Center for Financial Studies
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The Center for Financial Studies provides SNHU students and the general community with an integrated educational experience that includes financial analysis and planning.
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Browsing Center for Financial Studies by Author "Dhakar, Tej S."
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Item Anomalous behavior of the volatility of DJIA over the last century(Southern New Hampshire University, 2006) Hamid, Shaikh A.; Dhakar, Tej S.This 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.Item The behavior of the Consumer Price Index : 1913 to 2003(Southern New Hampshire University, 2005) Hamid, Shaikh A.; Dhakar, Tej S.This paper analyzes the seasonality in the monthly consumer price index (CPI) over the period January 1913 to December 2003. We examine three types of month effects: if the mean of monthly CPI changes of the entire data set, and of a given month were significantly different from zero; if the mean of monthly CPI changes of a given month was different from the mean of the other months; and if the variance of the monthly CPI changes for a given month was different from the variance of the other months. The mean of monthly CPI changes for the entire data set (0.27%) was found to be significantly greater than zero. The means of monthly changes show a downward trend from September to December. When the data are sliced into three sub-periods, we find an increasing trend in the means and medians of monthly changes but a decreasing trend in the standard deviations of the monthly changes. The mean of monthly CPI changes during the Republican presidencies (0.15%) was significantly lower than during the Democratic presidencies (0.38%). A revised version of this paper has since been published in the journal Applied Economics. Please use this version in your citations.Item The behavior of U.S. Producer Price Index : 1913 to 2004(Southern New Hampshire University, 2006) Hamid, Shaikh A.; Dhakar, Tej S.; Thirunavukkarasu, ArulThis 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.Item A new perspective on the anomalies in the monthly closings of the Dow Jones Industrial Average(Southern New Hampshire University, 2003) Hamid, Shaikh A.; Dhakar, Tej S.This 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.