Exometeorology is the study of atmospheric conditions of exoplanets and other non-stellar celestial bodies outside the Solar System, such as brown dwarfs. The diversity of possible sizes, compositions, and temperatures for exoplanets (and brown dwarfs) leads to a similar diversity of theorized atmospheric conditions. However, exoplanet detection technology has only recently
developed enough to allow direct observation of exoplanet atmospheres,
so there is currently very little observational data about
meteorological variations in those atmospheres.
Observational and theoretical foundations
Modeling and theoretical foundations
Climate models have been used to study Earth's climate since the 1960s and other planets in our solar system since the 1990s. Once exoplanets were discovered, those same models were used to investigate the climates of planets such as Proxima Centauri b and the now-refuted Gliese 581g. These studies simulated what atmospheric pressures
and compositions are necessary to maintain liquid water on each
terrestrial exoplanet's surface, given their orbital distances and rotation periods. Climate models have also been used to study the possible atmospheres of the Hot JupiterHD 209458b, the Hot NeptuneGJ 1214b, and Kepler-1649b, a theorized Venus analog.
These models assume that the exoplanet in question has an atmosphere in order to determine its climate. Without an atmosphere, the only temperature variations on the planet's surface would be due to insolation from its star.
Additionally, the main causes of weather - air pressure and air
temperature differences which drive winds and the motion of air masses -
can only exist in an environment with a significant atmosphere, as
opposed to a tenuous and, consequently, rather static atmosphere, like
that of Mercury. Thus, the existence of exometeorological weather (as opposed to space weather) on an exoplanet depends on whether it has an atmosphere at all.
Recent discoveries and observational foundations
The first exoplanet atmosphere ever observed was that of HD 209458b, a Hot Jupiter orbiting a G-type star similar in size and mass to our sun. Its atmosphere was discovered by spectroscopy; as the planet transited its star, its atmosphere absorbed some of the star's light according to the detectable absorption spectrum of sodium in the planet's atmosphere. While the presence of sodium was later refuted, that discovery paved the way for many other exoplanet atmospheres to be observed and measured. Recently, terrestrial exoplanets have had their atmospheres observed; in 2017, astronomers using a telescope at the European Southern Observatory (ESO) in Chile found an atmosphere on earth-sized exoplanet Gliese 1132 b.
However, measuring traditional meteorological variations in an
exoplanet's atmosphere — such as precipitation or cloud coverage — is
more difficult than observing just the atmosphere, due to the limited
resolutions of current telescopes. That said, some exoplanets have shown
atmospheric variations when observed at different times and other
evidence of active weather. For example, an international team of astronomers in 2012 observed variations in hydrogen escape speeds from the atmosphere of HD 189733 b using the Hubble Space Telescope. Additionally, HD 189733 b and Tau Boötis Ab have their hottest surface temperatures displaced eastward from their subsolar points, which is only possible if those tidally-locked planets have strong winds displacing the heated air eastward, i.e. a westerly wind. Lastly, computer simulations of HD 80606b predict that the sudden increase in insolation it receives at periastron spawns shockwave-like windstorms that reverberate around the planet and distribute the sudden heat influx.
Theorized weather
Empirical observations of weather
on exoplanets are still rudimentary, due to the limited resolutions of
current telescopes. What little atmospheric variations can be observed
usually relate to wind, such as variations in the escape speeds of atmospheric hydrogen in HD 189733b or just the speeds of globally circulating winds on that same planet.
However, a number of other observable, non-meteorological properties of
exoplanets factor into what exoweather is theorized to occur on their
surfaces; some of these properties are listed below.
Presence of an atmosphere
As
mentioned previously, exometeorology requires that an exoplanet has an
atmosphere. Some exoplanets that do not currently have atmospheres began
with one; however, these likely lost their primordial atmospheres due
to atmospheric escape from stellar insolation and stellar flares or lost them due to giant impacts stripping the exoplanet's atmosphere.
Some exoplanets, specifically lava planets,
might have partial atmospheres with unique meteorological patterns.
Tidally-locked lava worlds receive so much stellar insolation that some
molten crustvaporizes
and forms an atmosphere on the day side of the planet. Strong winds
attempt to carry this new atmosphere to the night side of the planet;
however, the vaporized atmosphere cools as it nears the planet's night
side and precipitates back down to the surface, essentially collapsing
once it reaches the terminator. This effect has been modeled based on data from transits of K2-141b as well as CoRoT-7b, Kepler-10b, and 55 Cancri e.
This unusual pattern of crustal evaporation, kilometer-per-second
winds, and atmospheric collapse through precipitation might be provable
with observations by advanced telescopes like Webb.
Exoplanets with full atmospheres are able to have diverse ranges
of weather conditions, similar to weather on the terrestrial planets and
gas giants of our Solar System. Planet-wide atmospheres allow for global air circulation, stellar thermal energy distribution, and relatively fast chemical cycling, as seen in the crustal material transportation by lava worlds' partial atmospheres and Earth's own water and carbon cycles. This ability to cycle and globally distribute matter and energy can drive iron rain on hot Jupiters, 2 km/s (4,500 mph) super-rotating winds on HD 189733b, and atmospheric precipitation and collapse on tidally-locked worlds.
Orbital properties
One of the most important factors determining an exoplanet's properties is its orbital period, or its average distance from its star. This alone determines a planet's effective temperature (the baseline temperature without added insulation from an atmosphere) and how likely the planet is to be tidally locked. These, in turn, can affect what chemical compositions of clouds can be present in a planet's atmosphere, the general motion of heat transfer and atmospheric circulation, and the locations where weather can occur (as with tidally-locked lava worlds with partial atmospheres).
For example, a gas giant's orbital period can determine whether its wind patterns are primarily advective (heat and air flowing from the top of the star-heated atmosphere to the bottom) or convective (heat and air flowing from down near the gradually contracting planet's core up through the atmosphere). If a gas giant's atmosphere receives more heat from insolation
than the planet's unending gravitational contraction, then it will have
advective circulation patterns; if the opposite heat source is
stronger, it will have convective circulation patterns, as Jupiter exhibits.
Additionally, an exoplanet's average incident stellar radiation,
determined by its orbital period, can determine what types of chemical
cycling an exoplanet might have. Earth's water cycle occurs because our
planet's average temperature is close enough to water's triple point
(at normal atmospheric pressures) that the planet's surface can sustain
three phases of the chemical; similar cycling is theorized for Titan, as its surface temperature and pressure is close to methane's triple point.
Similarly, an exoplanet's orbital eccentricity – how elliptical
the planet's orbit is – can affect the incident stellar radiation it
receives at different points in its orbit, and thus, can affect its
meteorology. An extreme example of this is HD 80606b's
shockwave-like storms that occur whenever the planet reaches the
innermost point in its extremely eccentric orbit. The difference in
distance between its apastron (analogous to Earth's aphelion) and its periastron (perihelion) is so large that the planet's effective temperature varies greatly throughout its orbit. A less extreme example is eccentricity in a terrestrial exoplanet's orbit. If the rocky planet orbits a dim red dwarf
star, slight eccentricities can lead to effective temperature
variations large enough to collapse the planet's atmosphere, given the
right atmospheric compositions, temperatures, and pressures.
In simple terms, risk is the possibility of something bad happening. Risk involves uncertainty
about the effects/implications of an activity with respect to something
that humans value (such as health, well-being, wealth, property or the
environment), often focusing on negative, undesirable consequences.
Many different definitions have been proposed. The international
standard definition of risk for common understanding in different
applications is "effect of uncertainty on objectives".
The understanding of risk, the methods of assessment and
management, the descriptions of risk and even the definitions of risk
differ in different practice areas (business, economics, environment, finance, information technology, health, insurance, safety, security etc). This article provides links to more detailed articles on these areas. The international standard for risk management, ISO 31000, provides principles and general guidelines on managing risks faced by organizations.
Definitions of risk
Oxford English Dictionary
The Oxford English Dictionary (OED) cites the earliest use of the word in English (in the spelling of risque from its French original, 'risque') as of 1621, and the spelling as risk from 1655. While including several other definitions, the OED 3rd edition defines risk as:
(Exposure to) the possibility of loss, injury, or other adverse or
unwelcome circumstance; a chance or situation involving such a possibility.
The International Organization for Standardization
(ISO) Guide 73 provides basic vocabulary to develop common
understanding on risk management concepts and terms across different
applications. ISO Guide 73:2009 defines risk as:
effect of uncertainty on objectives
Note 1: An effect is a deviation from the expected – positive or negative.
Note 2: Objectives can have different aspects (such as financial,
health and safety, and environmental goals) and can apply at different
levels (such as strategic, organization-wide, project, product and
process).
Note 3: Risk is often characterized by reference to potential events and consequences or a combination of these.
Note 4: Risk is often expressed in terms of a combination of the
consequences of an event (including changes in circumstances) and the
associated likelihood of occurrence.
Note 5: Uncertainty is the state, even partial, of deficiency of
information related to, understanding or knowledge of, an event, its
consequence, or likelihood.
This definition was developed by an international committee
representing over 30 countries and is based on the input of several
thousand subject matter experts. It was first adopted in 2002. Its
complexity reflects the difficulty of satisfying fields that use the
term risk in different ways. Some restrict the term to negative impacts
("downside risks"), while others include positive impacts ("upside
risks").
ISO 31000:2018 "Risk management — Guidelines" uses the same definition with a simpler set of notes.
Other
Many other definitions of risk have been influential:
"Source of harm". The earliest use of the word "risk" was as a synonym for the much older word "hazard", meaning a potential source of harm. This definition comes from Blount's "Glossographia" (1661) and was the main definition in the OED 1st (1914) and 2nd (1989) editions. Modern equivalents refer to "unwanted events" or "something bad that might happen".
"Chance of harm". This definition comes from Johnson's
"Dictionary of the English Language" (1755), and has been widely
paraphrased, including "possibility of loss" or "probability of unwanted events".
"Uncertainty about loss". This definition comes from Willett's "Economic Theory of Risk and Insurance" (1901). This links "risk" to "uncertainty", which is a broader term than chance or probability.
"Measurable uncertainty". This definition comes from Knight's "Risk, Uncertainty and Profit" (1921).
It allows "risk" to be used equally for positive and negative outcomes.
In insurance, risk involves situations with unknown outcomes but known
probability distributions.
"Volatility of return". Equivalence between risk and variance of
return was first identified in Markovitz's "Portfolio Selection"
(1952). In finance, volatility of return is often equated to risk.
"Statistically expected loss". The expected value of loss was used to define risk by Wald (1939) in what is now known as decision theory. The probability of an event multiplied by its magnitude was proposed as a definition of risk for the planning of the Delta Works in 1953, a flood protection program in the Netherlands. It was adopted by the US Nuclear Regulatory Commission (1975), and remains widely used.
"Likelihood and severity of events". The "triplet" definition of
risk as "scenarios, probabilities and consequences" was proposed by
Kaplan & Garrick (1981).
Many definitions refer to the likelihood/probability of
events/effects/losses of different severity/consequence, e.g. ISO Guide
73 Note 4.
"Consequences and associated uncertainty". This was proposed by Kaplan & Garrick (1981). This definition is preferred in Bayesian analysis, which sees risk as the combination of events and uncertainties about them.
"Uncertain events affecting objectives". This definition was adopted by the Association for Project Management (1997). With slight rewording it became the definition in ISO Guide 73.
"Uncertainty of outcome". This definition was adopted by the UK Cabinet Office (2002)
to encourage innovation to improve public services. It allowed "risk"
to describe either "positive opportunity or negative threat of actions
and events".
"Asset, threat and vulnerability". This definition comes from the Threat Analysis Group (2010) in the context of computer security.
"Human interaction with uncertainty". This definition comes from Cline (2015) in the context of adventure education.
Some resolve these differences by arguing that the definition of risk is subjective. For example:
No definition is advanced as the correct one, because
there is no one definition that is suitable for all problems. Rather,
the choice of definition is a political one, expressing someone's views
regarding the importance of different adverse effects in a particular
situation.
The Society for Risk Analysis
concludes that "experience has shown that to agree on one unified set
of definitions is not realistic". The solution is "to allow for
different perspectives on fundamental concepts and make a distinction
between overall qualitative definitions and their associated
measurements."
Practice areas
The
understanding of risk, the common methods of management, the
measurements of risk and even the definition of risk differ in different
practice areas. This section provides links to more detailed articles
on these areas.
Business risks arise from uncertainty about the profit of a
commercial business due to unwanted events such as changes in tastes,
changing preferences of consumers, strikes, increased competition,
changes in government policy, obsolescence etc.
Business risks are controlled using techniques of risk management.
In many cases they may be managed by intuitive steps to prevent or
mitigate risks, by following regulations or standards of good practice,
or by insurance. Enterprise risk management
includes the methods and processes used by organizations to manage
risks and seize opportunities related to the achievement of their
objectives; see also Financial risk management § Corporate finance.
Economic risk
Economics
is concerned with the production, distribution and consumption of goods
and services. Economic risk arises from uncertainty about economic
outcomes. For example, economic risk may be the chance that
macroeconomic conditions like exchange rates, government regulation, or
political stability will affect an investment or a company's prospects.
In economics, as in finance, risk is often defined as quantifiable uncertainty about gains and losses.
In finance, risk is the possibility that the actual return on an investment will be different from its expected return. This includes not only "downside risk"
(returns below expectations, including the possibility of losing some
or all of the original investment) but also "upside risk" (returns that
exceed expectations). In Knight's definition, risk is often defined as
quantifiable uncertainty about gains and losses. This contrasts with Knightian uncertainty, which cannot be quantified.
Epidemiology is the study and analysis of the distribution, patterns and determinants of health and disease. It is a cornerstone of public health, and shapes policy decisions by identifying risk factors for disease and targets for preventive healthcare.
In the context of public health, risk assessment
is the process of characterizing the nature and likelihood of a harmful
effect to individuals or populations from certain human activities.
Health risk assessment can be mostly qualitative or can include
statistical estimates of probabilities for specific populations.
A health risk assessment
(also referred to as a health risk appraisal and health &
well-being assessment) is a questionnaire screening tool, used to
provide individuals with an evaluation of their health risks and quality
of life
Health, safety, and environment risks
Health,
safety, and environment (HSE) are separate practice areas; however,
they are often linked. The reason is typically to do with organizational
management structures; however, there are strong links among these
disciplines. One of the strongest links is that a single risk event may
have impacts in all three areas, albeit over differing timescales. For
example, the uncontrolled release of radiation or a toxic chemical may
have immediate short-term safety consequences, more protracted health
impacts, and much longer-term environmental impacts. Events such as Chernobyl,
for example, caused immediate deaths, and in the longer term, deaths
from cancers, and left a lasting environmental impact leading to birth defects, impacts on wildlife, etc.
Information technology (IT) is the use of computers to store, retrieve, transmit, and manipulate data. IT risk (or cyber risk) arises from the potential that a threat may exploit a vulnerability to breach security and cause harm. IT risk management applies risk management methods to IT to manage IT risks. Computer security is the protection of IT systems by managing IT risks.
Information security
is the practice of protecting information by mitigating information
risks. While IT risk is narrowly focused on computer security,
information risks extend to other forms of information (paper,
microfilm).
Insurance risk
Insurance
is a risk treatment option which involves risk sharing. It can be
considered as a form of contingent capital and is akin to purchasing an option in which the buyer pays a small premium to be protected from a potential large loss.
Insurance risk is often taken by insurance companies, who then
bear a pool of risks including market risk, credit risk, operational
risk, interest rate risk, mortality risk, longevity risks, etc.
The term "risk" has a long history in insurance and has acquired
several specialised definitions, including "the subject-matter of an
insurance contract", "an insured peril" as well as the more common
"possibility of an event occurring which causes injury or loss".
The Occupational Health and Safety Assessment Series (OHSAS)
standard OHSAS 18001 in 1999 defined risk as the "combination of the
likelihood and consequence(s) of a specified hazardous event occurring".
In 2018 this was replaced by ISO 45001 "Occupational health and safety
management systems", which use the ISO Guide 73 definition.
Project risk
A project
is an individual or collaborative undertaking planned to achieve a
specific aim. Project risk is defined as, "an uncertain event or
condition that, if it occurs, has a positive or negative effect on a
project's objectives". Project risk management
aims to increase the likelihood and impact of positive events and
decrease the likelihood and impact of negative events in the project.
Safety risk
Safety is concerned with a variety of hazards that may result in accidents
causing harm to people, property and the environment. In the safety
field, risk is typically defined as the "likelihood and severity of
hazardous events". Safety risks are controlled using techniques of risk
management.
A high reliability organisation
(HRO) involves complex operations in environments where catastrophic
accidents could occur. Examples include aircraft carriers, air traffic
control, aerospace and nuclear power stations. Some HROs manage risk in a
highly quantified way. The technique is usually referred to as probabilistic risk assessment (PRA). See WASH-1400
for an example of this approach. The incidence rate can also be reduced
due to the provision of better occupational health and safety
programmes.
Security risk
Security is freedom from, or resilience against, potential harm caused by others.
A security risk is "any event that could result in the compromise
of organizational assets i.e. the unauthorized use, loss, damage,
disclosure or modification of organizational assets for the profit,
personal interest or political interests of individuals, groups or other
entities."
Security risk management involves protection of assets from harm caused by deliberate acts.
Risk is ubiquitous in all areas of life and we all manage these
risks, consciously or intuitively, whether we are managing a large
organization or simply crossing the road. Intuitive risk management is
addressed under the psychology of risk below.
Risk management refers to a systematic approach to managing
risks, and sometimes to the profession that does this. A general
definition is that risk management consists of "coordinated activities
to direct and control an organization with regard to risk".
ISO 31000, the international standard for risk management, describes a risk management process that consists of the following elements:
Risk treatment - selecting and implementing options for addressing risk.
Monitoring and reviewing
Recording and reporting
In general, the aim of risk management is to assist organizations in
"setting strategy, achieving objectives and making informed decisions".
The outcomes should be "scientifically sound, cost-effective,
integrated actions that [treat] risks while taking into account social,
cultural, ethical, political, and legal considerations".
In contexts where risks are always harmful, risk management aims to "reduce or prevent risks".
In the safety field it aims "to protect employees, the general public,
the environment, and company assets, while avoiding business
interruptions".
For organizations whose definition of risk includes "upside" as
well as "downside" risks, risk management is "as much about identifying
opportunities as avoiding or mitigating losses".
It then involves "getting the right balance between innovation and
change on the one hand, and avoidance of shocks and crises on the
other".
Risk assessment is a systematic approach to recognising and
characterising risks, and evaluating their significance, in order to
support decisions about how to manage them. ISO 31000 defines it in terms of its components as "the overall process of risk identification, risk analysis and risk evaluation".
Risk assessment can be qualitative, semi-quantitative or quantitative:
Qualitative approaches are based on qualitative descriptions of risks and rely on judgement to evaluate their significance.
Semi-quantitative approaches use numerical rating scales to
group the consequences and probabilities of events into bands such as
"high", "medium" and "low". They may use a risk matrix to evaluate the significance of particular combinations of probability and consequence.
Quantitative approaches, including Quantitative risk assessment
(QRA) and probabilistic risk assessment (PRA), estimate probabilities
and consequences in appropriate units, combine them into risk metrics,
and evaluate them using numerical risk criteria.
The specific steps vary widely in different practice areas.
Risk identification
Risk
identification is "the process of finding, recognizing and recording
risks". It "involves the identification of risk sources, events, their
causes and their potential consequences."
ISO 31000 describes it as the first step in a risk assessment process, preceding risk analysis and risk evaluation. In safety contexts, where risk sources are known as hazards, this step is known as "hazard identification".
There are many different methods for identifying risks, including:
Checklists or taxonomies based on past data or theoretical models.
Evidence-based methods, such as literature reviews and analysis of historical data.
Team-based methods that systematically consider possible deviations from normal operations, e.g. HAZOP, FMEA and SWIFT.
Empirical methods, such as testing and modelling to identify what might happen under particular circumstances.
Techniques encouraging imaginative thinking about possibilities of the future, such as scenario analysis.
Sometimes, risk identification methods are limited to finding and
documenting risks that are to be analysed and evaluated elsewhere.
However, many risk identification methods also consider whether control
measures are sufficient and recommend improvements. Hence they function
as stand-alone qualitative risk assessment techniques.
Risk analysis
Risk
analysis is about developing an understanding of the risk. ISO defines
it as "the process to comprehend the nature of risk and to determine the
level of risk".
In the ISO 31000 risk assessment process, risk analysis follows risk
identification and precedes risk evaluation. However, these distinctions
are not always followed.
Risk analysis may include:
Determining the sources, causes and drivers of risk
Investigating the effectiveness of existing controls
Analysing possible consequences and their likelihood
Understanding interactions and dependencies between risks
Determining measures of risk
Verifying and validating results
Uncertainty and sensitivity analysis
Risk analysis often uses data on the probabilities and consequences
of previous events. Where there have been few such events, or in the
context of systems that are not yet operational and therefore have no
previous experience, various analytical methods may be used to estimate
the probabilities and consequences:
Proxy or analogue data from other contexts, presumed to be similar in some aspects of risk.
Risk
evaluation involves comparing estimated levels of risk against risk
criteria to determine the significance of the risk and make decisions
about risk treatment actions.
In most activities, risks can be reduced by adding further
controls or other treatment options, but typically this increases cost
or inconvenience. It is rarely possible to eliminate risks altogether
without discontinuing the activity. Sometimes it is desirable to
increase risks to secure valued benefits. Risk criteria are intended to
guide decisions on these issues.
Types of criteria include:
Criteria that define the level of risk that can be accepted in pursuit of objectives, sometimes known as risk appetite, and evaluated by risk/reward analysis.
Criteria that determine whether further controls are needed, such as benefit-cost ratio.
The simplest framework for risk criteria is a single level which
divides acceptable risks from those that need treatment. This gives
attractively simple results but does not reflect the uncertainties
involved both in estimating risks and in defining the criteria.
The tolerability of risk framework, developed by the UK Health and Safety Executive, divides risks into three bands:
Unacceptable risks – only permitted in exceptional circumstances.
Tolerable risks – to be kept as low as reasonably practicable (ALARP), taking into account the costs and benefits of further risk reduction.
Broadly acceptable risks – not normally requiring further reduction.
Descriptions of risk
There are many different risk metrics that can be used to describe or "measure" risk.
Triplets
Risk is often considered to be a set of triplets (also described as a vector):
for i = 1,2,....,N
where:
is a scenario describing a possible event
is the probability of the scenario
is the consequence of the scenario
is the number of scenarios chosen to describe the risk
These are the answers to the three fundamental questions asked by a risk analysis:
What can happen?
How likely is it to happen?
If it does happen, what would the consequences be?
Risks expressed in this way can be shown in a table or risk register. They may be quantitative or qualitative, and can include positive as well as negative consequences.
The scenarios can be plotted in a consequence/likelihood matrix (or risk matrix).
These typically divide consequences and likelihoods into 3 to 5 bands.
Different scales can be used for different types of consequences (e.g.
finance, safety, environment etc.), and can include positive as well as
negative consequences.
An updated version recommends the following general description of risk:
where:
is an event that might occur
is the consequences of the event
is an assessment of uncertainties
is a knowledge-based probability of the event
is the background knowledge that U and P are based on
Probability distributions
If all the consequences are expressed in the same units (or can be converted into a consistent loss function), the risk can be expressed as a probability density function describing the "uncertainty about outcome":
One way of highlighting the tail of this distribution is by showing the probability of exceeding given losses, known as a complementary cumulative distribution function,
plotted on logarithmic scales. Examples include frequency-number (FN)
diagrams, showing the annual frequency of exceeding given numbers of
fatalities.
A simple way of summarising the size of the distribution's tail
is the loss with a certain probability of exceedance, such as the Value at Risk.
Expected values
Risk is often measured as the expected value of the loss. This combines the probabilities and consequences into a single value. See also Expected utility. The simplest case is a binary possibility of Accident or No accident. The associated formula for calculating risk is then:
For example, if there is a probability of 0.01 of suffering an
accident with a loss of $1000, then total risk is a loss of $10, the
product of 0.01 and $1000.
In a situation with several possible accident scenarios, total
risk is the sum of the risks for each scenario, provided that the
outcomes are comparable:
(terms defined above)
In statistical decision theory, the risk function is defined as the expected value of a given loss function as a function of the decision rule used to make decisions in the face of uncertainty.
A disadvantage of defining risk as the product of impact and
probability is that it presumes, unrealistically, that decision-makers
are risk-neutral. A risk-neutral person's utility is proportional to the expected value
of the payoff. For example, a risk-neutral person would consider 20%
chance of winning $1 million exactly as desirable as getting a certain
$200,000. However, most decision-makers are not actually risk-neutral
and would not consider these equivalent choices.
Volatility
In finance, volatility is the degree of variation of a trading price over time, usually measured by the standard deviation of logarithmic returns. Modern portfolio theory measures risk using the variance (or standard deviation) of asset prices. The risk is then:
The beta coefficient measures the volatility of an individual asset to overall market changes. This is the asset's contribution to systematic risk, which cannot be eliminated by portfolio diversification. It is the covariance between the asset's return ri and the market return rm, expressed as a fraction of the market variance:
Outcome frequencies
Risks of discrete events such as accidents are often measured as outcome frequencies,
or expected rates of specific loss events per unit time. When small,
frequencies are numerically similar to probabilities, but have
dimensions of [1/time] and can sum to more than 1. Typical outcomes
expressed this way include:
Individual risk - the frequency of a given level of harm to an individual. It often refers to the expected annual probability of death. Where risk criteria refer to the individual risk, the risk assessment must use this metric.
Group (or societal risk) – the relationship between the frequency and the number of people suffering harm.
Frequencies of property damage or total loss.
Frequencies of environmental damage such as oil spills.
Relative risk
In health, the relative risk is the ratio of the probability of an outcome in an exposed group to the probability of an outcome in an unexposed group.
An
understanding that future events are uncertain and a particular concern
about harmful ones may arise in anyone living in a community,
experiencing seasons, hunting animals or growing crops. Most adults
therefore have an intuitive understanding of risk. This may not be
exclusive to humans.
In ancient times, the dominant belief was in divinely determined
fates, and attempts to influence the gods may be seen as early forms of
risk management. Early uses of the word 'risk' coincided with an erosion
of belief in divinely ordained fate.
Risk perception
is the subjective judgement that people make about the characteristics
and severity of a risk. At its most basic, the perception of risk is an
intuitive form of risk analysis.
Heuristics and biases
Intuitive
understanding of risk differs in systematic ways from accident
statistics. When making judgements about uncertain events, people rely
on a few heuristic
principles, which convert the task of estimating probabilities to
simpler judgements. These heuristics are useful but suffer from
systematic biases.
The "availability heuristic"
is the process of judging the probability of an event by the ease with
which instances come to mind. In general, rare but dramatic causes of
death are over-estimated while common unspectacular causes are
under-estimated.
An "availability cascade"
is a self-reinforcing cycle in which public concern about relatively
minor events is amplified by media coverage until the issue becomes
politically important.
Despite the difficulty of thinking statistically, people are
typically over-confident in their judgements. They over-estimate their
understanding of the world and under-estimate the role of chance. Even experts are over-confident in their judgements.
Psychometric paradigm
The "psychometric paradigm" assumes that risk is subjectively defined by individuals, influenced by factors that can be elicited by surveys. People's perception of the risk from different hazards depends on three groups of factors:
Dread – the degree to which the hazard is feared or might be
fatal, catastrophic, uncontrollable, inequitable, involuntary,
increasing or difficult to reduce.
Unknown - the degree to which the hazard is unknown to those exposed, unobservable, delayed, novel or unknown to science.
Number of people exposed.
Hazards with high perceived risk are in general seen as less acceptable and more in need of reduction.
Cultural Theory
views risk perception as a collective phenomenon by which different
cultures select some risks for attention and ignore others, with the aim
of maintaining their particular way of life.[57]
Hence risk perception varies according to the preoccupations of the
culture. The theory distinguishes variations known as "group" (the
degree of binding to social groups) and "grid" (the degree of social
regulation), leading to four world-views:
Hierarchists (high group /high grid), who tend to approve of
technology providing its risks are evaluated as acceptable by experts.
Egalitarians (high group/low grid), who tend to object to technology
because it perpetuates inequalities that harm society and the
environment.
Individualists (low group/low grid), who tend to approve of technology and see risks as opportunities.
Fatalists (low group/high grid), who do not knowingly take risks but tend to accept risks that are imposed on them
Cultural Theory helps explain why it can be difficult for people with
different world-views to agree about whether a hazard is acceptable,
and why risk assessments may be more persuasive for some people (e.g.
hierarchists) than others. However, there is little quantitative
evidence that shows cultural biases are strongly predictive of risk
perception.
Risk and emotion
The importance of emotion in risk
While
risk assessment is often described as a logical, cognitive process,
emotion also has a significant role in determining how people react to
risks and make decisions about them.
Some argue that intuitive emotional reactions are the predominant
method by which humans evaluate risk. A purely statistical approach to
disasters lacks emotion and thus fails to convey the true meaning of
disasters and fails to motivate proper action to prevent them.
This is consistent with psychometric research showing the importance of
"dread" (an emotion) alongside more logical factors such as the number
of people exposed.
The field of behavioural economics
studies human risk-aversion, asymmetric regret, and other ways that
human financial behaviour varies from what analysts call "rational".
Recognizing and respecting the irrational influences on human decision
making may improve naive risk assessments that presume rationality but
in fact merely fuse many shared biases.
The "affect heuristic"
proposes that judgements and decision-making about risks are guided,
either consciously or unconsciously, by the positive and negative
feelings associated with them.
This can explain why judgements about risks are often inversely
correlated with judgements about benefits. Logically, risk and benefit
are distinct entities, but it seems that both are linked to an
individual's feeling about a hazard.
Fear, anxiety and risk
Worry or anxiety
is an emotional state that is stimulated by anticipation of a future
negative outcome, or by uncertainty about future outcomes. It is
therefore an obvious accompaniment to risk, and is initiated by many
hazards and linked to increases in perceived risk. It may be a natural
incentive for risk reduction. However, worry sometimes triggers
behaviour that is irrelevant or even increases objective measurements of
risk.
Fear
is a more intense emotional response to danger, which increases the
perceived risk. Unlike anxiety, it appears to dampen efforts at risk
minimisation, possibly because it provokes a feeling of helplessness.
Dread risk
It
is common for people to dread some risks but not others: They tend to
be very afraid of epidemic diseases, nuclear power plant failures, and
plane accidents but are relatively unconcerned about some highly
frequent and deadly events, such as traffic crashes, household
accidents, and medical errors. One key distinction of dreadful risks seems to be their potential for catastrophic consequences, threatening to kill a large number of people within a short period of time. For example, immediately after the 11 September attacks,
many Americans were afraid to fly and took their car instead, a
decision that led to a significant increase in the number of fatal
crashes in the time period following the 9/11 event compared with the
same time period before the attacks.
Different hypotheses have been proposed to explain why people fear dread risks. First, the psychometric paradigm
suggests that high lack of control, high catastrophic potential, and
severe consequences account for the increased risk perception and
anxiety associated with dread risks. Second, because people estimate the
frequency of a risk by recalling instances of its occurrence from their
social circle or the media, they may overvalue relatively rare but
dramatic risks because of their overpresence and undervalue frequent,
less dramatic risks.
Third, according to the preparedness hypothesis, people are prone to
fear events that have been particularly threatening to survival in human
evolutionary history. Given that in most of human evolutionary history people lived in relatively small groups, rarely exceeding 100 people, a dread risk, which kills many people at once, could potentially wipe out one's whole group. Indeed, research found
that people's fear peaks for risks killing around 100 people but does
not increase if larger groups are killed. Fourth, fearing dread risks
can be an ecologically rational strategy.
Besides killing a large number of people at a single point in time,
dread risks reduce the number of children and young adults who would
have potentially produced offspring. Accordingly, people are more
concerned about risks killing younger, and hence more fertile, groups.
Outrage
is a strong moral emotion, involving anger over an adverse event
coupled with an attribution of blame towards someone perceived to have
failed to do what they should have done to prevent it. Outrage is the
consequence of an event, involving a strong belief that risk management
has been inadequate. Looking forward, it may greatly increase the
perceived risk from a hazard.
One of the growing areas of focus in risk management is the field of human factors
where behavioural and organizational psychology underpin our
understanding of risk based decision making. This field considers
questions such as "how do we make risk based decisions?", "why are we
irrationally more scared of sharks and terrorists than we are of motor
vehicles and medications?"
In decision theory, regret (and anticipation of regret) can play a significant part in decision-making, distinct from risk aversion (preferring the status quo in case one becomes worse off).
Framing is a fundamental problem with all forms of risk assessment. In particular, because of bounded rationality
(our brains get overloaded, so we take mental shortcuts), the risk of
extreme events is discounted because the probability is too low to
evaluate intuitively. As an example, one of the leading causes of death
is road accidents caused by drunk driving – partly because any given driver frames the problem by largely or totally ignoring the risk of a serious or fatal accident.
For instance, an extremely disturbing event (an attack by hijacking, or moral hazards)
may be ignored in analysis despite the fact it has occurred and has a
nonzero probability. Or, an event that everyone agrees is inevitable may
be ruled out of analysis due to greed or an unwillingness to admit that
it is believed to be inevitable. These human tendencies for error and wishful thinking often affect even the most rigorous applications of the scientific method and are a major concern of the philosophy of science.
Framing involves other information that affects the outcome of a
risky decision. The right prefrontal cortex has been shown to take a
more global perspective while greater left prefrontal activity relates to local or focal processing.
From the Theory of Leaky Modules
McElroy and Seta proposed that they could predictably alter the framing
effect by the selective manipulation of regional prefrontal activity
with finger tapping or monaural listening.
The result was as expected. Rightward tapping or listening had the
effect of narrowing attention such that the frame was ignored. This is a
practical way of manipulating regional cortical activation to affect
risky decisions, especially because directed tapping or listening is
easily done.
Psychology of risk taking
A
growing area of research has been to examine various psychological
aspects of risk taking. Researchers typically run randomised experiments
with a treatment and control group to ascertain the effect of different
psychological factors that may be associated with risk taking.
Thus, positive and negative feedback about past risk taking can affect
future risk taking. In one experiment, people who were led to believe
they are very competent at decision making saw more opportunities in a
risky choice and took more risks, while those led to believe they were
not very competent saw more threats and took fewer risks.
Sex differences
Sex differences in financial decision making are relevant and
significant. Numerous studies have found that women tend to be
financially more risk-averse than men and hold safer portfolios.
A May 3, 2015 article in the Wall Street Journal by Georgette Jasen
reported that "when it comes to investing, men sometimes have their way
of doing things, and women have different ways."
Scholarly research has documented systematic differences in financial
decisions such as buying investments versus insurance, donating to
ingroups versus outgroups (such as terrorism victims in Iraq versus
USA), spending in stores, and the endowment effect-or asking price for goods people have. The majority of these studies are based on the theory of agency-communion developed by David Bakan in 1966;
according to this theory, due to factors such as socialization, males
are typically more agentic (focus on self, upside potential,
aggressiveness) and females typically more communal (focus on others,
downside potential, and nurturing). This framework robustly explains
many financial decision making outcomes.
Other considerations
Risk and uncertainty
In his seminal 1921 work Risk, Uncertainty, and Profit, Frank Knight established the distinction between risk and uncertainty.
... Uncertainty must be taken in a
sense radically distinct from the familiar notion of Risk, from which it
has never been properly separated. The term "risk," as loosely used in
everyday speech and in economic discussion, really covers two things
which, functionally at least, in their causal relations to the phenomena
of economic organization, are categorically different. ... The
essential fact is that "risk" means in some cases a quantity susceptible
of measurement, while at other times it is something distinctly not of
this character; and there are far-reaching and crucial differences in
the bearings of the phenomenon depending on which of the two is really
present and operating. ... It will appear that a measurable uncertainty,
or "risk" proper, as we shall use the term, is so far different from an
unmeasurable one that it is not in effect an uncertainty at all. We ...
accordingly restrict the term "uncertainty" to cases of the
non-quantitive type.
Thus, Knightian uncertainty is immeasurable, not possible to calculate, while in the Knightian sense risk is measurable.
Another distinction between risk and uncertainty is proposed by Douglas Hubbard:
Uncertainty: The lack of complete certainty, that is, the
existence of more than one possibility. The "true"
outcome/state/result/value is not known.
Measurement of uncertainty: A set of probabilities assigned
to a set of possibilities. Example: "There is a 60% chance this market
will double in five years."
Risk: A state of uncertainty where some of the possibilities involve a loss, catastrophe, or other undesirable outcome.
Measurement of risk: A set of possibilities each with
quantified probabilities and quantified losses. Example: "There is a 40%
chance the proposed oil well will be dry with a loss of $12 million in
exploratory drilling costs."
In this sense, one may have uncertainty without risk but not risk
without uncertainty. We can be uncertain about the winner of a contest,
but unless we have some personal stake in it, we have no risk. If we bet
money on the outcome of the contest, then we have a risk. In both cases
there are more than one outcome. The measure of uncertainty refers only
to the probabilities assigned to outcomes, while the measure of risk
requires both probabilities for outcomes and losses quantified for
outcomes.
Mild Versus Wild Risk
Benoit Mandelbrot
distinguished between "mild" and "wild" risk and argued that risk
assessment and analysis must be fundamentally different for the two
types of risk. Mild risk follows normal or near-normal probability distributions, is subject to regression to the mean and the law of large numbers, and is therefore relatively predictable. Wild risk follows fat-tailed distributions, e.g., Pareto or power-law distributions,
is subject to regression to the tail (infinite mean or variance,
rendering the law of large numbers invalid or ineffective), and is
therefore difficult or impossible to predict. A common error in risk
assessment and analysis is to underestimate the wildness of risk,
assuming risk to be mild when in fact it is wild, which must be avoided
if risk assessment and analysis are to be valid and reliable, according
to Mandelbrot.
The terms risk attitude, appetite, and tolerance
are often used similarly to describe an organisation's or individual's
attitude towards risk-taking. One's attitude may be described as risk-averse, risk-neutral, or risk-seeking. Risk tolerance looks at acceptable/unacceptable deviations from what is expected.
Risk appetite looks at how much risk one is willing to accept. There
can still be deviations that are within a risk appetite. For example,
recent research finds that insured individuals are significantly likely
to divest from risky asset holdings in response to a decline in health,
controlling for variables such as income, age, and out-of-pocket medical
expenses.
Gambling is a risk-increasing investment, wherein money on hand
is risked for a possible large return, but with the possibility of
losing it all. Purchasing a lottery ticket is a very risky investment
with a high chance of no return and a small chance of a very high
return. In contrast, putting money in a bank at a defined rate of
interest is a risk-averse action that gives a guaranteed return of a
small gain and precludes other investments with possibly higher gain.
The possibility of getting no return on an investment is also known as
the rate of ruin.
Risk compensation is a theory which suggests that people typically adjust their behavior
in response to the perceived level of risk, becoming more careful where
they sense greater risk and less careful if they feel more protected. By way of example, it has been observed that motorists drove faster when wearing seatbelts and closer to the vehicle in front when the vehicles were fitted with anti-lock brakes.
Risk and autonomy
The
experience of many people who rely on human services for support is
that 'risk' is often used as a reason to prevent them from gaining
further independence or fully accessing the community, and that these
services are often unnecessarily risk averse.
"People's autonomy used to be compromised by institution walls, now
it's too often our risk management practices", according to John O'Brien.
Michael Fischer and Ewan Ferlie (2013) find that contradictions between
formal risk controls and the role of subjective factors in human
services (such as the role of emotions and ideology) can undermine
service values, so producing tensions and even intractable and 'heated'
conflict.
Anthony Giddens and Ulrich Beck argued that whilst humans have always been subjected to a level of risk – such as natural disasters – these have usually been perceived as produced by non-human forces. Modern societies, however, are exposed to risks such as pollution, that are the result of the modernization process itself. Giddens defines these two types of risks as external risks and manufactured risks. The term Risk society
was coined in the 1980s and its popularity during the 1990s was both as
a consequence of its links to trends in thinking about wider modernity,
and also to its links to popular discourse, in particular the growing
environmental concerns during the period.