monte-carlo-simulation

Learning Objectives: Explain how a loss distribution is derived from an appropriate loss frequency distribution and loss severity distribution using Monte Carlo simulations. Describe the common data issues that can introduce inaccuracies and biases in the estimation of loss frequency and...

Learning Objectives: Describe and calculate VaR for linear derivatives. Describe the limitations of the delta-normal method. Explain the Monte Carlo simulation method for computing VaR and ES and identify its strengths and weaknesses. Describe the implications of correlation breakdown for a VaR...

Learning objectives: Explain the mechanics of different types of agency MBS products, including collateralized mortgage obligations (CMOs), interest-only securities (IOs), and principal-only securities (POs). Describe a dollar roll transaction and how to value a dollar roll. Describe the...

Learning objectives: Describe the basic steps to conduct a Monte Carlo simulation. Describe ways to reduce Monte Carlo sampling error. Questions: 21.5.1. Mary wants to approximate the expected value of an option. She conducts a Monte Carlo simulation and based on her initial sample size, n =...

The three approaches are 1. Parametric; aka, analytical; 2. Historical simulation; and 3. Monte Carlo simulation (MCS). The parametric approach assumes a clean function, the other two work with messy data. Historical simulation is betrayed by a histogram, MCS is betrayed by a random number...

Learning objectives: Describe the basic steps to conduct a Monte Carlo simulation. Describe ways to reduce Monte Carlo sampling error. Questions: 600.1. Although simulation methods might be employed in each of the following situations (or "use cases"), which situation below LEAST requires the...