Published research on sentiment

There have been a number of studies on sentiment indices which provides valuable insight into the versatile use of a sentiment index.  The literature uses sentiment indices to measure the relationship between market sentiment and prices and rates, such as stocks and foreign exchange.

Studies show sentiment can provide predictability of returns for stocks and exchange rates in the intermediate term, be used as a contrarian signal when trading, predict market volatility and be used as an explanitor in cross-sectional returns.

Additionally, studies show country sentiment ‘spill-over’ can affect value perceptions. These studies reveal the importance of including a sentiment index as one of many tools in the investment decision process.

We briefly document the key research in sentiment below.

Return predictability

Heiden, Klein, and Zwergel (2013) examine the relationship between market sentiment and exchange rate movements.  They employ the ‘sentix’ sentiment index.  They examine the predictability of exchange rates using short (one month) and intermediate (six months) time horizons between individual and institutional investors. They find that institutional investor sentiment has predictive power of the EUR/USD market over the intermediate time horizon. Hengelbrock, Theissen and Westheide (2013) also look at the effect of sentiment on stock prices and find their constructed indices have predictive power of returns using intermediate (six months) and long term (1 year) time horizons.

Lux (2011) looks at sentiment and stock prices but seeks to identify the lead/lag relationship and finds that intermediate (six months) time frame sentiment drives returns, while using a short (1 month) time frame finds a simultaneous relationship.


Research on the use of sentiment between private or institutional investors (Schmeling, 2007) finds that institutional investors take into account expected individual sentiment when forming their expectations in a way that higher (lower) expected sentiment of individuals lowers (increases) institutional return forecasts. Individual investors, however, neglect the information contained in institutional sentiment.

Different trading strategies can also be employed using sentiment such as Aissia (2016) finds that foreign and home sentiment are strong contrarian predictors of stock returns.

Byoung-Hyoug ( 2011) studies the effect of country specific sentiment on security prices and provides evidence that sentiment and perception of countries causes security prices to deviate from their fundamental values.


From a risk management perspective, studies such as Kumari & Mahakud (2015) find that past investor sentiment affects volatility positively and negatively. The negative investor sentiment influences volatility and supports the proposition that noise traders’ pessimism makes the markets highly volatile. Brown (1991) shows deviations from the mean level of sentiment are positively related to volatility in trading hours, whilst Lee, Jiang, & Indro (2002) find that bullish (bearish) changes in sentiment lead to downward (upward) adjustments in volatility.

Cross-sectional returns

Regarding cross-sectional returns, Lee, Schleifer, & Thaler (1991) document that investor sentiment affects the risk of common stocks and that firms with high sensitivity to this factor must be compensated for this extra risk (including that it affects small cap stock returns more). Baker & Wurgler (2006) suggest that investor sentiment has a significant effect on the cross-section of stock returns when sentiment-based demands or arbitrage constraints varied across stocks.


Aissia, D. B. (2016, February). Home and foreign investor sentiment and the stock returns. The Quarterly Review of Economics and Finance, 59, 71-77.

Baker, M., & Wurgler, J. (2006). Investor sentiment and the cross-section of stock returns. The Journal of Finance, 61(4), 1645-1680.

Brown, G. W. (1991). Volatility, Sentiment, and Noise Traders. Financial Analysts Journal, 60(4), 82-90.

Byoung-Hyoun, H. (2011). Country-specific sentiment and security prices. Journal of Finance, 100(2), 382-401.

Heiden, S., Klein, C., & Zwergel, B. (2013). Beyond fundamentals: Investor sentiment and exchange rate forecasting. European Financial Management, 19(3), 558-578.

Hengelbrock, J., Theissen, E., & Westheide, C. (2013). Market response to investor sentiment. Journal of Business Finance & Accounting, 40(7), 901-917.

Kumari, J., & Mahakud, J. (2015, December). Does investor sentiment predict the asset volatility? Evidence from emerging stock market India. Journal of Behavioural and Experimental Finance, 8, 25-39.

Lee, C. M., Schleifer, A., & Thaler, R. H. (1991). Investor Sentiment and the Closed Fund Puzzle. The Journal of Finance, 46(1), 79-109.

Lee, W. Y., Jiang, C., & Indro, D. C. (2002). Stock Market Volatility, Excess Returns, and the Role of Investor Sentiment. Journal of Banking and Finance, 26(12), 2277-2299.

Lux, T. (2011). Sentiment dynamics and stock returns: the case of the German stock market. Empir Econ, 41, 663-679.

Schmeling, M. (2007). Institutional and investor sentiment: Smart money and noise trader risk? International Journal of Forecasting, 23, 127-145.