scholarly journals Investor sentiment, optimism and excess stock market returns. Evidence from emerging markets

2014 ◽  
Vol 10 (4) ◽  
pp. 362-373 ◽  
Author(s):  
Karolina Daszynska-Zygadlo ◽  
Aleksandra Szpulak ◽  
Adam Szyszka
Keyword(s):  
Stock Market ◽  
Emerging Markets ◽  
Investor Sentiment ◽  
Market Returns ◽  
Stock Market Returns

Revisiting Macroeconomy–Stock Market Relationship During Times of Economic Crisis: A Study of Emerging Markets

2017 ◽  
Vol 13 (1-2) ◽  
pp. 52-69
Author(s):  
Gagan Deep Sharma ◽  
Mrinalini Srivastava ◽  
Mansi Jain
Keyword(s):  
Latin America ◽  
Financial Crisis ◽  
Stock Market ◽  
Emerging Markets ◽  
Economic Crisis ◽  
Global Financial Crisis ◽  
Market Returns ◽  
Stock Market Returns ◽  
Macroeconomic Variables ◽  
The Relationship

This article examines the relationship between six macroeconomic variables and stock market returns of 13 emerging markets from Latin America, Europe, Africa and Asia in the context of global financial crisis of 2008. The findings reveal some commonality in determination and variation of returns with macroeconomic variables from pre-crisis (1st January 2005–31st March 2009) to post-crisis period (1st April 2009–31st March 2016). Further, results show co-integration among most of the macroeconomic variables depicting significant implications for investors and policymakers.

LONG-TERM MEMORY IN EMERGING MARKETS: EVIDENCE FROM THE CHINESE STOCK MARKET

2006 ◽  
Vol 05 (03) ◽  
pp. 495-501 ◽  
Author(s):  
CHAOQUN MA ◽  
HONGQUAN LI ◽  
LIN ZOU ◽  
ZHIJIAN WU
Keyword(s):  
Stock Market ◽  
Emerging Markets ◽  
Emerging Market ◽  
Long Term Memory ◽  
Chinese Stock Market ◽  
Market Returns ◽  
Stock Market Returns ◽  
Term Memory ◽  
Rescaled Range Analysis

The notion of long-term memory has received considerable attention in empirical finance. This paper makes two main contributions. First one is, the paper provides evidence of long-term memory dynamics in the equity market of China. An analysis of market patterns in the Chinese market (a typical emerging market) instead of US market (a developed market) will be meaningful because little research on the behaviors of emerging markets has been carried out previously. Second one is, we present a comprehensive research on the long-term memory characteristics in the Chinese stock market returns as well as volatilities. While many empirical results have been obtained on the detection of long-term memory in returns series, very few investigations are focused on the market volatility, though the long-term dependence in volatility may lead to some types of volatility persistence as observed in financial markets and affect volatility forecasts and derivative pricing formulas. By means of using modified rescaled range analysis and Autoregressive Fractally Integrated Moving Average model testing, this study examines the long-term dependence in Chinese stock market returns and volatility. The results show that although the returns themselves contain little serial correlation, the variability of returns has significant long-term dependence. It would be beneficial to encompass long-term memory structure to assess the behavior of stock prices and to research on financial market theory.

scholarly journals Stock Returns and The Weather Effect: the Case of Ghana

2020 ◽  
Author(s):  
Sampson Atuahene ◽  
Kong Yusheng ◽  
Geoffrey Bentum-Micah
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Exchange ◽  
Investor Sentiment ◽  
Weather Conditions ◽  
Market Returns ◽  
Stock Market Returns ◽  
Economic Significance ◽  
Weather Changes ◽  
Brokerage Firms

In every economy, Stock markets are part of the key elements the build it up. A few decades ago, there has been a significant change in Ghana stock market returns (GSE). Our study examines the statistical and economic significance of investor sentiment, based on weather conditions/changes, on stock market returns. OLS models, assisted by unit root tests were employed in analyzing the data obtained from the Ghana stock exchange platform from 2000 to 2017. From our literature review, we discovered that investors’ perceptions play a central role in finalizing the direction of stock market returns. Regarding our empirical results, we tested whether weather variations influence the investment decisions of investors; we discovered that temperature and cloud cover significantly influences stock market returns. This is because of mood changes is associated with weather conditions variations. However, sunshine per our regression coefficient shows a statistically insignificant impact on investors’ investment choices. Precipitation to a large extend influence stock market activities further affecting its results negatively as our regression results depicted. We concluded stock brokerage firms, companies, and investors (foreign/local) must incorporate weather changes/effects when strategizing about their investment outcomes.

Predicting the effect of Googling investor sentiment on Islamic stock market returns

2020 ◽  
Vol 13 (2) ◽  
pp. 165-193
Author(s):  
Yousra Trichilli ◽  
Mouna Boujelbène Abbes ◽  
Afif Masmoudi
Keyword(s):  
Stock Market ◽  
Markov Model ◽  
Financial Markets ◽  
Hidden Markov Model ◽  
Hidden Markov ◽  
Investor Sentiment ◽  
Market Returns ◽  
Stock Market Returns ◽  
Content Type ◽  
The Relationship

Purpose The purpose of this paper is to evaluate the capability of the hidden Markov model using Googling investors’ sentiments to predict the dynamics of Islamic indexes’ returns in the Middle East and North Africa (MENA) financial markets from 2004 to 2018. Design/methodology/approach The authors propose a hidden Markov model based on the transition matrix to apprehend the relationship between investor’s sentiment and Islamic index returns. The proposed model facilitates capturing the uncertainties in Islamic market indexes and the possible effects of the dynamics of Islamic market on the persistence of these regimes or States. Findings The bearish state is the most persistent sentiment with the longest duration for all the MENA Islamic markets except for Jordan, Morocco and Qatar. In addition, the obtained results indicate that the effect of sentiment on predicting the future Islamic index returns is conditional on the MENA States. Besides, the estimated mean returns for each state indicates that the bullish and calm states are ideal for investing in Islamic indexes of Bahrain, Oman, Morocco, Kuwait, Saudi Arabia and United Arab Emirates. However, only the bullish state is ideal for investing Islamic indexes of Jordan, Egypt and Qatar. Research limitations/implications This paper has used data at a monthly frequency that can explain only short-term dynamics between Googling investor’s sentiment and the MENA Islamic stock market returns. Moreover, this work can be done on the stock markets while taking into account the specificity of each activity sector. Practical implications In fact, the findings of this paper are helpful for academics, analysts and practitioners, and more specifically for the Islamic MENA financial investors. Moreover, this study provides useful insights not only into the duration of the relationship between the indexes’ returns and the investors’ sentiments in the five states but also into the transition probabilities which have implications for how investors could be guided in their choice of future investment in a portfolio with Islamic indexes. Findings of this paper are important and valuable for policy-makers and investors. Thus, predicting the effect of Googling investors’ sentiment on the MENA Islamic stock market dynamics is important for portfolio diversification by domestic and international investors. Moreover, the results of this paper gave new insights into financial analysts about the dynamic relationship between Googling investors’ sentiment and Islamic stock market returns across market regimes. Therefore, the findings of this study might be useful for investors as they help them capture the unobservable dynamics of the changes in the investors’ sentiment regimes in the MENA financial markets to make successful investment decisions. Originality/value To the best of the authors’ knowledge, this paper is the first to use the hidden Markov model to examine changes in the Islamic index return dynamics across five market sentiment states, namely the depressed sentiment (S1), the bullish sentiment (S2), the bearish sentiment (S3), the calm sentiment (S4) and the bubble sentiment (S5).

Does Investor Sentiment Predict Future Mexican Stock Market Returns?

2017 ◽  
Author(s):  
Daniel Perez-Liston ◽  
Patricio Torres-Palacio ◽  
Sidika Bayram
Keyword(s):  
Stock Market ◽  
Investor Sentiment ◽  
Market Returns ◽  
Stock Market Returns
Sign in / Sign up

Export Citation Format

Share Document