The Hong Kong Stock Exchange (HKSE) is the second largest stock exchange market in Asia. The HKSE was established in the 19th century (McGuiness 2006, p. 892). Today the market ranks among top ten in the market capitalization. The market hit a record market capitalisation of US$1,063.9 trillion in 2010 and was ranked 8th place in the world (Garefalakis 2011, p. 56). The free-float-adjusted stock market index of Hang Seng Index (HSI) was established in 1969 (Gao & Kling 2005, p. 77). The shares traded in Hong Kong Stock Exchange HSI represent the highest index in the overall market turnover. Over 60 % of the value in HKSE is moved by HSI. The performance of Hong Kong Stock in the various sectors is significantly influenced by HSI. The 60% value moved in the HSI has high implication in the Chinese stock markets (McGuinness 2006, p. 896). According to McGuinnes (2006, p. 896),the daily performance of the HSI generates a lot of interest in China, Asia and around the world.
Market anomalies in the equity movements affect investors’ returns and lead to inefficiencies. According to Coutts & Sheikh (2000, p. 491), the leading cause of the anomalies is the calendar effect. According to Nikkinen, Sahlstrom and Aijo (2009, p. 107), month of the year or day of the week affect the stock markets indices. Studies on anomalies that relate to calendar effect have been general and not they lack emphasis on the significance of the calendar effect. Latif, Arshard and Farooq (2011, p. 9) noted that the anomalies relating to calendar effect are be due to data mining which lead to altering the normal pattern. The belief in the calendar effect causes a lot of speculation in the stock market; hence the anomalies. Anomalies slow down the activities of the markets and lead to changes in stock returns in the affected markets (Deysshappriya 2014, p. 179).
Anomalies and Calendar Effects
An anomaly is an unusual occurrence. Nikkinen et al. (2009, p.12) defined anomaly as a deviation from the usual order. In the stock market, anomalies are an indication of lack of efficiency in the markets. Anomalies are caused by chronology of events that lead to significant and lasting effect on the market. The key trigger of stock changes is the known information. Efficient market hypothesis stipulates that stock market prices reflect the known information. The implication is that the stock market indices depend on the information available. Therefore, an investor cannot outperform equity markets by application of the already available information (Linton, Maasoumis & Whang 2005, p. 737). However, studies point that there is evidence that returns in the stock exchange markets differ depending on the time, a phenomenon called calendar effect (Linton, Maasoumis & Whang 2005, p. 738). The calendar effect presents the anomalies that relate to the dayof the week effect or the month of the year effect or intra-monthly effect.
Day of the Week Effect
The calendar effect in relation to the day of the week postulates that expected returns and the standardised returns differ depending on the days. Many studies have been conducted to investigate closing stock indices in the five working days of the week Monday, Tuesday, Wednesday, Thursday, and Friday. Most of the studies have established anomalies. For instance, on many occasions, returns on Mondays have been found to be negative. The negativity has been attributed to the weekend effect (Al-Jarrah, Khames & Qteishet 2011, p. 9).
Month of the Year Effects
The month of the year involves the returns from January to December. The month of the year effect was discovered in 1942, when Eatchet reported anomalies that he termed as January effect (Basher & Sardosky 2006, p. 622). Since then, many studies have been conducted to investigate returns across the different months. The studies pointed to anomalies in January. Further extensive studies have indicated that the monthly changes are due to seasonal changes (Basher & Sardosky 2006, p. 623).
Aims and Objectives
There are varying school of thoughts in relation to the significance of calendar. The varying thoughts not only affect the investors in the theoretical days, but also present a challenge to the managers in endeavour to make accurate predictions. Studies carried on the calendar effect are specific to certain markets (Ariel 2002, p.163). Therefore, there have been the tendency to generalise the significance of the calendar effects. Ariel (2002, p. 162) noted that different factors and the business environment affect stock markets just as any other trade. There is thus the need to establish specific market effect for the various stock markets. The establishment of calendar effects in specified markets will play an integral role in managing the markets based on the evidence rather than generalisations. Therefore, the aim of this research will be to find out whether calendar effects influence the Hong Kong Stock Exchange Market HSI turnover. The study will also be aimed at establishing the significance of the calendar effect on the stock returns.
In order to achieve the objectives of the study, there is the need for research questions to guide the study. The questions will help in establishing the calendar effect on the Hong Kong Stock Exchange HIS. The following are the research questions:
- How does the day of week affect daily returns in the Hong Kong Stock Exchange Market HSI?
- What are the effects of the seasonality in the stock markets?
- How do the changes affect the trade in the market?
Significance of the Study
Hong Kong Stock Exchange market is strategically located in a region that has been experiencing economic boom (Garefalakis 2011, p. 55). Many multinationals are eyeing the opportunities emerging in the Asian region. Due to the HKSE rankings in Asia, second after Japan Stock Exchange it has attracted a lot of interests. The increased interest in the market calls for accurate information on the stock performance. According to Garefalakis (2010, p. 57), investors are attracted to markets that are relatively stable and with accurate stock movement information. The prices in the rational markets depend on the available information (Garefalakis 2011, p. 57). In the stock exchange, actions of investors determine the price movement. However, there are deviations that occur or disappear due to periodic factors. The changes in indices due to the time factor have a significant implication for investors. Therefore, the manager and the stockbrokers need to have in-depth understanding of the market operations.
Market efficiency hypothesis stipulates that markets are rational. A clear understanding of the calendar effect will help in the process of decision-making and in the directing of the new market entrants. Hence, a clear correlation and trends in the market will be imperative for steering the market to greater heights. In order to guarantee efficiency, the significance of the calendar effects will present managers with the right information. The information will be applicable for strategic action planning to maintain efficiency, competitiveness and effectiveness in the markets (Kohers et al. 2004, p. 169). According to Chen and Liang (2004, p. 2890), fundamental analysis of stock markets is the basis for making profits. The understanding of calendar effects will thus help in driving efficiency in Hong Kong Stock Exchange HSI.
There is a school of thought that in the current stock markets, efficient management has eliminated the calendar effect; hence, there are no effects on the returns (Kok and Wong 2004, p. 141). Another school of thought holds that calendar effects are common and have significant impacts on the returns. In this research, the focus will be to determine effects of the calendar effects on HKSE and subsequently establish whether they have any significance on the stock markets indices. The following literature review explores earlier findings of calendar effects on the stock market. The review will be critical in determining the direction of stock movements concerning calendar effects.
Day of the Week Effect
Studies carried in different international stock markets have pointed to evidence of periods affecting stock performance. The emphasis of the studies has been on the day of the week and the month of the year effect. In exclusive studies focusing on the stock markets in the Unites States, Nikkinen and Salhstrom (2004, p.108) noted that there exist anomalies that investors exploit. The exploitation of the anomalies results in the businesspersons earning abnormal returns. The findings by Nikkinen and Salhstrom (2004, p.111) contradict the market efficiency hypothesis postulation that the calendar anomalies effects have disappeared. In the argument, Paul and Theodore (2006, p. 118) noted that the calendar effects cannot be dismissed as early and the current studies have pointed to a definite trend in relation to daily variations.
Kiymaz and Berument (2003, p.371) noted that stock markets are dynamic, they change with time; hence, current calendar effects should be based on current trends. However, Leshno and Levy (2002, p. 1081) argued that the earlier studies have greatly relied on the normality assumption in which mean-variance was used as the core analysis approach. The weakness that related to the usage of the mean-variance is that higher moments tend to be ignored. Currently, nonparametric stochastic dominance (SD) approach is applied. The new approaches present an alternative that does not rely on assumption. The method is assumption-free and incorporates both the low and high moments to determine the calendar effects. Leshno and Levy (2000, p. 1082) conclude that the application of SD can bring a new perspective to the stock movements in relation to days of the week returns.
Thomas (2002, p.234) carried a study to investigate the calendar effects in Swedish stock markets. Thomas (2002, p.234) established that the day of the week had a significant effect on the returns. The study explored over 207 stocks in the Swedish market. Even though the sample was adequate to draw generalisation on the calendar effect, the inferences cannot be applied in other stock markets outside Sweden. In addition, the analysis used depended on the mean-variance; hence, there were assumptions that negated high moments. Dimitrios and Katerina (2003, p.89) conducted a similar study on the French stock exchange. There were anomalies observed in the study in relation to the day of the week. In the data analysed, Monday was found to have the highest volatility.
In yet another extensive study, Paul and Theodore (2006, p.131) examined the day of the week and month of the year effects in African market. The study entailed the analysis of Ghana Stock Exchange. The cross-sectional study analysed the closing prices share indices for a duration of ten years, from 1994-2004. Monday was found to have reduced returns compared to the other business days. The trends discovered in the Ghana stock markets pointed that calendar effects are rife. Similar trends were also found in Asian markets focusing on China and India equity markets (Gao & Kling 2005, p. 82). Even though the studies point to the trends, the studies did not quantify the significance in relation to the returns in the markets. There are still ranging debates on the market efficiency and the calendar effects implication of the particular markets.
Chen and Liang (2004, p.2893) explored market anomalies in relation to daily changes in five countries. The stock exchange markets analysed included Thailand, Philippines, Singapore, Malaysia and Indonesia. The studies were carried before and after the financial crisis in Asia. In the Malaysian market, Monday presented a significant abnormal effect. However, the study concluded that there were no daily seasonal anomalies in relation to the period before and after the time of crisis. In a follow-up analysis of the study, Kok and Wong (2004, p. 142) analysed the findings using the ordinary least square (OLS) approach. The results indicated that the day of the week had an effect on the Malaysian market. Negative Monday returns effects were noticed and positive Wednesday and Friday in the period before the crisis. During the crisis period running from 1996 to 1998, the anomalies were not experienced in the five markets. After the crisis, Malaysia showed only positive Tuesday effect.
The findings, before and after the crisis presented a level analysis for stock movement. The movements were established in three different market environments i.e. before, during and after the crisis. The changes during and after the crisis, depicted the caution that results in normal markets due to changes (Muhammad & Rahman 2010, p. 38). The relatively stable volatility in the five markets during and after the crisis related to the improved market knowledge that emerged after the hard economic times. Despite the changing patterns, the shift from negative to positive in the Asian markets substantiates that there was relative effect of the calendar effect in the stock markets.
In an empirical study to investigate the stock anomalies, Deyshappriya (2014, p.183) conducted an analysis of Colombo Stock Exchange in Sri Lanka. The investigation established that there was availability of the day of the week effects on the stock market. The study analysed the findings using both the OLS and GARCH models. The models showed that there were a positive effects from Tuesday to Friday, but Monday had a negative effect. Friday had a higher positive magnitude compared to the other days. The effects were noticed both in the two models. The study was carried during the Sri-Lanka’s unstable times of war. The turbulent business environment marked by war and turbulent political upheavals meant that investors relied on the available information to make decisions on the shares. Due to the unstable environment, Deyshappriya (2014, p.185) noted that unrealistic prediction could not be avoided.
The negative Monday was attributed to the period after weekend in which there was scant information on the business happenings. Deyshappriya (2014, p.185) noted that the high positive Fridays was due to the trends in the proceeding days and the need to sell the share before the uncertainties of the weekend. From the study, it is arguable that the day of the week effect is based on the information available. The periods proceeding holidays were likely to experience slowdowns as the investors speculated on the market happenings. For instance, weekends precede Mondays. Similar trends in relation to yearly trends have been noticed in January. The reason for negative January is related to December festivities; hence, scarce information on the start of the year results in negative returns in January. In addition, Thomas (2002, p. 231) noted that calendar effect that resulted in high volatility on Mondays were due to the after stock closing on Friday. The investors were certain on the opening prices on Mondays bearing in mind that weekends are generally considered stable days. The analysis of the stock after the post-war pointed that there was reduced volatility; the daily mean volatility after the war was negative. The stability was attributed to the stable economic climate.
Raj & Kumari (2006, p. 241) noted that the day of the week and the month of the year variations were high during uncertainty periods compared to certain periods. Based on the findings, market anomalies should be explicitly studied and understood by investors in order to ensure that investment decisions are fruitful and guarantee positive returns. In an earlier study concerning the stock markets in Sri-Lanka, Thilakarathne et al. (2008, p.102), found that there existed positive Friday effect and negative Monday effect. According to the study, not all markets relate to the Random Walk hypothesis, i.e. stock markets cannot be predicted. Nath and Dalvi (2005, p. 7) noted that many markets across the globe have realised reduced average returns on Mondays and the high returns on Fridays. As a result, a trend has been developed in which the calendar effect has been actualised based on past trends. Chen and Lian (2004, 2894) pointed that the day of the week exists and has an effect on the volatility and the returns.
Month of the Year Effect
In order to determine the calendar effect on months, Mehdian and Perry (2002, p. 142) investigated the monthly effect. In various studies carried, negative effect was found in January in the established stock markets. However, for the emerging markets, the effect was null. Similar trends were established by Hillier, Draper and Faff (2006, p. 47) in a study of different established markets in United States and Europe. Despite the indication of the calendar effects in the various markets studied, Gu (2003, p. 1397) pointed that there was evidence that the monthly calendar effect of January was on decline in US equity markets. Coutts and Sheikh (2000, p. 491) concurred with the findings. According to Coutts and Sheikh (2000, p. 491), calendar effects in the emerging markets have significant influence while in the developed markets depict stable movements. Al-Saad and Moosa (2005, p. 66) noted that the January effect is not definite. The effect depends on the seasonality. For instance, in the analysis of the indices in Kuwait Stock Exchange, there was a negative July effect. The market presented a deviation from the normal January effect in other markets. Al-Saad and Moosa (2005. P. 66) attributed the changes to the summer holidays.
Guler (2013, p. 642) carried a study to examine January effect in stock returns targeting emerging markets. The studied markets included India, Turkey, Shanghai and Brazil. Power ratio method was applied in the study. The study established January effect varied. Some markets had the effect while other did not have the effect. Guler (2013, p.643) established the existence of January effect in China, Argentina and Turkey. In the other markets studied, the January effect was not established in the stock returns especially in Brazil and India. Earlier studies conducted by Coutts and Sheikh (2000, p.490) that investigated seasonality’s in Hong Kong market found that there were no seasonality changes in the stock market.
Many studies have examined the seasonality behaviour. The primary aims of the studies were geared to bringing efficiency in the Markets. The studies carried cut across different markets, from the developed markets such as Japan, US, and UK to the developing markets such as Korea, Malaysia, Taiwan, and Thailand. The studies indicated the existence of seasonal changes in the stock markets that influence the months of the year.
Methodology represents the approaches that are applied in the collection of data. It also includes the approaches applied in the data analysis. The key factor underpinning data collection is to collect a representative sample from which acceptable inferences can be drawn. According to Denk (2010, p. 32), study methodology is systematic planning of actions that are applied to the collection of information. It also includes the subsequent analysis of data in a logical manner that helps in the realisation of the research purpose. Study methodology entails the use of different research designs to inform the process of the data collection. Examples of the study designs include descriptive, cross-sectional, experimental, and explorative researches.
The research design to be applied in this study will be cross-sectional study design in which empirical data on the stock indices will be collected and analysed. Cross-sectional study will help in giving the snapshots of the closing indices for the stock markets in the study period. By the application of cross-sectional study, the researcher is in a position to find out the timelines of day or monthly returns. According to Denk (2010), the cross-sectional studies are carried out repeatedly to give pseudo longitudinal study. The research design will focus on the trends in the Hong Kong Stock Exchange HIS. Great emphasis will be to collect substantive empirical data that for the analytical process. In order to supplement the empirical data, the Hong Kong stock exchange managers will be interviewed by use of structured questions. The empirical data will provide a comprehensive overview of the happening in the stock market in the different periods.
Sample frame entails the complete list of the attributes or the members of the population that are to be studied. A sample is usually drawn from the target population. Sampling frame represents the working population that is utilised in the study (Kothari 2005, p.95). In the case of the stock exchange, the sampling frame will entail all the indices recorded during the period of the study from January 1st, 2012 to December 31st, 2014. However, the sample frame will exclude some of the indices that relate to weeks in which five days returns were not obtained. The reason for the lack of five days data could be due to holidays. According to Sans (2011) if a sample frame is taken correctly it leads to a sample that can be used for the population as a whole.
The determination of the sample size depends on the number of replication that can be applied in drawing inferences about the population/units. The type of data required for the research normally determines the sample size. Sample sizes are important in determining the precision of the study (Neumann 2007, p. 13). The sample size in this study will entail the cross-sectional data covering the study period. Three year time duration from 2012 to 2014 will be used. The three-year period will ensure that monthly trends for the month of the years and the day of the week changes can be established. In addition, ten managers working in the HSKE will be interviewed. The interview of the managers will help in providing the implication for the different patterns realised in the study. The managers to be interviewed will be purposively selected. According to Neumann (2007 p. 14),the purposive sampling is used in cases where the targeted information can be obtained from specified people.
Data Collection Methods
According to Sans (2011, p.8), the method of data collection is normally influenced by the research strategies, the point of collection, and the person to carry out the research. The main types of data collection methods to be used in the study will include both the primary and secondary sources of data collection.
In order to collect in-depth information concerning HKSE and establish the significance in the stock market, primary information will play an integral role. Interviews will be conducted to gain more insights from experts. According to Kothari (2005, p. 104) interview are good research instruments applied in the collection of information in order to gain insights into trends and perceptions. They also serve to explore personal experiences and outcomes. The interviews will be guided interviews. They will probe to get specific information from the respondents. In this case, interviews will give first-hand information on the experiences of the interviewee in relation to stock markets. The interview will be directed by the structured questions, in line with the research objectives. Due to possible logistical challenges and the time constraints, it will be difficult to book a face-to-face appointment with the managers. The interview will be a telephone interview or video conferencing in which the managers will answer specific questions. The information collected durng the interview process will be recorded, typed, and preserved for the analysis.
The archival records are secondary sources of data. The source of data will include the recorded indices covering the period from 2012 to 2014. The data will be obtained from the HKSE database. An authorisation will be requested from the relevant personnel. The daily stock indices will provide the basis for determining the day of the week effect and the month of the effect.
There exist different approaches to the analysis of data. The primary data from the interview will be analysed to determine correlations. The significance of predictors will be tested by using multivariate logistics. The causal relationship will be based on the managers’ perspective on the calendar effect. The analysis will entail daily recordings of HIS for the study period. The primary aim of the study on the Hong Kong Stock Exchange HIS is to find out whether there are calendar effects in the stock markets. The calendar effects focus the on the day of the week and month of the year. The nature of the study will entail cross-sectional study design. In order to achieve the objectives, a suitable analysis non-parametric approach will be used.
Anomalies result in the stock market affect returns (Guler 2013, p. 647). The implication of the anomalies is the non-normal nature of the returns. Most of the studies employed the criterion of mean-variance which relies on the assumption of anomalies. The assumption are aligned to the lower moments; they thus miss the higher moment’s significance. Due to the limited nature of the studies, the significance of the anomalies has not been effectively established. The non-parametric approaches to be applied is the stochastic dominance approach (SD). According to Barret and Donald (2003, p. 79), SD endorses entire distribution of returns directly. SD has advantage over the parametric approaches when dealing with non-normal distribution. The SD does not rely on any assumption in relation to the distribution nature. It is thus suitably applied to any distribution.
The SD reveals the entire information for the period being studied, unlike the parametric measures that rely on the mean and variance (Lean et al. 2007, p.138). Hence, SD does not end up omitting some information especially from higher moments. Stock returns have non-normal distribution (Wong et al. 2005, p. 179). SD ranks different pairs of indices to a statistical degree of confidence. Therefore, The daily stock indices for the study period will be analysed using SD. The indices include the Hang Seng Indices. Due to possible holiday effect on the stock exchange trading, the weeks with holidays will be excluded from the study. The exclusion of the weeks with less than five trading days will be aimed at upholding consistent in the data analysis.
Primary Pilot Research
In order to determine the applicability of the methodologies, a pilot research was conducted. The research entailed collection of the data from purposively identified individuals presumed to be the managers in the stock markets. The individuals were purposively sampled; they included people with stock exchange knowledge and experience. The collection of the data was by use of interview schedules. The interviews were conducted through telephone calls. Preset questions were applied in the interview (See Appendix III). The application of structured questions was used as the principle research instrument for gathering the primary data.
The main aim of the study was to establish the calendar effect on the Hong Kong Stock Exchange; therefore, indices for the stock performance were necessary. The collection of the stock performance relied on secondary data that was obtained from selected databases. The pilot study included accessing different stock exchange databases to determine the accessibility of the data. In the process of trying to obtain data from the identified stock exchange databases, it was difficult without getting authorisation. Therefore, the pilot study was delayed for a day as I sought to get the required authorisation. Finally, I was able to access the databases and collect some data.
Validity of the Interview
Validity measures the degree to which a research instrument collects the data that is supposed to be collected (Oladipo, Adenaike &Ojewumi 2010, p. 12). The interview questions used to interview the different managers were same which ensured that the degree of external validity was achieved. Hence, the results obtained could be generalised. In addition, the questions were reviewed by a panel of experts which ensured that the appropriateness of the interview questions.
Reliability involves the consistency of the research instrument (Oladipo, Adenaike & Ojewumi, 2010, p. 13). The reliability of the research was achieved by using structured questions that ensured similar questions were presented to the different managers interviewed.
The study provided a prototype for the actual study. Key shortcoming was the collection of the secondary data. In order to avoid the challenge, authorisation for the access of the database for the Hong Kong Stock Exchange HIS will be requested in advance. In addition, in order to enhance validity and reliability of the interview, a committee of experts will be formed to develop and review the data collection instruments.
Project management entails the process of planning the various activities that are involved in the research process, organizing and controlling resources. According to Kirkland (2014, p. 73), project management entails setting clear timelines that involve the procedures to be followed in order to achieve specific goals. In the research, proposal, the project management entailed the compilation of the various activities, designing and implementation of a pilot research (See Appendix I & II, the time plan and a Gantt chart). In the process of implementation of the project, there were time constraints and thus some time had to be adjusted to cater for the changes. The changes were due to unforeseen constraints. According to Randolph (2014, p. 36) the primary constraint to achieving the initial time plan is due to functional challenges that relate to scope and budget allocations.
For instance, the implementation of the pilot project was not achievable as intended because the time allocated for the interviews was not adequate. In addition, the mock collection of the indices from the various selected databases was constrained because the databases could not be accessed without authorisation. As a result, there were procedures and telephone calls that I had to make to in order to get authorisation for the various databases. In order to lead an efficient and successful project management, Randolph (2014, p. 40) noted that optimisation of time and budgetary allocations are necessary. They should be integrated to allow achievement of the objectives that are predefined. My project management fell short of time optimisation. In order to correct the challenges, the rest of the research project has been re-evaluated. Projections have been made with adequate time allowance to integrate the remaining work. The pilot project provided insights on issues I am to expect in the actual project implementation. Therefore, the challenges faced during the pilot study will not be repeated during the actual study.
Al-Jarrah, I. M., Khamees, B. A., & Qteishat, I. H. 2011. ‘The turn of the month anomaly in Amman stock exchange: evidence and implications’. Journal of Money, Investment, and Banking, vol. 21, no. 1, pp. 5-11.
Al-Saad, K. and Moosa, I. 2005. ‘Seasonality in Stock Returns: Evidence from an Emerging Market’. Applied Financial Economics, vol. 15, no. 2, pp. 63-71.
Ariel, R. A. 2002. A Monthly Effect in Stock Returns. Journal of Financial Economics, vol. 18, no. 1, pp.161-174.
Barrett, G. and Donald, S. 2003. ‘Consistent Tests for Stochastic Dominance’. Econometrica, vol. 71, no. 1, pp. 71-104.
Basher, S. A., and Sadorsky, P. 2006. ‘Day of the week effect in emerging stock markets’. Applied Economics Letters, vol. 13, no. 1, pp. 621–628.
Bronfenbrenner, U. and Evans, G. 2000. ‘Developmental Science in the 21st Century: emerging Questions, Theoretical Models, Research Designs and Empirical Findings’. Social Development, vol. 9, no. 1, pp.115-125.
Chen Y. and Liang, B. 2004. ‘Timing Ability in the Focus Market of Stock markets’. Journal of Finance, vol. 56, no. 6, pp. 2871-2901.
Coutts, J.A. and Sheikh, M.A. 2000. ‘The January Effect and Monthly Seasonality in the All Gold Index on the Johannesburg Stock Exchange 1987-1997’. Applied Economics Letters, vol. 7, no. 1, pp. 489-492.
Denk, T. 2010. ‘Comparative multilevel analysis: proposal for a methodology’. International Journal of Social Research Methodology, vol.13, no.1, pp. 29-39.
Deysshappriya, N. 2014. ‘An Empirical Investigation on Stock Market Anomalies: the Evidence from Colombo Stock Exchange in Sri Lanka’. International Journal of Economics and Finance, vol. 6, no.6, pp.177-187.
Dimitrios, G. and Katerina, C. 2003. ‘Market Anomalies’. Journal of Financial Economics, vol. 32, no. 2, pp. 87-92.
Gao, L. and Kling, G. 2005. ‘Calendar Effects in Chinese Stock Market’. Journals of Economics and Finance, vol. 6, no. 1, pp.75-88.
Garefalakis, A. 2011. ‘Determinant Factors of Hong Kong Stock Market’. International Research Journal of Finance and Economics, vol. 62, no. 1, pp. 52-59.
Guler, S. 2013. ‘January effect in stock returns: evidence from emerging markets’. Interdisciplinary Journal of Contemporary Research in Business, vol. 5, no. 4, pp. 641- 648.
Gu, A.Y. 2003. ‘The declining January effect: evidence from U.S. Equity Markets’. The Quarterly Review of Economics and Finance, vol. 43, no. 1, pp. 395-404.
Hillier, D., Draper, P. and Faff, R. 2006. ‘Do precious metals shine? An investment perspective’. Financial Analysts Journal, vol. 62, no. 2, pp.42-62.
Kiymaz, H. and Berument, H. 2003. ‘The day of the week effect on stock market volatility and volume: international evidence’. Review of Financial Economics, vol. 1, no. 1, pp. 363- 380.
Kirkland, C. 2014. ‘Project Management: a problem-based approach’. Project Management Journal, vol. 45, no. 1, pp. 63-92.
Kohers, G., Kohers, N., Pandey, G. and Kohers, T. 2004. ‘The disappearing day of the week effect in the world’s largest equity markets’. Applied Economic Letters, vol. 11, no. 1, pp. 167-171.
Kok, K.L. and Wong, Y.C. 2004. ‘Time-of-the-month anomaly in ASEAN equity markets’. International Business and Finance, vol. 2, no. 1, pp.137-145.
Kothari, C. 2005. ‘Contemporary methods of quantitative data collection and analysis in literacy research’. Reading Research Quarterly, vol. 39, no. 1, pp.94-112.
Latif, M., Arshard, S., and Farooq, S. 2011. ‘Market efficiency, market anomalies, causes, evidences, and some behavioural aspects of market anomalies’. Research Journal of Finance and Accounting, vol. 2, no. 10, pp. 3-12.
Lean, S., Hooi, H., Smyth, R., and Wong, W. 2007. ‘Revisiting calendar anomalies in Asian stock markets using a stochastic dominance approach’. Journal of Multinational Financial Management, vol. 17, no. 2, pp.125-141.
Leshno, M., and Levy, H. 2002. ‘Preferred by “All” and Preferred by “Most” Decision Makers: Almost Stochastic Dominance’. Management Science, vol. 48, no. 1, pp.1074-1085.
Linton, O., Maasoumi, E., and Whang, Y. 2005. ‘Consistent Testing for Stochastic Dominance under General Sampling Schemes’. Review of Economic Studies, vol. 72, no. 2, pp. 735- 765.
McGuinness, P. B. 2006. ‘Turn-of the-month returns effects for small cap Hong Kong stocks’. Applied Economics Letters, vol. 13, no. 14, pp. 891-898.
Mehdian, S., & Perry, M. J. 2002. ‘Anomalies in US equity markets: a re-examination of the January effect’. Applied Financial Economics, vol. 12, no. 2, pp.141-145.
Muhammad, N. and Rahman, N. 2010. ‘Efficient market hypothesis and market anomaly: evidence from day-of-the week effect of Malaysian exchange’. International Journal of Economics and Finance, vol. 2, no. 2, pp. 35-42.
Nath, C. N., & Dalvi, M. 2005. ‘Day-of-the-week effect and market efficiency: evidence from Indian equity market using high frequency data of national stock exchange’. Journal of Emerging Market in Finance, vol. 11, no. 2, pp. 5–25.
Neumann, W. L. 2007. Social Research Methods: Qualitative and quantitative approaches. Journal of Research, vol. 3, no. 2, pp.35-44
Nikkinen, J. and Sahlstrom, P. 2004. ‘Scheduled domestic and US macroeconomic news and stock valuation in Europe’. Journal of Multinational Financial Management, vol. 14, no. 1, pp. 201-215.
Nikkinen, J., Sahlström, P. and Äijo, J. 2007. ‘Turn-of-the-month and intra-month effects: explanation from the important macroeconomic news announcements’. Journal of Futures Markets, vol. 27, no. 2, pp.105-126.
Nikkinen, J., Sahlstrom, P., Takko, K. and Aijo, J. 2009. ‘Turn-of-the-month and intra-month anomalies and US macroeconomic news announcement on the thinly traded Finnish Stock Market’. International Journal of Economics and Finance, vol. 1, no. 1, pp. 3-11.
Oladipo, S., Adenaike, F. and Ojewumi, A. 2010. ‘Establishing the reliability and validity scale’. IFE Psychologia, vol. 18, no. 2, pp. 1-23.
Paul A., and Theodore P. 2006. Modeling and forecasting volatility of returns on the Ghana Stock Exchange using GARCH Models’. Journal of Emerging Market in Finance, vol. 4, no. 2, pp.115-132.
Raj, M., and Kumari, D. 2006. ‘Day-of-the-week and other market anomalies in the Indian stock market’. International Journal of Emerging Markets, vol. 1, no. 3, pp. 235-246.
Randolph, S. 2014. ‘Maximizing project value: a project manager’s guide’. Project Management Journal, vol. 45, no. 2, pp.22-41.
Sans, W. 2011. ‘Sampling methods and market Surveillance’. Economic Quality Control, vol. 26, no. 2, pp. 2-11.
Thilakarathne, P. M. C. 2008. ‘Seasonality effect of emerging stock markets: evidence from Sri Lanka’. Journal of Multinational Financial Management, vol. 2, no. 1, pp. 97-107.
Thomas, H. 2002. ‘Trends and calendar effects in stock returns’. Australian Technical Analysts Association Journal, vol. 3, no. 1, pp. 222-234.
Wong, W., Thompson, H., Wei, S. and Chow, Y. 2005. ‘Do winners perform better than losers do? A Stochastic Dominance Approach’. International Journal of Emerging Markets, vol. 3, no. 2, pp. 135-246.
Appendix I: Time Plan
|Activity||Start time (March)||Duration|
|Designing the research methodology||16||4|
|Presentation of findings||30||1|
Appendix II: Gantt chart
Appendix III: Interview Schedule
Part 1: General Information
- How long have you been in the stock exchange management?
- What are your professional qualifications?
- What is your perspective of the calendar effect?
Part 2: Calendar Effects
- What are anomalies in stock markets?
- Are anomalies common in the stock exchange trade?
- What factors cause the anomalies in the stock market?
- As an experienced manager in the stock exchange, what trends have you observed?
- If yes, what are the observable trends from Monday to Friday?
- In relation to the months of the year, are there observable differences in the stock performance? Please give more explanation in relation to the various months of the year.
- Are there observable changes in stock returns after holidays?
- As a manager what is the significance of the stock changes and how does it affect the investors?