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Article
Publication date: 14 September 2020

Qiang Bu and Jeffrey Forrest

The purpose of this study is to investigate whether the direct and indirect sentiment measures are similar in explaining mutual fund performance.

Abstract

Purpose

The purpose of this study is to investigate whether the direct and indirect sentiment measures are similar in explaining mutual fund performance.

Design/methodology/approach

The authors examine the role of direct and indirect sentiment measures on fund performance in two scenarios. One is when a sentiment measure is added to market models, and the other is when it used independently. Also, the authors propose a system science theory to explain the findings.

Findings

The authors find that both direct and indirect sentiment measures are integral to the benchmark models to explain fund performance. However, while the explanatory power of the direct sentiment index is robust when used independently or collectively, the indirect sentiment measures can explain fund performance only when used along with other market factors.

Originality/value

Given the number of sentiment measures, it is critical to determine whether these measures contain the same information of sentiment. This paper represents the first study on this topic.

Details

International Journal of Managerial Finance, vol. 17 no. 3
Type: Research Article
ISSN: 1743-9132

Keywords

Article
Publication date: 24 June 2021

Chanapol Pornpikul and Sampan Nettayanun

The authors study the explanatory power of investor rationality and irrationality for value and momentum portfolios. We also examine the relationships during financial…

Abstract

Purpose

The authors study the explanatory power of investor rationality and irrationality for value and momentum portfolios. We also examine the relationships during financial crisis events, namely, the US subprime mortgage crisis (2007–2009) and the European debt crisis (2011–2013).

Design/methodology/approach

This study examines the influence of investors’ rationality and irrationality on the US stock market, using the multiple linear regression model and the stepwise regression model. Technically, the stepwise regression uses the machine-learning technique, with specific testing methods — forward selection, backward selection and stepwise selection — to find the best-fit model, according to Akaike’s Information Criterion (AIC). Thus, in this study, we will show the best model, as tested by the stepwise regression model.

Findings

Our empirical results contribute to the importance of reasons and emotions for stock-market returns and conclude that rationality and irrationality simultaneously explain the value and momentum portfolios, as well as the ETF portfolios. Also, the rational and irrational explanatory powers differ, depending on portfolios and different periods. Rational factors usually explain the volatility of the return to a greater extent than irrational factors. Moreover, during a financial crisis, the irrational factors remarkably increase their importance in explaining returns, especially for the ETF portfolios.

Originality/value

We expect this study’s contribution will show not only academic contribution but also benefit many stakeholders in the financial market. Investors and traders can identify various irrational factors of trading — for example, taking a long position during the panic in the market following the indicators in the models. Managers also reconsider the cost of the company by adding irrational factors when computing the equity’s expected return. Similarly, stock exchanges can adequately adjust their circuit breaker during a pessimistic-investor period. Finally, regulators can evaluate a complete picture of the stock market by adding irrational factors into their considerations.

Details

Review of Behavioral Finance, vol. 14 no. 5
Type: Research Article
ISSN: 1940-5979

Keywords

Article
Publication date: 1 December 2004

Kathryn Wilkens, Nordia D. Thomas and M.S. Fofana

We examine the stability of market prices for 35 technology and 35 industrial stocks for the period December 31, 1993 to October 31, 2002. A phase portrait plot of the…

Abstract

We examine the stability of market prices for 35 technology and 35 industrial stocks for the period December 31, 1993 to October 31, 2002. A phase portrait plot of the detrended log prices and de‐meaned returns of the two sectors shows a chaotic pattern in the stock prices indicating the presence of nonlinearity. However, when we compute the Lyapunov exponents, negative values are obtained. This shows that the price fluctuations for the 70 stocks result primarily from diffusion processes rather than from nonlinear dynamics. We evaluate forecast errors from a naïve model, a neural network, and ARMA models and find that the forecast errors are correlated with average changes in closed‐end fund discounts and other sentiment indexes. These results support an investor sentiment explanation for the closed‐end fund puzzle and behavioral theories of investor overreaction.

Details

Managerial Finance, vol. 30 no. 12
Type: Research Article
ISSN: 0307-4358

Keywords

Article
Publication date: 28 February 2020

Mobeen Ur Rehman and Nicholas Apergis

This study aims to investigate the impact of sentiment shocks based on US investor sentiments, bearish and bullish market conditions. Earlier studies, though very few…

Abstract

Purpose

This 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/approach

This 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.

Findings

The 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/implications

The 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 implications

This 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/value

The 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.

Details

Journal of Economic Studies, vol. 47 no. 3
Type: Research Article
ISSN: 0144-3585

Keywords

Article
Publication date: 6 September 2013

Mustafa Sayim, Pamela D. Morris and Hamid Rahman

This paper examines the effect of rational and irrational investor sentiment on the stock return and volatility of US auto, finance, food, oil and utility industries.

3357

Abstract

Purpose

This paper examines the effect of rational and irrational investor sentiment on the stock return and volatility of US auto, finance, food, oil and utility industries.

Design/methodology/approach

The American Association of Individual Investors Index (AAII) is used as a proxy for US individual investor sentiment. The US market fundamentals are regressed on investor sentiment in order to capture the effect of macroeconomic risk factors on investor sentiment. Then impulse response functions (IRFs) are generated from a VAR model to investigate the effect of unanticipated movements in US investor sentiment on both industry‐specific stock return and volatility.

Findings

The results show a significant impact of investor sentiment on stock return and volatility in all the industries. We find that the positive rational component of US individual investor sentiment tends to increase the stock return in these industries. We also document that unanticipated increase in the rational component of US individual investor sentiment has a significant negative impact only on the industry volatilities of US auto and finance industries.

Research limitations/implications

The results are based only on the 1999 – 2010 US industry‐specific stock return and volatility data and are confined to these industries.

Practical implications

The findings of this paper can help investors to improve their asset return generating models by incorporating investor sentiment. The findings can also help policymakers to design policies that stabilize sentiment and reduce volatility and uncertainty in the stock markets.

Originality/value

This paper adds to the growing literature on behavioral finance by filling a gap and addressing the impact of investor sentiment in the various US industries.

Details

Review of Behavioural Finance, vol. 5 no. 1
Type: Research Article
ISSN: 1940-5979

Keywords

Article
Publication date: 26 September 2008

Rob Beaumont, Marco van Daele, Bart Frijns, Thorsten Lehnert and Aline Muller

The purpose of this paper is to investigate the impact of individual investor sentiment on the return process and conditional volatility of three main US market indices

2917

Abstract

Purpose

The purpose of this paper is to investigate the impact of individual investor sentiment on the return process and conditional volatility of three main US market indices (Dow Jones Industrial Average, S&P500 and Nasdaq100). Individual investor sentiment is measured by aggregate money flows in and out of domestically oriented US mutual funds.

Design/methodology/approach

A generalised autoregressive conditional heteroscedasticity (GARCH)‐in‐mean specification is used, where our measure for individual sentiment enters the mean and conditional volatility equation.

Findings

For a sample period of six years (February 1998 until December 2004), we find that sentiment has a significant and asymmetric impact on volatility, increasing it more when sentiment is bearish. Using terminology of De Long et al., we find evidence for the “hold more” effect, which states that when noise traders hold more of the asset, they also see their returns increase, and the “create space” effect, which states that noise traders are rewarded for the additional risk they generate themselves.

Originality/value

In contrast to existing studies using explicit measures of market sentiment on low sampling frequencies, the use of daily mutual flow data offers a unique picture on investors' portfolio rebalancing and trading behavior. We propose an integrated framework that jointly tests for the effects of mutual fund flows on stock return and conditional volatility.

Details

Managerial Finance, vol. 34 no. 11
Type: Research Article
ISSN: 0307-4358

Keywords

Article
Publication date: 17 May 2019

Divya Aggarwal

The purpose of this paper is to review and discuss the literature focusing on defining and measuring sentiments so as to understand their role in stock market behavior.

Abstract

Purpose

The purpose of this paper is to review and discuss the literature focusing on defining and measuring sentiments so as to understand their role in stock market behavior.

Design/methodology/approach

Critical review of the literature by analyzing myriad scholarly articles. The study is based on an analysis of 81 scholarly articles to critically analyze the approach toward defining and measuring market sentiments. The articles have been examined to identify and critique different classification of sentiment measures. A discussion is built to scrutinize the sentiment measures under the purview of theoretical underpinnings of the investor sentiment theory as well.

Findings

With more than five decades of research, the sentiment construct in finance literature is still ill-defined. Myriad empirical proxies of sentiment measures have led to conflicting results. The sentiment construct defined in financial theories needs to be revisited from the lens of sentiments defined in psychology.

Research limitations/implications

The study is limited to analyzing the role of individual and institutional sentiments in equity markets. There is a need to explore sentiments with respect to different investment styles and strategies along with the type of investors.

Practical implications

Developing a suitable sentiment proxy can result in devising profitable trading strategies for investors. Understanding factors driving investor sentiments will help regulators to become more proactive and frame better policies.

Originality/value

This paper has leveraged psychology literature to highlight the limitations in development of sentiment construct in finance literature. By identifying stylized facts from reviewing the empirical literature, it highlights areas for future research.

Details

Qualitative Research in Financial Markets, vol. 14 no. 2
Type: Research Article
ISSN: 1755-4179

Keywords

Article
Publication date: 8 January 2020

Chaiyuth Padungsaksawasdi

Considering the unique data of the gold investor sentiment index in Thailand, the purpose of this paper is to investigate the bivariate dynamic relationship between the…

Abstract

Purpose

Considering the unique data of the gold investor sentiment index in Thailand, the purpose of this paper is to investigate the bivariate dynamic relationship between the gold investor sentiment index and stock market return, as well as that between the gold investor sentiment index and stock market volatility, using the panel vector autoregression (PVAR) methodology. The author presents and discusses the findings both for the full sample and at the industry level. The results support prior literature that stocks in different industries do not react similarly to investor sentiment.

Design/methodology/approach

The PVAR methodology with the GMM estimation is found to be superior to other static panel methodologies due to considering both unobservable time-invariant and time-variant factors, as well as being suitable for relatively short time periods. The panel data approach improves the statistical power of the tests and ensures more reliable results.

Findings

In general, a negative and unidirectional association from gold investor sentiment to stock returns is observed. However, the gold sentiment-stock realized volatility relationship is negative and bidirectional, and there exists a greater impact of a stock’s realized volatility on gold investor sentiment. Importantly, evidence at the industry level is stronger than that at the aggregate level in both return and volatility cases, confirming the role of gold investor sentiment in the Thai stock market. The capital flow effect and the contagion effect explain the gold sentiment-stock return relationship and the gold sentiment-stock volatility relationship, respectively.

Research limitations/implications

The gold price sentiment index can be used as a factor for stock return predictability and stock realized volatility predictability in the Thai equity market.

Practical implications

Practitioners and traders can employ the gold price sentiment index to make a profit in the stock market in Thailand.

Originality/value

This is the first paper to use panel data to investigate the relationships between the gold investor sentiment and stock returns and between the gold investor sentiment and stocks’ realized volatility, respectively.

Details

International Journal of Managerial Finance, vol. 16 no. 3
Type: Research Article
ISSN: 1743-9132

Keywords

Article
Publication date: 27 June 2019

Antti Klemola

The purpose of this paper is to propose a novel and new direct measurement of small investor sentiment in the equity market. The sentiment is based on the individual…

Abstract

Purpose

The purpose of this paper is to propose a novel and new direct measurement of small investor sentiment in the equity market. The sentiment is based on the individual investors’ internet search activity.

Design/methodology/approach

The author measures unexpected changes in the small investor sentiment with AR (1) process, where the residuals capture the unexpected changes in small investor sentiment. The author employs vector autoregressive, Granger causality and linear regression models to estimate the association between the unexpected changes in small investor sentiment and future equity market returns.

Findings

An unexpected increase in the search popularity of the term bear market is negatively associated with the following week’s equity market returns. An unexpected increase in the spread (the difference in popularities between a bull market and a bear market) is positively associated with the following week’s equity market returns. The author finds that these effects are stronger for small-sized companies.

Originality/value

By author’s knowledge, the paper is the first that measures the small investor sentiment that is based on the internet search activity for keywords used in the American Association of Individual Investor’s (AAII) survey questions. The paper proposes an alternative small investor sentiment measure that captures the changes in small investor sentiment in more timely fashion than the AAII survey.

Details

Review of Behavioral Finance, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1940-5979

Keywords

Article
Publication date: 6 April 2012

Robert A. Olsen

The purpose of this paper is to present a behavioral explanation of excess stock price volatility relative to present value theory.

2080

Abstract

Purpose

The purpose of this paper is to present a behavioral explanation of excess stock price volatility relative to present value theory.

Design/methodology/approach

The conceptual basis is the impact of affect on investor decisions. The empirical tests involve survey data collected from a sample of semi‐professional investors (AAII members) and investment advisors (CFPs).

Findings

It is suggested that affect causes investors to perceive an inverse ex ante relationship between risk perceptions and expected returns. Thus, new good or bad information has an amplified effect on stock valuations. In addition, investors tend to extrapolate recent short‐term market movements into the future.

Practical implications

The primary implications are that ex ante perceptions of risk and return vary inversely and that affect has a strong influence on valuation. This means that simple statistical measures of risk are unlikely to fully capture risk perceptions and that market volatility can be expected to be greater than a simple present value model would imply.

Originality/value

This paper is unique as to the conclusion that risk and return perceptions vary inversely ex ante and that affect can amplify stock price volatility.

Details

Qualitative Research in Financial Markets, vol. 4 no. 1
Type: Research Article
ISSN: 1755-4179

Keywords

1 – 10 of 38