A power producer is supposed to have a natural long position in power, meaning that when electricity prices rise they make a profit, but when prices decrease they face a loss.  Standard hedging practices for this situation can include using short positions, both linear (going short in power futures), or nonlinear, (buying power put options). In both cases, when electricity prices decrease, thay will have a profit in their short position that will offset their losses from selling the electricity at a cheaper price.  Analogously, when prices rise, they should have an extra profit on their operations that will be offset by their losses in the derivatives markets.

This is not working at the moment, even if the companies are selling their electricity at record-high prices, they are struggling to meet the cash required by the collateral required by the derivative markets clearing houses.  The problem is that the reason for the high electricity prices are exceptionally high gas prices, (gas is the main supply for electricity production).  This means that even if electricity prices are very high, the producers are not making additional profits since their margin is squeezed by high gas costs.  On top of this, thay are required to send liquidity to integrate the collaterals for their short positions in the market. Not a very appealing situation.

So, what went wrong? Does this mean that we do need to hedge open exposures? 

What we can learn from this case, is that we need to put more effort in understanding the exposure.  We assumed producers were long electricity, but for that to be true, at least for our purposes, they should be making extra profits with high prices and lower profits with lower prices.  And this is not the case these days.  High gas prices push electricity prices up, but margins and profits stay at the same levels.  In this situation high electricity prices, derived from increasing gas prices, do not mean extra profit for power producers.  The exposure has been poorly defined.  In some sense, higher or lower electricity prices, driven by variations in gas prices, should not significantly affect the profit of energy companies. In reality, electricity producers face a short exposure to gas prices, but they are translating this exposure to their final clients by increasing prices, this means that they are already operationally hedging that position.  In the end, the exposure was poorly defined, and this is why the hedge is not working.

The Facts

On Oct. 29,2018, Lion Air Flight 610 took off from Jakarta, Indonesia, and crashed into the ocean a few minutes later killing all 189 people on board.  The plane was a brand-new Boeing 737 Max, the weather was good, and -at the moment- nobody understood what had caused the plane to nosedive into the ocean.  In the next few hours pilot Bhavye Suneja, the Indonesian authorities, and the airline, were suspected of wrongdoing, but nothing had been concluded at the time.

When the black box was recovered, investigators noticed that the flight pattern of the plane had been erratic and that after takeoff there was a failure of the left-hand angle of attack indicator, a sensor located at the side of the plane cockpit that measures the angle of the nose during the flight.

Andy Pasztor, a Wall Street Journal journalist, started investigating the case.  Dennis Muilenburg, Chairman at Boeing, declined to comment on the investigation, but Boeing said that an American pilot would have never got into this kind of situation, and blamed the Indonesian crew for not doing everything they were supposed to do during the emergency.

On Nov. 11, twelve days after the accident, Boeing said it was a MCAS failure.  Nobody knew what that meant. After some research, it was only found in the abbreviation section of the plane manual.  MCAS stands for “Maneuvering Characteristics Augmentation System » and its a software code designed to pull the plane’s nose down when the angle of attack sensor detects that the plane is going up at an angle too steep that might cause it to stall.  Unfortunately, pilots did not know MCAS existed on the plane,  so a failure in the angle of attack sensor activated the MCAS and sent the aircraft’s nose down… into the ocean.

A senior executive at Boeing said that they had never informed nor trained the pilots on MCAS because they did not want to overwhelm them with lots of information.

On Nov. 27, 2018, Boeing Executives (with their lobbyists) visited the Allied Pilots Association, the Pilot’s Union, to discuss the matter.  They said that they will fix the software and that it will take about six weeks.  The pilots asked to ground the planes until then, but Boeing refused saying that there was no conclusive evidence that the accident was caused by this problem.

Boeing’s chairman went on National TV and, when questioned regarding the actions taken after the accident, said that the company pointed the pilots to existing procedures regarding how to handle this kind of problems, and repeated that the 737 Max was a safe plane.  Additionally, Boeing announced an increased stock buyback to $20Bn and an increase in dividends by 20%, reaffirming its bullish outlook to the capital markets.

Nineteen weeks after the first crash, on Mar. 10, 2019, the Ethiopian Airlines flight 302, headed for Nairobi, Kenia, crashed shortly after taking off Addis Ababa, killing all the 157 people on board.  Again, a brand-new Boeing 737 Max, on a perfectly fair-weather condition flight, nosedived; this time in a semidesert area.

Boeing immediately issued a statement saying that safety was their number one priority, and they had full confidence in the safety of the Max.  They also stated that the FAA did not mandate any further action at the time.  The FAA said that they had no plans to ground the 737 Max, at least until they had further data.  Elaine Chao, of the US Secretary of Transportation, flew on a Boeing 737 Max, and said that if they found evidence that linked a plane failure to the accidents, they would ground it.  The Chinese government however, unilaterally decided to ground the Boeing 737 Max, and several other countries followed almost immediately.

Once the black box of the Ethiopian Airlines flight was recovered and analyzed, it showed a similar flight pattern with respect to the Lion Air flight.  A few days later, at the accident site, the “jackscrew”, a vital piece of the aircraft that commands the stabilizer trim, was found.  It showed that it was set in a “full nose down” position, proving that the MCAS was to blame for the accident… again.  Within 30 minutes, President Trump was on National TV, grounding all the Boeing 737 Max.  After the announcement, all the grounded planes needed to be flown to their storage locations, but pilots did not want to fly them any longer…

At this point, the Congress became involved, and Rep. Peter Defazio (D-Oregon) started an investigation on the matter.  Additionally, the families of the victims started to put pressure on Congress in Washington DC.

After the second crash, Boeing blamed the Ethiopian crew.  They said they failed to do everything they were supposed to do.  Boeing was very aggressive campaigning in favor of their position that proposed human failure in both accidents.  Capt. Chesley (Sully) Sullenberger responded:“We should not be blaming the pilots; we should not expect the pilots to compensate flawed designs”.

Once the second black box was recovered and analyzed it showed that the Ethiopian crew in the cabin acted exactly as Boeing instructed them to do in case of this situation.  Unfortunately, this did not work either, because at such a speed, the  plane simply could not be trimmed up manually.

This had a severe impact on Boeing’s reputation.

The Company

Over several decades, Boeing had a strong reputation for excellence and safety.  Every single employee of the company had a clear understanding that safety and the security of every plane they manufactured was their responsibility, and they felt respected and valued, both by the company and society.

In 1997, when McDonnell Douglas and Boeing merged, this started to fall apart.  Harry Stonecipher, CEO of McDonnell Douglas, became the CEO of the Boeing Company, and the main focus was now on financial value and creating returns for shareholders.  Everybody had to focus on increasing share prices in Wall Street.  Original Boeing’s culture of not taking shortcuts and either doing it right or not doing it, changed to cheaper planes, less controls, lower quality, and faster time to market.  The new management started removing quality controls to speed up production, and former employees stated that anyone who reported a problem could easily be fired: the new culture was “kill the messenger ignore the problem”.  The company announced large layoffs and focused on doing more with less people.  At the time, they also moved the company headquarters to Chicago, IL.

A few years later, Boeing started to have a harsh competition from the European Airbus.  In 2003, after several great years for Airbus and bad years for Boeing, Airbus became market leader for the first time.  This increased the managerial pressure: it was all about designing and taking the product to the market as fast as possible and beating the competition. Quality and safety issues became less important.

In 2010, with oil prices at record high levels, Airbus introduced the new A320 Neo, the most fuel-efficient plane at the time.  The plane was the fastest seller plane in the history of aviation and sent Boeing’s top management in panic; they did not have a plane to compete with the Neo and had no time to design a new one.  So, in 2011 the company controversially announced the new Boeing 737 Max, under the claim of being the most efficient plane in the single aisle segment.  Essentially, they put a more fuel-efficient engine on the old 737 (a plane first launched in 1967).

To take the plane to the market as fast as possible, it was crucial that this was positioned as new version of the same plane, since this would significantly shorten the approval process by the FAA, and the airlines would not need to incur in the high cost of additional pilot training.  Boeing guaranteed airlines that the new plane will not need a new simulator training for pilots to fly it.

The Boeing 737 Max was launched and was a huge success; lots of orders came in and Boeing’s stock price skyrocketed.

The Investigation

Rep. Defazio has always said that he was waiting to receive information from the company to work on official evidence. Boeing was reluctant to send information, but after long negotiations and with the help of the house lawyers, he started receiving documents.  Among them was a report showing that in 2013, in the early stages of the project, a group of employees discussed the MCAS and its safety.  The problem was that new modern and efficient engines would not easily fit in a 40-year- old plane.  The fear was that the weight and location of the new engines would cause the balance of weight to move backwards, so the nose of the plane would rise and take it to a stall.  The MCAS was designed to level the plane in such an event.

Additionally, it was reported that the MCAS needed to be modified twice during the production process.  In the beginning it only worked at high speed, but then they realized that it needed to also work at lower speeds. This modification required a larger range of movement of the trimmer, which caused more radical nose dives of the plane.  The second modification made on the MCAS was that instead of relying on information from two sensors, it relayed on information from just one sensor.  The problem with this decision is that if the sensor gets damaged during the flight, it will send faulty information, and the MCAS will take over the plane and throw its nose down.

Nobody at Boeing told the airlines or the regulator about this new system, to avoid going  through a lengthy approval process that would delay their time to market, and additional pilot training that would increase the airlines cost of adopting the new plane.  As we have seen, pilots needed to be trained to learn how to react in case of an MCAS-related problem, but the company decided not to disclose this. In fact, they were stressing the point that this plane will not need simulator training for pilots, and that if the regulator asked for it, Boeing would not allow it to happen.  Paradoxically, in 2017, Lion Air asked Boeing whether they should not get extra training for their pilots for this new plane, and Boeing said there was no need for it, and went as far as mocking Lion Air for asking for it.  Internal reports disclosed that Boeing knew the potential failure of the MCAS would have catastrophic effects, but still decided to hide it and not offer training to the pilots.

After the Lion Air crash, the FAA had performed a Transport Aircraft Risk Assessment Methodology (TARAM), concluding that the Max could have crashed fifteen more times during its life, at the rate of one crash every two years.  Unfortunately, the study was not disclosed, but Boeing received the results and promised they would fix the problem before a new crash occurred.

Boeing, after learning about TARAM study, and essentially knowing that another Max could crash at any time, did nothing to eliminate the risk of a second crash.  They just bet on a second accident not happening before they could find a solution.

In the meantime, public opinion was discussing whether Boeing put an unsafe plane in the air, and if 346 lives is the cost of the company doing “Business as Usual” with a total disrespect for risk.

My Comments

The Boeing 737 Max case was a tragedy.  It happened, and we cannot go back in time and change the events.  What we can do is study them,and hopefully learn something about risk management, and the reasons why companies fail to do it right.  Because, let’s face it, this is a major failure in risk management, and it happened in a large corporation in an industry in which risk should be a serious matter.  It is worth noting that Boeing is regulated by the FAA, so there is also an issue with regulation and its ability to enforce an adequate risk management program, both at the design and execution level.  There is not an easy way to enforce a good risk management program.  Regulators require companies to show they have a program, but it is very difficult to know whether they are managing risks, or just having a risk management program.  We know that the only way of doing it properly is going through a cultural change in the whole company, and this must start at the top management level.

Having a real change in the perception of the importance of a company-wide risk management program in this case, would probably be the best way to honor the 346 people who paid with their lives the lack of risk management and planning in companies throughout the world.  I will discuss some insights in several short sub-topic discussions.

Company Culture

The former Boeing used to be a company obsessed with quality and safety. A company with several double checks and controls that made sure that they were putting the absolute best in their products.  In sum, a company in which safety and security of their planes was embedded in their DNA.  This strategy has probably been costly, and during “normal times” the company probably left some money on the table in the form of higher costs, especially according to companies that were mainly focused on the financial bottom line.  McDonnell Douglas seemed to be a more aggressive, results oriented and financially driven company.  In the clash of cultures, the latter prevailed, most likely because top management came from it, and the new merged company was mainly focused on one stakeholder: the shareholders.  The 737 Max accidents happened in 2018 and 2019. The prevailing idea of which stakeholder should a company satisfy had long shifted from shareholders to several stakeholders in the previous three decades.  The firm’s culture at the time of the design of the Max was antiquated and unacceptable, especially in an industry that needs a strong focus on safety and security.  We know that capital markets are important, but they are not our only stakeholder, and top management cannot fail to understand it.  This is a very important lesson to be learned from the Boeing accidents.  Company culture matters and matters a lot.

Identifying a Risk is Not Enough, it Needs to be Managed

Boeing’s management knew that there was a risk with the MCAS; the investigation reports showed that its impact could be catastrophic, so it must be the case that they have either severely underestimated the probability of occurrence, or the probability that a potential accident would be related to a design flaw of the plane. It might also have just been bluntly ignored.  In any case, nothing was done with respect to this risk; no risk management, no mitigation plan, nothing.

This is unacceptable!

In a world in which a surgeon faces charges if there is a flaw in a medical procedure and causes damage to a patient, how can top management have no responsibility in a case in which 346 people died.  In fact, a couple of months after the senate investigation, Dennis Muilenburg, Boeing’s Chairman, was asked to resign and received stock and pensions awards worth $62m.  In January 2021, the US Department of Justice charged Boeing with criminal conspiracy to defraud the FAA. The company agreed to pay $2.5Bn in fines and compensation to avoid criminal prosecution.

There are several issues we need to consider.  Who was involved in the decision of going ahead with a project that had an unacceptable risk?  Was the CEO, or someone in the C-suite, aware of this? Or maybe the decision had been delegated to a lower level in the organization so nobody at the C-Level was aware of the risks.  Either way, it would be a serious flaw in risk management.  In any case, there is a clear connection between this problem and the tone at the top set by the C-Suite that discouraged employees from raising any problems.  We need to make sure we can design risk management mechanisms that allow top management to be fully aware when there is a decision regarding safety, and human lives, and that encourages employees to raise any issue when they consider it important.

So, who is it to blame for these accidents?  Obviously, the chairman and CEO is the ultimate responsible, but for sure there is more to learn and discuss about how the process evolved.

These accidents raise another common misconception in risk management.  People tend to feel the need to quantify risk probabilities and impact. That is, unfortunately, a very dangerous idea.  How would you quantify the cost of an accident in a plane full of people?  Some might propose to use the cost of the compensations to the victims, plus the cost of fines and penalties, multiplied by the probability of occurrence.  This is completely flawed.  In a world in which we are in business to satisfy multiple stakeholders, we simply cannot quantify the cost of a human loss as compensation times probability. It is clear that once the accident happens, the probability is 1, and for the family of the victims the cost of the missing relative is much higher than the compensation cost calculated by the company.  So, when we have lives at stake, nobody should try to quantify the risk in terms of the effect on the cash flow.  This argument is still true for other types of less dramatic risks, like for example, how do we quantify the impact on reputation, is it even possible?  Do we need to quantify it, or can we just say, for example, that any risk defined as high or very high is not acceptable?  My suggestion is, do not try to quantify unquantifiable risks.  In the search for a quantification, we will necessarily use some assumptions that will, most probably, drive us towards wrong analysis.  Just define risks as “very low”, “low”, “medium”, “high” and “very high”, and be clear whether this impact is affecting the cash flow, the ability to operate, reputation, safety, among other aspects of the organization.

Crisis Management

The case shows that Boeing had absolutely no crisis management in place.  The way they handled the case was awful, in both accidents.  Obviously, good crisis management would have not brought back the 346 lives, but could have mitigated the impact of this crisis in the company’s reputation.  It is quite amazing that after the first accident they were not able to do something to improve the crisis management before the second event.  If this is true for a large US corporation like Boeing, imagine the crisis management capabilities of smaller firms around the world.  Companies need to improve their ability to manage crises, and this has to be done as a part of their risk management program, more specifically, as a mitigation strategy for certain risks in their risk map.

The Regulator

Another interesting issue is related to the role of the regulator. In the beginning they did not investigate enough on the new plane and underestimated the MCAS.  After the first accident, they suspected there was a problem with the plane, they studied it with the TARAM, and then they were certain that there was a problem with the plane. However, they  still decided to allow the Max to fly, indirectly allowing a second accident, and the loss of additional 157 lives.  In my view, there is negligence of the regulator in this case.  We should take the opportunity posed by this case to encourage regulators to improve their ability to help regulated companies to design and execute better risk management programs.

Corporate Risk Management

In the documentary (Downfall: the case against Boeing) it is said that Boeing was doing business as usual. This is quite common in most companies.  In some sense we can say that top management has a bias toward the avoidance to manage risks.  Boeing’s management knew that this could happen, but they (not sure who or at which level) decided that it was not important enough to act on it.  At that point in time, taking the product faster to the market was more important than a potential safety issue; not having to retrain the pilots was more important than a potential safety issue.  So, they just moved on ignoring risks.  This is extremely common, the low probability of occurrence of an accident gives people a strong incentive to neglect risks.  Considering how many flights the 737 Max has performed, having had two accidents, in percentage it seems like a small probability, which by the way, is something that Boeing’s CEO said on National TV. In most of the cases, in which the event does not happen, managers who neglect risks easily get away with it; no event, nobody realizes the risk was even there, lower costs and higher profits. The problem is that sometimes, the events do happen, and when this is the case we usually see large material and immaterial losses.  Usually after the event happens, we learn in the investigation that the tragedy could have been avoided if everybody had done their job, and this is mostly related to putting the risks on the table and acting.  This is called risk management.

When you are in the middle of a situation it is very difficult to make adequate decisions all the time, especially when there are large potential gains at stake.  Experienced mountaineers climbing Everest, for example, know that in their last push to the summit, if they do not summit before 1pm, they must go down, otherwise, the probability of not making it to base camp alive increases dramatically. This, which looks as a perfectly rational decision when discussed at a coffee store or in an office, is extremely difficult to accept when you have spent weeks in the expedition, and spent several hundred thousand dollars of your savings to reach it. Especially if the summit seems very close.  Therefore, the decision of going down at 1pm, no matter how close to the summit, must be done and agreed on before you start climbing. Once you are there, if you have the chance of not going down and pushing to the top, most probably you will make the irrational decision.  Technically, you have higher chances to overestimate your capabilities and even luck, and to underestimate the probability of occurrence and impact of an unwanted event.

Taking this Everest example to Boeing, probably in a rational environment, most of the people involved in the decision would have decided that the MCAS risk should have been disclosed and addressed.  Unfortunately, with all the pressure and the sense of urgency, nobody acted rationally, underestimating the probability of occurrence and impact.

This is the reason why risk management policies are so important.  A rational policy would have clearly stated, that “anything that has a risk in which the plane might fall causing losses of human lives, should not be neglected”. Unfortunately, if you do not have the policy, then irrationality kicks in and wrong decisions are made with potentially catastrophic results.

Let’s hope this tragedy helps top management and regulators in doing more rational risk management in the future.

FX exposure comes in different forms, some of them are fairly easy to recognize, while some others are not easy to identify, and even harder to hedge.  The easiest form of FX exposure is the one that appears when a firm has cash flows denominated in different currencies.  This happens when a company operating in its local currency has a financial or commercial debt or credit denominated in a foreign one.  This exposure is usually easy to characterize and recognize.  If the firm has a credit in a foreign currency, its revaluation with respect to the local one will generate a profit and if the firm has a debt denominated in the foreign currency, its revaluation will generate a loss.  Recognizing this exposure is straightforward; finance departments of companies around the world know their foreign currency denominated cash flows and the exposure they generate.  Hedging this exposure, once it has been recognized, is also usually easy, and can be done through the use of FX derivatives or by setting up an operational hedge.  An easy example of an operational hedge would be the generation of an opposite position by taking a commercial debt of credit in the foreign currency in such a way that both exposures offset each other at due time.  This type of exposure is usually referred as to Transaction Exposure, since it usually appears because of a transaction or a concatenation of them.

A company, however, can have an exposure to FX risk even when all its cash flows are denominated in the same currency.  This happens when either: (i) its clients or customers; (ii) its suppliers, or; (iii) its competitors, operate in a different currency.  Consider the case of a firm that exports a given product, and in order to avoid the problems caused by having cash flows denominated in different currencies decide to sell their products in local currency (assuming that it has the market power to do so).  Even having all its cash flows denominated in the same –local- currency, it cannot avoid the fact that its clients and customers hold a different currency in their pockets.  If the foreign currency, the one in the clients’ pockets, depreciates with respect to the exporter’s local currency, its products will become essentially more expensive for the foreign clients to buy them, and the exporting firm is likely to lose sales and ability to compete in that market.  This effect is similar in the case in which a firm has to purchase supplies from a foreign firm.  Even if the importer is able to force the supplier to denominate the transactions in local currency, it still cannot escape the fact that the supplier might become less and less efficient and, in the extreme, it might even go bankrupt because of the FX volatility; this would change an FX risk into a Supply Chain Risk.  In a similar fashion, even when a firm only trades within its own country and in its own currency, it can still face significant FX exposure.  Consider the case that a foreign firm enters a firm’s local market with its products produced in another country and its costs denominated in a foreign currency.  If this foreign currency devaluates with respect to the local market currency, the foreign firm will have a cost advantage and the local firm’s ability to compete will be affected by the local currency overvaluation.

These type of situation is usually denominated Economic Exposure.  It is not attached to a particular transaction, rather it is a situation that stems from the competitive environment of the firm.  This type of exposure is hard to identify and mitigate.  In order to identify it firms need to have a very clear risk management understanding, and dealing with these exposures is usually more complex than just taking derivative positions; it usually entails decisions affecting operations, logistics, human resources, etc.  In the case of having identified this risk, and in the impossibility of restructuring the firm, an, at least partial solution, might be designed by taking positions in financial instruments that generate a gain when the FX volatility generates a loss.  This is, however, a more complicate and potentially incomplete way of hedging the exposure.

These exposures can affect not only a firm but also a whole country or region. This was the case of the loss of competitiveness of European firms when the euro revaluated with respect to the US dollar and the rest of the world currencies a few years ago.  As a result of that, most European firms started having a hard time competing in both the global and local markets, several of them moved their production facilities outside Europe, generating an economic slowdown and a large unemployment, whose consequences we are still witnessing nowadays.

There is another kind of FX exposure, the one that appears when assets denominated in a foreign currency need to be translated into a local currency, usually for reporting purposes.  These assets can be fixed assets or even liquid ones, like a production facility or a stream of dividends.  In both cases, the devaluation of the foreign currency would diminish the value of those assets for the local company, generating an FX exposure.  This type of exposure is usually referred as Translation Exposure, and is usually hard to identify and hedge.

Most of the times firms fail to identify all the different flavors of FX exposure, and simply recognize the traditional Transaction Exposure.  The problem is that the other exposures, especially the Economic Exposure, is likely to generate larger damage, especially if it is not seen in advance.  As usually, it is of paramount importance to identify and monitor the determinants of FX risks, so we can anticipate threats and opportunities in due advance.

Assume that the government is requiring the construction of a bridge across a river.  As a first step several companies submit technical proposals. Only a few of them are accepted and are required to submit a financial proposal for the completion of the project.  Let’s assume that all the proposals have to be received by March 1, 2016, and the government will make a final decision of which seller will be awarded the project by November 1, 2016.  By March 1^st each seller has to submit a financial proposal for the construction of the bridge, in which –since the government does not want to bear any risk- they are required to offer a fixed price for the completion of the bridge.  By doing this, the government knows the final price of the bridge at the moment of receiving the offers.  But this certainty comes at a cost.  In any project there are risks to be borne and these do not disappear, they are just translated from one party to another.  In this case, the risks that are not assumed by the buyer are going to be assumed by the seller.  This is not necessarily a problem if the seller is able to assume these risks efficiently, but if this is not the case and inefficiencies generate a cost, then the society as a whole will pay for it.

To illustrate the nature of this problem lets continue the discussion of our example.  Let’s assume that the construction of the bridge needs the purchase of several tons of commodities, just for the sake of discussion assume that 100 tons of copper and 100 tons of aluminum are needed for this particular project, and as we all know these commodity prices are volatile (their annual volatility can be well above 30%).  Given that the government is not willing to assume the risk of these volatilities increasing the price of the bridge, the seller is required to provide a fixed price for the whole project as of March 1^st.  This fixed price is essentially transferring the exposure to commodity prices volatility to the seller.  The seller that ends up winning the bid and getting the concession, in November will have an open short position in Copper and Aluminum, since they will have promised to build a bridge for a given price, that will have a given assumed Aluminum and Copper price. This short position is easy to hedge using several hedging strategies involving the purchase of derivative instruments in the financial markets or with suppliers or using operational hedging strategies.  The problem is that, in order to have an open risk position that can be hedged, the seller needs to know that it has been awarded the contract, which might not alway be the case in a competitive bidding process.  The company that is awarded the contract will have a short position in November, while the other competitors –the ones not getting the deal- will not have a short position.  So, by March 1^st nobody has a hedgeable short position; by the time they submit their financial offer all the sellers have a contingent short position, that will become a short position for the winner of the project by November 1^st.  The problem is that between March and November commodity prices can change significantly, leaving the sellers exposed to potentially devastating volatility.  In other words, the problem with this approach is that the sellers are forced to assume a contingent risk position, that is essentially impossible to hedge between March 1^st and November 1^st.  A company participating in the offer for the bridge cannot hedge the position in March because if they get the deal in November, then the hedge purchased in March will offset the November exposure, but if they do not get the deal, their hedge purchased in March will not match any exposure, resulting in a risky position.

In order to overcome this problem firms willing to participate in the deal have three possible strategies: (i) increase the offer price in order to have some of this potential volatility mitigated by a “price cushion”, (ii) assume a serious risk of losing money in the project, and (iii) not offering to participate in the construction of the bridge.  None of these alternatives is particularly appealing for the potential participants in the offer, for the government and for the society as a whole.

The problem is that contingent risk positions cannot be hedged.  Fortunately there is a solution for this problem; a solution that does eliminate this non hedgeable risks.  The only party that has a certainty that will be exposed to these commodity prices fluctuations is the government. The government knows that in November they will grant the construction of the bridge to one of the sellers.  So, and based on this certainty, they government should change the bidding process and require the sellers to offer the bridge according to a price equation that allows commodity prices (in this example, just aluminum and copper prices) to vary before November 1^st hence firms will not need to include a contingent «price cushion» to account for future volatility.   In other words, the government should ask the sellers to offer something like:

Bridge Cost= 100 tons of Aluminum at Nov 1^st spot price + 100 tons of Copper at Nov 1^st spot price + FIXED AMOUNT OF $$

As we can see, this procedure forces the government to face an exposure to the volatility of aluminum and copper prices.  More specifically, the government is taking a short position in both commodities between March 1^st and November 1^st.  But, unlike in the case of the sellers, this position is not contingent, hence can be easily hedged by the government.  In order to hedge this position, the government could buy futures in the financial markets to cover 100 tons of each commodity, with expiration date November 1^st.  When the government awards the project and assigns the contract to the winner, the Bridge Cost shown in the previous equation will be calculated as a fixed amount of money since by then the commodity prices as of Nov 1^st will be known.  If November’s commodity prices result higher than March’s prices, the cost of the bridge will be higher than expected but the futures on the commodities will be sold at a profit that will exactly compensate the loss, and if November’s commodity prices happen to be lower than March’s prices, the bridge will be cheaper but the losses in the Futures contracts will wipe out the profits.  In other words, the government will be able to keep the cost of the bridge at the same level expected in March.

This approach requires that the entity that is requesting the project generate a risk map of the project and then decide which party is better equipped to assume each risk.  In the example we discussed above, it is easy to hedge the risks in the financial markets, and the only issue was which risks where confirmed and which where contingent, but in some other cases the problem might be that one party is better equipped than the other to assume a given confirmed risk because of the firm’s structure, informational advantage, financial structure, etc…  By following this approach projects should be more efficient from a pricing standpoint, with lower levels of extra costs and should attract more firms to the deal.

Firms invest significant amounts of money in emerging economies assuming the boom (or at least the stability) will last over time. Or maybe they are just underestimating the potential downside they are facing. I understand that companies need to open new markets and diversify into new –mostly emerging- markets, but I think that most of the times they are just running blindfolded through a potentially mined field. Things go well until they fail. In my opinion we could do a much better job if we could gain a deeper understanding of the political risks faced by the emerging economies, and getting to know their determinants. Oftentimes the determinants of the political risks are sociological and demographic issues that tend to be neglected by analysts and business people in general.

How often do we ask which are the factors that trigger political risk events? A whole country going into political trouble and instability cannot happen overnight. It takes a lot of time and early warning signs are usually out there, the problem is that we usually fail to see them, because we are not looking in the right direction.

There are two typical moments in which Emerging Markets tend to have significant political changes, these are: (i) election times, and (ii) times when there is a significant macroeconomic or social shock or downfall (these two are usually correlated). In these moments the probability of a change in the country’s public policy is higher. It is crucial to understand the signals provided by reality before events actually develop.

I would like to propose some groups of potential indicators that we could follow and would probably provide useful signals early warnings of political risk that should trigger further investigation.

Institutional quality is an indication of how easy is for somebody to steer the country away from rationality. In a country with poor institutions the President can do almost anything, generating large swings and throwing away years of efforts. It is not easy to measure institutional quality with a single indicator, but it could be done using several variables. Some of the indicators that could be used to approximate this are: the independence of the judiciary system, the legislators and the Central Bank from the central government; the efficiency of the justice; the perception of corruption in the government; the number of years that a single party has been in power; the quality of corporate governance; the freedom of speech for individuals and the press; etc. There are several independent indicators of institutional quality of a country; most of them are generated by well-respected and trustworthy independent sources.

Social wellbeing of the population is another important factor that we need to consider. If people in a country are struggling with unemployment, high inflation, high mortality rates, lack of satisfaction of their basic needs, etc. there is a higher probability of social instability. There are several indicators that help measuring this. Some of them are economic, like the Gini Index that measures the distance between the richest and the poorest percentiles in a society; an indication on the evolution of the wealth of the poorest sectors of the economy (independently from the distance to the richest); indicators of the levels of inflation and unemployment; the spread between active and passive interest rates; the level of use of the banking system in the population; and the level of capitalization of the local capital market; among others. Some other indicators are plainly demographic ones, like child mortality; life expectancy; number of people living in cities; level of literacy; etc. Another set of indicators that captures the social sentiment of the population is also needed: number of strikes; roadblocks; union activism; crime statistics, etc.

Another important determinant of political risk is the country’s level of infrastructure. Countries with more and better hospitals, schools, highways, airports, etc. are supposed to be more stable than countries that are struggling with lower levels of investment. There are several indicators that could be used to measure the levels of infrastructure, and most of them are easy to obtain from independent sources. Examples of these indicators are: number of hospitals (or hospital capacity), kilometers of paved roads, Internet access, quality and availability of 3G and 4G access, number of people with internet connection, etc.

As anybody can imagine, most of these indicators are easily available for almost any country. The problem is that firms are not used to a systematical collection and study of the data. Constructing a well-balanced index using some of the indicators proposed in this post, and following its evolution over time, should provide a fair sign on the evolution of the political risk in a given economy or region. It is extremely important that companies start taking these signs seriously, using all the available data in order to anticipate the future social and political situation of a country. The resulting information will generate a warning system that will help investors and analysts to understand the reality of the countries in which they are investing and the probable direction of their government decisions (or elections).

Let’s start by considering the easiest situation; if the car manufacturer needs to purchase plain aluminum to produce some parts of the car, they essentially have a direct short position in aluminum, and that exposure can be easily hedged in the London Metal Exchange (LME) purchasing aluminum futures, swaps, or call options. There is plenty of literature on how to hedge these exposures so we are not going to discuss this matter in this post (the “Videos on Hedging” section of this webpage shows videos –in Spanish- on this matter).

Let’s now consider a more complex situation; the purchase of aluminum wheels. In this case the company needs to purchase a certain number of aluminum wheels from its wheels supplier, so, strictly speaking, the firm is short aluminum wheels, not aluminum, so the exposure to the traded commodity volatility is indirect. We are prepared and well equipped to hedge exposures when we have a financial market and derivative contracts on the good we need to buy or sell, but in this case we do not have a market in which we can buy futures, swaps or call options on aluminum wheels, so we need to find a better alternative for hedging that position.

If we could prove that the prices of the wheels have a perfect positive correlation with the aluminum prices, and that that perfect correlation will hold in the future, then we can treat this exposure as a plain aluminum short position and hedge it in the aluminum futures and options market in the LME. But this situation of perfect correlation is unlikely to happen. I would argue that it is almost impossible to find in the economy. Let’s see why. The pricing equation of the wheels producer is something like this:

       Wheel Price: f (aluminum price, energy, salaries, other costs, profit margin, e)

As we can see, the price at which the supplier will be willing to sell the wheels to the car manufacturer is a function of several variables, most of them not directly controllable by the firm. This means that it is possible that in some periods of time aluminum prices and aluminum wheels prices might take different paths; i.e. with increasing aluminum prices we might see flat or decreasing wheel prices. This is quite common and happens because the variables in the pricing equation above have different volatilities and interactions. This happened in the aluminum cans industry in the beginnings of the nineties, when the can manufacturers in their quest for volume where charging prices that where non-correlated with the aluminum prices. In a similar fashion during several periods of the nineties, soybean oil prices where non-correlated (and during some periods of time also negatively correlated) with soybean prices, reflecting the potential dissociation between variables that we might assume highly correlated.

So, the problem is how to hedge a position in a product that is not a commodity and does not trade in the financial markets. The solution to this problem is to decompose the exposure and assign each portion of the risk to whoever should be its right owner: most suited to either assume it or to hedge it in an efficient manner.

The car manufacturing firm could ask the wheels suppliers to fix wheel prices through a forward contract for, say, a full year, in that case they would generate a long position in wheels that would offset its natural short position. That would be a nice hedge for the exposure, but at the cost of asking the wheels supplier to assume a risk he might not be suited to assume. By selling wheels at a fixed price the supplier is assuming the potential volatility of all the variables in its pricing equation. In theory the wheels producer should go to the financial markets and buy a hedge for whatever variable whose volatility it is not prepared to assume. The problem is that this is not always the case, and often times the fixed price contract results in an exposure that cannot be sustained by the firm and, as a result, the whole supply chain might be negatively affected. An increase in aluminum prices would affect our wheels supplier stuck with a fixed output price, and he might face significant problems, resulting in decreased product or service quality, financial distress, or even bankruptcy. None of these outcomes is desirable for the car manufacturer.

In order to avoid such a bad outcome the car manufacturing company willing to eliminate its exposure to wheel price volatility, could sign a contract with its wheel supplier in the following terms. The fixed price will be referred to all pricing components excluding aluminum prices. In other words, the pricing contract will be designed on an equation of this form:

       Wheel Price = Aluminum Spot Price (LME) + $xx

Where Aluminum Spot Price (LME) is the spot price of a pre-specified date, and $xx is a fixed amount of money for the whole period (in this case a year) that would cover all the other terms of the supplier’s pricing equation. Under this contract, the car manufacturer will be charged, whatever price the aluminum is trading on the LME, plus a fixed amount of $xx for the wheels. This means that the firm has changed from a short position in wheels (that cannot be hedged in the LME), for a short position in aluminum that could be easily hedged through any derivative contract in the LME. This decomposition allowed the aluminum price risk to be assumed by a firm that, in this case, was better suited to transfer it. It is quite obvious that the wheel manufacturer could have done this risk decomposition on its own! This is entirely true, but assumes that every firm has the same capabilities of identifying and managing risk exposures. And this is not necessarily true. The ability to manage risks is widely volatile across firms, and there is a significant value in allocating the risks to its natural owner.

This same analysis could have been done up or down in the supply chain, from the supplier to its own supplier or from the client to its own client. In this same example we focused on the aluminum prices exposure, but we could have also discussed the possibility of who is better suited to assume the energy prices exposures as well…

Every industry or value chain is affected by several risks whether we like them or not. It is essential to allocate them to whoever is most efficient in assuming them. This will not only improve the efficiency of the industry as a whole, but of the firm that is able of assigning the risks to its right owners eliminating the undesired volatility. This same discussion applies to almost every industry, and has higher value in those industries in which there is a larger asymmetry in the risk management capabilities.

Political risk arises when, because of a governmental decision a firm’s expected outcome is affected. Oftentimes the government decision affects the firm in a direct manner, for example in the case of an expropriation. We call this a direct political risk. In some other cases the government decision motivates another actor to take an action that affects the firm, for example if the government does not enforce the rule of law and third parties –in violation of the law- take an illegal advantage. We call this indirect political risk.

Both, direct and indirect political risks, affect the firm in a similar fashion. The capability of recognizing them improves our awareness and ability to identify these risks in advance, and provides tools to manage them in a successful way. Each type of political risk have a set of determinants that we need to monitor, but this will only be possible after a careful identification of these risks.

Political risks come in different flavors; there are several different ways in which a political risk can appear. The most famous manifestation of political risk is the expropriation; i.e. the government seizing the firm’s assets (or shares) from its original owners. The business press has reported several cases of expropriations by governments. Among the most famous ones we can mention Fidel Castro´s expropriation of the Cuban based Rum producer Bacardi in 1960, or Hugo Chavez’s expropriations of several companies like the Argentine steel company Sidor, the Colombian retailer Exito, the Venezuelan oil & gas PDVSA and the Mexican cement producer Cemex among many others.

It is interesting to notice, however, that the probabilities of expropriation are not uniform across industries or time. Companies in different industries will have different probabilities of being expropriated based on how appetizing they are to the government currently in power. In fact, it is useful to identify the reasons why a government might want to expropriate a firm. First, a government seeking popular support might do it just for the sake of getting some extra voters for the next election, especially if the country is under a populist regime with high levels of popular support. This is especially true for some type of firms: according to certain ideologies, natural resources, pension plans and social security among some other industries should be state-owned. Therefore, in a certain type of political environment, expropriation is more likely for firms in industries of those characteristics. A combination of these reasons explains the expropriations of several firms in Argentina during the first decade and a half of this new century, where the government has expropriated Utilities, Oil and Gas companies and the local Pension Funds. Additionally, some expropriations have been justified based on the belief that the government should manage some industries because of economic reasons such as its competitive structure.

Additionally, expropriations also need to consider the particular timing of the investment cash flows. It is very unlikely that a government will harass a firm during the time in which it is in the process of investing; they usually wait until most of the investment is in place and the firms is starting to harvest positive cash flows. In an interesting case of poor understanding of this reality, the argentine government started increasing the taxes requirements to the mining companies during their investment process and, as a result of that, the Brazilian Mining firm Vale do Rio Doce decided to leave the country, abandoning a large investment already in place. The mining industry is still adjusting to this in Argentina nowadays.

Sometimes expropriation of assets is not feasible or not economically suitable, so governments generate changes in the rule of law that essentially have a similar effect. The most common case is the one in which the government, by changing some regulation, appropriates a portion of the firm’s cash flows without seizing any physical assets. President Correa has done this in Ecuador by changing the royalties’ structure of the Oil and Gas firms and President Kirchner has done the same in Argentina by changing the export taxes for the agricultural firms. As a result of these changes the government has seized the cash flows of the private companies trying to leave enough returns to the private owners so they have an incentive in continuing the exploitation. Reality teaches, however, that this strategy hardly works in the long run. Changes in commodity prices, technological innovations, new substitute products, etc., jeopardize the whole structure and these experiments usually end in a big fail, leading to underinvestment and tragic loss of competitiveness at a firm and country level. Most of the times firms end up moving their investments towards countries in which they are allowed to keep a larger share of their cash flows.

A classic demonstration of indirect political risk is the outbreak of social unrest that might affect a firm or a given industry. We have seen several examples of this in the recent past. A few years ago, social activists have blocked the bridges connecting Argentina and Uruguay for about three years in a protest against the installation of the UPM-Botnia Pulp mill in the city of Fray Bentos in Uruguay. Recently social activists have blocked a newly built Monsanto facility, not allowing the plant to start operations. In a similar fashion, unions and social activists have blocked the plants of several US firms (the food manufacturing company Kraft, the printing company Donnelley and the manufacturing firm Lear, just to mention a few) outside Buenos Aires, Argentina in a protest for layoffs. The Argentine government has a very benevolent policy against strikes and social protests, allowing and protecting them, as a result, it is very common that argentine unions and social activists protest and go on strike every time they have an opportunity of doing so. At the time of writing this post there is a very severe situation in Peru with the Tia María Mining Project in the southern region of Arequipa. Social protests are mounting, the dead toll keeps growing and President Ollanta Humala is trying to solve the problem addressing the protesters. In some other cases, the government, for whatever reasons plays some role in the pressure put on the firms; this is the case, for example of the expropriation of PLUNA, the Uruguayan National Airline; the forced renegotiation of the agreement at Barrick’s Pueblo Viejo mining project in the Dominican Republic; or the current difficult legal situation of the Citibank branch in Argentina.

Wars and civil wars are other forms of political risks. Independently of the reasons that might have triggered them, these events generate a mayor disruption in the business climate of a region. Consider the big wars in Europe in the past century or the several examples of ferocious civil wars in the last decades to see how these affect the firm´s business. The Arab Spring started in Egypt in January 2011 and widespread through most of the region, and the ferocious Rwanda Civil War started in 1994 are examples of this.

Notice that the probabilities of social unrest are not uniform across countries and regions. In their book The Fat Tail, Ian Bremmer and Preston Keat studied the characteristics of the countries that experienced social unrest, and found several interesting regularities. Countries with more men than women, higher concentration of young people, higher number of unemployed, countries with more years of the same government in power, among other characteristics seemed to have a higher propensity of going into social unrest. Based on this idea, The Economist calculated The Shoe Thrower’s Index, a predictor of social unrest in countries in Arab countries that –looked in retrospective- worked with amazing accuracy. This idea could be reproduced in any region; it is only a matter of finding the right determinants of the risks of social unrest in a given region.

The changes in the economy and the institutional environment produced by the election of a new government are interesting forms of political risk. Especially in those countries in which an elected president has a large share of the political power, i.e. countries with poor institutional environment, each time a new president is elected, it might completely change the business and economic landscape. As a result, past winners might become new losers and vice-versa. It is interesting to notice that most of the forms of democratic government in a country are compatible with firms making profits in their operations provided they could adjust to what is required by this type of government. Just to take the example of the two extremes seen in Latin America nowadays. We have countries that move towards embracing pro-market policies, and countries that have a –higher or lower- degree of populism. In either regime firms can develop profitable businesses; the problem is that the structure needed to develop these businesses are quite different and not easy to adjust in a short time. Moreover, it is usually the case that several of these countries tend to switch between these regimes causing past winners to become losers and vice-versa fairly fast.

This was the case of Argentina: during the nineties the country embraced pro-market policies but the government failed to keep up with the necessary measures, and after a deep economic, political, social and institutional crisis, a new government embraced populist policies that have been governing the country since 2003. Some of the profitable firms from the nineties are now on the verge of bankruptcy, whereas formerly protected and non-competitive firms are now the new winners in the current political landscape. Given that these changes in regime seem to be happening, the main question posed by this fact is whether we are ready to forecast when this is going to happen and if we are able to redesign the firms in order to adjust towards the organizational form that is needed in the new political landscape. How can we know in advance when a country is going to shift towards a change in regime? There are some specific determinants of political risks that can predict these changes and we might want to keep an eye on. Doing this will allow us to foresee the evolution of political risks.

This improved understanding of political risks is only the beginning; we still need to include them in the risk management practice of the firm. The procedure is the same as with every risk; we need to make sure we identify and measure them and understand their determinants. After that, we assign owners to the risks and give somebody the responsibility of monitoring their determinants. Political risks also have mitigation strategies that we need to consider, but these will be considered in another post.

The main reason for this lack of value lays in the way these ERM models are designed and implemented. It is quite common to see models designed by third parties and implanted in the firm; externally designed models are implanted in the company as prosthesis in a human body. The main problem with this approach is that there is a lack of cultural adjustment to firms without a risk management culture, and implanting an externally designed model will not help in the adaptation. If the risk management system is not generated in the firm by its managers it will be extremely difficult for it to work in harmony with the company’s management and strategy. It will be seen as something external that has been transplanted into the organization and generates some sort of additional duties to some of the firm’s employees.

In order to obtain a proper design and implementation of an ERM program we need to follow two parallel paths, and keep in mind that it is extremely important that both start at the same time. The first one is a cultural change throughout the organization, and the second one is a well-designed risk management system.

The cultural change is a crucial aspect of any successful risk management program. If people are not aligned in why the organization needs to manage risks, then no system, no matter how well designed, will do the job. Risk management starts inside the brain of the firm’s employees. Risk management is about people keeping their eyes open at work and outside the office; an important insight might happen at a social event, while reading a book or in the golf links. Only people who is thinking in terms of risk management will be constantly looking for important insights and value them in a correct manner. For this to happen we need to have them understanding the paramount importance of constantly assessing and managing the firm’s risks. This is one of the main consequences of the successful implementation of a risk management program.

The well designed system, the second leg of a successful risk management program, calls for a set of procedures that ensures that all the individual risk management efforts of the firm’s managers are adequately conveyed towards where they are needed at the correct time. This means that every piece of information that is collected by people in the organization needs to be inputted where and when it is needed. It means also that that all the pieces of information will reach the decision maker at the correct time, for him or her to make a timely and informed decision regarding the treatment of a given risk. I personally like collaborative environments where every member of the organization can input data and/or receive information as required by the system design.

Let me provide a brief insight of how this works. A good risk management system has some persons that are the risk owners; they are responsible for managing one or more of the risks faced by the company. They manage these risks based on a set of policies designed by the firm’s board. These policies define how much of a given risk the firm is willing to assume, and how it will eliminate or transfer the residual of that risk. Additionally, each risk has its determinants (a previous post in this blog explains this concept), each of these determinants need to have an owner; somebody who is looking at it with the adequate timing. The information system requires that each owner of a determinant input the information on a pre-specified timing, and the aggregate information of all the determinants of each risk reaches the risk owner on time for its decision-making. Good systems have also a way for people to share risk-related information that they deem important for the whole company.

This system works fine, but the crucial issue is: who will be willing to input data on the system if he or she is not convinced about the importance of this action? The cultural change plays a key role here. Everybody in the organization needs to fully understand the importance of his or her action for the whole system to work properly. This is ensured by a cultural change in the organization.

The first step of any risk management program is the identification of the risks affecting the firm. This process is also the starting point of the cultural change in the company. It needs to be done by the firm’s management working as a team, discovering risks in a coordinated and collaborative way. This is an important milestone in any risk management implementation, since it is the starting point of both paths of the model: the system and the cultural change.

Both, the risk management system and the cultural change are needed for the risk management to work. They should not be implemented as a sequential process, a risk management implementation stand on two legs: (i) the system and (ii) the cultural change. Having the system without changing the firm’s culture just leads to a bureaucratic and inefficient system, having only the cultural change leads to frustration, since people understands the importance of the matter, is aware of what is happening but is unable to have the organization move in the right direction when needed. This is why a risk management implementation needs both legs to succeed.

1) Do you know which are the risks faced by your company?
It is not easy to list all the risks faced by a firm. Most of the times the list of risks firms use is bluntly incomplete, and they are hit by a risk that was not considered in any scenario, but happens anyway. Risks –that are usually classified, by its origin, in financial, operational, political and strategic- need to be listed, and this list must be done by the firm, no outsider can do it for you. The best way of assuring that the list will be complete is by having a heterogeneous team of senior management discussing it; the group should have heterogeneity coming from position, department, seniority, etc. The risk listing is the essential starting point of any good risk management process, having an incomplete risk map is one of the most frequent mistakes; if the risk is not listed in this first step it will not be considered in the whole process, and this could be dangerous.

2) Have you ever made the effort in learning the determinants of the risks that your firm is facing?
Managers need to know and understand the risk their firms are facing. Understanding a risk entails the need of knowing its past behavior, and trying to understand its future path. The future behavior of some risk factors is very difficult to predict, but in some cases we could have some additional information by knowing and understanding their determinants. The determinant of a given risk factor is what causes this factor to move in a certain way. For example, the determinants of the Arab Spring that took down President Mubarak in Egypt in 2011, where the underlying forces that were at work in the Egyptian Society (social discontent, economic weakness, years that Mubarak has been in power, etc…), that caused the population to rise against its government. Knowing the determinants of the mayor risks helps managers to understand their risks and to do a better job in predicting the future path. It is crucial that each determinant has an assigned owner; somebody in charge of understanding it, following the news on the matter, and informing them to whoever is in charge of it. This is a crucial step in risk management and in my experience one of the least developed aspects in the corporate world.

3) Do you know the probability of occurrence and the impact of the risks that your company is facing?
It is quite common that risks are organized in a Heat Map using two dimensions; (i) the magnitude of the potential impact and (ii) the distribution or probability of occurrence. This is an important step for the risk management process, since it helps us categorizing the importance of each risk for the organization. These estimations have to be made by those managers that have a better understanding of the risks, and do not need to be expressed in a quantitative manner; a low, medium, high, with a very low and very high in each scale will be sufficient to have a visual classification of the risks.

4) Have you ever considered where are those risks affecting your company? Is it in your cash flow, in the firm value, in the firm’s reputation, in its ability to compete, in its ability to attract talent?
When estimating the impact of a given risk factor it is extremely important to make sure we analyze its effect on cash flows and firm value, as usual, but we also consider the effects on reputation, and on the firm’s ability to compete and attract talent. I am aware that the effects of risk might end hitting the cash flows and firm value anyway, but knowing if we want to protect cash flow or reputation will be crucial for designing hedging strategies.

5) Have you screened which are all the possible hedging strategies for the risks in your risk map?
We need to study all the possible strategies that will help us mitigating or diminishing the risks faced by a firm. We need to diminish the probability of occurrence or the impact of the risk. This can be achieved by: (i) operational decisions (operational is not supposed to mean low-level decisions, it means decisions regarding the business operation and strategy), (ii) insurance contracts, and (iii) strategies using derivatives. It is important to know all the available hedging strategies so we can have more information for our next crucial decision; the one about which risks to be assumed and which risks to be transferred.

6) Which are the risks that you want to assume and which are those you want to transfer to others? Which are the risks by which your firm generates value for its stakeholders?
Life is risk; without risk there is no satisfaction. A firm cannot exist without assuming certain risks; no investor would invest in a firm that does not generate any profit above the risk-free rate. According to this intuition, a firm is an entity that generates value for its stakeholders by assuming the right risks, and efficiently transferring the other ones. Firms that do not have a well designed and established risk management practice go through existence by randomly bumping into all the risks that they meet in their way, and their generation of profit is a random process representing the average between the value created by the upside and the value destroyed by the downside.

7) How much of each risk (I am considering those risks that you decided to assume) are you planning to assume? Have you set a limit to the potential losses?
When a manager decides that the firm will assume a certain risk, the next important step is to define the adequate level of maximum risk that the firm will assume. In other words, they need to decide how much volatility of that risk factor they will assume. For this step to be well defined we need to (i) assign an owner to all the determinants of the risk under analysis, and (ii) define the strategy for an efficient elimination of the additional volatility in case it is needed. In other words, a firm deciding to assume oil price risk, will need to assign owners to the determinants of oil prices volatility, and decide at which level of oil prices they will have an option that will eliminate the residual risk.

8) Do you have a formal system that allows the risk related information obtained or generated by the individuals in your organization, to reach the adequate destination?
One of the most common problems in risk management is to generate a formal channel for the risk information to flow. A successful model requires a change in people’s awareness regarding the important of risk management, and a channel through which the valuable information is conveyed. Doing the former without the latter will only produce frustration in the organization, and having only the formal system without any awareness will only produce bureaucracy. People needs to have a –simple- procedure manual that explains who is in charge of looking at what, and who should they inform when there are news regarding that matter. The manual should also set the hedging policies.

9) How embedded is your risk management process in your competitive strategy? Do you really understand that risk management is about making money while avoiding losses? What is the meaning of “Profiting from the Upside Controlling the Downside”?
Risk management should be a part of our strategic planning process. As we said above, a firm generates value by assuming the right risks, it essentially does it by profiting when variables behave better than expected, but not running into trouble when variables behave worse than expected. In other words firms should profit from the upside generated by “good volatility”, controlling the downside generated by “bad volatility”. For this it is crucial to have risk management as a part of the strategy, and not as a part of the auditing process. Auditing should be on board, but not in charge.

10) Who is coordinating all the risk management efforts in the organizations?
A good risk management practice needs a team leader. It needs to have somebody in the organization that is supervising the whole process. The person in charge of the coordination of the whole practice is the chief risk officer, or CRO. The CRO is a new function for most organizations that are still struggling to find the best way of coordinating the risk management efforts. It has to be a senior person, with the ability of understanding the various different tasks involved in risk management (that change across firms), and of supervising and coordinating different senior executives in their risk management tasks. It is a position that we will start seeing more and more in the years to come.

The discussion of these ten questions with firms’ senior management will help organizations to have a much greater awareness about the importance of risk management; the first step towards improving their risk management abilities.

A risk determinant is the reason why a certain risk factor has a given behavior, is what causes such a behavior.  We can then state that a risk factor is a function of its determinants; RF: f (risk determinants).  Any given risk factor has several determinants, for example, currency devaluation can be caused by several different political reasons and or by several diverse macroeconomic causes.  These causes can change over time and across events.  Take for example the case of oil prices; everyone will probably agree that supply and demand issues are the main causes for their volatility.  On the supply side, we can probably count (i) political issues on the oil producing countries, (ii) technological advances on the production capacities, (iii) interest rates, etc.   On the demand side, we need to take into account issues like; (i) climate, (ii) growth of car market, (iii) use of alternatives sources of energy, etc.  Each of these variables are likely to cause volatility in oil prices, however, the specific influence of each variable is likely to change over time.  For example, political issues in producing countries can be very important at some point in time (they were crucial back in the ‘70s), and have no effect at another one.  This is exactly the problem when we measure data from the past: if during the time span of our data set, there is no effect of a particular variable, our model will predict no effect of that particular for the future.  So, there are three potential problems here, either (i) the effects of the variable were not captured by our data set because it did not affect the risk factor during the study time, or (ii) it affected the risk factor but we did not know it so we did not have the data to measure it, or (iii) it did not affect the data in the past, and this is the first time it happens.  In either case, our backward looking models will fail to correctly measure for the future.

A good example of what I have just stated is what happened with gas prices in the US.  As we can see in Chart 1, by mid-2008, the prices dropped from 13 to 3 USD/mmbtu in a few months.  This incredible, and unexpected, price drop occurred at about the same time in which gas producers found the way of extracting shale gas, thus dramatically increasing the expected gas reserves.

Chart 1 – Natural Gas Prices

Before 2007, shale gas was expensive and difficult to extract, therefore gas reserves outlook were expected to follow a slight decrease over time, as can be seen in Graph 2, pushing prices upward.  When technological innovations allowed gas producers to extract shale gas at a competitive price, the expected gas reserves grew starkly, and prices dropped accordingly (the projections in Chart 2 show that by 2040 around 50% of the total gas production will be shale gas).

Chart 2 – US Natural Gas Production (2012-2040 estimated)

The relevant question here is; how many energy companies were expecting this to happen?  This price drop caught most of the industry unprepared.  People following gas price dynamics have seen this in advance?  Past information on prices did not show any sign regarding the importance of the new extraction technologies and its potential in the determination of gas reserves… thus for somebody looking only at the data, this was invisible, however, for somebody understanding the determinants of the volatility of oil prices, this was probably something easy to see.   It is just a matter of be looking in the right direction…  The only way of having been able to see this in advance would have been to follow the evolution of the extraction technologies and its importance for the gas reserves.  Whoever identified this might have anticipated the fall in prices.

Managers, unfortunately, tend to underestimate the importance of identifying these risk determinants.  Short-term issues are usually assigned higher importance and therefore the relevance of risk determinants tends to be neglected.

Sometimes, risk determinants can be a bit detached from normal business operations.  They are often discussed in Universities’ research labs, and not close to the firms’ operations.  Just to give another example.  The evolution of solar energy is still slow with respect to its potential.  Solar cells are still expensive, but what if there were an innovation that allows them to improve its cost efficiency?  For example higher efficiency in the form of smaller surfaces needed to generate more energy?  This is likely to be caused by innovation on new materials: how many energy firms are closely following these innovations?  There are several similar examples affecting other risk factors. The volatility of commodity prices and macroeconomic variables, the occurrence of certain political risks, the volatility of the market for talent, the ability to obtain and retain important knowledge in the firms, etc…  All these risk factors have their key risk determinant.  It is crucial that firms learn how to identify them and find the way of assigning them an owner that is in charge of following their evolution.

The problem is that, as always happens in basic research, lots of these paths take nowhere.  It is also true that some of them also take to a large prize, but for most companies is impossible to follow them all.  This is against the classic short-termism force that most firms face but is crucial for a good risk management.  The owner of the risk determinants has to be aware of what is going on with that specific risk determinant.  Control panels of key variables should be monitored to identify key indicators in advance.  This would allow firms to have a much better grip of what is going on with the main risks they are facing, and be closer to profiting from the upside controlling the downside of each risk!