Are survey forecasts of individual and institutional investor sentiments rational?

Verma, Rahul; Verma, Priti

doi:10.1016/j.irfa.2007.04.001

Cited by 53 publications

(34 citation statements)

References 54 publications

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“…The survey approach enabled to measure direct response to a set of questions pertaining to a specific variable. Prominent surveys being used in US studies are the American association of individual investors (AAII) and investors Intelligence (II) as IS proxies to predict stock market movement (Brown and Cliff, 2004), (Zwergel and Klein, 2006), (Verma and Verma, 2008), (Verma and Soydemir, 2009) along with Michigan consumer confidence survey (Qiu and Welch, 2004). Another survey being widely used is sentix representing responses of German stock market participants (Schmeling, 2007), (Heiden et al, 2013) and (Bormann, 2013).…”

Section: Literature Reviewmentioning

confidence: 99%

Exploring relation between Indian market sentiments and stock market returns

Aggarwal

2017

AJER

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This paper aims to understand the relation between contemporaneous stock market returns and investor sentiments in Indian context. The analysis is done for daily data over a range of five years. Market measure proxies of investor sentiments including the market mood index and the volatility index are examined to explore their nature of association with the stock market returns. The results show that changes in sentiments have a higher explanatory power than sentiments at level when determining statistically significant relation with stock market returns. While the market mood index indicating optimism is positively related with stock returns, the VIX index also referred to as the fear guard index has a negative relation with stock returns. Moreover the market mood index seems to granger cause stock market returns and exhibit a long run association with stock market returns. With presence of sentiments impacting stock market returns established, more studies in context of developing countries are needed to understand the temporal dynamics between sentiments and stock markets. Contribution/ OriginalityThe current study examines the relationship between daily Indian contemporaneous stock market returns and investor sentiments over a time frame of five years. It had used two indices named market mood index and volatility index as proxies of investor sentiments to represent both optimism and fear in the market.

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Section: Literature Reviewmentioning

confidence: 99%

Exploring relation between Indian market sentiments and stock market returns

Aggarwal

2017

AJER

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“…Research works such as [28,10,40,79,78] used AAII index as a sentiment measure. Also, the University of Michigan Surveys of Consumers (UMSC) is a monthly sentiment index constructed from a consumer confidence survey answered by a random group of five hundred continental US households.…”

Section: Introductionmentioning

confidence: 99%

The impact of microblogging data for stock market prediction: Using Twitter to predict returns, volatility, trading volume and survey sentiment indices

Oliveira

Cortez

Areal

2017

Expert Systems with Applications

301

151

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In this paper, we propose a robust evaluation of the information content of microblogging data to forecast useful stock market variables: returns, volatility and trading volume of diverse dataset of indices and portfolios. We analyze a large Twitter dataset, from December 2012 to October 2015, with about 31 million messages related with 3,800 stocks traded in US markets. Also, we apply a sound prediction procedure (e.g., rolling window evaluation, four regression methods) along with a statistical test of predictive accuracy. Furthermore, we explore the diversity of traditional sentiment indicators and assess their complementarity value with microblogging sentiment. A Kalman Filter (KF) procedure is applied to create an unique daily sentiment indicator from a Twitter indicator and four other sentiment indicators (created from surveys). We also predicted two popular survey sentiment indicators using microblogging data. We found that Twitter sentiment and posting volume were particularly important for the forecasting of returns of S&P 500 index, portfolios of lower market capitalization and some industries. Additionally, KF sentiment was informative for the forecasting of returns. Furthermore, Twitter and KF sentiment indicators were useful for the prediction of some AAII and II survey sentiment indicators. These results show that microblogging data are relevant to forecast stock market behavior and can provide a valuable alternative for existing measures (e.g., survey sentiment) with various advantages (e.g., fast and cheap creation, daily frequency).

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“…5 Bhojraj and Sengupta (2003) find that higher levels of institutional ownership are related to higher bond ratings and lower yields due to lower agency costs and increased monitoring of management. Verma and Verma (2008) find that risk factors have stronger effects on institutional than individual investor sentiments. Other things being equal, this implies lower stock price volatility.…”

Section: The Concept Of Prudencementioning

confidence: 82%