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1996issue C041-9

A 1990s case on liquidity cycles, rank rotation, and cross-market sleeves

A historical quantitative book treated the liquidity cycle as its market-regime map, then used rank rotation to concentrate in a thin slice of trades and housed them in an equity, bond, and currency sleeve that could change with conditions.

  • A live quantitative basket showed that about 90 percent of profits came from about 5 percent of trades, which shifted the work from averaging many patterns to ranking the thin slice those trades shared.
  • The liquidity cycle was the core market-regime map: money moves from bonds to stocks to the real economy, and a steepening yield curve after weaker growth was treated as a weeks-to-months read on that flow.
  • When conditions were supportive, the preferred sleeve used five or six equity markets, four or five bond markets if bonds were favored, and three or four currencies, with five asset classes as a workable minimum.
  • Unlike tools were preferred to stacked versions of the same measure, and methods were stress-checked on older regimes such as 1982 or 1973-74 because a robust-looking stretch can fail when the cycle changes.
Entries in this reading3 entries

A historical book, not a single setup

The archive describes an early live application of a purely quantitative basket. About 90 percent of profits came from about 5 percent of trades. That result forced a shift from averaging many patterns to studying what the thin slice shared.

In this workflow, rank rotation means ordering candidates by those shared characteristics and concentrating in the small slice that historically produced most of the results. Diversification means spreading risk across several equity, bond, and currency markets so one trade sits inside a broader book rather than standing alone.

Liquidity as the regime map

The operator treated the liquidity cycle as a core regime map. The liquidity cycle is the sequence in which easier or tighter money first moves through bonds, then stocks, then the real economy. An expansion in liquidity during disinflation washes through the most liquid assets first.

When the economy weakens enough, the described sequence is that short-term rates fall and the yield curve steepens. That path was used as a weeks-to-months read on how liquidity is flowing through the system.

Here the yield curve is the spread between longer-term and shorter-term rates, used as a weekly-to-monthly growth and liquidity gauge. The market regime is the prevailing mix of liquidity, inflation, and growth that tells the book whether to expand, rotate, or stand aside. Asset allocation means choosing how much weight each market sleeve receives as those conditions change.

Weights across markets

A preferred allocation sleeve when conditions were supportive was five or six equity markets, four or five bond markets if bonds were favored, and three or four currencies. Five asset classes were treated as a workable minimum rather than a hard ceiling.

Unlike data and older regimes

Combining unlike data, such as a momentum tool with a volume-based tool, was presented as more useful than stacking several momentum measures. The top trades mixed quantitative signals with other information rather than more of the same.

The case argued that methods should be stress-checked on older regimes such as 1982 or 1973-74, because techniques that look robust in one stretch can fail when the cycle changes.

By late 1993 the same framework still found many individual names cheap relative to their growth even when the broad US market was not cheap on a macro basis. Most new listings were described as more stretched than the market itself.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
8 of 26 in the Asset allocation track
19971-8 pp.Next on Asset allocationRegime-aware allocation versus binary timingA timing rule should be judged against the historical window, the manager design, and a buy-and-hold benchmark, not as an isolated yes-or-no call.
All readings on this track · 26 readings
  1. 1990Stress-testing a futures sleeve across equity regimes
  2. 1990Staged sleeves from one equity forecast
  3. 1990Score a trade after allocation, diversification, and a drawdown limit
  4. 1993A three-sleeve regime map for equities, rates, and futures
  5. 1994Late-cycle breadth as an allocation exam
  6. 1994Ratio MACD crossover as a portfolio weight filter
  7. 1995Sizing a trend futures sleeve in a 1995 policy shift
  8. 1996A 1990s case on liquidity cycles, rank rotation, and cross-market sleeves
  9. 1997Regime-aware allocation versus binary timing
  10. 1998Hedge-fund sleeves under a hard drawdown limit
  11. 2010True diversification as portfolio construction
  12. 2012Regime-gated trend baskets and layered sizing
  13. 2013Score fund cost drag before the equity-versus-defensive mix
  14. 2013Cost-first fund mix in portfolio construction
  15. 2015Cost-first fund construction and the stock-bond mix
  16. 2016Audit the fund cost-stack, then set the sleeve-mix
  17. 2016Read fund listings through costs, then allocation, then diversification
  18. 2017A four-channel own-account book with signal-replacement
  19. 2017Listed REITs as a standalone portfolio sleeve
  20. 2017Cost-first stock and bond fund construction
  21. 2017Cost-first fund mix in a diversified portfolio
  22. 2018Mutual-fund costs come before returns in portfolio mixes
  23. 2018Cost gates before a stock-bond fund mix
  24. 2019Cost-stack and bond-equity mix around a trade
  25. 2019Evaluate diversification by correlation, not by the mix label
  26. 2020Cost-first fund sleeves and a stock-bond mix
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