Revisiting the Excess Volatility Puzzle Through the Lens of the Chiarella Model
Jutta G. Kurth, Adam A. Majewski, Jean-Philippe Bouchaud

TL;DR
This paper extends the Chiarella model to better calibrate long-term value drifts, enabling analysis of historical asset prices and revealing significant excess volatility and bimodal mispricings, challenging the Efficient Market Hypothesis.
Contribution
It introduces an improved calibration method for the Chiarella model that handles arbitrary long-term value drifts and applies it to historical data across multiple asset classes.
Findings
Excess volatility is large, e.g., about 4 times for stock indices.
Mispricings are often bimodal, indicating frequent deviations from fundamental values.
Results are consistent across asset classes, supporting the trend follower vs. fundamentalist dynamics.
Abstract
We amend and extend the Chiarella model of financial markets to deal with arbitrary long-term value drifts in a consistent way. This allows us to improve upon existing calibration schemes, opening the possibility of calibrating individual monthly time series instead of classes of time series. The technique is employed on spot prices of four asset classes from ca. 1800 onward (stock indices, bonds, commodities, currencies). The so-called fundamental value is a direct output of the calibration, which allows us to (a) quantify the amount of excess volatility in these markets, which we find to be large (e.g. a factor 4 for stock indices) and consistent with previous estimates; and (b) determine the distribution of mispricings (i.e. the difference between market price and value), which we find in many cases to be bimodal. Both findings are strongly at odds with the Efficient Market…
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Taxonomy
TopicsComplex Systems and Time Series Analysis · Financial Risk and Volatility Modeling · Financial Markets and Investment Strategies
