Study Of Month Effects On Stock Returns - Free Essay Example

Sample details Pages: 6 Words: 1847 Downloads: 9 Date added: 2017/06/26 Category Finance Essay Type Research paper Did you like this example? According to the well known efficient market hypothesis, the stock prices in the future cannot be predicted from the historical trends in the stock prices. The market price of a particular day depends upon the demand and supply on that particular day and has no dependency on the historical data. It states that the market is efficient and no one can take abnormal profits because there are no trends in the stock prices and they cannot be forecasted. Don’t waste time! Our writers will create an original "Study Of Month Effects On Stock Returns" essay for you Create order But in the recent researches that have been made in the stock indexes all around the world have given evidences of anomalies seen in the stock indexes and returns that clearly negate the efficient market hypothesis. These anomalies or the trends are called as the Calendar effects. There are many calendar effects that have been detected in the various stock exchanges; the most widely known and searched are January effect, December effect, September effect, Monday effect. And there are others also that depend upon the country that is under study for example the Halloween effect in US stock market and Xmas effect in the English stock markets and Ramadan effect in the Islamic countries are well known. It is interesting fact that even though a lot of research has been conducted on these calendar effects and they have shown a lot of evidence in the stock markets all around the world, even now this has not been honored as a part of the literature. Mainly because if these calendar effe cts are studied over a larger scale of data, they fall weak in their significance. And gave an impression that these are not a reality but a mere illusion of the data or data mining. We in our paper have tried to study if there are any anomalies in the Karachi Stock Exchange. A larger data sample is taken so that the effect of the data mining would be decreased. And other tests would also be run to check the validity of the data and minimize the corruption of data mining. This study would be helpful for the investors in the country and abroad in making the right decisions for gaining profits. The study would also be helpful for the researchers all around the world in understanding more clearly this illusion of calendar effects, better, because Karachi Stock Exchange is the one that has been least studied in this context. Finally it would be helpful for the Karachi Stock Exchange itself, we believe, in drawing the attention of the researchers towards it and giving a positive im age in the research world. LITERATURE REVIEW To see the calendar affects and their historical existence, we will have to go back till Fama (1960) introduced the term called as the efficient market hypothesis, according to which the stock markets shows a random walk behavior and that the stock prices are not affected by the historical patterns in the stock market or in other words, the stock prices cannot be predicted. Also the theory stated that there is a uniformity of information in the market. And everyone trading in the market has the same information available to him and because of this uniformity in the stock information; no investor can take the abnormal profits. Various studies and researches were then performed to study the existence of this efficient market hypothesis. But some results were found that were totally contradictory to the efficient market hypothesis and its random walk behavior. Angel Berges, John J. McConnell, and Gary G. Schlarbaum (1984) found out that January effect was visible in the Canadian stock exchange and that the January stock returns were higher than every other month of the year ranging on a data period of 29 years from 1951-1980. These researches gave rise to other researches being conducted on January effect and finding out if there were any other anomalies in the stock exchanges as well. Lakonishok, J., Smidt, S. (1988) studied the Dow Jones over a period of 90 years data and found out significant abnormalities in the stock prices, the most obvious the Monday effect, at the end of the month, at the end of the year and the holiday effect. Having searched on this large scale data of 90 years considering these anomalies due to mere luck is not likely. The research then spreading to the other countries showed the presence of these anomalies in them as well. Anup and Kishore Tandon (1994) conducted a research on five seasonal patterns in the stock markets of eighteen countries. End of the month anomaly was seen in many countries. The large January returns are also seen in most countries. Apart from that Boudreaux (1995) also conducted research on stock markets of seven countries to find out significant positive monthly effects in Australia and Canada, while negative monthly effect in Japanà ¢Ã¢â€š ¬Ã¢â€ž ¢s market. P Hansen  (2003) conducted research on 27 stock indices from 10 countries, Denmark, France, Germany, Hong Kong, Italy, Japan, Norway, Sweden, UK, and USA and found 17 possible calendar effects containing 12 month-of-the-year and the 5 day-of-the-week effects. Grimbacher, Swinkels and van Vliet (2010) used a sample from 1963-08 find the Halloween and the turn of the month effects as the most significant of all anomalies and the January effect to be the weakest. These anomalies in the stock exchanges have shown varying results in different countries. For example Bin Li, Benjamin Liu (2010) performed the research in New Zealand Stock Exchange found out significant positive results in June and negative results in August , an anomaly that is not to be seen in UK stock exchanges. Also there was a very less significant January and April effects, present in just two industries indices in the sector. Also there has been a lot of controversy regarding the acceptance of these calendar anomalies as realistic or just because of a mere chance or because of the data mining. Jacobsen, Zhang (2010) used a wide scale data of 317 years of UK stock exchange to verify if these calendar effects were real or just by mere chance. The results also proved the existence of the calendar anomalies. And also shows a change in these anomalies along the time. Pre 1850 there was a December present in the market that changed into the famous January effect afterwards. Underperformance of the stock in the months of July and October is also evident in the data. So there has been a research in the stock exchanges all around the globe and they have found anomalies in the stock exchange returns, despite of the fact that they mi ght have been seen because of the data mining factor. A recent attention has also been given to the Karachi Stock Exchange as well to study if there exists any anomaly in KSE. F Husain (1998) took 36 individual stocks, 8 sector indices, and the general market index, covering the period from January 1, 1989 to December 30, 1993 to study if there was any Ramadan effect in the stock market and found out that although stock returns decline in the month of Ramadan, the reduction, in general, is not significant. There is strong evidence of a significant decline in the volatility of stock returns in this month. S Ali (2009) went to research with a bigger scale data of the KSE comprising closing daily, weekly and monthly data of the KSE 100 index for period starting November 1991 to October 2006. The results again showed neither monthly calendar effects nor days of the week effects. Positive average returns were witnessed in the first and second week while the third and fourth week sh owed average negative returns. There are no monthly calendar effects in the market either. DATA METHADOLOGY We have used the daily Karachi Stock Index ranging across a period of five years from January 2006 to December 2010.The close of day Rt is computed from KSE 100 index as follows: Rt =ln (It/I t-1) Rt is the daily return on KSE100 index on day t. It and I t-1 are closing values of the month respectively. To investigate the calendar effect we estimate the following regression equation: Rt =ÃŽÂ ²1Jt+ ÃŽÂ ²2Ft+ ÃŽÂ ²3MRt+ ÃŽÂ ²4APt+ ÃŽÂ ²5MYt+ ÃŽÂ ²6JNt+ ÃŽÂ ²7JLt+ ÃŽÂ ²8AUt+ ÃŽÂ ²9St+ ÃŽÂ ²10Ot+ ÃŽÂ ²11Nt +ÃŽÂ ²12Dt+à ¡Ã‚ ½Ã‚ ²t Where Rt is the daily returns and Jt, Ft, MRt, APt, MYt, JNt, JLt, AUt, St, Ot, Nt Dt are dummy variables for January, February, March, April, May, June, July, August, September, October, November, December respectively. If it is January than J=1 and à ¢Ã¢â€š ¬Ã…“0à ¢Ã¢â€š ¬? for all other days of the year, if it is February then F=1 and F= 0 for all other days of the year and so forth, à ¡Ã‚ ½Ã‚ ² is a ra ndom term. B1 à ¢Ã¢â€š ¬Ã¢â‚¬Å" B12 are co-efficient to be estimated using OLS. Empirical Results We conducted study to investigate the Calendar effect in Karachi stock exchange. We calculate monthly market returns for each month of the year, by using KSE-100 index daily data. Descriptive Statistics: Table- 1 Descriptive Statistics months Minimum Maximum Sum Mean Std. Deviation Variance Skewness Kurtosis Statistic Statistic Statistic Statistic Statistic Statistic Statistic Std. Error Statistic January -5.2785 4.7051 13.2874 .119706 1.4792473 2.188 -.789 .229 3.671 February -5.1349 4.1101 20.7684 .205628 1.3439130 1.806 -.354 .240 2.518 March -4.5007 5.3012 25.6476 .231059 1.5719945 2.471 .052 .229 1.590 April -3.9478 4.3185 15.3018 .143008 1.3536062 1.832 -.080 .234 2.408 May -4.6204 3.5514 -42.1196 -.382905 1.5753882 2.482 -.582 .230 .389 June -6.0418 8.2547 11.8456 .109681 2.1339432 4.554 .218 .233 2.150 July -4.5345 3.8806 5.1754 .046625 1.5524969 2.410 -.554 .229 1.439 August -3.9848 4.3948 -25.1996 -.229087 1.7060419 2.911 - .140 .230 .129 September -2.6705 2.9424 22.4747 .210044 .9636335 .929 .453 .234 .955 October -4.4355 2.8350 18.1200 .163244 1.0256923 1.052 -.889 .229 4.644 November -4.6738 2.7165 -2.3470 -.021934 1.1849094 1.404 -.775 .234 2.411 December -4.8184 2.6518 -41.2052 -.371218 1.5305945 2.343 -1.303 .229 1.285 By descriptive statistics we noted that mean return of the March is higher than the rest of the months. The mean return on March is 0.231059 whereas the mean returns of the rest of the months is an average of -0.018596. The higher mean return shows that there is March effect in Karachi stock exchange. Table- 2 Regression Analysis Model Unstandardized Coefficients Standardized Coefficients T B Std.Error Beta B (Constant) .047 .141 .331 Jan .073 .199 .014 .367 Feb .159 .204 .028 .779 Mar .184 .199 .034 .926 Apr .096 .201 .018 .479 May -.430 .200 -.080 -2.151 Jun .063 .201 .012 .314 July .033 .148 .006 .221 Aug -.276 .200 -.051 -1.381 Sep .163 .201 .030 .813 Oct .117 .199 .022 .585 Nov -.069 .201 -.013 -.341 Dec -.418 .199 -.078 -2.097 Regression results and related statistics are presented in table 2 and ANOVA test results are presented in table 3 Table- 3 ANOVA Model Sum of Squares Df Mean Square F Sig. 1 Regression 60.081 11 5.462 2.480 .004(a) Residual 2848.185 1293 2.203 Total 2908.265 1304 The results show that there is March effect in Pakistani stock market. The t value for the month of March is 0.926 which indicates a greater impact on the Rt. ANOVA suggest that the model is significant with F significance 0.004. Which indicate the fitness of the model. CONCLUSION In this study we have examined daily returns of KSE-100 Index, from the period starting 2006 till end of 2010, with a purpose to find out if there exist any monthly anomalies in the returns. In Karachi Stock Exchange, trading occurs five days a week (Monday, Tuesday, Wednesday, Thursday and Friday) throughout the year. The Efficient Market Hypothesis explains that there are constant market returns for the whole year. Empirical results of this study indicate that there is a significant March effect in Karachi Stock market. And this is proven by both the regression results and the descriptive statistics that are highest for the month of March than any other month of the year. March Returns are more volatile compared to other months of the year. So the results have concluded that in the recent five years, there has existed a month effect in Karachi stock market which is the March Effect. And thus the Efficient Market Hypothesis is violated in KSE.

Chapter 2 Review of Related Literature Sample - 1295 Words

CHAPTER 2 REVIEW OF RELATED LITERATURE AND STUDIES FOREIGN STUDIES In its broadest sense, impeachment is the process by which public officials may be removed from office on the basis of their conduct. Strictly speaking, it is the decision by a legislature to accuse an official of one or more offenses that warrant removal according to constitutional standards. A vote to impeach then triggers a trial based on those charges. The most famous impeachment proceedings have involved presidents, but every state has its own procedures. Most follow the federal model in general, but vary widely in their specifics. At the federal level, impeachment starts in the House of Representatives, where members may initiate resolutions to impeach a†¦show more content†¦Without a state House, the Nebraska Senate votes to impeach before passing articles on to the state Supreme Court for a trial. Oregon is the only state without constitutional provisions for impeachment of a governor or other executive and judicial officers, according to the NCSL. Those officials m ay be removed from office, but not by the state s legislature. State courts in Oregon may try public officials for criminal offenses, but the procedure depends upon the jurisdiction of a crime. LOCAL STUDIES Section 1, Article XI of the 1987 Constitution declares that â€Å"Public office is a public trust. Public officers and employees must at all times be accountable to the people, serve them with utmost responsibility, integrity, loyalty, and efficiency, act with patriotism and justice, and lead modest lives.â€Å" These words echo loud and clear today as our country’s leaders find themselves at the brink of conducting this constitutional process. Impeachment has been defined as a national inquest into the conduct of public men. 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Multi-generational plan Free Essays

It is widely known that the clash between the baby boomers and the generation Xers goes way back especially in the work place. As a result certain jobs could get compromised because of these clashing attitudes. It was well known though that both these generations could actually present ideas that could help the business running. We will write a custom essay sample on Multi-generational plan or any similar topic only for you Order Now The main problem about these two generations is the fact that they seldom go along with each other. But who are the baby boomers and the generation Xers? The baby boomers were widely known to be the people born between 1946 to 1964 while the generation Xers were people born between 1965 to 1980. Baby boomers were known to have plenty of opinions when it comes to political issues and they usually believe in longer time for work while the generation Xers witnessed or lived the technological boom of the world and are more skeptic than any other generations (â€Å"Workplace generation gap: Understand differences among colleagues,†). The long term goal then is on how these two generations could come together for the benefit of the company or business. The main key to make these generations come together is to eliminate the tension between the two by helping each other understand the usual personality or outlook that each generation has. There could be a program that would lead to the understanding of the two generations. Although, those organizing these programs should be on alert on what they ought to do especially when this kind of program could easily lead to prejudice. A good suggestion of this program is to put the two generations in each others shoes. A group dynamic could be done and these activities/projects should reflect a certain aspect where both generations could be useful. Then the next step here is to render respect for each of the generations. The respect should come out genuine. If respect were done for the sake of respect then these people might not have really understood the plight of each generation. References: Workplace generation gap: Understand differences among colleagues. (July 6, 2005).  Ã‚   Retrieved August 1, 2007, from http://www.cnn.com/HEALTH/library/WL/00045.html       How to cite Multi-generational plan, Essay examples

Microeconomics Principles. Problems - and Policies

Question: Discuss about the Microeconomics for Principles. Problems, and Policies. Answer: Introduction: The market force in a purely competitive market determines Price and quantity. In a competitive market a seller is price taker. Market supply is the aggregate output produced by all the firms (Baumol and Blinder 2015). As per law of demand, quantity demanded of normal good increases when price increases, ceteris paribus. Here, the assumption is other things such as income of the consumer, price of the other related goods and preference of the consumers remain the same. It has been assumed that the beef market is perfectly competitive. This assumption indicates that there is large number of sellers of beef and consumers have perfect information regarding product and quality (Parkin and Bade n.d). As per case study, multiple substitutes of beef exist in the market. Initial equilibrium is achieved in the market at the point E. S1 and D are initial demand and the supply curves in the beef market. At this point, total market demand for beef and total supply meets each other to clear the market. One of the main reasons for the rising price of beef in the market is decrease in supply of beef. Production of beef has decreased in West Australia as the number of cattle going to the local abattoirs has decreased. Moreover, number of processed claves has also decreased. Therefore, quantity supply of red meat has decreased. As the supply of cattle has reduced, supply of beef has reduced in the market. The market supply curve of beef has shifted to the left. At each price supply of beef has reduced compared to initial level. Change in price and supply of substitute goods have been ignored in this analysis as ceteris paribus assumption is held. Movement of price is along the demand curve. At P1 prices, demand is more than supply of supply of beef and hence, excess demand is created in the market. Firms are unable to supply beef by the amount of excess demand due to low production. Therefore, prices start to increase to clear the market assuming ceteris paribus. As price starts to rise above P1, some consumers, who do not want to buy same quantity at a higher price, are excluded from the market. Consequently quantity demand starts to decreases. The gap between demand and supply starts to decrease to absorb excess demand from the market. Price rises until the new equilibrium is reached at the point where new supply curve cuts the demand curve in the market. It has assumed that market demand has not changed. E2 is the new equilibrium, where new beef price is restored at P2 and the quantity demanded reduced to Q2. Elasticity of demand is determined by the change in the quantity demanded in response to the price of the product. Elasticity may be price elastic, inelastic and unitary elastic. Demand is elastic when the quantity demanded changes more than proportionately compared to change in price of the product, ceteris paribus. Thimmapuram and Kim (2013) mentioned that price elasticity of demand is negative as per law of demand. Law of demand states a negative relationship between price and quantity and the hence, the price elasticity of demand is negative. Weyl and Fabinger (2013) stated that price elasticity of demand is of two types such as own price elasticity and cross price elasticity. Own price elasticity reflects the change of quantity demanded due to change in own price of the concerned product. On the other hand, cross price elasticity refers to the change in quantity demanded due to change in price of a related good such as either substitute or complementary. Price elasticity of demand for beef is price elastic as it abides by the law of demand. One reason for elastic demand is availability of alternative in the market at a lower price. As the price of the beef increases by a small unit, quantity demanded of beef in west Australia increases more than proportionately. Same instance happens when price of beef falls. ep 1. When, price of beef rises, consumer surplus reduces. Ability of the consumer to purchase same quantity at a given price decreases. Therefore, consumer expenditure on beef decreases. When price increases other things remaining same, purchasing price of the consumer falls. The people with low income reduce consumption of beef and find other alternatives in the market. As the price elasticity of beef is greater than one, hence, small in price has greater impact on consumer expenditure (McConnell, Brue and Flynn 2014). Furthermore, as there is other alternative meet such as Spaghetti bolognaise and T-bone steaks, chicken in the market with falling price, consumers can easily move for those products. Hence, from the above discussion in can be inferred that consumer expenditure on beef market is reduced. The markets that are related to the beef market are chicken, Spaghetti bolognaise and T-bone steaks in West Australia. These are the substitute product of beef. As cited by Hall and Lieberman (2012), when price of good rises, demand for substitute good rises as demand for the concerned product falls. When the effect of price change on substitute goods are concerned, it is assumed that other things such as price for the product, income of the consumers and their preferences remain the same (Rios, McConnell and Brue 2013). Demand curve shifts to the left or right as the when price of substitute good changes. The following figure shows the effect of price change of beef on the market of other types of meet in West Australia. As price of beef increases, demand for other type of meet with low price increases. Hence, demand increases in the related market. However, in short run, there is no increase in supply. Therefore, excess demand is created at price P2. Price of other types of meet rises in the market in order to manage demand. Consumer surplus in this related market is reduced as well. As a consequence, price rises until the new demand curve cuts the existing supply curve. The new equilibrium price is P2, which is greater than previous one and the equilibrium quantity is Q2, which is greater than previous. Quantity sold in the market rises as demand has risen. References Baumol, W.J. and Blinder, A.S., 2015.Microeconomics: Principles and policy. Cengage Learning. Hall, R.E. and Lieberman, M., 2012.Microeconomics: Principles and applications. Cengage Learning. McConnell, C.R., Brue, S.L. and Flynn, S.M., 2014. Microeconomics: Principles.Problems, and Policies,16. Parkin, M., and Bade, R., (n.d) Microeconomics: Australia in the Global environment. First Edition. Rios, M.C., McConnell, C.R. and Brue, S.L., 2013.Economics: Principles, problems, and policies. McGraw-Hill. Thimmapuram, P.R. and Kim, J., 2013. Consumers' price elasticity of demand modeling with economic effects on electricity markets using an agent-based model.IEEE Transactions on Smart Grid,4(1), pp.390-397. Weyl, E.G. and Fabinger, M., 2013. Pass-through as an economic tool: Principles of incidence under imperfect competition.Journal of Political Economy,121(3), pp.528-583.