Investor sentiments and performance of ESG funds in emerging and developed markets.

Abstract

The niche of sustainable finance, despite relatively new, has become a mainstay in the discourse of global finance. Whilst there are multiple factors driving the research interest in this space, chief amongst this, is the purported consequentiality of sustainability concerns that is relatable to even people lacking financial knowledge. In this light, this study sought to examine the impact of investor sentiments on Environmental, Social and Governance (ESG) index returns and risk performance under bull and bear market conditions in emerging (BRICS) and developed (G7) markets. The study further examined the nature of volatility and the impact of investor sentiments, as well as the return and volatility spillovers among countries within and across the emerging and developed markets. Using the Morgan Stanley Composite Index (MSCI) ESG data from 01/10 /2007 to 31/12/2022, a composite investor sentiments (CIS) index was constructed using eight fundamental market sentiment proxies, which were further included in the empirical models employed. Firstly, employing a Markov Regime Switching Model, the study examined the impact of investor sentiment on ESG performance in bull and bear market conditions. Herein, findings of the study noted that investor sentiment impacts the performance of ESG funds in emerging markets more than in developed markets regardless of market conditions. More so, whilst the study established ESG performance varies across bull and bear conditions, from the standpoint of ESG return performance, the study established that emerging ESG markets performed better in bull market condition and developed ESG markets performed better in bear market condition. Conversely, from the dimension of ESG volatility performance, the study established that developed markets exhibited a higher volatility in bull market condition and emerging markets exhibited higher volatility in bear market condition. Secondly, adopting GARCH models such as the EGARCH, GJR-GARCH and GARCH-X models, the study evaluated the nature of volatility and the influence of investor sentiments on volatility of ESG funds in emerging and developed markets. Within this context, the research findings based on the mean equation coefficient suggest that there is a weak-form of market efficiency across emerging and developed ESG market blocs except the USA ESG market. Also, the study empirically established that based on the leverage effect, negative shocks (bad news) are more likely to increase the volatility of ESG returns than positive shocks (good news) in both emerging and developed market blocs. Additionally, the study established that although investor sentiments impacts the volatility of ESG returns regardless of market characterizations, emerging ESG markets are extensively more susceptible to investor sentiments than developed ESG markets. Thirdly, utilizing a Multivariate GARCH models such as the DCC-VARMA-AGARCH, DCCVARMA- GARCH and the CCC-VARMA-AGARCH models, the study explored the nature of return and volatility spillovers dynamics within and across emerging and developed ESG markets. In this regard, findings of the study evidenced that although there is evidence of return spillovers across emerging and developed ESG markets, ESG returns in emerging markets are likely to be adversely affected by the spillovers from developed markets. Also, the study also established that although there is evidence of return spillovers across emerging and developed markets, the developed ESG market bloc especially the USA and the EU, have significant volatility spillover influence on the volatility of emerging ESG markets. In addition to this, the findings of the study further established that negative shocks (bad news) from developed markets increases the volatility spillovers of ESG returns in emerging markets by more than positive shocks (good news), not viceversa. In general, these findings accentuate diverse implications from the standpoint of several finance theories. Most evidently, from the perspective of the Efficient Market Hypothesis (EMH) theory, the findings challenge the notion of market efficiency by suggesting that investor sentiment can influence the performance of ESG funds, indicating potential inefficiencies in pricing. Likewise, from the standpoint of behavioral finance theory, the findings emphasize the importance of psychological factors in investment decision-making, highlighting how investor sentiment drives market outcomes. Lastly, the Adaptive Market Hypothesis (AMH) theory acknowledges the dynamic nature of markets and the role of investor behavior in shaping them, suggesting that the impact of sentiment on ESG fund performance is adaptive to market conditions. This research contributes to the finance literatures in the sphere of sustainable finance and ESG investing. In particular, this study offers novel critical contributions on how investor sentiment is intertwined with the discourse of ESG performance, risk and risk spillovers across market conditions and characterizations. Given these empirical revelations, this study recommends that individual and institutional stakeholders keen on sustainability concerns and ESG investing should consider the influence of market conditions on ESG performance, the distinctiveness of ESG market characterizations with regards to returns and risk spillovers, the subsisting relationships among ESG markets as well as the overarching impact of investor sentiments on ESG performance and volatility. Thus, the empirical establishments of this research are relevant for investment decision making, risk management, global financial markets and development of sustainable finance theory.