Assessing the Effect of Investor Sentiments on Housing and Stock Returns in Saudi Arabia: Application of Nonlinear ARDL Modelling

Abstract

This study investigates the symmetric and asymmetric impacts of investor sentiment on stock and real estate market returns in Saudi Arabia from 2009 to 2022. Employing the nonlinear autoregressive distributed lag (NARDL) approach, it models potential differential effects of positive and negative changes in sentiment. The empirical analysis utilizes monthly data on market returns, sentiment indices constructed through principal component analysis, and macroeconomic control variables. The results unveil significant asymmetric influences, with negative sentiment shifts exerting disproportionately greater impacts compared to positive changes. For the stock market, deteriorating sentiment steepens bearish declines, revealing an inherent negativity bias, while the housing market responds positively to worsening sentiments. The control variables representing money supply, industrial production, consumer confidence, and global uncertainty are significant return predictors. The evidence highlights the merits of tracking investor psychology to formulate countercyclical policies that could preempt sentiment-fueled mispricing. Overall, modeling asymmetries provides critical behavioral insights with salient practical implications. Dataset: DOI number or link to the deposited dataset in cases where the dataset is published or set to be published separately. If the dataset is submitted and will be published as a supplement to this paper in the journal Data, this field will be filled by the editors of the journal. In this case, please make sure to submit the dataset as a supplement when entering your manuscript into our manuscript editorial system. Dataset License: license under which the dataset is made available (CC0, CC-BY, CC-BY-SA, CC-BY-NC, etc.)