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Lesson 06 of 06 · published

The risk-free asset — what it actually is

~25 min · risk-free

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The asset that (almost) doesn't shake

Most assets have some σ. Stocks, bonds, real estate, commodities — they all wiggle. But one class of asset is treated as almost risk-free: short-term government debt of stable countries (US Treasury bills, Korean treasury bills, German Bunds at the short end, etc.).

Why "almost"? Two reasons. First, even a 3-month T-bill has a tiny σ — interest rates can move during those 3 months. Second, governments can default in theory (rare for major economies, common for some emerging markets). The "risk-free" label is shorthand, not literal.

For practical finance math, though, we treat short-term high-quality government debt as having σ ≈ 0 and zero default risk. Its return is the risk-free rate, written r_f.

Why the risk-free rate matters

r_f shows up everywhere. It's the foundation that everything else gets compared to:

  • Discount rate. The r in TVM equations starts from r_f and adds a "risk premium" for non-risk-free cash flows. So r = r_f + premium.
  • Excess return. When measuring how a stock or fund did, you usually subtract r_f first. "5% return on a stock when T-bills paid 4%" is only 1% of excess return — that 1% is what the risk earned you, not the 5%.
  • Sharpe ratio. Track 9 — return per unit of risk, computed using excess returns over r_f.
  • CAPM. Track 9's foundational equation: E(R) = r_f + β × (E(R_m) − r_f). Right there, r_f shows up twice.
  • Risk-free portfolio anchor. Track 9 again — the efficient frontier extends through any tangent line drawn from r_f, opening up the "capital allocation line" idea.

Real numbers, real ranges

r_f isn't a fixed number — it changes with monetary policy. Some recent benchmarks (US 3-month T-bill, approximate):

  • 2010-2015: 0.0-0.1% — near zero, post-financial-crisis
  • 2018-2019: 2.0-2.4% — Fed normalization
  • 2020 (COVID): 0.1% — emergency easing
  • 2023-2024: 4.5-5.5% — Fed tightening cycle
  • 2025-2026: started declining as Fed eased — varies by month

So when finance models use r_f = 4% in 2024 and r_f = 0.1% in 2020, they're both right for their period. The number changes; the role of r_f in the math doesn't.

Why a higher r_f is bad for risky assets

This is one of the most important consequences of r_f being part of the discount rate. When r_f rises, r in equations like P = FCF / (r − g) rises too. Bigger denominator → smaller P. Higher r_f → lower asset prices, all else equal.

This is why the 2022 Fed rate-hike cycle crushed stocks and bonds simultaneously. r_f went from near-zero to 4-5% in 18 months. The discount rate on every future cash flow rose. Bond prices dropped (math is direct — Track 7). Growth stocks dropped harder than value stocks (high-growth → cash flows are way in the future → discounting hits them more). Track 7 covers the 2022 carnage in detail; this lesson is the seed.

The takeaway

r_f = the return on short-term high-quality government debt. Treated as σ ≈ 0 by convention. Foundation of every other rate (r = r_f + premium), of excess returns, of Sharpe and CAPM. Changes with central bank policy. When r_f rises, prices of everything else fall (because the denominator in valuation grows). When r_f falls, the reverse. Almost every market move has r_f doing something quietly in the background.

Exercise

  1. If r_f = 4% and a stock returned 7% last year, what's the excess return?
  2. If r_f rises from 2% to 5% (and growth expectations don't change), in the Gordon Growth model P = C/(r − g), what direction does P move? Why?
  3. Why are growth stocks more sensitive to changes in r_f than value stocks? (Hint: think about when the cash flows arrive in each.)
  4. Roughly, what was r_f in your country last week? (You can look this up — the point is to anchor the abstract concept to a real number.)

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