Security Market Returns
Stock markets returns have been the subject of many studies for centuries. The first seminal work on this subject can be found in Saunders his work on impact of cloud cover on market returns in 1993 (Keef & Roush, 2007b). Cao & Wei (2005) argue that in investment finance, market returns are sensitive to diverse factors within the market and outside the market. Among the diverse factors that have been investigated in these studies is the influence on weather on stock market returns. There are diverse ways that this aspect can be perceived from a researcher’s point of view. According to Cao & Wei (2005), of the aspects is evidence that there is a correlation between stock market returns and the weather conditions prevailing in a given period. However, Chang et al (2006) observe that existing empirical literature do not have a unanimous consensus on the exact impact of weather conditions on market returns. While some advocate the reasoning that in deed there is a relationship between these two variables, some object to it.
Another seminal work supporting the arguments of Yuan, Zheng & Zhu (2006) can be traced to earlier 1990s when Saunders (Dowling & Lucey, 2005) conducted a study to determine the impact of cloud cover on market returns. Dowling & Lucey (2005) also alludes to the seminal works of Trompley which studied the same problem. More recently, cloud cover effect on market returns was performed by Keef & Roush (2007b). Their findings indicated that returns were very low during days characterized by 100% cloudy cover than days with a 0% to 20% cloudy cover. However, the differences in returns were not significant. This had also been observed by Tompley in 1997 and Saunders in 1993 as Dowling & Lucey (2005) indicate. Although not imparting a significant effect on returns, the general deductions of Dowling & Lucey (2005) and Keef & Roush (2007b) indicate that generally there is a negative correlation between cloudy cover and market returns.
Loughran & Schultz (2004) present a quantitative analysis of the impact of clouds on the stock returns in New York and find that the stocks with the highest returns (0.073%) are those studied under overcast relative to a 0.063% average return for clear skies all day. For days with scattered clouds, Loughran & Schultz (2004) found that the New York stock return was averagely 0.046% and 0.054% in cloudy days. Consequently, the percentage of clouds in the sky exhibited some effect on the changes of returns in New York. Moderate clouds (scattered was found to have significant effect on the stock returns. In regard to the economic effect of cloud cover on stock market returns, Loughram & Schultz (2004) argue that investors can enhance their margin of their returns by monitoring the trend in cloud cover. For instance, a day with a overcast will be a very busy day in trading and there will be a significant increase in stock market turnover and returns. However, the economic effect is not significant as the statistical significance because in economics, there are diverse other factors that come to play.
The studies of Dowling & Lucey (2005) and Keef & Roush (2007b) are supported by Akhtari (2010) who take a different approach in evaluating cloudy cover on security market returns. He analyzes the impact of sunshine on stock markets returns using Wall Street as a case study. Akhtari (2010) uses the regression analysis model to find the relationship between cloudy cover (availability of sunshine) and the Dow Jones Industrial Average market index from 1948 to 2010 on an annual frequency.
The findings confirmed the results that were observed in the seminal works of Dowling & Lucey (2005), Keef & Roush (2007b) and Keef & Roush (2007a). There was a negative relationship between cloud cover and the gross Dow Jones Index representing market return. Logically, it can be observed that sunshine will have a positive effect on market returns. In other words, when there is full sunshine, the day is not cloudy and hence returns are high (extrapolating the findings of Dowling & Lucey (2005), Keef & Roush (2007b), Keef & Roush (2007a) and Yuan, Zheng & Zhu (2006). In regard to modeling the impact of sunshine or cloudiness on security markets, Hirshleifer & Shumway (2003) augment the regression model used in Akhtari (2010).
Question Four Temperature is another indicator of weather that has been investigated by diverse researchers to decipher its impact on security market returns. One of the best literatures in this area is that of Cao& Wei (2005). Similar studies have been undertaken by Keef & Roush (2003), Loughran & Schultz (2004), Kamstra, Kramer & Levi (2003) and Pardo & Valor (2003). Temperature has been used as one of the variables in many of the studies and the findings indicate that there is a negative relationship between security market returns and the degree of temperature in the course of the day.
To some extent, there is some relationship between cloudy cover, sunshine and temperature. In other words, days with full cloudy cover are assumed to be colder than those with full sunshine which are presumed to have high temperatures. However, there is some confusion in results when the above empirical studies are assessed critically. In other words, if high temperatures result in low returns (negative relationship) and high temperature is associated with sunny days which, according to Akhtari (2010) have positive relationship, then clearly there is confusion or lack of consensus. Nonetheless, these two results will be expected during the study and contrary finding will not be unusual.
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