About This Chapter
Value at Risk - Chapter Summary
In this chapter, you'll find short easy-to-understand lessons on value at risk to help you fully understand these concepts. Subjects covered here include risk exposure and the key elements of value at risk. Feel free to go back and review the lessons as many times as needed to ensure your comprehension. The lesson quizzes and chapter test also help to identify any areas where you're struggling and might need to focus your attention. If you still have questions, reach out to one of our experts through the Dashboard. After completing this chapter, you should be able to:
- Define risk exposure, its analysis and evaluation
- Outline the key elements of value at risk
- Calculate value at risk using the variance-covariance method
- Discuss the historical simulation for calculating value at risk
- Use the Monte Carlo simulation in risk management
- Detail method comparisons and overall limitations for value at risk
1. Key Elements of Value at Risk
Along with the return they hope to get, investors are also concerned with the risk of losing big dollars. Value at Risk (VaR) is a set of statistical tools that allow investors to quantify risk. Let's look at what is needed to use VaR tools.
2. Value at Risk: Method Comparisons & Overall Limitations
Investors often worry about the risk of losing big dollars. Value at risk (VAR) tools give them a way to approximate how much those losses might be with a certain confidence level. Let's go through three ways to calculate VAR.
3. Historical Simulation for Calculating Value at Risk
Investors like to hear about the prospects for big gains in investments, but what about the risk for big losses? Value at Risk tools can quantify the answer. We will illustrate the historical simulation method with an example and explanation.
4. Variance-Covariance Method for Calculating Value at Risk
Investors get excited about the profit opportunities for investments, but they need to consider the risk of big losses too. We will consider the variance-covariance method of calculating value at risk, which quantifies the chances for big losses.
5. Using the Monte Carlo Simulation in Risk Management
In this lesson, students will learn how the Monte Carlo simulation enables testing of preliminary task estimates to help reduce project uncertainty and risk.
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Other chapters within the Finance 305: Risk Management course
- Foundations of Risk & Risk Management
- Enterprise-Level Risk
- Investment Risks
- Identifying Financial Risk
- Risk Measurement & Metrics
- Risks in Planning & Accounting
- Regulatory Responses to Risk Management
- Insurance Solutions in Risk Management
- Decision Making, Biases & Risk
- Required Assignments for Finance 305