Methodology
Technical specification: every formula and detail →
The chart is wide: scroll sideways to follow each branch.
The Hour (H)
Where the market sits on the cycle clock, 1 to 12 o’clock.
Cycle Score (C)
C = 50 +Fundamentals (F)+Market Mood (M)
50 is the neutral midpoint; the result is clipped to 0–100.
Fundamentals (F)
What is actually happening in the market.
F = Position + Leading
Position
Standing and momentum combined into one place on the clock, because where fundamentals sit only means something alongside which way they are moving. Strength sets how firmly that place is held.
Standing (FS)
Occupancy and rent growth: where supply meets demand.
½·Z(Rent Growth)
+ ½·Z(Occupancy)
- 12-month rent growth
- Occupancy rate
Momentum (FΔ)
Which way occupancy and rents are moving: where rents head next.
½·Z(Δ Rent Growth)
+ ½·Z(Δ Occupancy)
- Rent growth change
- Occupancy change
Strength (RF)
How far from normal fundamentals are, either way.
√(F̃S² + F̃Δ²)
- Standing, blended
- Momentum, blended
Leading (FL)
Supply arriving with a lag, and the first turn in occupancy.
− 4·Z(Δ² Occupancy)
- Under construction
- Occupancy acceleration
Market Mood (M)
What investors, lenders and developers are pricing in.
M = SP + ST + SC + SR
Repricing (SP)
Closed-sale pricing: the clearest read on investor optimism.
Z(Δ Price Growth)
- Closed-sale prices
- Change in growth
Transactions (ST)
Whether buyers and sellers can agree at all: market conviction.
Z(Transaction Volume)
- Quarterly deal count
- Vs. past-year pace
Credit (SC)
Lenders’ willingness to lend: the market’s appetite for risk.
credit freeze]
- National stress
- Local deal trend
Replacement (SR)
Price vs. build cost: a warning of systemic exuberance.
(p − 0.90) ÷ 0.10)
- Price ÷ build cost
- Markets past 90th
Key terms
- Z(x) — Z-score: how unusual a reading is for this market, in standard deviations above or below its own historical average. Generally capped at ±2, except for Standing and Momentum.
- Δ / Δ² — Change over four quarters / the change in that change.
- F̃ — Blended reading: 60% this quarter, 40% last.
- Supply — Units under construction ÷ existing stock.
- p — This market's percentile of price ÷ replacement cost, against its own history.
- Hour (H) — The Cycle Score placed on the clock. On the rising side H = 6 + 6·C/100, on the falling side H = 6 − 6·C/100. A score of 0 sits at 6 o’clock and 100 at 12; 50 sits at 9 on the rising side and 3 on the falling side. The side is set by the direction of fundamentals.
- RF — Signal strength is used to do two things: dampen the influence of markets that are close to normal and cap the impact of extreme readings. It takes into account both where fundamentals are today and which direction they are moving. The farther and more decisively a market is from normal, the stronger the signal. By dividing by RF the Pythagorean geometry built into the formula caps the Position term at ±35, preventing unusually strong readings from having too much influence. At the same time, markets sitting close to normal receive less weight, since they are often in transition with no clear direction.
- SC trigger — National stress: high-yield spreads in the top 10% of their history and higher than a year ago, or bank lending standards (Fed survey) tightened by a net 40 or more. It counts for a market only when that market’s own price and deal momentum is negative, so the stress has actually reached it.
- SR trigger — Ramps from this market’s 90th percentile (0 points) to its 100th (45 points), and only when 60% or more of markets are past their own 90th at the same time. While it is on, positive SP and ST readings count as zero, so good news cannot offset it.
Research Foundations
The studies each part of the model leans on, as cited in the white paper.
Mueller (1995, 1999)
Divides the physical market cycle into four phases (recovery, expansion, hypersupply and recession) and shows how rent growth differs across them. The clock’s four quadrants follow this model.
Mueller, G. (1995). Understanding real estate’s physical and financial market cycles. Real Estate Finance 12(1); (1999). Real estate rental growth rates at different points in the physical market cycle. Journal of Real Estate Research 18(1).
Rosen and Smith (1983)
Rents adjust toward a natural vacancy rate: they rise when vacancy is below it and fall when it is above.
Rosen, K. & Smith, L. (1983). The price-adjustment process for rental housing and the natural vacancy rate. American Economic Review 73(4).
Wheaton and Torto (1988)
Vacancy relative to its structural level predicts the direction of future rent changes.
Wheaton, W. & Torto, R. (1988). Vacancy rates and the future of office rents. AREUEA Journal 16(4).
Hendershott and Shilling (1982)
The relative cost of renting and owning shifts household demand between the two tenures.
Hendershott, P. & Shilling, J. (1982). The economics of tenure choice, 1955–1979. Research in Real Estate 1.
Sinai and Souleles (2005)
Owning hedges rent risk, so rent volatility itself changes the demand for renting.
Sinai, T. & Souleles, N. (2005). Owner-occupied housing as a hedge against rent risk. Quarterly Journal of Economics 120(2).
DiPasquale and Wheaton (1992)
Links the space market, the asset market and construction: when asset values rise above the cost of building, development follows, adds to the stock and later weighs on rents.
DiPasquale, D. & Wheaton, W. (1992). The markets for real estate assets and space: a conceptual framework. AREUEA Journal 20(2).
Wheaton (1999)
Construction lags and durable stock make real estate prone to cycles, as supply decided in one environment delivers into another.
Wheaton, W. (1999). Real estate “cycles”: some fundamentals. Real Estate Economics 27(2).
Grenadier (1995, 1996)
Slow supply adjustment makes cycles persist, and developers’ option exercise can set off building cascades that overshoot demand.
Grenadier, S. (1995). The persistence of real estate cycles. JREFE 10(2); (1996). The strategic exercise of options: development cascades and overbuilding in real estate markets. Journal of Finance 51(5).
Plazzi, Torous and Valkanov (2010)
Richer valuations are followed by lower subsequent returns rather than stronger rent growth: optimism is pulled forward into price.
Plazzi, A., Torous, W. & Valkanov, R. (2010). Expected returns and expected growth in rents of commercial real estate. Review of Financial Studies 23(9).
Stein (1995)
Down-payment constraints make trading volume move with prices, so volume falls as markets weaken.
Stein, J. (1995). Prices and trading volume in the housing market: a model with down-payment effects. Quarterly Journal of Economics 110(2).
Genesove and Mayer (2001)
Loss-averse sellers hold out for past prices, so deal volume dries up before measured prices adjust.
Genesove, D. & Mayer, C. (2001). Loss aversion and seller behavior: evidence from the housing market. Quarterly Journal of Economics 116(4).
Lown and Morgan (2006)
Tightening bank lending standards lead changes in loan growth and economic activity.
Lown, C. & Morgan, D. (2006). The credit cycle and the business cycle: new findings using the Loan Officer Opinion Survey. Journal of Money, Credit and Banking 38(6).
Gilchrist and Zakrajšek (2012)
Credit spreads capture investors’ willingness to bear risk, and widening spreads foreshadow downturns.
Gilchrist, S. & Zakrajšek, E. (2012). Credit spreads and business cycle fluctuations. American Economic Review 102(4).
Tobin (1969)
Investment rises when market value exceeds replacement cost (Tobin’s q above one).
Tobin, J. (1969). A general equilibrium approach to monetary theory. Journal of Money, Credit and Banking 1(1).