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A market sentiment indicator, behaviourally grounded, for the analysis and forecast of volatility and bubbles

Clio Ciaschini (Department of Economic and Social Sciences, Polytechnic University of Marche, Ancona, Italy)
Maria Cristina Recchioni (Department of Economic and Social Sciences, Polytechnic University of Marche, Ancona, Italy)

Review of Behavioral Finance

ISSN: 1940-5979

Article publication date: 2 November 2022

Issue publication date: 3 January 2024

297

Abstract

Purpose

This work aims at designing an indicator for detecting and forecasting price volatility and speculative bubbles in three markets dealing with agricultural and soft commodities, i.e. Intercontinental Exchange Futures market Europe, (IFEU), Intercontinental Exchange Futures market United States (IFUS) and Chicago Board of Trade (CBOT). This indicator, designed as a demand/supply odds ratio, intends to overcome the subjectivity limits embedded in sentiment indexes as the Bull and Bears ratio by the Bank of America Merrill Lynch.

Design/methodology/approach

Data evidence allows for the parameter estimation of a Jacobi diffusion process that models the demand share and leads the forecast of speculative bubbles and realised volatility. Validation of outcomes is obtained through the dynamic regression with autoregressive integrated moving average (ARIMA) error. Results are discussed in comparison with those from the traditional generalized autoregressive conditional heteroskedasticity (GARCH) models. The database is retrieved from Thomson Reuters DataStream (nearby futures daily frequency).

Findings

The empirical analysis shows that the indicator succeeds in capturing the trend of the observed volatility in the future at medium and long-time horizons. A comparison of simulations results with those obtained with the traditional GARCH models, usually adopted in forecasting the volatility trend, confirms that the indicator is able to replicate the trend also providing turning points, i.e. additional information completely neglected by the GARCH analysis.

Originality/value

The authors' commodity demand as discrete-time process is capable of replicating the observed trend in a continuous-time framework, as well as turning points. This process is suited for estimating behavioural parameters of the agents, i.e. long-term mean, speed of mean reversion and herding behaviour. These parameters are used in the forecast of speculative bubbles and realised volatility.

Keywords

Citation

Ciaschini, C. and Recchioni, M.C. (2024), "A market sentiment indicator, behaviourally grounded, for the analysis and forecast of volatility and bubbles", Review of Behavioral Finance, Vol. 16 No. 1, pp. 17-38. https://doi.org/10.1108/RBF-07-2021-0128

Publisher

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Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

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