Risk-aggregation is the aggregation of individual risks of companies, departments, or investments in the sense of risk management. [1] The main purpose of risk-aggregation is to determine the total risk scope expressed by a risk measure. [2] In addition, risk-aggregation enables the determination of the probability of severe crises. Severe crises are usually the result of combined effects of individual risks.
The risk-aggregation is essential for the risk analysis and is based on the identified, quantified and evaluated risks from the risk inventory. The risk-aggregation uses ideally the integrated business planning as database. It includes income statement, balance and cashflow. Thereby, the identified and quantified risks are assigned and combined to the individual planning positions. [3] In the context of planning the aim of risk-aggregation is to establish the effect of total risk measure on future financial key figures, covenants, and credit rating. [4] Therefore, the risk-aggregation is necessary to estimate the future situation of a project or company.
To run a risk-aggregation the relevant risks must be quantified and analyzed by the Monte Carlo method. The Monte Carlo method is appropriate because risks cannot be added like costs but risks also exert combination effects on the aggregate total risk measure. Furthermore, risky value drivers like capital cost, cashflow and probability of default can be derived from the total risk measure. [5] The risk analysis is the source of information for the company valuation in relation to the insolvency- or revenue risk. Thereby, the risk-aggregation is mandatory to decide a simulation-based company credit rating.
The Monte Carlo method is the only convenient simulation method for a risk-aggregation because the simulation can aggregate any quantity of risks with different probability distributions. In the process, the Monte Carlo method forms many future scenarios from risks and their combination effects. [6]
The result is a histogram with the frequency distribution of the desired target value such as cashflow or Earnings before interest and taxes and its realistic range over a certain period. Furthermore, many company-relevant key figures can be derived from the Monte Carlo methods such as: [7]
- Value at Risk: Indicates, at a given probability level, which loss amount will not be exceeded with this probability.
- Credit rating: Result from the proportion of scenarios that lead to overindebtedness or illiquidity.
- Expected Value: Indicates what happens on average in all future scenarios.
- Standard Deviation: Variation around the expected value.
- Risk adjusted capital: Required equity capital in the amount of the possible losses to avoid overindebtedness.
This makes it possible to determine financial key figures like cost of capital or enterprise value with reference to risks. Therefore, the risk-aggregation creates more transparency in planning security, and it is the only way to meaningfully determine risk-based financial key figures.
- Simulation method available on risknet
- ^ Stephan Eckstein/Michael Kupper/Mathias Pohl, Robust risk aggregation with neural networks, 2018, p. 1230
- ^ Frank Romeike/Hendrik Florian Löffler, Ergebnisse der Expertenstudie „Wert- und Effizienzsteigerung durch ein integriertes Risiko- und Versciherungsmanagement“,2007, p.402
- ^ Werner Gleißner, Auf nach Monte Carlo – Simulationsverfahren zur Risiko-Aggregation, 2004, p. 31
- ^ Werner Gleißner, Risikoanalyse, Risikoquantifizierung und Risikoaggregation, 2017, p. 9
- ^ Werner Gleißner, Cost of capital and probability of default in value-based risk management, 2019, p. 1250
- ^ Thomas Berger/Werner Gleißner, Integrated management systems: linking risk management and management control systems, 2018, p. 229
- ^ Werner Gleißner, Valuation Beyond CAPM: How to Calculate With Earnings Risk and Insolvency, 2020, p. 7
Risk-aggregation is the aggregation of individual risks of companies, departments, or investments in the sense of risk management. [1] The main purpose of risk-aggregation is to determine the total risk scope expressed by a risk measure. [2] In addition, risk-aggregation enables the determination of the probability of severe crises. Severe crises are usually the result of combined effects of individual risks.
The risk-aggregation is essential for the risk analysis and is based on the identified, quantified and evaluated risks from the risk inventory. The risk-aggregation uses ideally the integrated business planning as database. It includes income statement, balance and cashflow. Thereby, the identified and quantified risks are assigned and combined to the individual planning positions. [3] In the context of planning the aim of risk-aggregation is to establish the effect of total risk measure on future financial key figures, covenants, and credit rating. [4] Therefore, the risk-aggregation is necessary to estimate the future situation of a project or company.
To run a risk-aggregation the relevant risks must be quantified and analyzed by the Monte Carlo method. The Monte Carlo method is appropriate because risks cannot be added like costs but risks also exert combination effects on the aggregate total risk measure. Furthermore, risky value drivers like capital cost, cashflow and probability of default can be derived from the total risk measure. [5] The risk analysis is the source of information for the company valuation in relation to the insolvency- or revenue risk. Thereby, the risk-aggregation is mandatory to decide a simulation-based company credit rating.
The Monte Carlo method is the only convenient simulation method for a risk-aggregation because the simulation can aggregate any quantity of risks with different probability distributions. In the process, the Monte Carlo method forms many future scenarios from risks and their combination effects. [6]
The result is a histogram with the frequency distribution of the desired target value such as cashflow or Earnings before interest and taxes and its realistic range over a certain period. Furthermore, many company-relevant key figures can be derived from the Monte Carlo methods such as: [7]
- Value at Risk: Indicates, at a given probability level, which loss amount will not be exceeded with this probability.
- Credit rating: Result from the proportion of scenarios that lead to overindebtedness or illiquidity.
- Expected Value: Indicates what happens on average in all future scenarios.
- Standard Deviation: Variation around the expected value.
- Risk adjusted capital: Required equity capital in the amount of the possible losses to avoid overindebtedness.
This makes it possible to determine financial key figures like cost of capital or enterprise value with reference to risks. Therefore, the risk-aggregation creates more transparency in planning security, and it is the only way to meaningfully determine risk-based financial key figures.
- Simulation method available on risknet
- ^ Stephan Eckstein/Michael Kupper/Mathias Pohl, Robust risk aggregation with neural networks, 2018, p. 1230
- ^ Frank Romeike/Hendrik Florian Löffler, Ergebnisse der Expertenstudie „Wert- und Effizienzsteigerung durch ein integriertes Risiko- und Versciherungsmanagement“,2007, p.402
- ^ Werner Gleißner, Auf nach Monte Carlo – Simulationsverfahren zur Risiko-Aggregation, 2004, p. 31
- ^ Werner Gleißner, Risikoanalyse, Risikoquantifizierung und Risikoaggregation, 2017, p. 9
- ^ Werner Gleißner, Cost of capital and probability of default in value-based risk management, 2019, p. 1250
- ^ Thomas Berger/Werner Gleißner, Integrated management systems: linking risk management and management control systems, 2018, p. 229
- ^ Werner Gleißner, Valuation Beyond CAPM: How to Calculate With Earnings Risk and Insolvency, 2020, p. 7