A new perspective on the anomalies in the monthly closings of the Dow Jones Industrial Average

Version of RecordThis study explores three types of month effects in the Dow Jones Industrial Average: (a) for a given period, if the mean of monthly percentage changes of each month was different from zero, (b) for a given period, if the mean of monthly percentage changes for a month was different from the means of all the other months, and (c) for a given period, if the variance of the monthly percentage changes for a month was different from the variances of all the other months. For our entire data set (May 1896 to December 2002) we find that the means of monthly percentage changes of only July, August, January and December were significantly greater than zero (months put in descending order). But the means of none of these three months were significantly higher compared to the means of all the other months. With a mean percentage change of -1.25%, only September appears with significant negative returns. And this mean is significantly lower compared to the means of all the other months. In other words, for the entire data set, we have a negative September effect. Month effect with respect to variance (variance of monthly percentage changes for a month being significantly different from all the other months) was found for January, February and December (lower variances), and April (higher variance). When we look at the first half of the twentieth century versus the second half, we see more pronounced month effects in the second half - considering all three types of effects we analyze. December exhibited all three types of effects in this period. When we sub-divide the last century into four 25-year periods, we find more pronounced month effects in the last quarter than in the previous three quarters. When we sub-divide the data into 10-year periods, we do not find any consistent and discernible pattern. The month effect varies with the time period we consider and the type of effect we analyze. Though one would expect the DJIA stocks to be free from seasonal patterns since each one of them are closely followed by a large number of analysts, the existence of any type of month effect is surprising. However, given that no discernible pattern is detectable is a reflection of efficiency of the DJIA stocks to a large degree.Hamid, S. A. & Dhakar, T. S. (2003). A new perspective on the anomalies in the monthly closings of the Dow Jones Industrial Average (Working Paper No. 2003-04). Southern New Hampshire University, Center for Financial Studies

A Comparative Study: Globalization and Development of Regions of Europe, Asia Pacific, and Latin America

Globalization is one of the most significant concepts of our time that has led to countless academic discussions and public debates. Several empirical literatures have explored how globalization has impacted developed and developing economies. It is critical to study the effects of regional globalization and the impact of different methodological perspectives. This paper examines the effects of globalization across various regions of Europe, Asia Pacific and Latin America. The secondary data used for this paper is obtained from Statista and the World Bank. The methodologies used include One-way Anova, Regression Analysis and Ancova. The findings of the Anova show how globalization significantly impacts the regions discussed in this paper. This indicates that the regions derived substantial benefits from globalization. The regression analysis results highlight that there is no relationship between globalization and democracy, and the Ancova results support that the interaction of region and democracy is not significant. We therefore conclude that the growth and development of these regions related to globalization is based on increased competition, employment, investment and capital flows, foreign trade, spread of technical know-how, spread of culture, high standard of education, and structural institutions. This paper provides a platform to better inform policy makers in these regions, as well as the world, on how the benefits of globalization lead to the expansion and growth of developed and developing countries. Keywords: Globalization Index, Europe, Asia Pacific, Latin America, Democracy Index, Ancova DOI: 10.7176/IAGS/89-03 Publication date: January 31st 202

Global shock transmission to emerging markets

Author's OriginalThe process of global integration has intensified the competition in world markets during the 1990s. In the new environment, many developing countries are increasingly relying upon greater trade integration for upgrading their international competitiveness and promoting their dynamic comparative advantage. In view of growing global integration, this paper attempts to analyze whether Indian, Hungarian and Polish economies have become more internationalized as a result of economic reforms embraced by each of these countries in early 1990s and hence vulnerable to global economic cycles: the integration hypothesis. The paper applies variance decompositions derived from vector auto regression to assess the degree of economic integration of the three economies with U.S. economy. The study concludes that, in the pre-liberalization period U.S. economy did not influence the Indian, Hungarian and Polish economies. Shocks from U.S. had no impact on their aggregates. In the post liberalization period, however, the results are mixed. Hungarian aggregates show very low degree of integration with US followed by Poland, and India. Although, all the three countries have shown varying degrees of integration in the post-liberalization period, none of the economies are found to be overly vulnerable to international shocks. It can be argued that despite opening of economy and transition towards integration with the global economy, the degree of integration across countries still remains significantly low.Dasari, U., Dhakar, T. S., & Samii, M. (2003, July). Global shock transmission to emerging markets. Paper presented at the Academy of International Business Annual Meeting, Monterey, California. Retrieved from http://academicarchive.snhu.ed

The behavior of U.S. Producer Price Index : 1913 to 2004

Version of RecordThis paper analyzes the behavior of U.S. PPI over the period January 1913 to March 2004 using monthly “all commodities index” values. The mean of monthly percentage index changes for the entire data set (0.23%) was significantly greater than zero. January, July and November had mean monthly percentage changes which were significantly greater than the mean changes of the other months over the entire period. March, May and September had mean percentage changes significantly lower than the other months. We find that there is some periodicity to all commodities index. The mean of monthly commodities index changes during the Republican presidencies (0.08%) was significantly lower than the mean changes during the Democratic presidencies (0.38%) and so were the medians. We slice the entire data into three sub-periods. We find that though the means and medians have significantly increased over the three sub-periods, the standard deviations of the means have decreased. Granger causality tests reveal that while oil prices affected the all commodities index and the finished goods index, the causal relationship is not true the other way at the 99% significance level. The findings have implications for policy makers, analysts, investors, and manufacturers.Hamid, S. A., Dhakar, T. S., & Thirunnavukkarasu, A. (2006). The behavior of U.S. Producer Price Index: 1913 to 2004 (Working Paper No. 2006-04). Southern New Hampshire University, Center for Financial Studies

Anomalous behavior of the volatility of Dow Jones Industrial Average over the last century

Version of RecordThis study explores month effects in terms of standard deviations of monthly and daily percentage changes of the Dow Jones Industrial Average. During the last century, the standard deviation of the monthly percentage changes of April (6.63%) is significantly higher than the standard deviations for the other months. The monthly standard deviations of daily percentage changes as a measure of volatility exhibit a slightly rising trend, peaking in October and are all significantly different from zero. The mean monthly standard deviation of daily percentage changes for October (1.08%) was the maximum and also significantly higher than the means of the other months. The DJIA became less volatile in terms of monthly as well as daily percentage changes during the second half of the last century compared to the first half. If we divide the data for the last century into decades, the thirties stand out as the most volatile period in terms of monthly as well as daily percentage changes. Based on both dimensions, the decades prior to 1940 experienced higher standard deviations compared to the subsequent decades. So it appeared that the stock market became more volatile in recent times – but that was in points, not in percentage terms.Hamid, S. A. (2006). Anomalous behavior of the volatility of DJIA over the last century (Working Paper No. 2006-03). Southern New Hampshire University, Center for Financial Studies