Assessing dynamic qualities of investor sentiments for stock recommendation

2021 ◽  
Vol 58 (2) ◽  
pp. 102452
Author(s):  
Jun Chang ◽  
Wenting Tu ◽  
Changrui Yu ◽  
Chuan Qin
2021 ◽  
Vol 72 ◽  
pp. 102112
Author(s):  
Ata Assaf ◽  
Husni Charif ◽  
Khaled Mokni

2018 ◽  
Vol 7 (3) ◽  
pp. 332-346
Author(s):  
Divya Aggarwal ◽  
Pitabas Mohanty

Purpose The purpose of this paper is to analyse the impact of Indian investor sentiments on contemporaneous stock returns of Bombay Stock Exchange, National Stock Exchange and various sectoral indices in India by developing a sentiment index. Design/methodology/approach The study uses principal component analysis to develop a sentiment index as a proxy for Indian stock market sentiments over a time frame from April 1996 to January 2017. It uses an exploratory approach to identify relevant proxies in building a sentiment index using indirect market measures and macro variables of Indian and US markets. Findings The study finds that there is a significant positive correlation between the sentiment index and stock index returns. Sectors which are more dependent on institutional fund flows show a significant impact of the change in sentiments on their respective sectoral indices. Research limitations/implications The study has used data at a monthly frequency. Analysing higher frequency data can explain short-term temporal dynamics between sentiments and returns better. Further studies can be done to explore whether sentiments can be used to predict stock returns. Practical implications The results imply that one can develop profitable trading strategies by investing in sectors like metals and capital goods, which are more susceptible to generate positive returns when the sentiment index is high. Originality/value The study supplements the existing literature on the impact of investor sentiments on contemporaneous stock returns in the context of a developing market. It identifies relevant proxies of investor sentiments for the Indian stock market.


2020 ◽  
Vol 47 (3) ◽  
pp. 433-465 ◽  
Author(s):  
Mobeen Ur Rehman ◽  
Nicholas Apergis

PurposeThis study aims to investigate the impact of sentiment shocks based on US investor sentiments, bearish and bullish market conditions. Earlier studies, though very few, only consider the effect of investor sentiments on stock returns of emerging frontier Asian (EFA) markets.Design/methodology/approachThis study uses the application of regime switching model because of its capability to explore time-varying causality across different regimes unlike traditional linear models. The Markov regime switching model uses regime switching probabilities for capturing the potential asymmetries or non-linearity in a model, in this study’s case, thereby adjusting investor sentiments shocks to stock market returns.FindingsThe results of the Markov regime switching method suggests that US sentiment, bullish and bearish market shocks act as a main contributors for inducing variation in EFA stock market returns. The study’s non-parametric robustness results highlight an asymmetric relationship across the mean series, whereas a symmetric relationship across variance series. The study also reports Thailand as the most sensitive market to global sentiment shocks.Research limitations/implicationsThe sensitivity of the EFA markets to these global sentiment shocks highlights their sensitivity and implications for investors relying merely on returns correlation and spillover. These findings also suggest that spillover from developed to emerging and frontier equity markets only in the form of returns following traditional linear models may not be appropriate.Practical implicationsThis paper supports the behavioral aspect of investors and resultant spillover from developed market sentiments to emerging and frontier market returns across international equity markets offering more rational justification for an irrational behavior.Originality/valueThe study’s motivation to use the application of regime switching models is because of its capability to explore time-varying causality across different regimes unlike traditional linear models. The Markov regime switching model uses regime switching probabilities for capturing the potential asymmetries or non-linearity in a model, in the study’s case, thereby adjusting investor sentiments shocks to stock market returns. It is also useful of the adjustment attributable to exogenous events.


2019 ◽  
Vol 36 (2) ◽  
pp. 114-129 ◽  
Author(s):  
Mobeen Ur Rehman ◽  
Nicholas Apergis

Purpose This paper aims to explore the impact of investor sentiments on economic policy uncertainty (EPU). The analysis also considers the momentum effect, stock market returns volatility and equity pricing inefficiencies across markets, which, to the best of the authors’ knowledge, has not been addressed in the literature. The role of these control variables has collectively been considered to have important behavioral implications for international investors Design/methodology/approach Quantile regressions are used for estimation purpose, as it provides robust and more efficient estimates rather than those coming from the traditional regression model. Findings The momentum effect is negative and significant only at higher quantiles, while oil prices are positive and significant across all quantiles. The exchange rate exerts a negative and significant effect on EPU, whereas equity price volatility (i.e. investor sentiment) exerts a negative and significant impact on EPU in most of the quantiles. Research limitations/implications The results have important implications for international investors and policymakers, especially in terms of the breakdown of economic policy uncertainty across different sample markets. The breakdown of complete sample period into sub-samples acts as a robust analysis and documents the similarity of the results for the Asian and developed markets cases, but not in the case of the European markets. Practical implications The findings imply the importance of financial stability that impacts the accumulation of systemic risks and adds smoothness to the financial cycle in particular geographical areas. Originality/value The contribution of this paper is threefold. First, existing literature highlights and empirically tests the impact of economic policy uncertainty on different market, macro-economic and global control variables. The analysis, however, performs it in the reverse order, i.e. analyzing the impact of the momentum effect (investor sentiment variables), equity market inefficiencies and volatility (market variables) and exchange rates and Brent oil (control variables). Second, to check the sensitivity of economic policy uncertainty, the analysis analyzes a wide range of markets, segregated as emerging, developed and European regions over the sample period to generate region-wise implications. Finally, the analysis explores the relationship of aforementioned variables with economic policy uncertainty keeping in view the non-linear structure and prior evidence and investor sentiments and economic policy uncertainty in the regression model.


Sign in / Sign up

Export Citation Format

Share Document