Volatility is an important component of asset pricing; an increase in volatility on markets can trigger changes in the risk distribution of financial assets. In conventional financial theory, investors are considered to be rational and any changes in relevant risk are assumed to be a result of the movement in fundamental factors. However, herein this study, it is hypothesized that there are movements in risk that are driven by volatility linked to sentiment-driven noise trader activity whose patterns are irreconcilable with changes in fundamental factors. This assertion is tested using a daily sentiment composite index constructed from a set of proxies and Generalised Autoregressive Conditional Heteroscedasticity models on the South African market over a period spanning July 2002 to June 2018. The results show that there is a significant connection between investor sentiment and stock return volatility which shows that behavioural finance can significantly explain the behaviour of stock returns on the Johannesburg Stock Exchange. It is, thus, recommended that due to the inadequacies of popular asset pricing models such as the Capital Asset Pricing Model, consideration should be made towards augmenting these asset pricing models with a sentiment risk factor.
The efficient market hypothesis describes an efficient market as one in which investors cannot consistently predict stock returns because prices instantly reflect all the information flowing into the market. However, return predictability has been documented in many markets. This study tests the predictability of returns using two valuation ratios-the dividend and earnings yields-on the South African market, at both aggregated and sectoral level. Unlike most studies in South Africa, this study employs an apposite present value model, accounts for structural breaks and investigates the non-linearity of the relationship between stock returns and valuation ratios. The results show that returns are predictable at both aggregated and sectoral levels. This finding has implications for market efficiency through enhanced price discovery which, in turn, has implications for investment and portfolio management. However, it should be noted that statistical significance may not ABOUT THE AUTHORS Kudakwashe Joshua Chipunza is a former postgraduate student at the University of KwaZulu-Natal in the School of Accounting, Economics and Finance. His research interests include financial markets, financial inclusion and development finance.Hilary Tinotenda Muguto is a PhD candidate at the University of KwaZulu-Natal under the HEARD division. His research interests include healthcare equity and finance, financial markets, behavioural finance, investment analysis and development economics.
There is mounting evidence of stock return predictability based on valuation ratios across various stock markets. Most studies in this regard assume that the link between stock returns and valuation ratios is constant and linear. Yet, return predictability may vary according to the prevailing market regime. Accordingly, this study investigated whether the dividend and price-earnings valuation ratios predict returns on six sector indices on the Johannesburg Stock Exchange and whether that predictability is dependent on the prevailing market regime. The study employed a Markov regime-switching model over a sample period spanning from 1996:01 to 2018:12. The results showed that in most sectors, predictability was present, and its significance was dependent on whether the market was in a bullish or bearish regime. These findings are useful to investors who use valuation ratios to predict returns and adjust portfolios in various sectors across different market regimes on the South African market.
While prior studies have examined the predictive effect of macroeconomic and country risk components on property stock index dynamics, limited explanations exist in the literature regarding the time-varying effect of investor sentiment on housing prices. Accordingly, this study assesses the impact of investor sentiment on housing properties’ returns and the effect of investor sentiment on the conditional volatility of housing price indices under different market conditions, using GARCH, GJR-GARCH, E-GARCH and Markov-switching VAR models. We found investor sentiment to significantly impact the risk premium of the property returns, where property returns increased with positive changes in investor sentiment, and conditional volatility of property returns decreased with the same changes in investor sentiment. Investor sentiment exerts positive predictive influences on the prices of small and medium houses, in both bullish and bearish market conditions but does not affect the large housing market segment. This makes the implementation of risk-related diversification across small and medium real estate portfolios more effective than large real estate portfolios. Our findings show that investor sentiment is a plausible driver of mass investor redemption actions under conditions of uncertainty.
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