Public Holiday’s Effect in Pakistani Stock Market Dr. Saqib Gulzar Department of Management Sciences, COMSATS Institute of Information Technology, Wah Cantt, Pakistan Nazish Yameen Malik Department of Management Sciences, COMSATS Institute of Information Technology, Attock Cantt, Pakistan Abstract: The primary aim of this study is to review the public holiday’s effect in Pakistani capital market. It is try to find out the trading activities situation prior to and post of holidays. In this paper, we utilized regression technique with dummy variables for testing the daily data of Karachi Stock Exchange 100 Index and selected sectors for time period of January 2000 to December 2009. The empirical results advocate that Pre-pre holidays and pre holiday effect declined over last ten years on daily basis. However, post holiday’s effect indicating higher mean returns than other trading days. Keywords: Pre-pre holidays effect, Pre holidays, and Stock Market. 1. Introduction Stock market of a country play vital role in the uplift of any economy. The productivity can be enhancing by effective and efficient use of the available resources of the economy. An efficient capital market channels economic resources from the savers to investors and producers. Regulators and practitioners of an efficient capital market develop the market in most proficient manner to gain the confidence of the investors. Market efficiency Hypothesis (EMH) is considered one of the utmost controversial theories in finance literature. Eminent scholars have done a number of studies on this issue and reported conflicting results. Efficient Market Hypothesis is modestly theory of investment that defines “it is impossible to beat the market” because in efficient stock market the share prices integrate and imitate all the related information and its causes. Stock are always at their fair value in capital market is basic element of EMH, so it is sticky for investor to either purchase undervalued shares or sell shares overestimated prices. . The derivation of the EMH is that though expert stock select and marketing timing is impossible to outperform the overall market. Only chance of high return is if the investors select more risky assets for their investment. The French mathematicians, Louis Bachelier, in 1900, first time introduced the concept of efficient market hypothesis in his dissertation, “The theory of Speculation”. His exertion was largely ridiculed in the initial stages. But in 1950s independent work support his thesis. The market efficiency hypothesis appeared as bloated in theoretic 1 position in mid of 1960s, when Paul Samulson circulated Bacheliers work among the economists. Eugene Fama in 1965 published a paper arguing for the random walk hypothesis and the proof of efficient market hypothesis is published by Samuelson. The efficient market hypothesis itemized in to three forms. “Week form efficiency”, “semi-strong form efficiency” and “strong form efficiency”. These forms have diverse inferences for market work. No abnormal return can be added by penetrating investment tactics based on the ancient asset values or additional financial statistics in “Weak form efficient market”. The abnormal returns cannot be predicted by technical analysis in weak form efficient market but fundamental analysis may still produce abnormal returns. In “weak form efficient market” the recent stock prices are finest and truly predict the value of assets. In “weak form efficient market” fundamental analysis is used to identify assets that are “undervalued” or “overvalued". In “semi-strong form” efficient market the prices move in an arbitrary small but finite amount of time and in unbiased trend to publicly new information, no abnormal return can be made by using that information. Fundamental analysis technique fails to reliably produce the abnormal returns in “semi-strong form efficient market”. The third form of the efficient market is strong form efficient market. In this form the prices of assets imitate all info and no market participant can receive abnormal return. Strong efficient market is impossible in case where legal bindings to private information becoming public, as with insider trading laws. This paper is prearranged as follows: Section II briefly explores the theoretical and empirical literature in this area. Section III shed light on the methodology and data section process of this study. While the regression results are explain in Section IV. Section V argues conclusion and practical implication of the study. 2. Literature Review The “efficient market” refers to the situation where current security market prices fully replicate all open information. Whenever new information included into the price so that prices become information. It can be said that market efficiency means asset prices change swiftly and correctly to the information. Fama (1965a) develop a model which is called as “Random walk theory” which defines that information conquers randomly so asset prices changes cannot be projected. Then he first time introduces the term “Efficient Market” in a financial literature, a market where the reaction current prices of assets to new information should be immediate. An Efficient Market Hypothesis (EMH) proposes that there should be no abnormality in stock returns. Calendar anomalies are the share price anomalies that are credited to calendar. This area remained for researchers as a growing interest from the last many decades. Fields (1934) applied regression approach on S & P 500 index for 40 years data and found an erratic fashion of advances on trading days previous long holiday weekends. The January effect was study by Wachtel (1942) on the Dow-Jones Industrial for a period of 1927 to 1942 and documented a regular bullish tendency from January to December. 2 Since after his work, a number of scholars have contributing to this issue by adopting more compressive tool and techniques persistent by empirical evidences. Glutekin & Glutekin (1983) study the January effect on seventeen Countries selected by using weighted indices approach. They permitted the presence of January effect for thirteen countries”. Rogalski (1984) study the “weekend effect” on the stock prices. His work found that “weekend effect” exists only between December and February and the Monday returns are positive value in January. It all means month of January has no Monday effect. Weekend effect on Japanese and Australian stock markets was studied by Jaffe and Westfield (1985a), the study presented lowest return on Tuesday, and they explain this phenomenon of lowest return was due the time difference between the operating periods of two stock exchanges. Harris (1986) developed a model for hourly data of individual firms to scrutinize emergent return patterns within a day. He applied same model for monthly basis return but find no significance results. The monthly effect was study by Ariel (1987) by taking window event as (-1, +4), is the last working day of previous month and four days of coming month. His work proved the existence of high return for window event of CRSP index for the time horizon 1963 to 1981. The month effect of window event of (-1, +3) , the last working day of previous month and the first three days of coming month was studied by Lakonishok and Smidt (1988) on the Dow Jones Industrial. They studied a period of ninety years from 1897 to 1986 and documented that cumulative average return of 0.473% for his event window which is higher than cumulative average return for rest of the month”. Day-of-the-week effect was studied by Solnik and Bousquet (1990) on the Paris Bourse; provided the evidence of strong negative effect found on Tuesday. Ariel (1990) studied the trading day prior to holidays, stocks advance with disproportionate frequency and show high mean returns averaging nine to fourteen times the mean return for the remaining days of the year over the 1963-1982. Cheung & Bishop et al (1993) studied the public holiday’s effect on the stock returns of the US stock market. They found these pre-holiday have high return of 7 to 6 times greater than other days. Non parametric tests applied and one-third of the total return accruing to the US market portfolio over the 1963-1982 periods was earned on the eight trading days before holiday market closing. Kim and Park (1994) studied the holiday effect in stock returns and additional insight into the effect. They reported abnormal high returns on the trading days before holidays. Their study was conducted on “NYSE”, “AMEX” and “NASDAQ”. The holiday effect was also observed in U.K and Japanese Stock market. Balaban (1995) analyzed the month of year effect on the Turkish stock exchange. He documented that January, June and September have significant high returns than remaining months of the year. Five window event i-e (-2, +3) effect was studied by Hansel and Ziemba (1996) on US stock exchange to prove the existence of TOM effect. They study period was 1928 to 1993 and evident returns on -1, +2 & +3 days have high significant returns. The effect Ramadan on stock prices in Pakistan Capital market was studied by Husain (1998). He documented that volatility is significant low during the weeks of the holy 3 month and does not find any momentous changes in average returns during month of Ramadan. His work does not compare average returns of Ramadan with remaining months of the year. Hansen and Lunde (2003) studied the effect calendar anomalies on stock return of the stock market of Denmark, France, Germany, Hong Kong, Italy, Japan, Norway, Sweden, UK, and USA, and find that the calendar anomalies will affect the stock returns. Ali and Akbar (2005) study the Monday effect on the stock returns and assumed as a bad day, because stock market is bearish in first day of the week but show high return on Friday, hence last day of the week is bullish. Friday effect on stock market was study by Gao and Kling (2005) on the Chinese Stock and found the market is more profitable on Friday as compared to the other days of the week. A study was conducted by Seyyed, Abraham, and Al-Hajji (2005) to examine the Ramadan effect on stock prices of firms listed in Saudi Arabian stock market. They considered several sector indices in their study and find out during the month of Ramadan trading volatility disappeared significantly. Abadir and Spierdijk (2005) examine festivity effect on the stock return considering the data from Muslim countries established stock exchanges. They take a pre-festivity silent period of negative means the return in this period is zero and once the market enter into post-festivity period the markets starts positive returns. They studied this effect during the month of Ramadan which befalls every year at a different time of the Western calendar. Their results cannot be applied to fixed calendar effect. Chong & Robert et all (2005). Study the weather effect on the stocks considering the stock markets, U.S, U.K and Hong Kong exchanges. The results for the three exchanges are same and show decrease in returns. Marrett & Worthington (2007) analysis the holiday effect on daily stock returns of Australian firms. Their sample consists of both large and small capitalized firms for the time period of Monday, 9 September 1996 to Friday 10 November 2006. In this study they consider eight annual holidays especially for New Year’s Day. These days are “, Australia Day” (26 January), “Easter Friday” and “Easter Monday”, “ANZAC Day” (25 April), “the Queen’s Birthday” (second Monday in June), “Christmas Day and Boxing Day”. Regression analysis is used for analysis. The results showed that overall return of the market effect by the pre-holiday but the returns of retail industry have more stress due to the pre-holiday effect. Their results also mentioned post-holiday doesn’t affect the Australian industry. Ushad (2008) examine the month effect (January effect) on stock return of the emerging markets by focusing the Stock Exchange of Mauritius (SEM). The monthly stock returns data used for analysis for period of 1989 to 2006. The monthly return data was computed from SEMDEX data source. The regression results find that the average returns are lowest in the month of March while show maximum return in the month of June. When the mean-return test is used to compare returns across the periods, the mean returns remain same and statistically significant across all months. 4 Nousheen and Z.A shah et al (2009) studied the effect of “Turn of the Month” and “Time of the Month” on the daily returns of the KSE-100 index. The data of the stock daily return was collected for the period of stating November 1991 to December 2007. Regression is used for the data analysis. Their studied find out that average daily return are high at “turn of the month” than rest of the month days. They also find the average return in “first third of the month” are significantly maximum than the remaining “two thirds of the month”. Cao and Premachandra et al (2009) examine that the “holidays effect”. The continuation of this pre-holiday effect is obsessed by factors applicable to New Zealand. It is a hunt to determine the effect mainly towards the less liquidity of smaller stocks and the reluctance of small investors to buy before the market closed. They used multiple regression analysis to proof their results. After checking the effect of pre-pre, pre and post holidays they also check holiday’s effect individually regarding public holidays”. After discussing the above literature it is found that calendar anomalies like January effect, Weekend effect, Turn of the month effect, Monday effect, Ramadan effect already has been presented in Pakistan but also different regions of the world. Moreover, as important as this issue is, there has been at best no empirical attention devoted to the application of public holiday’s effect to the Pakistani economy. The main objective of this study is to find out the trading activities (returns situations) prior to and post of the public holidays in Pakistani stock market 3. Methodological Frame Work and Data The purpose of this study is to contribute towards a very important aspect of calendar anomalies known as holiday’s effect. Major emphasis is to check the relationship of daily returns due to prior to, post of public holidays and non-holiday’s returns effect. This section describing the data collection, selection of variables, and possible used descriptive statistic and quantitative analysis (dummy variable regression model) to confirmation the hypothesis. H0: Effect of pre-pre holidays, pre holidays, post holidays and other trading days are not equal Our hypothesis is supporting by Worthington (2007) that rationale pre-pre holidays, pre holidays, post holidays and other days are not equal. And found the higher pre holidays over other trading days in Australian market. Same like Vos Cheung et al (1993) also find out that there is no equal effect of pre-pre holidays, pre holidays, post holidays and other trading days. And returns exhibit a form of holiday’s seasonality. 5 a. Econometric Model Rt = β0 + β1DPRE-PRE + β2DPRE + β3DPOST + µ t “Rt” is the dependent variable in our model and calculated as the daily stock index return for time period “t”. The first explanatory variable is “DPRE-PRE” a dummy variable dispensed a value of “1” for the pre-pre-holiday days (i.e., trading days that immediately precede the pre-holiday) and value “0” for other days. The second explanatory variable is “DPRE” is dummy variable having a value 1 for preholiday trading days (i.e. the trading day directly before holiday) and “0” for non-preholiday trading days. In estimated model “DPOST” is independent variable and taken as dummy variable having value “1” for the post-holiday and “0” for other days. “µt” is the error term or disturbance term of the model. The estimated model is supported by Vos et al (1993), Worthington et al (2007) and Paremachandra et al (2009) who find out the effect of public holidays in different stock market. b. Data Set and Sample Data is driven from the websites of “Karachi Stock Exchange” (KSE) and yahoo finance. The sample firms selected from KSE-100 index on the bases their market capitalization. The selected companies have 85% market cap of the market capitalization. The daily return data of the sampled firms from 1st January 2000 to 31st December 2009. The daily returns are obtained by using formula, with natural log for reducing the size effect of daily prices. R t = ln (Pt / Pt-1 ) *100 Where, Rt is the daily index return. “Pt” and “Pt-1” are the index price at time t and t-1 respectively. Same formula has been used as the one that was used for calculating the daily returns for sectors. Refinancing “holidays” as those public holidays when market remained closed. The following holidays are included: “Ashura, Eid-ul-Azha”, “Pakistan Day”, “Labor Day”, “Eid Milad-un Nabi”, “Independence Day”, “Allama Iqbal’s birthday”, “Quaid-e-Azam Muhammad Ali Jinnah’s birthday” and “Eid-ul-Fitr”. But some of them are irregular holidays like “Ashura”, “Eid-ul-Fitr”, “Pakistan Day”, “Eid Milad-un-Nabi” and “Eid-ulAzha”. 4. Empirical Results and Finding In table 4.1 Pre-pre holidays Mean value is 0.33 which is less than other trading days 0.82 in Index data. And pre holidays 0.4 times less than other days. Our results contradict with Vos Cheung (1993) who finds 3.8 times higher pre holidays mean returns than of other days. Premachandra et al (2009) also finds higher mean returns before holidays than other trading days in Newzeland stock market but post holidays mean value is 1.02 and 1.03 times higher than other trading days in daily index data. 6 Table 4.1: Descriptive Analysis of Index Descriptive Stats KSE 100 Index Other Trading days: Mean St. Dev Skewness Kurtosis Pre-pre holidays: Mean St. Dev Skewness Kurtosis Pre holidays: Mean St. Dev Skewness Kurtosis Post holidays: Mean St. Dev Skewness Kurtosis 0.8169 0.2386 -0.43 0.35 0.3333 0.4795 0.74 -1.55 0.3333 0.4795 0.74 -1.55 0.8333 0.1795 0.74 -1.55 Standard deviation is the most commonly reported measure of the dispersion. Standard deviation for the other days in daily index data is 0.239. It tells us the value in the data tends to differ from the mean by ± 0.239. The high value of standard deviation in pre-pre holidays and pre holidays can be deviate from the mean value by ± 0.479. Standard deviation of post holidays is 0.179 which can deviate from the mean value by that ratio over 30 observations. a. Regression Analysis The result of pre-pre holidays in table 4.2 indicates insignificant returns. Which are -0.05 times less than other days shows that investors do not concentrate on investment due to coming holidays. Same like pre holidays also -0.04 times less than other normal days indicating insignificant relation. Our pre-pre holidays and pre holidays returns contradicting the results with Premachandra et al (2009) and Worthington et al (2007) who finds significantly higher pre-pre and pre holidays returns than those of other trading days in Newzeland and Australian stock market. Vos Cheung (1993) also finds 3.8 times higher pre holidays returns than of other days. 7 Table 4.2: Estimation of Dummy Variable Regression of KSE 100 Index 0.008081 23.96 # of times p-value greater/less than other days(βi/β0) 0.000*** 1 -0.00045 -0.94 0.357 -0.05525 -0.00039 -2.82 0.421 -0.04826 0.008736 0.88 0.420 1.081067 tCoefficient value Variables “Other days” “Pre-preholiday” β2 “Pre –holidays” β3 “Postholidays” β0 β1 Note: *** indicates significant at 1%. F-stats R-square 0.037 0.52 Durbin-Waston stats 1.96 But post holidays mean returns increasing from other days by 1.08 times. It again contradicts the results with Premachandra et al (2009) suggests lower post holidays mean returns than other days mean returns. In Pakistani stock market peoples concentrate to invest in stock after holiday that is why trading activity increased. But prior of holidays investors show less attention towards the investment in stock market. Over all regression model explains 37 percent of the variation in the dependent variables due to the independent and explanatory variables. Durbin Waston stat is 1.96 which is close to 2 which provides the evidence that there is no autocorrelation in our data. 5. Conclusion/ Recommendations Anomalies refer to the situation when security or group of securities performs opposite to the concepts of market efficiency. Market efficiency called when security prices fully reflect all available information. And anomalies reflect inefficiency within markets. Some anomalies occur once and disappear, while some anomalies occur again and again. The intention of this paper is to investigate the holiday’s effect in Pakistani capital market specifically prior to, post of public holidays and non-holidays effects with daily 100 index returns. Major emphasis of this study is to find out that either holiday’s effect exist in Pakistan or not. Ten years daily data from 1st January 2000 to 31 December 2009 collected from the websites of Karachi Stock Exchange and yahoo finance. Before applying the dummy variable regression model, graphically we checked data’s stationary. Daily effects are exhibit insignificant by the Pakistani stock market. According to results of Equation, effect of pre-pre holidays, pre holidays declined. Reason behind the declining of pre holidays can be that investors avoid investing in stocks. Same like we see individual pre holiday’s effect also declined. Our results support by Husain (1998), Mustafa (2005) and Al-Hajzi (2005) who finds lower returns situation before Eid festivals etc. because people’s consumption increases before Eid festivals, Aushura and Eid 8 Milad-un Nabi. Their expenses increases hence savings decreases. And Chong & Robert et al (2005) define pre holiday’s effect significantly declined in Hong Kong market. But our results contradict with Vos Cheung et al (1993), Worthington (2007) and Premachandra et al (2009) who found high stock returns before holidays in Australia and Newzeland stock market. But post holidays mean returns increased in last decade. Same as when we check post holidays affect individually it also examine almost same results. In Pakistan investors take time of holidays to think about investment. So after holiday peoples give attention towards investment. So trading activity situation increased after holidays. Our results support by Mustafa (2005) who founds high stock returns after holidays and also results are supporting by Vos Cheung et all (1993) who define some time high and some time low returns after public holidays. Before holidays consumption of peoples increases due to higher prices of foods, cloths and other commodities in Eid festivals, Independence day, Pakistan day and Aushura. But after holiday’s investors, start investing in stocks. 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