Extreme risks are risks of very bad outcomes or "high consequence", but of low probability. They include the risks of terrorist attack, biosecurity risks such as the invasion of pests, and extreme natural disasters such as major earthquakes.
The estimation of the probability of extreme events is difficult because of the lack of data: they are events that have not yet happened or have happened only very rarely, so relevant data are scarce. Thus standard statistical methods are generally inapplicable.
If there is some relevant data, the probability of events at or beyond the range of the data may be estimated by the statistical methods of extreme value theory, developed for such purposes as predicting 100-year floods from a limited range of data of past floods. In such cases a mathematical function may be fitted to the data and extrapolated beyond the range of the data to estimate the probability of extreme events. The results need to be treated with caution because of the possibility that the largest values in the past are unrepresentative, and the possibility that the behavior of the system has changed.
In cases where the event of interest is very different from existing experience, there may be no relevant guide in the past data. Nassim Nicholas Taleb argues in his black swan theory that the frequency and impact of totally unexpected events is generally underestimated. With hindsight, they can be explained, but there is no prospect of predicting them.
Banks need to evaluate the risk of adverse events other than credit risks and market risks. These risks, called operational risks, include the major events most likely to cause bank failure, such as massive internal fraud. The international compliance regime for banks, Basel II, requires that such risks be quantified using a mixture of statistical theory, such as extreme value theory, and scenario analysis conducted by internal committees of experts. A bank regulator (such as the Federal Reserve in the United States) oversees the result. Negotiations between the parties result in a system that combines quantitative methods with informed and scrutinized expert opinion. This gives the potential to avoid as far as possible the problems caused by the paucity of data and the bias of pure expert opinion. [1]
Similar methods combining quantitative methods with moderated expert opinion have been used[ by whom? ] to evaluate biosecurity risks such as risks of invasive species that have potentially massive impacts on a country's economy or ecology. [2]
Finance refers to monetary resources and to the study and discipline of money, currency, assets and liabilities. As a subject of study, it is related to but distinct from economics, which is the study of the production, distribution, and consumption of goods and services. Based on the scope of financial activities in financial systems, the discipline can be divided into personal, corporate, and public finance.
Value at risk (VaR) is a measure of the risk of loss of investment/Capital. It estimates how much a set of investments might lose, given normal market conditions, in a set time period such as a day. VaR is typically used by firms and regulators in the financial industry to gauge the amount of assets needed to cover possible losses.
Financial engineering is a multidisciplinary field involving financial theory, methods of engineering, tools of mathematics and the practice of programming. It has also been defined as the application of technical methods, especially from mathematical finance and computational finance, in the practice of finance.
Nassim Nicholas Taleb is a Lebanese-American essayist, mathematical statistician, former option trader, risk analyst, and aphorist. His work concerns problems of randomness, probability, complexity, and uncertainty.
Financial risk management is the practice of protecting economic value in a firm by managing exposure to financial risk - principally operational risk, credit risk and market risk, with more specific variants as listed aside. As for risk management more generally, financial risk management requires identifying the sources of risk, measuring these, and crafting plans to mitigate them. See Finance § Risk management for an overview.
Futures techniques used in the multi-disciplinary field of futurology by futurists in Americas and Australasia, and futurology by futurologists in EU, include a diverse range of forecasting methods, including anticipatory thinking, backcasting, simulation, and visioning. Some of the anticipatory methods include, the delphi method, causal layered analysis, environmental scanning, morphological analysis, and scenario planning.
Financial risk modeling is the use of formal mathematical and econometric techniques to measure, monitor and control the market risk, credit risk, and operational risk on a firm's balance sheet, on a bank's accounting ledger of tradeable financial assets, or of a fund manager's portfolio value; see Financial risk management. Risk modeling is one of many subtasks within the broader area of financial modeling.
The following outline is provided as an overview of and topical guide to finance:
The black swan theory or theory of black swan events is a metaphor that describes an event that comes as a surprise, has a major effect, and is often inappropriately rationalized after the fact with the benefit of hindsight. The term is based on a Latin expression which presumed that black swans did not exist. The expression was used until around 1697 when Dutch mariners saw them in Australia. After this, the term was reinterpreted to mean an unforeseen and consequential event.
The RiskMetrics variance model was first established in 1989, when Sir Dennis Weatherstone, the new chairman of J.P. Morgan, asked for a daily report measuring and explaining the risks of his firm. Nearly four years later in 1992, J.P. Morgan launched the RiskMetrics methodology to the marketplace, making the substantive research and analysis that satisfied Sir Dennis Weatherstone's request freely available to all market participants.
Probability of default (PD) is a financial term describing the likelihood of a default over a particular time horizon. It provides an estimate of the likelihood that a borrower will be unable to meet its debt obligations.
Credit analysis is the method by which one calculates the creditworthiness of a business or organization. In other words, It is the evaluation of the ability of a company to honor its financial obligations. The audited financial statements of a large company might be analyzed when it issues or has issued bonds. Or, a bank may analyze the financial statements of a small business before making or renewing a commercial loan. The term refers to either case, whether the business is large or small. A credit analyst is the finance professional undertaking this role.
In economics and finance, a Taleb distribution is the statistical profile of an investment which normally provides a payoff of small positive returns, while carrying a small but significant risk of catastrophic losses. The term was coined by journalist Martin Wolf and economist John Kay to describe investments with a "high probability of a modest gain and a low probability of huge losses in any period."
Tail risk, sometimes called "fat tail risk," is the financial risk of an asset or portfolio of assets moving more than three standard deviations from its current price, above the risk of a normal distribution. Tail risks include low-probability events arising at both ends of a normal distribution curve, also known as tail events. However, as investors are generally more concerned with unexpected losses rather than gains, a debate about tail risk is focused on the left tail. Prudent asset managers are typically cautious with the tail involving losses which could damage or ruin portfolios, and not the beneficial tail of outsized gains.
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, often focusing on negative, undesirable consequences. Many different definitions have been proposed. One international standard definition of risk is the "effect of uncertainty on objectives".
Quantitative analysis is the use of mathematical and statistical methods in finance and investment management. Those working in the field are quantitative analysts (quants). Quants tend to specialize in specific areas which may include derivative structuring or pricing, risk management, investment management and other related finance occupations. The occupation is similar to those in industrial mathematics in other industries. The process usually consists of searching vast databases for patterns, such as correlations among liquid assets or price-movement patterns.
Under the Basel II guidelines, banks are allowed to use their own estimated risk parameters for the purpose of calculating regulatory capital. This is known as the internal ratings-based (IRB) approach to capital requirements for credit risk. Only banks meeting certain minimum conditions, disclosure requirements and approval from their national supervisor are allowed to use this approach in estimating capital for various exposures.
Mathematical finance, also known as quantitative finance and financial mathematics, is a field of applied mathematics, concerned with mathematical modeling in the financial field.
In marketing, Bayesian inference allows for decision making and market research evaluation under uncertainty and with limited data. The communication between marketer and market can be seen as a form of Bayesian persuasion.
Dragon king is a double metaphor for an event that is both extremely large in size or effect and born of unique origins relative to its peers. DK events are generated by or correspond to mechanisms such as positive feedback, tipping points, bifurcations, and phase transitions, that tend to occur in nonlinear and complex systems, and serve to amplify Dragon king events to extreme levels. By understanding and monitoring these dynamics, some predictability of such events may be obtained.