Course overview and introduction This section describes the course and explains its goals, content, level, style and structure and lists the course outcomes that participants can expect to achieve. This section introduces Monte carlo: What it is and how and why it is done. This is the spreadsheet used in the course. It contains the examples discussed in the course videos. Download the spreadsheet to try out the examples covered in the course. Histogram essentials Histograms and frequency distributions are an important part of Monte Carlo. These slides give an introduction to the histogram used in this course. This video shows a walkthrough of using the course histogram. The walkthrough example is on the spreadsheet tab Histogram_essentials. These slides illustrate two modes the histogram can run in. The simpler mode is the more commonly useful but the extended mode is also occasionally useful. This video is a walkthrough showing the two histogram modes. The walkthrough example is on the spreadsheet tab Histogram_3_column. These exercises cover the topics discussed earlier in this section. Process essentials Normal, rectangular and other distributions are used in Monte Carlo to model riskiness. These distributions can be generated by processes. This section gives an overview of processes. This video introduces how the course spreadsheet works with processes. The example given is of the simplest process: A rectangular distribution. The example discussed is on the spreadsheet tab Processes_1. Having introduced processes and histograms we can now bring the two together. This section shows the structure of a simple but complete model that uses a process and histogram. This video is a walkthrough showing how a simple Monte Carlo model is structured and operated. The example is on the spreadsheet tab Process_plus_histogram. These exercises cover the topics discussed earlier in this section. Risky growth A common Monte Carlo model of growth allows a normally distributed risk component. This section introduces that topic and contrasts that risk model with the earlier and simpler rectangular risk process. This video is a walkthrough showing how to use the course normal distribution process. The example is on the spreadsheet tab Risky_growth_process. Value at risk (VAR) We apply Monte Carlo to a practical problem - determining VAR (value at risk). This section introduces both VAR and the method we will use to determine it. This video is a walkthrough showing how to determine a simple VAR figure. The example is on the spreadsheet tab VAR. These exercises cover the topics discussed earlier in this section. Credit / default modelling Earlier examples have concerned asset price risk. In this section we introduce another class of financial risk - credit risk and show how Monte Carlo can be applied in that domain. This video is a walkthrough showing how credit default events can be modelled. The example is on the spreadsheet tab Default_modeling. Credit default exercises. Derivative modelling In this section we look at applying Monte Carlo to derivative and option modelling. This video is a precursor leading into derivative valuation. The example discussed in the video is on the spreadsheet tab Derivative. These exercises require you to build on the analysis done in the preceding video and price a range of options. Multiple risk factors Up till now we have dealt with single risk factors. This section introduces multiple risk factors and multi-asset processes. This video is a walkthrough showing how multi-asset processes are modelled in the course spreadsheet. The example discussed is on the spreadsheet tab Multi_asset. This video is a walkthrough showing how Monte Carlo can be applied to a scenario incorporating two risky assets: A South-African gold producer. The example is on the spreadsheet tab Gold_in_ZAR2. These exercises require you to analyse, interpret and extend some of the results obtained earlier. Roundup and conclusion This section is a brief roundup of some of the advantages and disadvantages of Monte Carlo. 