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International Monetary Fund uses Monte Carlo Simulation for Stress Testing

International Monetary Fund uses Monte Carlo Simulation for Stress Testing

An IMF working paper this month contemplates the effectiveness of lending arrangements the institution makes to various countries around the world.  The paper, “Assessing IMF Lending: A Model of Sample Selection,” seeks to identify and understand common factors that make programs effective – or not.  Using Monte Carlo simulation to assess the ...
The Efficient Frontier and Monte Carlo Software – Part II: Resampling

The Efficient Frontier and Monte Carlo Software – Part II: Resampling

Let’s move on from Part I of this blog series on the Efficient Frontier, formulated over half a century ago by Harry Markowitz, to the New Frontier postulated by investment advisor Richard Machaud.  Michaud is the author of Efficient Asset Management: A Practical Guide to Stock Portfolio Optimization and Asset Allocation (Oxford University ...
The Efficient Frontier and Monte Carlo Software – Part I: Background

The Efficient Frontier and Monte Carlo Software – Part I: Background

This article from IndexUniverse.com details just one of the ways Monte Carlo simulation can be tuned to the combined unfolding of time and risk.  First, a little background. Since Harry Markowitz won the Nobel Prize in Economics in 1990, the Efficient Frontier has been the line in the sand under which portfolio managers wiggle their toes. ...
The Efficient Frontier and Monte Carlo Software – Part III: Huang Litzenberger

The Efficient Frontier and Monte Carlo Software – Part III: Huang Litzenberger

In Part II of this series, we mentioned the existence of an analytic method to calculate the Efficient Frontier of a portfolio. Here we provide the formulas for this method. As for other methods to calculate the Efficient Frontier, this method requires knowledge of the variance-covariance matrix of the set of assets, as well as the ...
Portfolio Optimization Part II: An Overview of Markowitz-related Approaches

Portfolio Optimization Part II: An Overview of Markowitz-related Approaches

This entry follows on from Part I, describing optimal portfolio selection for portfolios where the expected return and standard deviation are sufficient to describe the decision-makers’ risk profile (i.e. the criteria to be used in deciding what is meant by “optimal”). There are several ways to calculate this optimal or “Efficient” ...
Portfolio Optimization Part I: An Introduction to Markowitz-related Approaches

Portfolio Optimization Part I: An Introduction to Markowitz-related Approaches

The topic of the selection and weighting of assets (or projects) associated with an optimal portfolio is a large and complex one.  For example in general business applications, the determination of the optimal set of companies or subsidiaries that a holding company or conglomerate should own may depend on a large number of factors (including ...
Some Best Practice Principles in Excel Modeling

Some Best Practice Principles in Excel Modeling

This blog briefly posts some fairly standard “best practice principles” in Excel modeling. The following principles are generally to be applied to Excel models (in fact, in practice, many of these may need to be varied or interpreted in a slightly different way than it might seem at first: The model should be objectives driven, that is, ...
Calculation of Pi using Simulation and Other Approximations

Calculation of Pi using Simulation and Other Approximations

Just for fun, here we talk about using Monte Carlo simulation to estimate the value of π (3.14159…). A circle of radius one will have area equal to π, and a square drawn around that circle will have area 4. When centered at the origin the circle has the equation x^2+y^2=1. Therefore if one were to conduct a simulation in which: Random ...
Analyzing Renewables in a Utility Energy Mix

Analyzing Renewables in a Utility Energy Mix

Renewables pose real challenges for utility operators, particularly solar and wind power. Renewables such as biomass, geothermal, and hydro, however, are as controllable as fossil fuel plants. How do you account for the uncertainty inherent in the more unpredictable sources of renewable energy? Using DecisionTools Suite products @RISK, ...
New and Improved Tornado Graphs in @RISK 7.5

New and Improved Tornado Graphs in @RISK 7.5

It’s often difficult to determine which factors require the most attention in business decisions which can lead to focusing on the wrong things while ignoring what’s most important.  Tornado graphs are an effective way to determine which aspects have the most impact on a business decision, so you can focus on what matters rather than ...
Software Review: @RISK Professional, in Project Manager Today

Software Review: @RISK Professional, in Project Manager Today

Project Manager Today took an in-depth look at @RISK Professional, saying: "All projects involve risks, but it’s vital to understand what those risks are and how they might affect your budget and schedule. @RISK is a well-established software tool that’s been designed to help you do that." It's a thorough review of features, with helpful ...
Is it Best to Hedge Your Lettuce? @RISK and StatTools Help Answer the Question

Is it Best to Hedge Your Lettuce? @RISK and StatTools Help Answer the Question

Agriculture is traditionally one of the highest risk economic activities. In California, many produce farm operations use a rule-of-thumb to manage their seasonal finances–often aiming to contract 80% of their crop in advance to buyers at set prices, and leaving the remaining 20% to be sold at spot prices in the open market. The rationale for ...

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