced by sweet talk, but made blind by
   greed, thousands have fallen prey. 
2. Danger, without opportunity, is foolhardy:
   In investing, taking on risk without an expectation of a reward is a
   road to ruin. If you are investing in a risky project or investment,
   your expected return should be higher to reflect that risk, even though
   fate may deliver actual returns that are worse than expected. Note that
   this common-sense statement leaves lots of details untouched, including
   how you measure risk and how you convert that risk measure into a higher
   “expected” or “required” return.
3. It is uncertainty about outcomes, not expected outcomes, that comprise risk:
   In investing, we often make the mistake of assuming that risk comes
   from expected bad outcomes, when it is uncertainty about this
   expectation that drives risk.  Let me use two illustrations to bring
   this home. In my last point on inflation, I noted that a currency with
   higher inflation can be expected to depreciate over time against a
   currency with lower inflation. That expected devaluation in the
   high-inflation currency is not risk, though, since it can and should be
   incorporated into your forecasts. It is uncertainty about whether and
   how much that devaluation will be, arising from shifting inflation
   expectations or market-induced noise, that is risk. In posts spread over
   many years, including this one,
   I have also argued against the notion that badly-managed firms are
   riskier than well-managed ones, and the reason is simple. If a firm is
   badly managed, and you expect it to remain badly managed, you can and
   should build in that expectation into your forecasts of that company’s
   earnings and value. Thus, a badly managed firm, where you expect that to
   be the status quo, will be less risky than a well managed firm, where
   there is much more uncertainty about management turnover and quality in
   the future.
4. Risk is in the future, not the past:
   Risk is always about the future, since the past has already revealed
   its secrets. That said, many of our perspectives about, and measures of,
   risk come from looking backwards, using the variability and outcomes of
   past data as an indicator of risk in the future. That may be
   unavoidable, but we have to be clear that this practice is built on the
   presumption that there have been no structural changes in the process
   being examined, and even if true, that the estimates that come from the
   past are noisy predictors of the future. 
5. Upside versus Downside Risk:
   If risk comes from actual outcomes being different from expectations,
   it is worth noting that those outcomes can come in better than expected
   (upside) or worse than expected. Since the entire basis of investing in
   risky assets is to benefit from the upside, it is downside risk that
   worries us, and in keeping with this perspective, there have to been
   attempts to derive risk measures that focus only on or more on downside
   risk. Thus, rather than use the variance in earnings or stock prices as a
   measure of risk, you compute the semi-variance, drawing on those
   periods where earnings and returns are less than expected. I think a
   more sensible path is to measure all risk, upside and downside, and
   think of good investing as a process of finding investments that have
   more upside risk than downside risk.

Risk and Hurdle Rates

    In
investing and corporate finance, we have no choice but to come up with
measures of risk, flawed though they might be, that can be converted
into numbers that drive decisions. In corporate finance, this takes the
form of a hurdle rate, a minimum acceptable return on an investment, for it to be funded. In investing, it becomes a required return
that you need to make an investment; you buy investments if you believe
that you can make returns greater than their expected return and you
sell investments if not. In this section, I will begin with a breakdown
of risk’s many components and use that structure to develop a framework
for assessing the risk-adjusted required return on an investment.

The Components of Risk

Note
that you are more exposed to more risks, when you are looking at young
companies, with growth potential, than when analyzing older, more mature
firms, and that a greater proportion of risks at young companies are
likely to be economic, micro and discrete risks. It is no wonder that
investors and analysts who collect more and build bigger models, to
value young companies, expecting that they will get better valuations,
find frustrations instead. To get from
these general risk categories into explicit risk measures and required
returns, I adopt a simple structure (perhaps even simplistic), where I
accept that I am a price taker when it comes to some risks (interest
rates and risk premiums) and focus on the components of risk that
companies can change through their choices on business, geography and
debt load:

Note
that in this structure, which yields costs of equity for companies and
required returns for equity investors, each component is designed to
carry a single burden, with the risk free rate reflecting the currency
that you analyzing the company in, the measure of relative risk
capturing the risk of the company’s business mix and debt load, and the
equity risk premium incorporating the risk of the geographies of its
operations.

1. Relative Risk Measures

    Before
we embark on how to measure relative risk, where there can be
substantial disagreement, let me start with a statement on which there
should be agreement. Not all stocks are equally risky, and some
stocks are more risky than others, and the objective of a relative risk
measure is to capture that relative risk. The disagreements rise in
how to measure this relative risk, and risk and return models in finance
have tried, with varying degrees of success, to come up with this
measure. At the risk of provoking the ire of those who dislike portfolio
theory, the most widely model for risk, in practice, is the capital
asset pricing model, and beta is the relative risk measure. Embedded in
its usage is the assumption that the marginal investors in a stock,
i.e., those large investors who set prices with their trading, are
diversified, and that you can estimate the “non-diversifiable” risk in a
stock, by regressing returns on a stock against a market index. I believe that a company’s regression beta is an extremely
noisy measure of its risk, and mistrust the betas reported on
estimation services for that reason. I also believe that it is healthier
to estimate the beta for a company by looking at the average of the
regression betas of the companies in the sector that it operates in, and
adjusting for the financial leverage choices of the company, since
increasing dependence on debt also increases the relative risk of the
company. As in prior years, I report industry-average betas, cleaned up
for debt, at this link,
for US companies, and you can sector-average beta for regional and
global companies as well. At the start of 2022, the ten sectors (US)
with the highest and lowest relative risk (unlettered betas),  are shown
below.

Download sector average betas (US, Global)

2. Geographical Risk

Beta
measure the macro risk exposure of the businesses that a company
operates in, but they are blunt instruments, incapable of capturing
either country risk (from operating in the riskiest parts of the world)
or discrete risk (from default, nationalization or other events that
truncate a company’s life). For measuring country risk, I fall back on
an approach that I have used for the last three decades to estimate
equity risk premiums for countries, where I start with the equity risk
premium for the US and then augment that number with a country risk
premium, estimated from the default spread for the country:

The
equity risk premium for the US is the implied equity risk premium of
4.24%, the process of estimating which I described in an earlier data update post this
year. The sovereign ratings for countries are obtained from Moody’s and
S&P, and the default spread for each ratings class comes from my
estimates for the start of 2022. To illustrate, at the start of 2022,
India was rated Baa3 by Moody’s and the default spread (my estimate) for
this rating was 1.87%. I scale that default spread up to reflect the
higher volatility in stocks, relative to bonds, and I use 1.16,
estimated from as the ratio of historical volatilities in S&P’s
emerging market stock to the volatility in an emerging bond indices.
This approach yields a country risk premium of 2.18% for India, and an
equity risk premium of 6.42%, to start 2022:

India’s ERP at the start of 2022 = Mature Market ERP + Default Spread for India * Rel Vol of Equity
                                                  = 4.24% + 1.87% (1.16) = 6.42%

Using this approach to the rest of the world, here is what I get at the start of 2022:

Download country equity risk premiums

3. Debt, Default Risk and Hurdle Rates

    Almost
all of the discussion so far has been about equity funding and its
costs, but companies do raise funds from debt. While I will use a future
post to talk about how debt levels changed in 2022, across the world, I
want to talk about the cost of debt in this one. Specifically, the cost
of debt for a company is the rate at which it can borrow money, long
term, and today, and not the cost of the debt that is already on its
books. The build up to a cost of debt is simple:

A
company’s default spread reflects concerns that lenders have about its
capacity to meet its contractual commitments, and it clearly will be a
function not only of the level and stability of its earnings, but even
of the country in which it is incorporated.

    As
companies raise money from both debt and equity, they face an overall
cost of funding, which will reflect how much of each component they use,
and the resulting number is the cost of capital. The picture below
illustrates the linkages between the costs of equity and debt, and how
as you borrow more, the effects on cost of capital are unpredictable,
pushing it down initially as you replace more expensive equity with
cheaper debt, but then pushing it up as the negative effects of debt
offset its benefits:

At
the start of 2022, the median global company has a cost of capital of
6.33%, in US$ terms, and the median US company has a cost of capital of
5.77%. (To convert these values into other currencies, use the approach
that I used in the last post, of adding differential inflation to the
number).

Hurdle Rate Delusions

The
two biggest forces that drive corporate financial and investor decision
making are me-too-ism and inertia. The former (me-too-ism) leads
companies to do what others in their peer group are doing, borrowing
when they are, paying dividends because they do and even embarking on
acquisitions to be part of the crowd. The latter (inertia) results in
firms staying with policies and practices that worked for them in the
past, on the presumption that they will continue to work in the future.
Not surprisingly, both these forces play a role in how companies and
investors set hurdle rates. Both individual investors and companies seem
to operate under the delusion that hurdle rates should reflect what they want to make on investments, rather than what they need to make.
The difference is illustrated every time an equity investor, in this
market, posits that he or she will not buy shares in a company, unless
he or she can make at least double digit returns, or a company, again in
this market, contends that it uses a hurdle rate of 12% or 15%, in
deciding whether to take projects. Individual investors who demand
unrealistically high returns in a market that is priced to deliver 6-7%
returns on stocks will end up holding cash, and many of them have been
doing so for the bulk of the last decade. Companies that institute
hurdle rates that are too high will be unable to find investments that
can deliver higher returns, and will lose out to competitors who have
more realistic hurdle rates. In short, companies and investors,
demanding double digit returns, have to decide whether they want to
remain delusional and be shut out of markets, or recalibrate their
expectations to reflect the world we live in.