Consider risk and uncertainty in the airline business and ways that firms deal with them. Some, such as Southwest Airlines, have made extensive use of financial instruments to hedge fuel risks, whereas others leave positions open. Delta Airlines recently purchased an oil refinery with hedging as a motivation. The list of shocks that might affect profitability for airlines stretch well beyond fuel prices and include natural disasters, such as the eruption of the Icelandic volcano Eyjafjallajökull in 2010 or apparent pilot suicide as on the German Wings flight that crashed in the Alps in March 2015. Entry by low price competitors on key routes, changes in environmental regulation or airport landing rights are other examples of events that have the possibility to hurt profitability. How should firms manage such risks and uncertainties?
A simple view of the received wisdom on firm strategy in the face of risk is that firms should strive to maximize expected profits. If there are some reasons for firms to limit variability in profits, such as taxes or binding credit constraints, corporations should then use derivatives instruments to hedge against risks. For bankers, this view then provides a clear motivation for promoting the use of derivatives instruments. However, the last few years have provided several challenges to such a view—be it the notion of large unforeseen shocks (“black swans” in the parlance of Nassim Nicholas Taleb) or evidence that derivatives portfolios are often too small to have an important overall impact on firm value, as shown in a seminal article from 2003 by Guay and Kothari entitled “How much do firms hedge with derivatives?”. Furthermore, substantial interest has been triggered by the concepts of operational hedging and real options, and it is often not clear how they fit in with derivatives use.
The present article outlines an approach to synthesize results on different means of managing risk and uncertainty. A book length treatment is found in Friberg: Managing Risk and Uncertainty: A Strategic Approach, published by MIT Press in December 2015. We follow Frank Knight (1921) and define Risk as randomness described by a probability distribution and Uncertainty as randomness that does not follow such a distribution. Uncertainty may thus reflect difficulties of assessing the probability of different events as well as difficulty in describing the possible states of the world (as in Donald Rumsfeld’s memorable phrase “unknown unknowns”). To the orthodox, risk is mainly reserved to situations where we toss coins or draw balls from an urn, but I would also be inclined to use risk to describe movements in the prices of commodities and financial assets. We associate higher risk with more volatile prices of inputs or outputs. We associate more uncertainty with situations where there is strategic interaction, unpredictable regulation or potential for drastic innovations.
We may schematically think of firms operating in markets marked by different levels of risk and uncertainty in the Risk-Uncertainty Matrix (RUM) below.
An example of a situation with low risk and low uncertainty would thus be a service firm with a large number of small customers, stable input prices and little potential for competition or regulatory changes, such as a local ski area with a stable snow cover. A gold mine would be a typical example of a situation characterized by low uncertainty and high risk. A firm competing in a market with rapidly changing technology and strategic alliances would be an example of high uncertainty and low risk. Competition in airline markets finally would be an example of a situation with both high uncertainty (entry/exit of competitors matter much, sensitive to regulatory changes) and of high risk (affected by exchange rates and prices of jet fuel). Clearly the position in the matrix can change with conditions. A mid-1900s telephone operator was the epitome of stability—a far cry from today’s intense competition with ever new ways of transmitting information and a key importance of winning license auctions.
Below we present four strategies to deal with risk and uncertainty, which pull together insights from many different fields of research and cast them into a common setting. We take the fundamental competitive position of the firm as given, and ask: How, if at all, should the strategy be modified to manage risk and uncertainty? We assume that there are two types of shocks, those due to risk and those due to uncertainty. We assume that shocks that are due to risk are hedgeable using derivatives or by insurance contracts. In contrast, shocks due to uncertainty are not hedgeable on financial markets. The lack of probability distribution for uncertain variables makes it hard to think in terms of maximizing expected profits, since forming expectations is the key difficulty. We therefore assume that firms maximize expected profits subject to a constraint that the firm is able to survive also in a worst-case scenario. This worst case represents the worst case that one wants the firm to be able to survive, not the worst imaginable case. The intention is not to design a firm strategy that allows it to survive a giant meteor strike on earth. An airline may, for instance, determine that it wants to be able to survive its fleet being grounded for two weeks—no matter what unforeseen event would bring about such an outcome.
The first strategy follows the strategy that would be optimal if risky variables were close to their expected values and uncertainty shocks don’t present a threat to firm survival. The better the access to capital that the firm has, the greater the shocks the firm can take on the chin. A firm following this strategy would be doing sensitivity tests, but if the firm in the end doesn’t let risk and uncertainty considerations affect fundamental decisions of what it produces and sells, the firm follows the benchmark strategy.
Financial Hedging Strategy
The essence of financial hedging is that it makes the value of the firm less sensitive to changes in risk factors. For an airline, we may think of an idealized situation where by trading in forward contracts on jet fuel the firm is perfectly hedged against the effects of prices of jet fuel on profits. On the other hand, uncertainty still remains and ash clouds, terrorists crashing into the World Trade Center or the appearance of a new competitor are not easily hedged on financial markets. The potential for adverse uncertainty shocks is therefore the same as in the benchmark. We assume that there is a small cost of setting up the ability to engage in financial hedging strategy. If risk factors hover around their expected value, the profits are thus lower under the financial strategy; but if lower tail outcomes triggered by risk factors are a concern, the financial hedging strategy will be preferred.
Note that it may also be useful to distinguish between two reasons for derivatives use. What concerns us in this strategy is to avoid costly lower tail outcomes that have a major impact on firm value, and these are the motivations that have been largely explored in the academic literature. Another motivation for using derivatives is to make it easier to determine the need for liquid funds in a firm in the short to medium run. While the latter explanation has not been the focus of the academic literature, the empirical evidence is largely consistent with this being an important motivation for derivatives use.
Consider now the strategy that we term “flexible”. It is a strategy that explicitly takes account of how risk factors can take on different values and that there will be shocks due to uncertainty. A firm that follows this strategy tailors operations and processes in a way so as to be able to quickly respond and make the best of the conditions—it strives to make profits more responsive to positive shocks and less so to negative shocks; using a technical term, we would say that it strives to make profits into a convex function of the risk factor. This implies that expected profits for a firm increases as conditions become more variable—by adjusting and making the most of favorable conditions, profits increase in good times, and in bad times the flexible firm will cut back and thereby limit the harm. Such flexibility can, for instance, come about via production possibilities (such as being able to rapidly adjust volumes or input sourcing) or via marketing-related strategies (such as an ability to set different prices to different consumer groups). The strategy can be seen as a simple way to capture real options—the essence of which is that they become more valuable as risk increases. The flexibility can also be generated by choosing to organize lines of control in the firm to be more flexible. In keeping with standard assumptions in economics, all good things come at a cost—and we assume that there is a fixed cost of building up the capacity to be flexible. In the airline setting, flexibility can, for instance, be associated with leasing rather than owning planes or having a large share of personnel that are on short-term contracts. Having a diverse fleet of airplanes is another way to gain flexibility, enabling a better fit between local market conditions and the size of planes. Such flexibility would be associated with higher maintenance costs. In the figure below, we illustrate such convexity of profits relative to the benchmark. We consider a case where a “passive” strategy would lead to profits improving one-for-one with the risk factor and where a flexible strategy implies adjustment—the more risk factors deviate from their expected values, the greater the difference.
Operational Hedging Strategy
We finally consider the strategy of “operational hedging”. This refers to ways of adjusting operations or management processes so as to make the profits of the firm less sensitive to changes in risk factors and uncertainty shocks. One example of an operational hedging strategy would be to diversify—for an airline to also own another business that is less sensitive to those risks. An airline that also owned a soft drink business could thus be an example of operational hedging. Buying planes that are more fuel efficient would be another way of engaging in operational hedging—if they are costlier to purchase, they might be less profitable when fuel prices are around average, but they make profits less sensitive to swings in the fuel price. For instance, in their 2014 article “Does Operational and Financial Hedging Reduce Exposure? Evidence from the U.S. Airline Industry”, Stephen Treanor and coauthors examine the sensitivity of the stock market valuation to the price of jet fuel of airlines. They find that both financial hedges and fleet diversity lower the sensitivity; the strongest effect that they find, however, relates to fuel efficiency and hence to operational hedging.
In a very schematic way, one might then suggest that strategies are especially worth pondering for firms in the following way.
Summing up: A long tradition in economics and finance has tried to make progress by in essence treating uncertainty as risk. This article has hoped to show that there is a promise of a way forward in a setting that treats them as different, while still keeping the insights on risk that the literature of the last 50 years has brought us.