The impact of investor sentiment on sectoral returns and volatility: Evidence from the Johannesburg stock exchange

Muguto, Hilary Tinotenda; Muguto, Lorraine; Bhayat, Azra; Ncalane, Hawaa; Jack, Kara Jasmine; Abdullah, Saadia; Nkosi, Thabile Siphesihle; Muzindutsi, Paul-François

doi:10.1080/23322039.2022.2158007

Cited by 5 publications

(3 citation statements)

References 112 publications

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“…[8] showed that surprises about inflation and unemployment rate announcements carried predictive content for the stock market volatility of the Johannesburg stock exchange (JSE), based on the Glosten-Jagannathan-Runkle-generalized autoregressive conditional heteroskedasticity (GJR-GARCH) model [14]. In addition, we also draw comparisons of our findings related to US fundamentals on the South African stock market volatility with the role of economic sentiment of the US, the influence of which on the South African stock returns variability has been reported by [15,16]. In other words, we aim to compare the influence of US fundamentals versus behavioural aspects in shaping the risk profile of the stock market of an emerging market economy.…”

Section: Introductionmentioning

confidence: 85%

Drivers of Realized Volatility for Emerging Countries with a Focus on South Africa: Fundamentals versus Sentiment

2023

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We use a quantile machine learning (random forests) approach to analyse the predictive ability of newspapers-based macroeconomic attention indexes (MAIs) on eight major fundamentals of the United States on the realized volatility of a major commodity-exporting emerging stock market, namely South Africa. We compare the performance of the MAIs with the performance of a news sentiment index (NSI) of the US. We find that both fundamentals and sentiment improve predictive performance, but the relative impact of the former is stronger. We document how the impact of fundamentals and sentiment on predictive performance varies across the quantiles of the conditional distribution of realized volatility, and across different prediction horizons. Specifically, fundamentals matter more at the extreme quantiles at short horizons, and at the median in the long-run. In addition, we report several robustness checks (involving sample period and alternative definitions of realized volatility), and indicate that the obtained results for South Africa also tend to carry over to other emerging countries such as, Brazil, China, India, and Russia. Our results have important implications for investors with volatility being an input for portfolio allocation decisions. In addition, with stock market variability also capturing financial uncertainty, its accurate prediction based on US fundamentals and sentiment also has a role in policy design to prevent possible collapse.

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Section: Introductionmentioning

confidence: 85%

Drivers of Realized Volatility for Emerging Countries with a Focus on South Africa: Fundamentals versus Sentiment

2023

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“…, 2020; Chhatwani and Mishra, 2021; Okunevičiūtė Neverauskienė et al. , 2022; Muguto et al. , 2022).…”

Section: Introductionmentioning

confidence: 99%

“…Investment decisions are subject to a variety of uncertainties, which are caused by the complex conditions of the financial market (Sallam, 2020;Khan et al, 2020;Chhatwani and Mishra, 2021; Okunevi ci ut_ e Neverauskien_ e et al, 2022; Muguto et al, 2022). These uncertainties can arise from fluctuations in sentiments and future expectations of investors (Potrich et al, 2015;Guo et al, 2023;Muguto et al, 2022;Ahmed et al, 2022;Hoekstra and G€ uler, 2022). Additionally, the existence of uncertainty shocks can be triggered by a range of unexpected events, capable of generating significant market instability.…”

Section: Introductionmentioning

confidence: 99%

Exogenous shock: hierarchical effect of the industrial entrepreneur confidence in the mist of the COVID-19 pandemic

Conceição,

Lima

2023

RBF

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PurposeIn the context of investment decisions, the intricate interplay between exogenous shocks and their influence on investor confidence significantly shapes their behaviors and, consequently, their outcomes. Investment decisions are influenced by uncertainties, exogenous shocks as well as the sentiments and confidence of investors, factors typically overlooked by decision-makers. This study will meticulously examine these multifaceted influences and discern their intricate hierarchical nuances in the sentiments of industrial entrepreneurs during the COVID-19 pandemic.Design/methodology/approachEmploying the robust framework of the generalized linear latent and mixed models (GLLAMM), this research will thoroughly investigate individual and group idiosyncrasies present in diverse data compilations. Additionally, it will delve deeply into the exogeneity of disturbances across different sectors and regions.FindingsRelevant insights gleaned from this research elucidate the adverse influence of exogenous forces, including pandemics and financial crises, on the confidence of industrial entrepreneurs. Furthermore, a significant discovery emerges in the regional analysis, revealing a notable homogeneity in the propagation patterns of industrial entrepreneurs' perceptions within the sectoral and regional context. This finding suggests a mitigation of regional effects in situations of global exogenous shocks.Originality/valueWithin the realm of academic inquiry, this study offers an innovative perspective in unveiling the intricate interaction between external shocks and their significant impacts on the sentiment of industrial entrepreneurs. Furthermore, the utilization of the robust GLLAMM captures the hierarchical dimension of this relationship, enhancing the precision of analyses. This approach provides a significant impetus for data-informed strategic directions.

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Outperforming the market: a comparison of Star and NonStar analysts’ investment strategies and recommendations

Vukovic,

Kurbonov,

Maiti

et al. 2024

Humanit Soc Sci Commun

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We employ StarMine to investigate the impact of analyst recommendations on stock performance. We test whether star-ranked analysts generate abnormal returns and outperform non-stars in short and long portfolios. Utilizing buy-and-hold calendar-time portfolio methodology, we calculate portfolio alphas using various asset pricing models, including CPM, the Fama and French 3-factor model, and the Carhart 4-factor model. Results indicate that all analyst groups can generate abnormal returns exceeding the market average. Star-ranked analysts outperform non-stars in short portfolios by 0.5523% in monthly alpha, though no significant difference exists in long portfolio alphas. We also conduct regressor endogeneity tests and explore investor sentiment mechanisms by utilizing the GARCH model and frequency-domain causality analysis, with NASDAQ as a proxy for investor sentiment. These tests reveal that the momentum factor is exogenous, and investor sentiments have a statistically significant positive effect on stock return volatility, with changes occurring between 5 and 10 days. This research underscores the value of analyst insights for investors, validates StarMine’s ranking effectiveness, and suggests market participants can benefit from incorporating analyst recommendations into their investment decisions. Our study makes a significant contribution to the existing literature by introducing a novel approach to understanding investor sentiment mechanisms through a causality model.

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The impact of investor sentiment on sectoral returns and volatility: Evidence from the Johannesburg stock exchange

Cited by 5 publications

References 112 publications

Drivers of Realized Volatility for Emerging Countries with a Focus on South Africa: Fundamentals versus Sentiment

Drivers of Realized Volatility for Emerging Countries with a Focus on South Africa: Fundamentals versus Sentiment

Exogenous shock: hierarchical effect of the industrial entrepreneur confidence in the mist of the COVID-19 pandemic

Outperforming the market: a comparison of Star and NonStar analysts’ investment strategies and recommendations

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