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A computational technique that uses repeated random sampling to obtain the probability distribution of an uncertain outcome. Applied in project management to assess the impact of risk variables on project cost and schedule. Example: Project managers can simulate the total cost of a project by applying Monte Carlo Simulation to estimate the range of possible outcomes and their probabilities.

A method to predict the effect of changes in one variable on another variable. Commonly applied in finance to assess the impact of interest rate changes on bond prices. Example: Analysts can use sensitivity analysis to understand how changes in the cost of raw materials affect the final product price.

A statistical technique used to measure the maximum loss that an investment portfolio could face over a specific period of time at a given confidence level. Banks use VaR to quantify the level of financial risk within their portfolios. Example: A bank may calculate daily VaR of its trading portfolio to determine the potential maximum loss over the next trading day.

A decision-making technique that uses weighted average of possible outcomes, considering each outcome's probability. Primarily applied in project risk management. Example: If a project has a 70% chance of a $100,000 profit and a 30$50,000 loss, its EMV is $55,000.$

A graphical representation of decisions and their possible consequences. It is used to create a plan that is most likely to reach the goal. Employed extensively in strategic decision-making and project management. Example: Before launching a new product, a company may use a decision tree to determine potential market responses and their financial implications.

A risk management technique used to evaluate the resilience of financial institutions by subjecting them to hypothetical stress scenarios. Banks apply stress testing to determine their ability to withstand economic crises. Example: A bank may stress test its loan portfolio by simulating severe economic downturns to assess potential impacts on loan defaults.

Involves collecting and analyzing data to identify patterns and trends. It is widely used for market risk analysis and portfolio management. Example: An investor could use statistical analysis to understand the historical volatility of a stock and estimate its risk profile.

A process of analyzing possible future events by considering alternative outcomes. Hence, enabling an organization to anticipate the impact of different scenarios. Used often in strategic planning and financial forecasting. Example: A company may perform scenario analysis to determine how changes in the inflation rate could affect its future cash flows.

A risk assessment technique that measures the average loss over a specified time period beyond the Value at Risk. Used by investors to manage tail risk in portfolios. Example: An investment firm might use CVaR to assess the risk of extreme loss in a stock portfolio during market turmoil.

A performance measure that adjusts the return of an investment by the amount of risk taken. Financial institutions use it to compare the profitability of different business units. Example: A bank could use RAROC to evaluate the performance of its investment banking division versus its retail banking division.

A technique where historical data is used to simulate future risk scenarios. It is commonly used in finance to assess the market risk of an investment. Example: An asset manager may use historical simulation to forecast potential losses in a stock portfolio by analyzing the historical price movements.

A method for calculating operational risk by modeling loss frequency and loss severity distributions separately, and then combining them. Widely used by banks for regulatory capital calculation. Example: A financial institution might implement LDA to estimate potential operational losses due to process failures.

A branch of statistics dealing with the extreme deviations from the median of probability distributions. Utilized to assess the risk of rare, high-impact events. Example: An insurance company might use EVT to determine the pricing of catastrophic event coverage such as earthquakes or floods.

Statistical models that are used to forecast economic outcomes by accounting for various economic variables and relationships. Applied in macroeconomic risk analysis and policy decision-making. Example: A government body may use econometric models to predict the impacts of a change in interest rates on national unemployment rates.