Synchronicity In Individual Stock Returns For Companies Listed On Stock Exchange Of Mauritius: Literature Review
Definition of Synchronicity
Stock return synchronicity is the parallel movement of individual firm’s stock returns together with the market return. The co-movements of the stock would depend on whether more information is available for the firm or for the market and the extent to which they are relatively capitalised into the stocks. In simpler words, Roll (1988) describes synchronicity as the level of variation in each firm’s share price relative to the whole market variation. According to Jung et al (1985), synchronicity does not depend either on time or space or time. Stock synchronicity could be in both directions that is upward or downward meaning that when the market index rises, the firm’s stock price also goes up and when the market index falls, so does the individual firm’s share price. Hence as accurately described by Khandaker and Heaney (2008), synchronicity refers to the movement of share prices in the same direction over a certain time. The higher the stock price synchronicity, the more likely it is for the market information can explain the stock price changes.
Morck et al (2000), who were among the first ones to do ground-breaking research on this topic, defines synchronicity as the degree of co-movement between the individual stock return and market return. This notion has been valid ever since. In their paper, Du et al (2007) refers to synchronicity as “the extent to which individual stock prices move up and down en masse.” By these definitions, we can infer that the more would each firm’s stock price move together the more synchronous would be the market.
Measures of Synchronicity
There are three main measures of synchronicity.
The classical measure
The first measure was used by both Roll (1988) and Morck et al (2000) and is known as the classical synchronicity measure. It focuses on the parallel movement of stocks. Given that these co-movements can be either upwards or downloads, the classical measure will be used to determine the fraction of the net change in prices for a particular country over a period of time. This can be computed as follows: where njtup is the number of stocks in country j whose prices rise in week t and njtdown is the number of stocks whose prices fall. Studies like Morck, Yeung and Yu (2000) and Khandaker and Heaney (2008) used this measure in an attempt to calculate the synchronicity level. The advantage of using this measure over the other two is that it is a simple model and the market-wide movements can be determined even over relatively short period of time. However only market-wide movement can be determined though this measure and hence individual stock synchronicity cannot be found.Therefore, since this study is about analysing each stock synchronicity level, this measure can definitely not be used as no such values for each firm could be obtained. The values obtained from this measure range from 1.0 to 0.5 which represents perfect synchronisation and least synchronisation level possible whereby there is the same number of stock price rises and falls.
R-Square Measure
The second measure was introduced by Morck and is derived from the CAPM model. It is known as the R2 and is used to measure synchronicity level at individual level from which you could obtain the country synchronicity as well by averaging the figure. A linear regression will be performed for each stock i traded in market m: where, for firm i and period t, Rm is the market return, is a constant,i is the coefficient and is the random errors. R2im that is the coefficient of determination measures the percentage of stock return i that is explained by the local market. The value of R2 normally lies between 0 and 1 and the bigger this value, the higher would be the synchronicity. Hence, in order to avoid with large skewness and kurtosis, the synchronicity level of the market would be the logistic transformation of the average of R2im obtained for all the stocks shown below: λ j = log [ R2im / (1- R2im)]
Studies like Durnev et al. (2003) and Pagano and Schwartz (2003) interpret R2 as a measure of price efficiency or inefficiency. The accuracy of the R2 measure for price informativeness has been questioned because of errors in prediction and noisiness associated. While studies like Jin and Myers (2006), Chan and Hameed (2006) and Morck et al. (2000) argues that informative stock prices would lead to lower R2 values that is lower level of stock return synchronicity, Dasgupta et al. (2006)’s findings are contradictory.
Zero-Return days Measure
The third measure is called the zero-return measure and was established by Skaife et al. (2006). This measure was introduced because the stock market synchronicity could not capture the market level information well. They came up with the idea based on what Lesmond et al. (1999) pointed out. This was that if the trading cost exceed the information signals, investors will not trade at all, hence ultimately stock prices will not change. Therefore, there are zero returns. This measure is used to capture the degree to which prices are informationally efficient.
Reasons for measuring the Stock price synchronicity level
Every investor must be aware of the synchronicity level in their specific country because the higher the synchronicity, the higher will be the macro-economy or system risks. This is so because the companies’ incomes seem to be affected in the same way. Because of the concentration of industries in the market, there are very few chances for diversification.High stock co-movements could be an indicator of the presence of too flexible regulations and poor property rights. This could reduce the efficiency of the market since arbitrageurs would be unwilling to deal in such markets due to high difficulty and huge costs involved in procuring firm-specific information. In such a case, less firm-specific information would be integrated in the stock prices.
Moreover, less stringent laws could promote more insider trading and hence discourage public to trade in such market. Therefore, higher stock return synchronicity could indicate that information is not equally available to both insiders and public investors.
Empirical Evidence
Stock market synchronicity concept goes way back in time. French and Roll (1986) and Roll (1988) concluded that low stocks price synchronicity is a result of high level of market information as well as high stock prices. While Roll (1988) focused on information integrated in stock prices, Morck et al (2000) focused more on the worldwide aspect and performed a cross-country analysis whereby they deduced that there was a negative relationship between the size of a country and its synchronicity level. On the other hand, GDP Growth and earning co-movements were found to be positively correlated with the synchronicity level. In order to conduct this analysis, Morck et al (2000) took a sample of 40 countries with a total of 15290 firms so as to measure their stock return synchronicity. They also revealed that the number of stocks would also affect the country’s synchronicity such that the fewer the number of listed companies, the higher would be the stock return synchronicity. Moreover, Morck et al (2000), by using good governance indices, found that market size and the good governance indices have a significant relationship and hence suggested that market size could be a vital element in explaining stock synchronicity.
They also argued that higher level of property rights and higher stock prices synchronisation co-exist together. They also found that lower levels of property rights were predominantly more existent in emerging countries while better protection of property rights were found in developed countries. Another finding of theirs is that there is a positive link between GDP per capita and good governance index. Hence, according to all these findings, developed countries like US or UK with high GDP per capita and good governance index should have lower level of price co-movements. Moreover, they stated that this was the opposite for emerging countries additionally due to significant or sudden changes in monetary policies and higher inflation rates. These can be supported by the study of Li et al (2003) whereby they concluded that Mexican stocks, being an emerging country, experiences higher stock synchronicity as compared to a developed country like Canada.
Skaife et al (2006) analysed R-square values with respect to the price informativeness and concluded that despite all being developed countries, in Australia, the higher the price informativeness, the higher would be the R-square values which is the opposite for Germany and Japan. Studies like Jin and Mayers (2004), Greenwood and Sosner (2002), Barberis et al. (2005) and Wurgler (2000) evidenced that there is a negative correlation between low GDP per capita countries and their stock price synchronicity. This could be the result of lack of transparency as concluded Jin and Mayers (2004) who tried to establish a relationship between corporate transparency measures and stock synchronicity through computation of R-values. They concluded that lack of transparency would restrict firm-specific information to investors and hence market information would explain more the total variation rather than the firm-specific information causing the price of stocks to move more synchronously with the market.
