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At the Calculated Risk Real Estate Newsletter this week: Click on graph for larger image. MBA: Mortgage Delinquencies Increased Slightly in Q4 2024 Fannie and Freddie: Single Family Serious Delinquency Rates Increased in December Lawler: Revisions Almost Eliminate Household/Establishment Survey Employment Growth Gap 1st Look at Local Housing Markets in January • Asking Rents Mostly Unchanged Year-over-year ICE Mortgage Monitor: “Lowest calendar year home price growth of any year since 2011”
The key reports this week are January CPI and Retail sales. ----- Monday, February 10th ----- No major economic releases scheduled. ----- Tuesday, February 11th ----- 6:00 AM: NFIB Small Business Optimism Index for January. Testimony, Fed Chair Jerome Powell, Semiannual Monetary Policy Report to Congress, Before the U.S. Senate Committee on Banking, Housing, and Urban Affairs ----- Wednesday, February 12th ----- 7:00 AM ET: The Mortgage Bankers Association (MBA) will release the mortgage purchase applications index. Consumer Price Index for January from the BLS. The consensus is for 0.3% increase in CPI, and a 0.3% increase in core CPI. The consensus is for CPI to be up 2.9% year-over-year and core CPI to be up 3.2% YoY. Testimony, Fed Chair Jerome Powell, Semiannual Monetary Policy Report to Congress, Before the U.S. House Financial Services Committee ----- Thursday, February 13th ----- 8:30 AM: The initial weekly unemployment claims report will be released. The consensus is for an increase to 224 thousand from 219 thousand last week. Producer Price Index for January from the BLS. The consensus is for a 0.2% increase in PPI, and a 0.3% increase in core PPI. Q4 Quarterly Report on Household Debt and Credit ----- Friday, February 14th ----- 8:30 AM: Retail sales for January is scheduled to be released. The consensus is for a no change in retail sales. 9:15 AM: The Fed will release Industrial Production and Capacity Utilization for January. This graph shows industrial production since 1967. The consensus is for a 0.3% increase in Industrial Production, and for Capacity Utilization to increase to 77.7%.
From Manheim Consulting today: Wholesale Used-Vehicle Prices Increased in January Wholesale used-vehicle prices (on a mix, mileage, and seasonally adjusted basis) moved 0.4% higher in January compared to December, causing the Manheim Used Vehicle Value Index (MUVVI) to increase to 205.6, a gain of 0.8% from a year ago. The seasonal adjustment to the index muted the movement for the month, as non-seasonally adjusted values rose faster than seasonally adjusted values. The non-adjusted price in January increased by 0.6% compared to December, moving the unadjusted average price up 1.1% year over year. emphasis added Click on graph for larger image. The Manheim index suggests used car prices increased in January (seasonally adjusted) and were up 0.8% YoY.
Today, in the Calculated Risk Real Estate Newsletter: Lawler: Revisions Almost Eliminate Household/Establishment Survey Employment Growth Gap A brief excerpt: From housing economist Tom Lawler: Revisions Almost Eliminate Household/Establishment Survey Employment Growth Gap There is much more in the article.
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In the first five posts, I have looked at the macro numbers that drive global markets, from interest rates to risk premiums, but it is not my preferred habitat. I spend most of my time in the far less rarefied air of corporate finance and valuation, where businesses try to decide what projects to invest in, and investors attempt to estimate business value. A key tool in both endeavors is a hurdle rate – a rate of return that you determine as your required return for business and investment decisions. In this post, I will drill down to what it is that determines the hurdle rate for a business, bringing in what business it is in, how much debt it is burdened with and what geographies it operates in. The Hurdle Rate - Intuition and Uses You don't need to complete a corporate finance or valuation class to encounter hurdle rates in practice, usually taking the form of costs of equity and capital, but taking a finance class both deepens the acquaintance and ruins it. It deepens the acquaintance because you encounter hurdle rates in almost every aspect of finance, and it ruins it, by making these hurdle rates all about equations and models. A few years ago, I wrote a paper for practitioners on the cost of capital, where I described the cost of capital as the Swiss Army knife of finance, because of its many uses. In my corporate finance class, where I look at the first principles of finance that govern how you run a business, the cost of capital shows up in every aspect of corporate financial analysis: In business investing (capital budgeting and acquisition) decisions, it becomes a hurdle rate for investing, where you use it to decide whether and what to invest in, based on what you can earn on an investment, relative to the hurdle rate. In this role, the cost of capital is an opportunity cost, measuring returns you can earn on investments on equivalent risk. In business financing decisions, the cost of capital becomes an optimizing tool, where businesses look for a mix of debt and equity that reduces the cost of capital, and where matching up the debt (in terms of currency and maturity) to the assets reduces default risk and the cost of capital. In this context, the cost of capital become a measure of the cost of funding a business: In dividend decisions, i.e., the decisions of how much cash to return to owners and in what form (dividends or buybacks), the cost of capital is a divining rod. If the investments that a business is looking at earn less than the cost of capital, it is a trigger for returning more cash, and whether it should be in the form of dividends or buybacks is largely a function of what shareholders in that company prefer: The end game in corporate finance is maximizing value, and in my valuation class, where I look at businesses from the outside (as a potential investor), the cost of capital reappears again as the risk-adjusted discount rate that you use estimate the intrinsic value of a business. Much of the confusion in applying cost of capital comes from not recognizing that it morphs, depending on where it is being used. An investor looking at a company, looking at valuing the company, may attach one cost of capital to value the company, but within a company, but within a company, it may start as a funding cost, as the company seeks capital to fund its business, but when looking at investment, it becomes an opportunity cost, reflecting the risk of the investment being considered. The Hurdle Rate - Ingredients If the cost of capital is a driver of so much of what we do in corporate finance and valuation, it stands to reason that we should be clear about the ingredients that go into it. Using one of my favored structures for understanding financial decision making, a financial balance sheet, a cost of capital is composed of the cost of equity and the cost of debt, and I try to capture the essence of what we are trying to estimate with each one in the picture below: To go from abstractions about equity risk and default risk to actual costs, you have to break down the costs of equity and debt into parts, and I try to do so, in the picture below, with the factors that you underlie each piece: As you can see, most of the items in these calculations should be familiar, if you have read my first five data posts, since they are macro variables, having nothing to do with individual companies. The first is, of course, the riskfree rate, a number that varies across time (as you saw in post on US treasury rates in data update 4) and across currencies (in my post on currencies in data update 5). The second set of inputs are prices of risk, in both the equity and debt markets, with the former measured by equity risk premiums, and the latter by default spreads. In data update 2, I looked at equity risk premiums in the United States, and expanded that discussion to equity risk premiums in the rest of the world in data update 5). In data update 4, I looked at movements in corporate default spreads during 2024. There are three company-specific numbers that enter the calculation, all of which contribute to costs of capital varying across companies; Relative Equity Risk, i.e., a measure of how risky a company's equity is, relative to the average company's equity. While much of the discussion of this measure gets mired in the capital asset pricing model, and the supposed adequacies and inadequacies of beta, I think that too much is made of it, and that the model is adaptable enough to allow for other measures of relative risk. I am not a purist on this measure, and while I use betas in my computations, I am open to using alternate measures of relative equity risk. Corporate Default Risk, i.e, a measure of how much default risk there is in a company, with higher default risk translating into higher default spreads. For a fairly large subset of firms, a bond rating may stand in as this measure, but even in its absence, you have no choice but to estimate default risk. Adding to the estimation challenge is the fact that as a company borrows more money, it will play out in the default risk (increasing it), with consequences for both the cost of equity and debt (increasing both of those as well). Operating geographies: The equity risk premium for a company does not come from where it is incorporated but from where it does business, both in terms of the production of its products and services and where it generates revenue. That said, the status quo in valuation in much of the world seems to be to base the equity risk premium entirely on the country of incorporation, and I vehemently disagree with that practice: Again, I am flexible in how operating risk exposure is measured, basing it entirely on revenues for consumer product and business service companies, entirely on production for natural resource companies and a mix of revenues and production for manufacturing companies. As you can see, the elements that go into a cost of capital are dynamic and subjective, in the sense that there can be differences in how one goes about estimating them, but they cannot be figments of your imagination. The Hurdle Rate - Estimation in 2025 With that long lead in, I will lay out the estimation choices I used to estimate the costs of equity, debt and capital for the close to 48,000 firms in my sample. In making these choices, I operated under the obvious constraint of the raw data that I had on individual companies and the ease with which I could convert that data into cost of capital inputs. Riskfree rate: To allow for comparisons and consolidation across companies that operate in different currencies, I chose to estimate the costs of capital for all companies in US dollars, with the US ten-year treasury rate on January 1, 2025, as the riskfree rate. Equity Risk Premium: Much as I would have liked to compute the equity risk premium for every company, based upon its geographic operating exposure, the raw data did not lend itself easily to the computation. Consequently, I have used the equity risk premium of the country in which a company is headquartered to compute the equity risk premium for it. Relative Equity Risk: I stay with beta, notwithstanding the criticism of its effectiveness for two reasons. First, I use industry average betas, adjusted for leverage, rather than the company regression beta, because because the averages (I title them bottom up betas) are significantly better at explaining differences in returns across stocks. Second, and given my choice of industry average betas, none of the other relative risk measures come close, in terms of predictive ability. For individual companies, I do use the beta of their primary business as the beta of the company, because the raw data that I have does not allow for a breakdown into businesses. Corporate default risk: For the subset of the sample of companies with bond ratings, I use the S&P bond rating for the company to estimate the cost of debt. For the remaining companies, I use interest coverage ratios as a first measure to estimate synthetic ratings, and standard deviation in stock prices as back-up measure. Debt mix: I used the market capitalization to measure the market value of equity, and stayed with total debt (including lease debt) to estimate debt to capital and debt to equity ratios The picture below summarizes my choices: There are clearly approximations that I used in computing these global costs of capital that I would not use if I were computing a cost of capital for valuing an individual company, but this approach yields values that can yield valuable insights, especially when aggregated and averaged across groups. a. Sectors and Industries The risks of operating a business will vary widely across different sectors, and I will start by looking at the resulting differences in cost of capital, across sectors, for global companies: There are few surprises here, with technology companies facing the highest costs of capital and financials the lowest, with the former pushed up by high operating risk and a resulting reliance on equity for capital, and the latter holding on because of regulatory protection. Broken down into industries, and ranking industries from highest to lowest costs of capital, here is the list that emerges: Download industry costs of capital The numbers in these tables may be what you would expect to see, but there are a couple of powerful lessons in there that businesses ignore at their own peril. The first is that even a casual perusal of differences in costs of capital across industries indicates that they are highest in businesses with high growth potential and lowest in mature or declining businesses, bringing home again the linkage between danger and opportunity. The second is that multi-business companies should understand that the cost of capital will vary across businesses, and using one corporate cost of capital for all of them is a recipe for cross subsidization and value destruction. b. Small versus Larger firms In my third data update for this year, I took a brief look at the small cap premium, i.e, the premium that small cap stocks have historically earned over large cap stocks of equivalent risk, and commented on its disappearance over the last four decades. I heard from a few small cap investors, who argued that small cap stocks are riskier than large cap stocks, and should earn higher returns to compensate for that risk. Perhaps, but that has no bearing on whether there is a small cap premium, since the premium is a return earned over and above what you would expect to earn given risk, but I remained curious as to whether the conventional wisdom that small cap companies face higher hurdle rates is true. To answer this question, I examine the relationship between risk and market cap, breaking companies down into market cap deciles at the start of 2025, and estimating the cost of capital for companies within each decile: The results are mixed. Looking at the median costs of capital, there is no detectable pattern in the cost of capital, and the companies in the bottom decile have a lower median cost of capital (8.88%) than the median company in the sample (9.06%). That said, the safest companies in largest market cap decile have lower costs of capital than the safest companies in the smaller market capitalizations. As a generalization, if small companies are at a disadvantage when they compete against larger companies, that disadvantage is more likely to manifest in difficulties growing and a higher operating cost structure, not in a higher hurdle rate. c. Global Distribution In the final part of this analysis, I looked at the costs of capital of all publicly traded firms and played some Moneyball, looking at the distribution of costs of capital across all firms. In the graph below,I present the histogram of cost of capital, in US dollar terms, of all global companies at the start of 2025, with a breakdown of costs of capital, by region, below: I find this table to be one of the most useful pieces of data that I possess and I use it in almost every aspect of corporate finance and valuation: Cost of capital calculation: The full cost of capital calculation is not complex, but it does require inputs about operating risk, leverage and default risk that can be hard to estimate or assess for young companies or companies with little history (operating and market). For those companies, I often use the distribution to estimate the cost of capital to use in valuing the company. Thus, when I valued Uber in June 2014, I used the cost of capital (12%) at the 90th percentile of US companies, in 2014, as Uber's cost of capital. Not only did that remove a time consuming task from my to-do list, but it also allowed me to focus on the much more important questions of revenue growth and margins for a young company. Drawing on my fifth data update, where I talk about differences across currencies, this table can be easily modified into the currency of your choice, by adding differential inflation. Thus, if you are valuing an Indian IPO, in rupees, and you believe it is risky, at the start of 2025, adding an extra 2% (for the inflation differential between rupees and dollars in 2025) to the ninth decile of Indian costs of capital (12.08% in US dollars) will give you a 14.08% Indian rupee cost of capital. Fantasy hurdle rates: In my experience, many investors and companies make up hurdle rates, the former to value companies and the latter to use in investment analysis. These hurdle rates are either hopeful thinking on the part of investors who want to make that return or reflect inertia, where they were set in stone decades ago and have never been revisited. In the context of checking to see whether a valuation passes the 3P test (Is it possible? Is it plausible? Is it probable?), I do check the cost of capital used in the valuation. A valuation in January 2025, in US dollars, that uses a 15% cost of capital for a publicly traded company that is mature is fantasy (since it is in well in excess of the 90th percentile), and the rest of the valuation becomes moot. Time-varying hurdle rates: When valuing companies, I believe in maintaining consistency, and one of the places I would expect it to show up is in hurdle rates that change over time, as the company's story changes. Thus, if you are valuing a money-losing and high growth company, you would expect its cost of capital to be high, at the start of the valuation, but as you build in expectations of lower growth and profitability in future years, I would expect the hurdle rate to decrease (from close to the ninth decile in the table above towards the median). It is worth emphasizing that since my riskfree rate is always the current rate, and my equity risk premiums are implied, i.e., they are backed out from how stocks are priced, my estimates of costs of capital represent market prices for risk, not theoretical models. Thus, if looking at the table, you decide that a number (median for your region, 90th percentile in US) look too low or too high, your issues are with the market, not with me (or my assumptions). Takeaways I am sorry that this post has gone on as long as it has, but to end, there are four takeaways from looking at the data: Corporate hurdle rate: The notion that there is a corporate hurdle rate that can be used to assess investments across the company is a myth, and one with dangerous consequences. It plays out in all divisions in a multi-business company using the same (corporate) cost of capital and in acquisitions, where the acquiring firm's cost of capital is used to value the target firm. The consequences are predictable and damaging, since with this practice, safe businesses will subsidize risky businesses, and over time, making the company riskier and worse off over time. Reality check on hurdle rates: All too often, I have heard CFOs of companies, when confronted with a cost of capital calculated using market risk parameters and the company's risk profile, say that it looks too low, especially in the decade of low interest rates, or sometimes, too high, especially if they operate in an risky, high-interest rate environment. As I noted in the last section, making up hurdle rates (higher or lower than the market-conscious number) is almost never a good idea, since it violates the principle that you have live and operate in the world/market you are in, not the one you wished you were in. Hurdle rates are dynamic: In both corporate and investment settings, there is this almost desperate desire for stability in hurdle rates. I understand the pull of stability, since it is easier to run a business when hurdle rates are not volatile, but again, the market acts as a reality check. In a world of volatile interest rates and risk premia, using a cost of capital that is a constant is a sign of denial. Hurdle rates are not where business/valuation battles are won or lost: It is true that costs of capital are the D in a DCF, but they are not and should never be what makes or breaks a valuation. In my four decades of valuation, I have been badly mistaken many times, and the culprit almost always has been an error on forecasting growth, profitability or reinvestment (all of which lead into the cash flows), not the discount rate. In the same vein, I cannot think of a single great company that got to greatness because of its skill in finessing its cost of capital, and I know of plenty that are worth trillions of dollars, in spite of never having actively thought about how to optimize their costs of capital. It follows that if you are spending the bulk of your time in a capital budgeting or a valuation, estimating discount rates and debating risk premiums or betas, you have lost the script. If you are valuing a mature US company at the start of 2025, and you are in a hurry (and who isn't?), you would be well served using a cost of capital of 8.35% (the median for US companies at the start of 2025) and spending your time assessing its growth and profit prospects, and coming back to tweak the cost of capital at the end, if you have the time. YouTube Video Data Updates for 2025 Data Update 1 for 2025: The Draw (and Danger) of Data! Data Update 2 for 2025: The Party continued for US Equities Data Update 3 for 2025: The times they are a'changin'! Data Update 4 for 2025: Interest Rates, Inflation and Central Banks! Data Update 5 for 2025: It's a small world, after all! Data Update 6 for 2025: From Macro to Micro - The Hurdle Rate Question! Data Links Cost of capital, by industry grouping: US, Global, Emerging Markets, Japan, Europe, India, China) Cost of capital distribution, by industry Paper links The Cost of Capital: The Swiss Army Knife of Finance
The key reports this week are January CPI and Retail sales. ----- Monday, February 10th ----- No major economic releases scheduled. ----- Tuesday, February 11th ----- 6:00 AM: NFIB Small Business Optimism Index for January. Testimony, Fed Chair Jerome Powell, Semiannual Monetary Policy Report to Congress, Before the U.S. Senate Committee on Banking, Housing, and Urban Affairs ----- Wednesday, February 12th ----- 7:00 AM ET: The Mortgage Bankers Association (MBA) will release the mortgage purchase applications index. Consumer Price Index for January from the BLS. The consensus is for 0.3% increase in CPI, and a 0.3% increase in core CPI. The consensus is for CPI to be up 2.9% year-over-year and core CPI to be up 3.2% YoY. Testimony, Fed Chair Jerome Powell, Semiannual Monetary Policy Report to Congress, Before the U.S. House Financial Services Committee ----- Thursday, February 13th ----- 8:30 AM: The initial weekly unemployment claims report will be released. The consensus is for an increase to 224 thousand from 219 thousand last week. Producer Price Index for January from the BLS. The consensus is for a 0.2% increase in PPI, and a 0.3% increase in core PPI. Q4 Quarterly Report on Household Debt and Credit ----- Friday, February 14th ----- 8:30 AM: Retail sales for January is scheduled to be released. The consensus is for a no change in retail sales. 9:15 AM: The Fed will release Industrial Production and Capacity Utilization for January. This graph shows industrial production since 1967. The consensus is for a 0.3% increase in Industrial Production, and for Capacity Utilization to increase to 77.7%.
Plus! Thematic ETFs; Event-Driven Ads; Lagging Demand; Implementation; Labor Price Discrimination