Endogenous vs Exogenous Instability: An Out-of-Sample Comparison

Domenico Delli Gatti, Filippo Gusella and Giorgio Ricchiuti

No 11082, CESifo Working Paper Series from CESifo

Abstract: Given the unobserved nature of expectations, this paper employs latent variable analysis to examine three financial instability models and assess their out-of-sample forecasting accuracy. We compare a benchmark linear random walk model, which implies exogenous instability phenomena, with a linear state-space model and a nonlinear Markov regime-switching model, both of which postulate endogenous fluctuations phenomena due to heterogeneous behavioral heuristics. Using the S&P 500 dataset from 1990 to 2019, results confirm complex endogenous dynamics and suggest that the inclusion of behavioral nonlinearities improves the model’s predictability both in the short, medium, and long run.

Keywords: endogenous instability; exogenous instability; behavioral model; forecasting analysis (search for similar items in EconPapers)
JEL-codes: C13 C51 E37 G10 (search for similar items in EconPapers)
Date: 2024
New Economics Papers: this item is included in nep-for, nep-hme and nep-mon
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Working Paper: Endogenous vs Exogenous Instability: An Out-of-Sample Comparison (2024)
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