Risk modeling
Encyclopedia
For risk modeling in general see risk modeling
Financial risk modeling refers to the use of formal econometric techniques to determine the aggregate risk
in a financial portfolio
. Risk modeling is one of many subtasks within the broader area of financial modeling
.
Risk modeling uses a variety of techniques including market risk
, value at risk
(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. Such risks are typically grouped into credit risk
, liquidity risk
, interest rate 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
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.
Modeling the changes by distributions with finite variance is now known to be inappropriate. Benoît Mandelbrot
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
a bit more than 1/2. Large changes up or down are more likely than what one would calculate using a Gaussian distribution with an estimated standard deviation
.
and its modeling have been under question in the light of corporate scandals in the past few years (most notably, Enron), Basel II
, the revised FAS 123R and the Sarbanes-Oxley Act
, and for their failure to predict the Financial Crash of 2008.
Risk modeling
For risk modeling in general see risk modelingFinancial risk modeling refers to the use of formal econometric techniques to determine the aggregate risk in a financial portfolio...
Financial risk modeling refers to the use of formal econometric techniques to determine the aggregate risk
Financial risk
Financial risk an umbrella term for multiple types of risk associated with financing, including financial transactions that include company loans in risk of default. Risk is a term often used to imply downside risk, meaning the uncertainty of a return and the potential for financial loss...
in a financial portfolio
Portfolio (finance)
Portfolio is a financial term denoting a collection of investments held by an investment company, hedge fund, financial institution or individual.-Definition:The term portfolio refers to any collection of financial assets such as stocks, bonds and cash...
. Risk modeling is one of many subtasks within the broader area of financial modeling
Financial modeling
Financial modeling is the task of building an abstract representation of a financial decision making situation. This is a mathematical model designed to represent the performance of a financial asset or a portfolio, of a business, a project, or any other investment...
.
Risk modeling uses a variety of techniques including market risk
Market risk
Market risk is the risk that the value of a portfolio, either an investment portfolio or a trading portfolio, will decrease due to the change in value of the market risk factors. The four standard market risk factors are stock prices, interest rates, foreign exchange rates, and commodity prices...
, value at risk
Value at risk
In financial mathematics and financial risk management, Value at Risk is a widely used risk measure of the risk of loss on a specific portfolio of financial assets...
(VaR), historical simulation
Historical simulation
Historical simulation in finance's value at risk analysis is a procedure for predicting value at risk by 'simulating' or constructing the cumulative distribution function of assets returns over time. Unlike most parametric VaR models, Historical Simulation does not assume any distribution on the...
(HS), or extreme value theory
Extreme value theory
Extreme value theory is a branch of statistics dealing with the extreme deviations from the median of probability distributions. The general theory sets out to assess the type of probability distributions generated by processes...
(EVT) in order to analyze a portfolio and make forecasts of the likely losses that would be incurred for a variety of risks. Such risks are typically grouped into credit risk
Credit risk
Credit risk is an investor's risk of loss arising from a borrower who does not make payments as promised. Such an event is called a default. Other terms for credit risk are default risk and counterparty risk....
, liquidity risk
Liquidity risk
In finance, liquidity risk is the risk that a given security or asset cannot be traded quickly enough in the market to prevent a loss .-Types of Liquidity Risk:...
, interest rate risk
Interest rate risk
Interest rate risk is the risk borne by an interest-bearing asset, such as a loan or a bond, due to variability of interest rates. In general, as rates rise, the price of a fixed rate bond will fall, and vice versa...
, and operational risk
Operational risk
An operational risk is, as the name suggests, a risk arising from execution of a company's business functions. It is a very broad concept which focuses on the risks arising from the people, systems and processes through which a company operates...
categories.
Many large financial intermediary firms use risk modeling to help portfolio managers assess the amount of capital reserves
Capital requirement
Capital requirement refers to -The standardized requirements in place for banks and other depository institutions, which determines how much capital is required to be held for a certain level of assets through regulatory agencies such as the Bank for International Settlements, Federal Deposit...
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
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...
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.
Modeling the changes by distributions with finite variance is now known to be inappropriate. Benoît Mandelbrot
Benoît Mandelbrot
Benoît B. Mandelbrot was a French American mathematician. Born in Poland, he moved to France with his family when he was a child...
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 law
A power law is a special kind of mathematical relationship between two quantities. When the frequency of an event varies as a power of some attribute of that event , the frequency is said to follow a power law. For instance, the number of cities having a certain population size is found to vary...
a bit more than 1/2. Large changes up or down are more likely than what one would calculate using a Gaussian distribution with an estimated standard deviation
Standard deviation
Standard deviation is a widely used measure of variability or diversity used in statistics and probability theory. It shows how much variation or "dispersion" there is from the average...
.
Criticism
Quantitative risk analysisRisk analysis (Business)
Risk analysis is a technique to identify and assess factors that may jeopardize the success of a project or achieving a goal.This technique also helps to define preventive measures to reduce the probability of these factors from occurring and identify countermeasures to successfully deal with these...
and its modeling have been under question in the light of corporate scandals in the past few years (most notably, Enron), Basel II
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...
, the revised FAS 123R and the Sarbanes-Oxley Act
Sarbanes-Oxley Act
The Sarbanes–Oxley Act of 2002 , also known as the 'Public Company Accounting Reform and Investor Protection Act' and 'Corporate and Auditing Accountability and Responsibility Act' and commonly called Sarbanes–Oxley, Sarbox or SOX, is a United States federal law enacted on July 30, 2002, which...
, and for their failure to predict the Financial Crash of 2008.
See also
- Black-Scholes model
- Financial risk managementFinancial risk managementFinancial risk management is the practice of creating economic value in a firm by using financial instruments to manage exposure to risk, particularly credit risk and market risk. Other types include Foreign exchange, Shape, Volatility, Sector, Liquidity, Inflation risks, etc...
- Knightian uncertaintyKnightian uncertaintyIn economics, Knightian uncertainty is risk that is immeasurable, not possible to calculate.Knightian uncertainty is named after University of Chicago economist Frank Knight , who distinguished risk and uncertainty in his work Risk, Uncertainty, and Profit:- Common-cause and special-cause :The...
- Financial modelingFinancial modelingFinancial modeling is the task of building an abstract representation of a financial decision making situation. This is a mathematical model designed to represent the performance of a financial asset or a portfolio, of a business, a project, or any other investment...
- Value-at-RiskValue at riskIn financial mathematics and financial risk management, Value at Risk is a widely used risk measure of the risk of loss on a specific portfolio of financial assets...
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 BrigoDamiano BrigoDamiano Brigo is an applied mathematician, and current Gilbart Chair of Financial Mathematics at King's College, London, known for a number of results in systems theory, probability and mathematical finance.-Main results:...
, Antonio Dalessandro, Matthias Neugebauer and Fares Triki, explaining how to use different stochastic processes for risk measurement.