Friday, March 22, 2013
Monday, December 3, 2012
6:47 AM 60 comments
The operating, or “fundamental,” risk of a company is the risk a company faces because of the business it is in. For example, the profits a firm makes depend on the demand for its goods and the costs of producing the goods, so it inherently faces the risk that costs could increase and/or demand could fall, which would affect the profits of the firm.
Operating risks result from the investment decision of the firm, and are separate from financial risk, which results from the financing decision. One way to measure operating risk is through activity analysis, which studies how the operating activities of the company generate profits, see below.
Fundamental Risk and Beta
A different measure of risk, beta, is based on stock returns. It measures the sensitivity of a stock’s return to the market as a whole. In its pure form, it does not pay attention to fundamentals. However, people have developed the concept of a “fundamental beta” which takes into account information such as operating and financial risk. One argument in favor of this approach is that beta typically is calculated using historical data, while fundamentals provide information about the future performance of a firm.
So one question you can ask is whether beta reflects fundamental risk. For example, do firms with high operating risk have high betas, or more broadly, if there is a systematic relationship between beta and fundamentals.
Operating risk in “Activity Analysis” is measured by the “Degree of Operating Leverage.” The ideas underlying this measure can be developed as follows. From the firm’s financial statements we can first estimate a firm’s Earnings Before Interest and Taxes (EBIT) which provides a measure of the operating income for a firm. One measure of operating risk is the Degree of Operating Leverage (DOL) defined by
This definition is related to the concept of elasticity in economics: it measures the percentage change of one variable due to a percentage change in another. So here, operating risk is defined as the elasticity of a firm’s EBIT to Sales Revenue.
Why is this measure of operating risk? Because it tells you how sensitive profits are to changes in sales. If they are very sensitive, then it could mean, for example, that the firm has high fixed costs, so it is more exposed to a downturn in sales than a firm with low fixed costs. Numerically, consider a firm that has a fixed cost of $50m and then a variable cost of $1 per unit. If it sells 100m units at $2 each, it has a profit of $50m (200m in revenue minus 100m in variable costs minus 50m in fixed costs). If sales drop by 10% to 90m units, profit drops to 180m – 90m – 50m = 40m, which is a 20% drop in profit. If the same firm had zero fixed costs, its profit would drop by 10% if sales dropped by 10%.
In the lesson, you will learn how to calculate the DOL for Wal-Mart and Intel. Then, you will compare them to the betas, and see if a higher DOL is associated with a higher beta. At the end of the lesson is an exercise that lets you conduct a more systematic analysis of the relationship between operating risk and beta.
To access the lesson, from the FSA module, simply select it from the Lessons menu:
6:44 AM 116 comments
Big data refers to the amount of data a typical organization now processes to solve business problems. This rapidly developing area is reshaping approaches to business education as has recently been discussed in Business Education Journals such as BizEd (November/December 2012). For example, in their lead article “Where Technology meets Business” it was observed that:
“… in today’s world, where everyone can buy databases, technology alone isn’t a competitive advantage. The advantage rests in how an organization uses it. …. Tomorrow’s CEOs won’t need to connect wires and switches---but they will need to connect the dots…”
The Interactive Financial Statement Analysis (IFSA) is designed to meet these demands. First, it provides immediate access to big data. This data includes the interactive financial reports now required by the SEC from publicly listed corporations. Second, IFSA combines big data with technology to provide the conceptual framework necessary for connecting the dots. This conceptual framework steps you through a structured and visual approach to understanding a company from the financial data it generates. These steps include:
· Analyzing financial reports including the business model and strategy
· Common Size Analysis (horizontal and vertical analysis)
· Analyzing Profitability
· Analyzing Operations
· Analyzing Risk
· Analyzing Reporting Quality
· Analyzing price ratios to connect the dots between fundamentals and returns
Today’s business environment places increasing demands on the user to combine business analytics with big data because the sheer complexity of the problem forces a user to understand the underlying economic drivers of the data. In the blogs on this site we illustrate how business analytics lets you work with big data to generate increasingly finer information. For example, Understanding the Degree of Operating Leverage blog introduces you to the problem of analyzing operating risk. This is the risk associated with operating leverage, measured by combining business analytics with the horizontal analysis of a corporation’s cost behavior. The technology lets you pull of this analysis quickly for any publicly listed corporation and its competitors, but as the quote in the introduction asserts, the comparative advantage is not created from the database and the technology, but from knowing how to use this information. The Interactive Financial Statement Module shows you how to acquire these skills -- by doing!