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July – December 2018

Investor attention to market categories and market volatility: The case of emerging markets

emerging markets

Jarkko Peltomäki, Prof Michael Graham and Anton Hasselgren

  • OCT 2018
  • Tags Insights, Finance
17 minutes to read

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Jarkko Peltomäki, Prof Michael Graham and Anton Hasselgren

Using investor attention as a way to explore financial market phenomena

In the immediate aftermath of the Brexit vote in the UK in June 2016, various news outlets reported that the most searched words and phrases by individuals in the UK, according to Google Trends, were based on terms related to the vote. This highlighted the usefulness of an important variable garnered to capture individuals’ attention to specific events, thus validating the use of the Google-based search volume index (SVI) to investigate financial market phenomena, like market performance, in finance literature. However, relating SVI to financial market patterns has been empirically problematic because we cannot be certain that trading decisions are made on the basis of information gathered from a Google search.

In this article, we estimated three practical innovations of the investor attention variable that incorporate investors’ trading decisions and applied them to equity and foreign exchange (FX) markets volatility in a specific market category, namely emerging markets (EMs):

  • First, based on the Multiple Resource Theory, we estimated a refined proxy for attention from the search volume index (SVI) and abnormal trading volumes (ATV) in the market. We did this by taking the first principal component of SVI and ATV. Thus, we reinforced an obvious online query with market-based information on trading volumes to increase the possibility that information from an internet search is used when making trading decisions. This maximises the amount of variation captured from both variables and accentuates the signal value regarding investment activity.
  • Second, we disentangled the variation in the SVI variable most likely to affect EM-specific volatility. To do this, we took the first principal component (PCA) of SVI and excess ATV, the difference between abnormal trading volume in emerging markets and the United States.
  • Third, we split SVI and the new PCA-based proxy for investor attention into expected and unexpected attention. This points to the component of attention most likely to impact price behaviour.

An inherent assumption in asset pricing models is that financial markets extract and instantaneously include new information in asset values. Yet, news cannot be reflected in prices until agents pay attention to and act on the information. The Multiple Resource Theory suggests that investor attention to specific events can be broken down into three stages: perception, processing and action. Filtering trading-related attention to any market category is challenging as investor attention to a financial asset does not automatically translate into trading decisions and action.

In this study, we have attempted to capture and apply the full spectrum of the dynamics in the information processing in the innovations we estimate. Proxies for attention in existing literature have mainly focused on the individual stages of investor attention. For example, SVI captures perception and processing while ATV focuses on action, with no links between the two.

Attention is a scarce cognitive resource, implying investors with limited time and effort use only a limited set of information. Implicitly, to efficiently allocate scarce attention, investors categorise assets or markets at the initial step of the portfolio allocation decision. This makes categorisation based on shared commonalities crucial from the viewpoint of information processing as it enables, with reasonable efficiency, the processing of a large volume of information.

Yet, the literature that looks at the important role of investor attention in determining stock price volatility is silent on the impact of attention on the volatility of returns in key market categories.

The emerging market category, which encompasses a wide variety of countries with different characteristics, it is an important market category. The literature has, for instance, established that the EM’s risk profile is inherently different from that of developed markets, and that it is a segregated part of the global stock market. Thus, the EM category merits an in-depth understanding in order to enhance its contribution to global stock portfolio diversification. Therefore, we re-examined the hypothesis that investor attention explains stock market volatility and applied it specifically to the emerging market category using our newly developed measures of attention. We therefore hypothesised that EM equity market volatility increases with investor attention to EM economies.

We also examined whether investor attention exerts any measurable influence on volatility in the EM foreign exchange (FX) market. The focus on the EM currency category has some merits as some EM currencies are currently included in the top most traded currencies. Also, EM currencies are seen as an important risk factor in EM equity returns. In the market itself, the financial press recently speculated about the increase in foreign exchange instability as a result of policy divergence across countries. The Bank for International Settlements has noted significant swings in capital flows to and from EMs, resulting in a reappraisal of its FX market intervention strategies. This suggests important changes in the patterns in the EM category of the FX market. However, empirical evidence on the impact of investors’ information acquisition on currency price dynamics, including volatility, is limited.

Evidence on whether or not investor attention is a significant driver of price behaviour or volatility in EM currency markets should therefore have practical applications for trading and predicting the direction of the EM economies.

What does the literature say?

The theoretical literature on the implications of limited attention for asset pricing shows that attention constraints lead to lagged investor responses to fundamental shocks and predictable consumption changes. In addition, when selecting a portfolio in the presence of rational inattention, investors with greater risk aversion or longer investment horizons tend to update news less frequently, but select more precise news updates. Moreover, the propensity to concentrate on market and industry-level information, rather than firm-specific information, is characteristic of investor inattention.

The empirical literature has examined the relationship between investor attention and asset returns using different proxies for attention. Earlier research looked at the important role that mass media outlets play in disseminating information to investors and inferred indirect measures of attention such as headline news, media coverage and advertising expenses. These proxies all show important effects on financial variables. Other studies inferred investor attention from abnormal trading volumes (ATV). Using these proxies, some researchers provide evidence that investors’ propensity to buy stocks that catch their attention is greater than the propensity to sell.

Recognising the growth and importance of the internet as an information hub for investors, a strand of research has explored internet-based attention proxies. While proxies such Wikipedia updates and blogposts have been used, the literature has lately converged around Google-based search queries (SVI) as a measure of attention. The SVI is correlated to, but different from, other proxies for attention such as trading volume and media coverage. Importantly, SVI is shown to be positively associated with future stock returns. The internet-based proxy for investor attention also shows that an increase in attention improves market efficiency and leads to a significant change in short-term index returns. The literature review for this study has also noted a long-term change in attention following a shock to index returns. There is strong evidence that internet search volumes regarding market states include relevant information about investor attention and that they perform well at predicting future market performance.

The SVI variable actively incorporates expressed interests by economic agents. However, researchers cannot be sure that investors who source their information from the internet use it to make trading decisions. That is why we have measured investor attention by estimating three practical innovations of the investor attention variable to emerging markets. We combine the proxies through principal component analysis (PCA) to extract information from several variables.

In the FX market volatility literature, two important results came to the fore. First, attention and FX market volatility go hand in hand. Second, attention predicts FX market volatility. It was also noted that EM currency return is a significant risk factor of EM equity returns. Given this explanatory role of currency returns for emerging equity markets, we have related our initial hypothesis to EM foreign exchange volatility to test a second hypothesis: FX market volatility in emerging markets increases with investor attention to emerging markets.

What data and analyses were used?

The data used in the empirical analyses were obtained from varied sources. The data on the MSCI Emerging Market Index, the S&P 500 Index and the MSCI Emerging Market Currency Index used to estimate the market returns and return volatilities was drawn from the Thomson Reuters DataStream. Two currencies were pegged in the MSCI Emerging Market Currency Index, namely the Jordanian Dinar and the Chinese Yuan. The data period was 16 April 2004 to 12 December 2014. Various analyses were conducted, including descriptive statistics, pairwise correlations for all pairs of variables and Pearson correlations.

Measures of investor attention and volatility

We used the US Google-based Search Volume Index (SVI), employing the search word emerging markets to represent attention to the EMs category. This search term typically relates to information of a financial nature, which minimises the level of noise in the search word. The Google data is normalised as the probability of a search on the particular search word for a specific region and time measures the probability of a search during an entire week. We labelled this variable the Emerging Market Search Volume Index (EMSVI) and interpreted it as capturing the attention of retail investors. This measures the overall interest in the asset category displayed by potential and actual retail investors. We also split the EMSVI variable into expected and unexpected components. The expected EMSVI, EXPEMSVI, represents expected attention to emerging markets while the unexpected EMSVI, UNEXPEMSVI, represents shocks to attention not anticipated by the market.

We included abnormal trading volume (ATV), defined as the ratio of the daily trading volume over the yearly average, as an alternative proxy for attention in our empirical analyses. This investor attention variable should capture the last stage, action, in the information processing procedure, where investors have paid enough attention to make a buy/sell/keep investment decision. This measure of attention complements the SVI. The trading volumes in emerging markets and the US are represented by the respective trading volumes of the MSCI Emerging Market Exchange Traded Fund and the Standard and Poor Depositary Receipt Exchange Traded Fund, for which the data was accessed from Yahoo! Finance.

However, a measure of investor attention based on an internet search query cannot explicitly state that the agents who searched for the information acted on it to make trading decisions. In this paper we also used a refined measure for investor attention, which increases the probability that internet search results are incorporated into investor decisions, thus taking into consideration action. To do this, we combined measures to capture a wider spectrum of investor attention.

Conclusion

What is the impact of investor attention on stock market and FX market volatility in emerging economies using innovative attention proxies that capture all the dynamics of the information processing stages?

This paper examined whether investor attention has explanatory power regarding emerging market equity and currency volatility. Attention is a scare resource and investors, making portfolio allocation decisions, categorise the market based on shared commonalities to gain incremental knowledge. Thus, from an information processing viewpoint, large volumes of information in certain categories can be processed efficiently to enable efficient trading decisions to be made.

In this paper we estimated and applied various attention innovations to examine the information processing and actions in relation to emerging markets, namely Google-based search volume index (EMSVI) and abnormal trading volumes (EMATV) in the market:

  • First, we took the first principal component of the EMSVI (Google-based search volume index in emerging markets) and the EMATV (abnormal trading volumes in emerging markets) to form a new attention variable, based on Multiple Resource Theory. We argued that this new attention variable is better in capturing the possibility that retail investors, who see headlines and search for information (proxied by the Google-based search volume index), use that information in their trading decisions (abnormal trading volumes).
  • Second, we disentangled the variation in the SVI variable that is most likely to affect EM-specific volatility by taking the first principal component of SVI and excess ATV. This means the enhanced investor attention variables potentially have stronger economic significance relative to the Google-based search volume index (SVI) proxy.
  • Third, we split attention into an expected and an unexpected component to inform on the component attention that most likely impacts price behaviour. Our results indicated that the economic significance of the enhanced attention variables is higher than the traditionally used Google-based SVI proxy.

We found that investor attention has a significant influence on stock market volatility as well as excess volatility in EMs. This finding has three implications:

  • Categorisation matters, as the emerging market category is linked to investor information processing.
  • Investor attention to the EM category of the global stock market is a relevant determinant of stock market volatility in EMs.
  • EM equities have a segregated role in the global market.

Our results also showed that both expected and unexpected (shocks to) attention are significant when explaining changes in excess EM equity volatility. However, investor attention to EMs does not show any measurable impact on EM FX volatility, which suggests that the predictive power of attention in relation to FX volatility cannot be generalised. This finding implies that information processing about the EM category does not affect FX similar to equities.

Overall, our results showed that investors in emerging market equities should be aware that the riskiness of their investment is exposed to investor attention to the EM category. It is also clear that the measuring of investor attention in research can benefit from adopting a multi-dimensional approach, taking into account various aspects and levels of attention.

  • Original article: Peltomäki, J., Graham, M., & Hasselgren, A. (2018). Investor attention to market categories and market volatility: The case of emerging markets. Research in International Business and Finance, 44, 532-546. Click here
  • Prof Michael Graham lectures in Infrastructure Finance and Corporate Finance at the University of Stellenbosch Business School. He is also head of USB’s Development Finance portfolio of programmes.

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