Market Sentiment Measurements
- Explain the idea behind this measure (0.5-1 page) and summarize three research papers applying this method (0.5page for each summary)
- Discuss some of the implications. For example, does this measure have any predictive power? Does it explain any market anomalies? Are there any implications on asset prices or any other asset indicators?
- What are some of the important drawbacks of this measure?
Introduction
Market sentiment plays an empirical role in describing the variation of the stock market. For the purpose of this paper, market sentiment is the overall attitude that investors have regarding a specific financial market or security. It describes the tone or feeling prevailing in the market or crowd psychology as revealed through the price and activity movement of the securities traded in that market (Yang, Mo & Liu, 2015). In other words, falling prices would indicate bearish market sentiment while rising prices would indicate bullish market sentiment.
The idea behind market sentiment measurements
Understanding the market tone variation is critical for the investors to determine the trading direction and the likely outcomes. Information about the market sentiment unleashes the opportunity for investors to take advantage of the prevailing trends and hence avoid missing essential business opportunities (Yang, Mo & Liu, 2015). In this regard, the idea behind market sentiment measurement is to assess the confidence level of the investors towards a specific asset or market. Such knowledge helps the investors to avoid purchasing property when the market sentiment is too high or selling during extremely low market sentiment. This is critical to maximize opportunities by avoiding both extremes. These include a market situation when greed is extremely high or when fear is pervasive. In this regard, investors need to understand crowd psychology to grasp a better perspective of bearishness and bullishness (Yang, Mo & Liu, 2015). With such knowledge, the investors are able to optimize on business when both extremes are at balance. Market sentiment measurements, is thus, triggered by the need to understand the market effects on particular security by assessing the market statistics.
Summary of Research papers
Asif Khan, M., Ahmad, R., Azmi, A., & Akbar, M. (2019). A new sentiment index for the Islamic stock market. Investment Analysts Journal, 48(2), 146-172.
The study investigated the predictability of Google search volume (GSV) while determining a better market sentiment measurement for seven United States (US) Islamic stock markets. The authors used the principal component analysis to illustrate an index with higher and more persistent R-squared values (Asif Khan et al., 2019). The Islamic stock markets are based on the ethical standards of Sharia through quantitative and qualitative screening criteria. The article excluded the stocks, including pork and alcohol. In this regard, a critical difference is empirical between the bullish and bearish market conditions of Islamic stocks and other stocks due to the strict market conditions.
According to the authors, the stock prices for both noise and informed traders is set by the stock market. As the informed traders influence the prices to the actual value by eradicating price dispersion, noise traders base their trading on pseudo-signals (Asif Khan et al., 2019). The article highlighted three approaches to measure the market sentiment, which includes survey approach, market-based proxies, and the search-based approach. To reduce bias resulting from differences in trading days, the authors convert data into weekly occurrences.
Baker, M., & Wurgler, J. (2007). Investor sentiment in the stock market. Journal of economic perspectives, 21(2), 129-152.
Baker and Wurgler argued that investors are subject to sentiment. The article asserts that investor sentiment is a belief about future investment risks and cash flows that exceed justification by the current facts. The article develops a macroeconomic and “top-down” sentiment approach which defines the stocks with higher potential of getting affected by the market sentiment (Baker & Wurgler, 2007). According to the authors, market sentiments are measurable and have effects on both individual firms and the stock market. Besides, difficult stocks to arbitrage are highly affected by the sentiment.
Further, this approach faces the challenges of assessing the stocks with limited arbitrage potential, characterizing uniformed demand, and understanding the variation in investor investment periodically. However, despite these challenges, understanding this approach provides substantial payoffs. For instance, the standard methodology used to assess the fundamental market betas improves the clarity of interpretation (Baker & Wurgler, 2007). Also, the effects of sentiments on the cost of capital results to real consequences for the allocation of corporate investment capital between the more speculative and safer firms.
Gao, Z., Ren, H., & Zhang, B. (2018). Googling investor sentiment around the world. Journal of Financial and Quantitative Analysis (JFQA), Forthcoming.
The article studied the effects of market sentiments on stock prices. The article constructed a weekly measure of sentiment between 2004 and 2014 for 38 markets, based on household’s Google search behaviour (Gao, Ren & Zhang, 2018). According to the authors, sentiment measure is a contrarian predictor of country-level market returns. The article highlights the challenges that face the sentiment literature, which include difficulty in measuring the market sentiment and constraining of previous evidence by market coverage and time-frequency. However, the article recommends future research to enhance the understanding of international markets forms a behavioural perspective.
The research objectives included determining whether the sentiment measure is a contrarian predictor of country-level market returns, investigating the return prediction of global sentiment, and validate the search-based index as a proxy for investor sentiment. The results revealed that 36 out of 38 markets depicted a negative correlation between sentiment and the following week’s returns (Gao, Ren & Zhang, 2018). Further, economic-related and non-economics sentiment index components can predict market returns independently. The controlled variables included the unemployment rate, changes in liquidity, consumer price, and default spreads. The exclusion criteria included the use of local currency returns and financial crisis period.
Implications of the Market Sentiment Measurements
The markets are mostly driven by greed, emotion, and fear in the short-term situation. These describe the psychological forms that influence decision making by traders and investors. For instance, the fear of missing out an asset may drive an investor to pay prices for an asset that they have no idea about. In this case, the investor does not purchase the asset because it is a valuable investment, but because they fear losing out the opportunity to buy when it is available and maybe ‘regret’ in future. In this regard, it is possible to conclude that the sentiment index that indicates a high tendency to purchase stock at high prices (bullish) sentiment indicates a future shortage. As such, the investors hurry to grasp their inventory before they get out of the market. By contrast, a low tendency to purchase when prices are low (bearish) sentiment indicates a high availability of the stock market and hence the investors are reluctant to purchase. Such is because they feel no need to hurry to buy stock that may not increase in value and consequently lose their money.
Further, during the bearish markets, the investors tend to sell out property and stock at extremely low prices below their value. Such is due to the fear of feeling the pain of losing money and hence sell out to get rid of the stock. Accordingly, this implies the ability of emotions to influence investors in making irrational decisions. Such is because market lows and highs usually experience extreme levels of negativity and positivity. In this regard, this measure can predict the market behaviour and hence help the investors to assess if a market is driven by rational decision making or by emotions. Besides, the buyers can take advantage of the prevailing low prices of stock and property and reserve for potential future benefits when the value goes up.
Additionally, market sentiment measurement helps to determine the volume which can be used to indicate the general feeling in the market. Such is based on the options and stocks by pointing towards falling and rising interests. For instance, an increasing company’s share price against its dropping volumes would indicate a weakening sentiment. Such enhances the ability for the investors to make informed decisions. However, it is challenging to measure the volumes in a forex market since the business activities are carried out over the counter rather than in a centralized market stock exchange. This makes it difficult to assess data on the trading volumes.
Tools for Measuring Market Sentiment
Market sentiment measurement relies on various tools to determine the market mood. Such include the Commitment of Traders (COT) which is published weekly to indicate the net short and long positions of the commercial traders. Though the COT, it is possible to assess the market dynamics by indicating the position of the most prominent market players such as corporations and banks regarding their options and futures. Besides, COT helps to determine how these players are committed regarding the current market moods. In this case, if the market has been bullish and then the COT indicates that these traders have shifted to a more bearish attitude, this would indicate a future turn in the market. Hence, the investors would use such an indicator to make informed decisions.
Another tool to measure market sentiment is the Volatile Index (VIX) which is also referred to as ‘fear index’. This measures implied volatility and tracks option prices whereby the former protects the investors against potential alteration of prices. In this case, if the implied volatility is high, then the chances for altering the current trend is high. By contrast, low implied volatility indicates a rather stable sentiment and the possibility for the current trend to continue.
High/low sentiment ratio is the other tool. This implies an efficient tool for assessing whether a market is in a bearish or bullish state. It compares the number of stocks heading to their highest or lowest levels in the last fifty-two weeks (Oliveira-Brochado, 2019). An average direction towards the lows indicates a bearish mood while towards the highs indicates a bullish mood. Based on the outcomes of this tool’s analysis, the investors grasp the mood of the market efficiently and on a timely basis hence making informed decisions.
Does it explain any market anomalies?
Market sentiment measurements depict a crucial tool for explaining market anomalies. According to Oliveira-Brochado (2019), a negative relationship exists between the extended position and the sentiment index while a positive relationship exists between the short position and the index. Such indicates that a reversion pattern influences anomalies where excessively optimistic periods tend to influence negative returns. Therefore, a behavioural component can explain the anomalies on asset pricing. In this regard, based on practical implications, the pieces of evidence about the different anomaly-based strategies help the investors in decision making. Further, this index assesses the state of the market as either bearish or bullish. In this regard, it is possible to indicate the fate of the companies with high performance in the market capitalization.
Benefits of the Approach
Market sentiment index enables investors to create an insightful, data-based strategy which enhances the ability to make informed decisions regarding market trends. Through the internet search behaviour, analyzing the market sentiment helps to understand the insights provided by the customers (Oliveira-Brochado, 2019). Customers provide information regarding what products they are interested in and the features they are looking for. Such is important for investors to adjust accordingly by spotting the remarks and making viable conclusions. Additionally, through this strategy, investors grasp essential information regarding the distinct components from those of the competitors. With the knowledge about the stronghold points, they can leverage them for better performance (Oliveira-Brochado, 2019). Thus, the sentiment index helps to assess the marketing performance.
Important Drawbacks of this Measure
While the market sentiment measurement provides an essential ground to make prediction of market behaviour, this approach has various limitations. According to Koo, Chae and Kim (2019), there are two types of investors which are irrational and rational arbitrageurs who are sentiment free. In this regard, mispricing may arise as the irrational traders make decisions based on their sentiments while the rational traders encounter limits to arbitrage. Such mispricing influences the investors into making inappropriate decisions which may negatively affect their investment goals.
Further, the current wave of technology and globalization has ignited the use of social media platforms to gather and spread information. This explains the crucial relationship that exists between internet search behaviour and market sentiment measurements. Such also includes influencing the financial markets. Social media platforms provide a ground for interaction between customers and business owners. For instance, most of the big corporations operate Twitter accounts, where critical activities. Despite this crucial relationship between the two variables, any form of negativity regarding a business entity would quickly spread extensively hence influence negative impacts on its brand image and performance. As Barberis, Shleifer & Vishny (1998) highlighted, negative news spread faster than the positive news, and this could depict risky impacts on the corporations. In other words, investors would spend enormous amounts of capital to establish brand images, only to lose it quickly through the social media platforms should a slight mistake occur regarding their products.
Besides, market investment is an important variable to describe the stock rates of return. According to the sentiment index analysis, a positive sentiment period stocks which are attractive and optimistic speculators with less attractiveness to arbitrageurs depict lower returns (Barberis, Shleifer & Vishny, 1998). However, a contrast period of negative sentiment, the pattern is reversed or attenuated.
Another setback of market sentiment measurement is its low accuracy level. The tools picked randomly by the commercial classifiers to measure the investor sentiment most likely report the wrong result. In this regard, it becomes difficult to predict market behaviour by measuring the sentiments using the analysis tools. Further, longer texts are difficult to classify hence making it hard to detect sentiment performance. A slight decrease or increase in performance can be noted for longer texts with negative or positive sentiments.
Conclusion
In retrospect, marketing sentiment measurement is an important determinant factor for the mark the behaviour. It provides stable ground and a clear picture of the current market trends, which enables the investors to make timely decisions. This paper explained the idea behind this approach in reference to some articles that describe market sentiment measurement. Important implications, limitations, and anomalies associated with this model were also discussed. Overly, market sentiment measurement specifies the market mood hence enabling the investors to make appropriate decisions regarding selling and buying of stocks.
References
Asif Khan, M., Ahmad, R., Azmi, A., & Akbar, M. (2019). A new sentiment index for the
Islamic stock market. Investment Analysts Journal, 48(2), 146-172.
Baker, M., & Wurgler, J. (2007). Investor sentiment in the stock market. Journal of economic
perspectives, 21(2), 129-152.
Barberis, N., Shleifer, A., & Vishny, R. (1998). A model of investor sentiment. Journal of
financial economics, 49(3), 307-343.
Gao, Z., Ren, H., & Zhang, B. (2018). Googling investor sentiment around the world. Journal
of Financial and Quantitative Analysis (JFQA), Forthcoming.
Koo, B., Chae, J., & Kim, H. (2019). Does Internet Search Volume Predict Market Returns and
Investors’ Trading Behavior?. Journal of Behavioral Finance, 20(3), 316-338.
Oliveira-Brochado, A. (2019). Google Search-Based Sentiment Indexes. IIMB Management
Review.
Yang, S. Y., Mo, S. Y. K., & Liu, A. (2015). Twitter financial community sentiment and its
predictive relationship to stock market movement. Quantitative Finance, 15(10), 1637-1656.