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Check rules of thumb : Investing and corporatefinance are full of rules of thumb, many of long standing. When valuing or analyzing a company, I find myself looking for and using macro data (riskpremiums, default spreads, tax rates) and industry-level data on profitability, risk and leverage.
While the universe of companies is diverse, with approximately half of all firms from emerging markets, it is more concentrated in marketcapitalization, with the US accounting for 40% of global marketcapitalization at the start of the year. Macro Data I do not report much macroeconomic data for two reasons.
In this section, I will lay out a mechanism for evaluating the effects of borrowing on the cost of funding a business, i.e., the cost of capital, and talk about why firms may under or overshoot this optimal.
Regional Breakdown My data sample for 2022 includes every publicly traded firm that is traded anywhere in the world, with a marketcapitalization that exceeds zero. A few of these variables are macro variables, but only those that I find useful in corporatefinance and valuation, and not easily accessible in public data bases.
Since I am lucky enough to have access to databases that carry data on all publicly traded stocks, I choose all publicly traded companies, with a market price that exceeds zero, as my universe, for computing all statistics. Equity RiskPremiums 2. Return on (invested) capital 2. Costs of equity & capital 4.
In corporatefinance and investing, which are areas that I work in, I find myself doing double takes as I listen to politicians, market experts and economists making statements about company and market behavior that are fairy tales, and data is often my weapon for discerning the truth.
In the first five posts, I have looked at the macro numbers that drive global markets, from interest rates to riskpremiums, but it is not my preferred habitat. The second set of inputs are prices of risk, in both the equity and debt markets, with the former measured by equity riskpremiums , and the latter by default spreads.
Since the companies involved in building the AI infrastructure are the ones that are most tangibly (and immediately) benefiting from the AI boom, they are also the companies that have seen the biggest boost in market cap, as the AI story heated up.
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