The above plots three asset price bubbles (defined in hindsight as big price run-ups followed by big declines); in Nasdaq, Nikkei 225, and nominal Shiller Home Price Index.

All three were sampled on a monthly basis. Values were transformed by taking the log (to allow % change in value to scale), and further adjusting the log values so all three bubbles peaked at the same nominal value. Timescale is in month numbers, with all three aligned so their respective bubble peaks coincided in time.

The Nasdaq cuts off at the present, rebounding much better than Nikkei did after the same elapsed time after peak. Nasdaq also had a faster/steeper gain than Nikkei, and commensurately faster/steeper decline. Nominal house prices show less noise and a slower move - rather similar to Nikkei - might be expected with lower liquidity.

A story still unfolding.

My friend asked me the other day about how I said lower "noise" might be a result of lower liquidity? How do I figure?

Perhaps incorrectly: How does transaction price behavior change when average transaction time goes from seconds to months? In the case of financial instruments, large bid-ask and long time between transactions could increase volatility. OTOH volatility spikes usually correlate with volume spikes.

The smoothness of Shiller HPI may also be due to price anchoring; loans don't get funded unless the house appraises, and appraisals are mostly based on recent comparable sales.

It is also possible that HPI is more flexionistic and with less valid price discovery than Nasdaq or Nikkei. 





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