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Beta & Risk 1. Equity RiskPremiums 2. EBIT & EBITDA multiple s 5. Working capital needs Thus, I compute pricing multiples based on revenues (EV to Sales, Price to Sales), earnings (PE, PEG), book value (PBV, EV to Invested Capital) or cash flow proxies (EV to EBITDA). Return on Equity 1. Debt Details 1.
In my last three posts, I looked at the macro (equity riskpremiums, default spreads, risk free rates) and micro (company risk measures) that feed into the expected returns we demand on investments, and argued that these expected returns become hurdle rates for businesses, in the form of costs of equity and capital.
By the same token, it is impossible to use a pricing metric (PE or EV to EBITDA), without a sense of the cross sectional distribution of that metric at the time. For example, I have seen it asserted that a stock that trades at less than book value is cheap or that a stock that trades at more than twenty times EBITDA is expensive.
Concept of notional interest : It is proposed to introduce notional interest, the idea of which is to allow the deduction during 10 consecutive years of this "synthetic" interest, within the famous limit of 30% of the company's EBITDA. riskpremium if the company is an SME as defined by European law).
In short, if you don't like betas and have disdain for modern portfolio theory, your choice should not be to abandon risk measurement all together, but to come up with an alternative risk measure that is more in sync with your view of the world.
After the 2008 market crisis, I resolved that I would be far more organized in my assessments and updating of equity riskpremiums, in the United States and abroad, as I looked at the damage that can be inflicted on intrinsic value by significant shifts in riskpremiums, i.e., my definition of a crisis.
Thus, as you peruse my historical data on implied equity riskpremiums or PE ratios for the S&P 500 over time, you may be tempted to compute averages and use them in your investment strategies, or use my industry averages for debt ratios and pricing multiples as the target for every company in the peer group, but you should hold back.
Staying with the safety theme, I looked at US companies, broken down by debt burden (measured as debt to EBITDA): On this dimension, the numbers actually push against the flight to safety hypothesis, since the companies with the least debt performed worse than those with the most debt.
In this post, I will expand my analysis of data in 2024, which has a been mostly US-centric in the first four of my posts, and use that data to take you on my version of the Disney ride, but on this trip, I have no choice but to face the world as is, with all of the chaos it includes, with tariffs and trade wars looming.
Measuring the Debt Burden With that tradeoff in place, we are ready to examine how it played out in 2024, by looking at how much companies around the world borrowed to fund their operations. Note that the divergence between book and market debt ratios in the last two columns varies widely across sectors and regions.
Global Finance: What surprised you in 2024? In the second quarter, growth in Ebitda [earnings before interest, taxes, depreciation and amortization] outpaced interest expense growth for high-yield corporates. There are certain sectors that we think are offering better risk/reward. That’s a level we haven’t seen since 2005.
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