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US 10-City Composite Historical Replay: 1990-03 to 1992-08

PropertyCity IndexUSCrash1990-03 to 1992-08Difficulty 2/5FreeView charts

Replay 30 monthly bars of US 10-city property data from March 1990 through August 1992, navigating a 6.6% drawdown across six decision points. You step through each historic bar, make choices, and receive an AI coach review of your reasoning — simulated capital, education only.

30K lines
6Decision points
2Difficulty
monthlyGranularity

30 monthly bars · 6 decision points · 1990-03 to 1992-08 · Property

Key facts

Peak-to-trough drawdown of 6.6% with a 1.1% run-up.

Max drawdown
−6.6%
Max run-up
+1.1%
Largest single-month move
−0.8%
Bars
30 Monthly bars
Decision points
6

Every figure above is computed programmatically from this replay’s own candle series — no editorial input, no LLM. Methodology: Methodology

How to play
  1. The market advances day by day. You only see candles up to the current day — as if you were really there.

  2. At key decision points choose Buy / Trim / Exit / Hold. Each decision advances the timeline by one day.

  3. After settlement you get a six-dimension score and an AI coach review. Your result enters the scenario leaderboard.

Event Replay

What happened — and what it teaches

The early 1990s presented American property investors with one of the decade's most challenging environments. A recession had taken hold, casting doubt over the stability of the US 10-city composite property market. Between March 1990 and August 1992, participants would navigate 30 monthly bars of historical data across six decision points—two of them critical—while the broader economic backdrop remained uncertain.

What unfolded was a measured but persistent contraction. The index declined from 82.76 to 77.31, representing a -6.6% drawdown spread across the period. Notably, the largest single monthly move amounted to just 0.8%, indicating that the downturn unfolded gradually rather than through dramatic shocks. This slow-burn decline tested whether trainees could recognize cumulative erosion and adjust positions before losses compounded.

The scenario's greatest value lies in teaching emotional regulation under ambiguity. With no visible cliff to signal the bottom, participants had to rely on process over prediction. The two critical decision points forced choices about risk tolerance when certainty was scarce. For training purposes, this period illustrates how patience, position sizing, and psychological discipline matter more than timing genius when markets grind lower across multiple bars.