Financial risk modeling is the use of formal mathematical and econometric techniques to measure, monitor and control the

market risk Market risk is the risk of losses in positions arising from movements in market variables like prices and volatility. There is no unique classification as each classification may refer to different aspects of market risk. Nevertheless, the mos ...

credit risk A credit risk is risk of default on a debt that may arise from a borrower failing to make required payments. In the first resort, the risk is that of the lender and includes lost principal and interest, disruption to cash flows, and increased ...

, and operational risk on a firm's balance sheet, on a bank's

trading book The Fundamental Review of the Trading Book (FRTB), is a set of proposals by the Basel Committee on Banking Supervision for a new market risk-related capital requirement for banks. Background The reform, which is part of Basel III, is one of t ...

, or re a fund manager's portfolio value; see Financial risk management. Risk modeling is one of many subtasks within the broader area of financial modeling.

Application

Risk modeling uses a variety of techniques including

value at risk Value at risk (VaR) is a measure of the risk of loss for investments. It estimates how much a set of investments might lose (with a given probability), given normal market conditions, in a set time period such as a day. VaR is typically used by ...

(VaR), historical simulation (HS), or extreme value theory (EVT) in order to analyze a portfolio and make forecasts of the likely losses that would be incurred for a variety of risks. As above, such risks are typically grouped into

model risk In finance, model risk is the risk of loss resulting from using insufficiently accurate models to make decisions, originally and frequently in the context of valuing financial securities. However, model risk is more and more prevalent in activities ...

, liquidity risk, and operational risk categories. Many large financial intermediary firms use risk modeling to help portfolio managers assess the amount of capital reserves to maintain, and to help guide their purchases and sales of various classes of financial assets. Formal risk modeling is required under the

Basel II Basel II is the second of the Basel Accords, which are recommendations on banking laws and regulations issued by the Basel Committee on Banking Supervision. It is now extended and partially superseded by Basel III. The Basel II Accord was publi ...

proposal for all the major international banking institutions by the various national depository institution regulators. In the past, risk analysis was done qualitatively but now with the advent of powerful computing software, quantitative risk analysis can be done quickly and effortlessly.

Criticism

Modeling the changes by distributions with finite variance is now known to be inappropriate.

Benoît Mandelbrot Benoit B. Mandelbrot (20 November 1924 – 14 October 2010) was a Polish-born French-American mathematician and polymath with broad interests in the practical sciences, especially regarding what he labeled as "the art of roughness" of phy ...

found in the 1960s that changes in prices in financial markets do not follow a Gaussian distribution, but are rather modeled better by Lévy stable distributions. The scale of change, or volatility, depends on the length of the time interval to a

power Power most often refers to: * Power (physics), meaning "rate of doing work" ** Engine power, the power put out by an engine ** Electric power * Power (social and political), the ability to influence people or events ** Abusive power Power may ...

a bit more than 1/2. Large changes up or down, also called ''

fat tails A fat-tailed distribution is a probability distribution that exhibits a large skewness or kurtosis, relative to that of either a normal distribution or an exponential distribution. In common usage, the terms fat-tailed and heavy-tailed are somet ...

'', are more likely than what one would calculate using a Gaussian distribution with an estimated

standard deviation In statistics, the standard deviation is a measure of the amount of variation or dispersion of a set of values. A low standard deviation indicates that the values tend to be close to the mean (also called the expected value) of the set, whil ...

. Quantitative risk analysis and its modeling have been under question in the light of corporate scandals in the past few years (most notably, Enron),

, the revised FAS 123R and the

Sarbanes–Oxley Act The Sarbanes–Oxley Act of 2002 is a United States federal law that mandates certain practices in financial record keeping and reporting for corporations. The act, (), also known as the "Public Company Accounting Reform and Investor Protecti ...

, and for their failure to predict the financial crash of 2008. From The Economist print edition. Rapid development of financial innovations lead to sophisticated models that are based on a set of assumptions. These models are usually prone to

. There are several approaches to deal with model uncertainty. Jokhadze and Schmidt (2018) propose practical model risk measurement framework based on Bayesian calculation. They introduce superposed risk measures that enables consistent market and model risk measurement.

Bibliography

* * Machina, Mark J., and Michael Rothschild (1987). "Risk," '' The New Palgrave: A Dictionary of Economics'', v. 4, pp. 201–206. *

References

External links

Risk World
is a web site devoted to risk, with a collection of books.
A Stochastic Processes toolkit for Risk Management
at SSNR.com is a tutorial paper by Damiano Brigo, Antonio Dalessandro, Matthias Neugebauer and Fares Triki, explaining how to use different stochastic processes for risk measurement. {{Financial risk Actuarial science

Application

Criticism

See also

Bibliography

References

External links