Stock Returns and Valuation Ratios at Sector Level in South Africa: The Regime-switch Modelling Approach

2020 ◽  
pp. 097215092097664
Author(s):  
Kudakwashe Joshua Chipunza ◽  
Hilary Tinotenda Muguto ◽  
Lorraine Muguto ◽  
Paul-Francois Muzindutsi
Keyword(s):  
Stock Returns ◽  
Regime Switching ◽  
Stock Exchange ◽  
Return Predictability ◽  
Stock Return Predictability ◽  
Switching Model ◽  
Johannesburg Stock Exchange ◽  
Market Regime ◽  
Markov Regime Switching Model ◽  
Valuation Ratios

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.

scholarly journals A Markov regime switching approach to estimating the volatility of Johannesburg Stock Exchange (JSE) returns

2019 ◽  
Vol 16 (1) ◽  
pp. 215-225
Author(s):  
Emmanuel K. Oseifuah ◽  
Carl H. Korkpoe
Keyword(s):  
Regime Switching ◽  
Stock Exchange ◽  
Information Criteria ◽  
Markov Regime Switching ◽  
Regime Switching Model ◽  
Switching Model ◽  
Johannesburg Stock Exchange ◽  
Industry Standard ◽  
Egarch Model ◽  
Markov Regime Switching Model

The study used the Markov regime switching model to investigate the presence of regimes in the volatility dynamics of the returns of JSE All-Share Index (ALSI). Volatility regimes are as a result of sudden changes in the underlying economy generating the market returns. In all, twelve candidate models were fitted to the data. Estimates from the regime switching model were compared to the industry standard non-switching GARCH (1,1) using the Deviance Information Criteria (DIC). The results show that the two-regime switching EGARCH model with skewed Student t innovations describes better the return of the JSE Index. Additionally, we backtest the model results in order to confirm our findings that the two-regime switching EGARCH is the best of the models for the sample period.

scholarly journals Return predictability and valuation ratios: sector-level evidence on the Johannesburg stock exchange

2020 ◽  
Vol 8 (1) ◽  
pp. 1817252
Author(s):  
Kudakwashe Joshua Chipunza ◽  
Hilary Tinotenda Muguto ◽  
Lorraine Muguto ◽  
Paul-Francois Muzindutsi
Keyword(s):  
Stock Exchange ◽  
Return Predictability ◽  
Johannesburg Stock Exchange ◽  
Valuation Ratios

scholarly journals An Empirical Study of the Effect of Investor Sentiment on Returns of Different Industries

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Chuangxia Huang ◽  
Xin Yang ◽  
Xiaoguang Yang ◽  
Hu Sheng
Keyword(s):  
Stock Returns ◽  
Regime Switching ◽  
Investor Sentiment ◽  
Regime Switching Model ◽  
Switching Model ◽  
Current Period ◽  
Lag Period ◽  
Markov Regime Switching Model ◽  
The Relationship ◽  
Positive Effect

Studies on investor sentiment are mostly focused on the stock market, but little attention has been paid to the effect of investor sentiment on the return of a specific industry. This paper constructs a proxy variable to examine the relationship between investor sentiment and the return of a specific industry, using the Principle Component Analysis, and finds that investor sentiment is positively correlated with the industry return of the current period and negatively correlated with that of one lag period; we classify investor sentiment as optimistic state and pessimistic state and find that optimistic investor sentiment has a positive effect on stock returns of most industries, while pessimistic investor sentiment has no effect on them; this paper further builds a two-state Markov regime switching model and finds that sentiment has different effect on different industries returns on different states of market.

scholarly journals Stock Return Predictability with Financial Ratios: An Empirical Study of Listed Manufacturing Companies in Sri Lanka

2018 ◽  
Vol 8 (4) ◽  
pp. 471
Author(s):  
Saradhadevi Anandasayanan
Keyword(s):  
Stock Returns ◽  
Stock Return ◽  
Predictive Power ◽  
Stock Exchange ◽  
Return Predictability ◽  
Financial Ratios ◽  
Series Data ◽  
Manufacturing Companies ◽  
Dividend Yield ◽  
Stock Return Predictability

This study attempts to investigate financial ratios’ predictive power, using the yearly time series data during the period of 2012-2017 for 33 listed manufacturing companies in Colombo Stock Exchange. This study specifically identifies the financial ratios, which are acknowledged as the predictors of stock returns in the share market, to test the stock return predictability. The financial ratios include the ratio of dividend yield, earnings per share, and earnings yield which are most useful and effective on stock return predictability in order to cover a wide range of predictions which have been used by all most all the previous researches. The stock return predictability is analyzed by regressing the dividend yield, earning per share and earning yield respectively on the yearly stock returns from 2012 to 2017. The results show high predictability power, since the R2-value is high and the coefficients are very significant and autocorrelation corrected standard errors. The results reveal that the three ratios hold a somehow predictive power regarding stock returns of the Listed Manufacturing Companies in Colombo Stock Exchange.

scholarly journals Jump Dynamics And Volatility Components For OECD Stock Returns

2013 ◽  
Vol 29 (3) ◽  
pp. 777 ◽  
Author(s):  
Khaled Guesmi ◽  
Farhan Akbar ◽  
Irfan A. Kazi ◽  
Walid Chkili
Keyword(s):  
Stock Returns ◽  
Regime Switching ◽  
Font Size ◽  
Regime Switching Model ◽  
Switching Model ◽  
Developed Markets ◽  
Political Events ◽  
High Volatility ◽  
Jump Dynamics ◽  
Markov Regime Switching Model

<span style="font-family: Times New Roman; font-size: small;"> </span><p style="margin: 0in 0.5in 0pt; line-height: 11.5pt; mso-line-height-rule: exactly;" class="MsoNormal"><span lang="EN-GB" style="font-size: 10pt;"><span style="font-family: Times New Roman;">The paper applies Markov Regime Switching Model (MRSM) to investigate the volatility behaviour of twelve OECD stock markets (U.S.A, France, Ireland, Netherlands, Spain, Denmark, Norway, Sweden, Switzerland, UK, Australia and Japan) for the period 2004-2010. The results highlight two different regimes: the first regime consist of low mean high volatility whereas the second regime is categorized by high mean low volatility. We conclude that the periods of high volatility are generally synchronous to several economic and/or political events in all the developed markets during the period under investigation.</span></span></p><span style="font-family: Times New Roman; font-size: small;"> </span>

scholarly journals Asymmetric Reactions of China’s Stock Market to Short-Term Interest Rates

2016 ◽  
Vol 8 (5) ◽  
pp. 260 ◽  
Author(s):  
Fang Fang ◽  
Weijia Dong ◽  
Xin Lv
Keyword(s):  
Stock Market ◽  
Interest Rates ◽  
Stock Returns ◽  
Regime Switching ◽  
Developed Countries ◽  
Short Term ◽  
Bear Market ◽  
Bull Market ◽  
Negative Effect ◽  
Markov Regime Switching Model

This paper investigates how China’s stock market reacts to short-term interest rates, as represented by the Shanghai Interbank Offered Rate (Shibor). We adopt the Markov Regime Switching model to divide China’s stock market into Medium, Bull and Bear market; and then examine how Shibor influences market returns and risk in different market regimes. We find that short-term interest rates have a significant negative effect on stock returns in Medium and Bull market, but could not affect stock returns in Bear market. In addition, different maturities of Shibor have different effects on stock returns. Furthermore, we find that the short-term interest rates have a negative effect on market risk in Bull market, but a positive effect in Bear market. Our findings show that China’s market is quite peculiar and distinctive from the U.S. market or other developed countries’ markets in many ways.

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