Choi and Skiba (2015) Institutional herding in international markets Journal of Banking and Finance 55 [246-259] Financial Investment assignment 2018-2019 Student group Cadau Michele Musicò Simone Domenico Achille Onori Filippo Voelkening Daniel Nicole Choi and Hilla Skiba’s paper studies herding behavior of institutional investors in international markets. The extant literature has documented a tendency of individual and institutional investors to herd. Papers by Lakonishok (1992), Sias (2004) and Barber (2009) have confirmed herding behavior in investors’ trades at the security level in a single market setting and Choi and Sias (2009) have documented it at the industry level. With their paper Nicole Choi and Hilla Skiba study investors’ herding behavior in the global environment, in a multi-market setting, using comprehensive holdings data. After selecting 41 “target countries” they tried to show at first the existence of wide-spread herding. Moreover, after documenting that institutional herding stabilizes prices, they tried to investigate the relation between institutional investors’ herding behavior and the level of information asymmetry in the target countries. At last they examined if the speed of the price adjustment of a security to its fundamental value is faster in transparent or non-transparent markets. Herding behavior is the tendency of individual or institutional investor to follow each other in and out of the same securities, from market to market. In the extant literature, it is discussed whereas herding is based on fundamental information, making markets more efficient, or on the contrary it destabilizes prices of securities. This division led to “fundamental information based” and “non-fundamental information based” explanation for herding behavior. The first category includes “investigative herding” where all investors analyze the same data and use similar methods to valuate securities, reaching the same results and making the same decisions (unintentional herding). Then there are “informational cascades” that occur when investors ignore their own private information about a security or a market and make decisions by inferring from other investors, assuming that their trades are based on signals from fundamental information. The second category includes at first “reputational reasons”, which is the tendency to copy investment decisions taken by others that, for example, record strongly positive historical performances; secondly, there is “characteristic herding”, that occurs when investors are attracted to the same securities’ characteristics, like some firm’s features that are positively correlated with the future returns of stocks; lastly there are “fads”. The data used by the researchers have been extrapolated from FactSec’s database. These quarterly data range from the last quarter of 1999 to the first quarter of 2010, providing the information about which securities the institutional investors have been holding, and for how much time. These facts were collected by FactSec through the mandatory report that companies must fill, but also by searching in the funds’ website and having a direct contact with the companies. The total of investors has the domicile in 86 different states, and they hold securities from 41 different countries. The data used are referred to single portfolios inside each institution, and they do not consider the national securities holdings. The researchers measured the herding propensity by taking a regression where the dependent variable is the number of institutional buyers and the independent is the lagged value of that variable (in 𝑡 −1 ). The beta of this regression was taken as measure of the institutional herding propensity. Because herding behaviour can arise also from a momentum investment strategy and not only as a long-run strategy, the authors tested if the relation (the beta) between institutional investors’ trading during the current quarter and the previous one arises because of institutions’ preference for momentum securities or not. With this purpose, they added a quarterly lagged return to the original regression. If institutional investors’ herding propensity is due to their momentum chasing behaviour, the coefficient of the lagged “buyers” variable will lose its significance after adding the lagged returns from previous quarter. The results of this regression show that institutional investors herding across international markets exists and is economically and statistically significant. Concerning the modified regression (the one with lagged returns), the results show that in 31 out of 41 target countries, institutional investors are momentum chasers, and this is evidenced by the presence of positive coefficients on lagged return. However, institutional investors propensity to herd is not fully explained by their momentum trading. The only difference that can be made is on the type of “force” that pulls this herding behaviour. On one side investors may follow the same strategy that other have made in the past quarter, hoping for good results. On the other side they may herd only in the view of faster and higher returns that arises from a momentum trading on one security. Then it is examined whether information asymmetry level of a target country is related to the herding propensity of its institutional investors. The authors explain that the degree of information asymmetry in each target country is measured along five dimensions: 1) Stock market development: they estimate each target country’s stock market development by the total market capitalization as a percent of GDP, the fraction of investable shares of the total shares outstanding (Float), and the standard deviation of the value-weighted stock market return (Volatility). All the data required to compose the proxies are obtained from World Bank, WorldScope and Compustat. From a statistical point of view all these variables are inversely related to the variable information asymmetry except for Volatility. 2) Ease of access to information: they proxy the dimension “access to information” by taking into account the number of Internet users per 100 people in the population, the number of Newspapers in circulation per 1000 people, and the overall access to Media in the country. All the proxies used in this category are inversely related to information asymmetry. The data were obtained by World Bank. 3) Corporate transparency: the third dimension is analysed by the authors by proxying several accounting transparency measures obtained from Bushman et al. Those measures include: Disclosure Intensity of the companies, International accounting Principle, Analyst Coverage, Insider Trading, Security Disclosure and Anti-self-dealing index. All these estimations are inversely related to information asymmetry. 4) Investor independence: they approximate the conditions under which investors work, indeed they measured investor rights by the index of Investor Protection constructed by La Porta et al. and by indices of Investment Freedom, Financial Freedom, and Economic Freedom obtained by Heritage Foundation. As always, they assume that all these proxies are inversely related to information asymmetry. 5) Macroeconomic factors that could relate to information environment: the selected variables are GDP per Capita in USD and the average annual Inflation. The basic assumption made by the authors is that GDP per Capita is inversely related to information asymmetry and vice versa Inflation is positively related to information asymmetry. Moreover, Choi and Skiba added two more variables to the regression: in their sample developed countries takes a dummy variable value of 1 if a country is classified as a developed country by World Bank and zero (0) otherwise. The second new variable is another dummy indicator variable “English” that takes a value of one for countries whose primary language is English. The main contribution brought to the financial literature from this paper consist in the fact that international institutional herding exists, because of the significant coefficients of the regression. Further results come through two tests of hypothesis. The first test shows that the herding propensity is negatively correlated with the information asymmetry level of each country, meaning that the herding behaviour probably has investigative nature and it is unintentional. The second hypothesis taken in exam in the paper is related to the speed of the adjustment process of security prices. The outcome is that the convergence of the price of a security to its fundamental value is faster in the countries with more transparency in financial information, which means with a lower level of information asymmetry. In other words, in the paper it is presented why the herding propensity is a process through which the new information are incorporated in the security prices as fast as the market is transparent.