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1990issue C081-5

Earnings yield, rate correlation and regression for equity value

The case study inverts a headline price-to-earnings ratio into a local earnings yield, sets that yield beside interest rates, then uses rolling price-to-rate correlation and a two-factor residual as dated checks on a foreign multiple.

  • Treat earnings divided by price, not price divided by earnings, as the first valuation measure, because the latter inverts the earnings-to-cost relationship.
  • Compare that earnings yield with short-term and long-term interest rates rather than judging a price-to-earnings ratio in isolation.
  • A rolling 50-month correlation can stay tight for years and then fade about a year before a later market slip.
  • A linear regression of equity prices on earnings and interest rates produces a regression-implied value that can mark when the market trades above the estimated relationship.
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A three-step hygiene check

TradersWeek editorial: before treating a foreign equity market as an obvious calamity, run a three-step valuation hygiene check. Invert the headline multiple into a local earnings yield, watch rolling price-to-rate correlation for regime decay, then read a two-factor earnings-and-rates residual as a dated warning rather than as a crash headline.

In early 1987 Japanese price-to-earnings ratios were described as well above 60 while U.S. ratios were in the low 20s, and the October 1987 decline was larger in New York than in Tokyo.

Invert the headline multiple

The case study treats earnings divided by price, not price divided by earnings, as the first valuation measure because the latter inverts the earnings-to-cost relationship. That earnings yield is the arithmetic inverse of a price-to-earnings ratio.

A price-to-earnings ratio is treated as an inverted and incomplete screen unless it is turned back into a yield and compared with local rates.

Compare the yield with local rates

The second valuation step compares that earnings rate with short-term and long-term interest rates rather than judging the multiple in isolation.

Over a six-year window, Japanese price-to-earnings ratios sat near 50 or 60 for about half the observations, a visual that looks extreme until the inverse earnings yield is placed next to Japanese rates.

Correlation analysis here is a rolling statistical measure of how tightly monthly average equity prices co-move with earnings or with interest rates, including how that tightness can fade before a later decline.

Correlations were computed on a rolling 50-month window. A value of +1 means two series move together, -1 means they move in opposite directions, and 0 means no measurable linear link.

For several years monthly average Japanese equity prices showed a correlation of about +0.8 with earnings and about -0.8 with interest rates. That tight negative price-to-rate correlation decayed about a year before the later market slip, and the plotted relationship stayed high until just before the 1990 decline.

Read the two-factor residual as a dated warning

Linear regression here is a fitted relationship that treats equity prices as the outcome and earnings plus interest rates as the explanatory inputs, producing a dated implied level against which the market can be compared.

A linear regression with equity prices as the effect and earnings plus interest rates as the causes produced a fitted value that moved below price from early 1989 as Japanese rates rose. That regression-implied value marks stretches when the market traded above the estimated relationship.

Except for a brief late-1987 stretch tied to high bond rates, the fitted series was not below price for most of the sample and in many months led price higher.

TradersWeek editorial: read the stretch when price stood above the fitted path as a dated warning, not as a crash headline.

A high multiple is not a self-explanatory break

Intermarket analysis here means reading one country's equity multiples against that country's interest-rate alternatives, and against a higher-rate market, instead of treating a foreign price-to-earnings number as self-explanatory.

The intermarket reading is that higher U.S. interest rates require higher equity earnings yields, so a low-rate Japanese market can carry high multiples without that contrast alone proving a valuation break.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
4 of 37 in the Correlation analysis track
19911-12 pp.Next on Correlation analysisName the window, then combine leadersThe correlation coefficient between Treasury bonds and a broad equity index changes with every span from 3 days to 300 days, so the calendar window has to be named before any combination is built.
All readings on this track · 37 readings
  1. 1988Constructing a lead-aware correlation coefficient
  2. 1989A precious-metal price as a changing intermarket equation
  3. 1990Two clocks for copper: a factor regime, a regression baseline, and leftover moving-average timing
  4. 1990Earnings yield, rate correlation and regression for equity value
  5. 1991Name the window, then combine leaders
  6. 1991Constructing a two-market linear correlation check
  7. 1991Constructing a commodity-bond correlation regime filter
  8. 1992Building intermarket context with linear correlation
  9. 1993Inverse-scale overlays as a gold-equity regime filter
  10. 1994Constructing seasonal slots from windows, analog years, and implied volatility
  11. 1995Pin one reference close and roll companion correlations as an overlay
  12. 1995Rolling correlation windows for shifting intermarket regimes
  13. 1998Gold as a cross-market regime barometer
  14. 1999The gold-bond inverse is a regime, not a cause
  15. 1999A nested lag test of gold leading bond yields
  16. 1999Constructing spreads from stock and intermarket correlation
  17. 2000Evaluating headline versus food-and-energy-excluded CPI as bond-yield context
  18. 2005A late EUR/USD fifth wave tested by the Bund-Treasury gap
  19. 2006Intermarket dislocation as context for short-horizon momentum
  20. 2008Map ordinary 12-month outcomes before stacking valuation, rates, and seasonality
  21. 2008A clean-energy theme inside the oil-and-energy regime
  22. 2014Quantitative-easing overlays as fragile belief regimes
  23. 2015Three intermarket checks from the late-2014 crude decline
  24. 2015Basket construction via rank, correlation, and locked rules
  25. 2015Construct a CAD-oil pair from percent-of-range Bollinger maps
  26. 2015CAD/USD and crude: first the correlation, then the band gap
  27. 2017Correlation regime versus moving-average crossover for S&P 500 exposure
  28. 2017Updating intermarket systems after correlation shifts
  29. 2017Constructing a correlation-divergence regime filter for yen and Nikkei context
  30. 2018Clustered negative troughs in an energy-index pairwise correlation
  31. 2018Filter pairwise-correlation before reading an intermarket regime
  32. 2018Moving-average supports in the March 2018 correlation shock
  33. 2020Bond spreads as an equity regime lens
  34. 2020Crash-protection folklore as a correlation regime question
  35. 2020Constructing a bounded correlation-trend-filter
  36. 2020Constructing a correlation-to-line trend filter
  37. 2020Bitcoin correlation regimes across equities and gold
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