Investor Sentiment And The Near-Term Stock Market

Cliff, Michael T.; Brown, Gregory W.

doi:10.2139/ssrn.282915

Cited by 165 publications

(184 citation statements)

References 34 publications

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“…We conjecture that such a temporal increase in forecast biases could be due to behavioural factors. Our results, indeed, appear to support recent models of behavioural finance in which significant changes in market sentiment lead to structural breaks in the behaviour of market participants (Barberis, Shleifer and Vishny, 1998; and Brown and Cliff, 1999).…”

Section: Discussionsupporting

confidence: 88%

The Quality of Analysts’ Earnings Forecasts During the Asian Crisis: Evidence from Singapore

Loh¹,

Mian

2003

Business Fin & Account

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We bring together three disparate strands of literature to develop a comprehensive empirical framework to examine the efficiency of security analysts' earnings forecasts in Singapore. We focus specifically on how the increased uncertainty and the negative market sentiment during the period of the Asian crisis affected the quality of earnings forecasts. While we find no evidence of inefficiencies in the pre-crisis period, our results suggest that after the onset of the crisis, analysts (1) issued forecasts that were systematically upward biased; (2) did not fully incorporate the (negative) earnings-related news; and (3) predicted earnings changes which proved too extreme. Copyright Blackwell Publishers Ltd, 2003.

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Section: Discussionsupporting

confidence: 88%

The Quality of Analysts’ Earnings Forecasts During the Asian Crisis: Evidence from Singapore

Loh¹,

Mian

2003

Business Fin & Account

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“…The equity market sentiment literature uses various direct survey‐based measures to capture investor sentiment. For example, Brown and Cliff (, ) use a “bull–bear” spread, defined as the percentage of stock investment newsletters deemed to be bullish minus the percentage categorized as bearish, as classified by Investors’ Intelligence . Brown and Cliff (, ) relate the bull–bear spread to deviations from fundamental values and examine both short‐ and long‐run effects of sentiment on stock returns.…”

Section: Measuring Investor Sentimentmentioning

confidence: 99%

“…For example, Brown and Cliff (, ) use a “bull–bear” spread, defined as the percentage of stock investment newsletters deemed to be bullish minus the percentage categorized as bearish, as classified by Investors’ Intelligence . Brown and Cliff (, ) relate the bull–bear spread to deviations from fundamental values and examine both short‐ and long‐run effects of sentiment on stock returns. The authors find that the bull–bear spread is highly correlated with contemporaneous stock returns but has little short‐run predictive power (Brown and Cliff ).…”

Section: Measuring Investor Sentimentmentioning

confidence: 99%

“…Brown and Cliff (, ) relate the bull–bear spread to deviations from fundamental values and examine both short‐ and long‐run effects of sentiment on stock returns. The authors find that the bull–bear spread is highly correlated with contemporaneous stock returns but has little short‐run predictive power (Brown and Cliff ). However, taking a longer term perspective of two to three years, periods of high sentiment are followed by low returns as stock prices mean revert (Brown and Cliff ).…”

Section: Measuring Investor Sentimentmentioning

confidence: 99%

“…The empirical literature on investor sentiment and asset pricing has largely focused on public stock markets ( e.g ., Neal and Wheatley , Brown and Cliff , , Baker and Wurgler , , Kumar and Lee , Han , Baker, Wurgler and Yuan ). This focus is understandable given the difficulties associated with obtaining return information on private equity investments (Kaplan and Schoar ).…”

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confidence: 98%

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Investor Sentiment, Limits to Arbitrage and Private Market Returns

Ling

Naranjo

Scheick

2013

Real Estate Economics

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This article examines the relation between investor sentiment and returns in private markets. Relative to more liquid public markets, private investment markets exhibit significant limits to arbitrage that restrict an investor's ability to counteract mispricing. Using vector autoregressive models, we find a positive and economically significant relation between investor sentiment and subsequent private market returns. We provide further long-horizon regression evidence suggesting that private commercial real estate markets are susceptible to prolonged periods of sentiment-induced mispricing as the inability to short-sell in periods of overvaluation and restricted access to credit in periods of undervaluation prevents arbitrageurs from entering the market.A growing behavioral approach in the economics and finance literature recognizes the bounded rationality and psychological biases of investors who often rely on and are influenced by computational shortcuts, heuristics, frame dependence and intuition when making decisions in a complicated and uncertain world with market frictions (e.g., Kahneman, Slovic and Tversky 1982, Barberis andThaler 2003). As a result, changes in asset prices may be driven by more than changes in market fundamentals. 1 Furthermore, these temporary price deviations can persist if there are significant limits to arbitrage as shown theoretically by De Long et al. (1990) and Shleifer and Vishny (1997), among others. Recent empirical research suggests this movement away from

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Market timing using combined forecasts and machine learning

Mascio

Fabozzi

Zumwalt

2020

Journal of Forecasting

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Successful market timing strategies depend on superior forecasting ability. We use a sentiment index model, a kitchen sink logistic regression model, and a machine learning model (least absolute shrinkage and selection operator, LASSO) to forecast 1-month-ahead S&P 500 Index returns. In order to determine how successful each strategy is at forecasting the market direction, a "beta optimization" strategy is implemented. We find that the LASSO model outperforms the other models with consistently higher annual returns and lower monthly drawdowns.

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Investor Sentiment And The Near-Term Stock Market

Cited by 165 publications

References 34 publications

The Quality of Analysts’ Earnings Forecasts During the Asian Crisis: Evidence from Singapore

The Quality of Analysts’ Earnings Forecasts During the Asian Crisis: Evidence from Singapore

Investor Sentiment, Limits to Arbitrage and Private Market Returns

Market timing using combined forecasts and machine learning

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