I had the pleasure of attending The Decision Quality Conference 2018 in London last week. This provided a good reminder of some of the close linkages between risk assessment and Decision Quality.
Some commentators on risk assessment consider that “heat maps” are a waste of time. This posting discusses some of their advantages and disadvantages. A much more detailed discussion is also contained in my book Business Risk and Simulation Modelling in Practice.
A question often asked is the best way to deal with modelling dependencies in risk models. The topic is in fact incredibly rich; in this post, we just recap some of the basic elements that apply in many simple cases. [Read more…] about Modelling Dependency in Risk Models: Some Basics
The new website www.valuationdecisions.com is now complete – it is an update and replacement of www.michaelrees.co.uk. The new site reflects more accurately the type of business and focus for Michael’s activities going forward, as well as allowing the integration of other activities, people, potential staff and business partners.
- Model design and best practices, including the optimisation of data structures and layout, maximising transparency, balancing complexity with flexibility, dealing with circularity, model audit and error-checking.
- Sensitivity and scenario analysis, simulation, and optimisation.
- Data manipulation and analysis.
- The use and choice of Excel functions and functionality, including advanced functions and those from all categories, as well as of VBA and its key areas of application within financial modelling.
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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.