San Diego Historical Replay: 2014-09 to 2017-02
Replay 30 monthly bars of a San Diego property cycle from 2014-09 to 2017-02, where prices climbed 14.8% with a tiny 0.4% drawdown. Step through each decision point, weigh the housing data, and receive an AI coach review of your simulated choices.
30 monthly bars · 6 decision points · 2014-09 to 2017-02 · Property
Key facts
Peak-to-trough drawdown of 0.4% with a 14.9% run-up.
- Max drawdown
- −0.4%
- Max run-up
- +14.9%
- Largest single-month move
- +1.3%
- 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
The market advances day by day. You only see candles up to the current day — as if you were really there.
At key decision points choose Buy / Trim / Exit / Hold. Each decision advances the timeline by one day.
After settlement you get a six-dimension score and an AI coach review. Your result enters the scenario leaderboard.
Related scenarios
- US 10-City Composite Historical Replay: 2014-09 to 2017-022014 · Lv.2
- US 20-City Composite Historical Replay: 2014-09 to 2017-022014 · Lv.2
- San Francisco Historical Replay: 2014-09 to 2017-022014 · Lv.3
- New York Historical Replay: 2014-09 to 2017-022014 · Lv.1
- Seattle Historical Replay: 2014-09 to 2017-022014 · Lv.3
- Boston Historical Replay: 2014-09 to 2017-022014 · Lv.2
Event Replay
What happened — and what it teaches
San Diego's housing market entered a sustained recovery phase in late 2014, marking the fifth distinct boom cycle replayed in this series. Over 30 monthly bars spanning September 2014 to February 2017, participants navigate a market transitioning from post-crisis stabilization to renewed optimism, with six decision points punctuating the trajectory—two of which present critical inflection moments. The scenario tests whether trainees can read evolving supply-demand dynamics, interest rate signals, and local employment trends in a market that rewarded patience and conviction.
The data reveals a steady appreciation arc: prices advanced from 203.18 to 233.18, delivering a 14.8% cumulative return over the period. Remarkably, the maximum drawdown measured just 0.4%, and the largest single-month fluctuation reached only 1.3%, reflecting an exceptionally calm trending environment. These compressed volatility metrics made the cycle deceptively simple in retrospect, yet the two critical decision points demanded clarity on entry timing and conviction sizing—choices that separated disciplined participants from reactive ones.
The episode illustrates several timeless principles: low-volatility trends can foster complacency, causing traders to underweight tail risks; disciplined position management matters more than prediction accuracy; and psychological anchoring to entry prices often disrupts exits from profitable positions. Trainees learn that even gentle, persistent moves require systematic processes to capture, and that the apparent ease of a 0.4% drawdown conceals the emotional discipline required to stay invested through minor fluctuations. This San Diego cycle serves as a laboratory for mastering conviction without overconfidence.
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