Financial Reporting requirements often demand that estimates of value are made for illiquid assets or instruments (e.g. private equity, property, some types of bonds, and other bespoke instruments). Valuations conducted in such contexts (whether done internally or by external experts), are often “smoothed”. This generally understates volatility (and risk), resulting in a potential over-allocation of assets to such asset classes. [Read more…] about The Effects of Appraised Valuations on Volatility and Capital Allocations to Illiquid Assets
Despite the fact that the world is uncertain, this is often overlooked in forecasting activities which most often rely on a single case or a small set of scenarios. This blog briefly highlights some of the key practical benefits (both quantitative and qualitative) of using uncertainty approaches to forecasting.
In Excel, one can multiple a matrix by itself (using the MMULT function), and hence raise a matrix to any power by repeated calculations. However, there is no function to calculate partial powers (e.g. square roots) of matrices. In this blog, we describe one useful way to do so.
Recently I had the pleasure to visit Hanoi, Vietnam, to run a course on the economic evaluation of projects, taking into account the risks and uncertainties inherent in the projects. The course was built around a fully integrated hands-on exercise in which a project was evaluated using a realistic financial model which took into account the key uncertainties across the full life cycle.
Core economic and financial theory states that it is the average (mean or Expected Value) of the cash flows that should be discounted at a rate which reflects the time value of money and the systemic risks within the cash flows. However, many practitioners use a “base case” forecast that may have been provided by a management team. Such forecasts are inherently biased (either due to structural reasons or due to other biases, such as optimism, pessimism or a mix of types across the assumptions). Therefore, the issue arises as to how to use these for business valuation purposes.
The blog presents a few ideas on how to overcome (or at least reduce) some of the main organisational challenges to introducing risk modelling, as discussed in the previous blog.
The introduction of quantitative risk analysis (particularly full uncertainty models) poses a large range of organisational challenges. This post discusses a number of these, whilst a later post will discuss some of the ways to help to overcome these.
Valuation is generally regarded as a mixture of a science and an art: Whilst, generally speaking, fairly well established financial theory can be used as the basis of most valuations required in practice, there is still a variety of methods and models that can be applied, leading to the potential for several valuation outcomes, especially as estimates are often required for the values for key inputs. In this post, I cover a range of mistakes that are most frequently made in valuation analysis and modelling. [Read more…] about Common Mistakes in Valuation Modelling
There is widespread evidence that risks are very often ignored by people, organisations and businesses taking important decisions. This is despite the availability of tools (such as Excel add-ins) to simplify the modelling of risk. Many of the challenges and tools are covered in my book Business Risk and Simulation Modelling. In this post, I mention some of the areas. [Read more…] about Why Do We Ignore Risks?