Anomali Pada Bursa Efek Indonesia

Anomaly occurs when the return earned is not in accordance with the value it should be and makes the capital market inefficient. The anomalies tested were the day of The Week Effect, Week Four Effect, January Effect and Sell In May And Go Away. The population used is 144 Manufacturing stocks listed on the Indonesia Stock Exchange. The data analysis technique used to prove the occurrence of anomalies is the Z-value large sample difference test. This study examines anomalies not only in the short term, but also in the long term. The research results prove that there are no anomalies in manufacturing companies in Indonesia in the long run. In the short term, anomalies can occur, namely the sell in May effect in 2015 and the January Effect in 2017 on manufacturing companies on the Indonesia Stock Exchange.

Are soft commodities markets affected by the Halloween effect?

Within the last three decades commodity markets, including soft commodities markets, have become more and more like financial markets. As a result, prices of commodities may exhibit similar patterns or anomalies as those observed in the behaviour of different financial assets. Their existence may cast doubts on the competitiveness and efficiency of commodity markets. It motivates us to conduct the research presented in this paper, aimed at examining the Halloween effect in the markets of basic soft commodities (cocoa, coffee, cotton, frozen concentrated orange juice, rubber and sugar) from 1999 to 2020. This long-time span ensures the credibility of results. Apart from performing the two-sample t-test and the rank-sum Wilcoxon test, we additionally investigate the autoregressive conditional heteroskedasticity (ARCH) effect. Its presence in our data allows us to estimate generalised autoregressive conditional heteroskedasticity [GARCH (1, 1)] models with dummies representing the Halloween effect. We also investigate the impact of the January effect on the Halloween effect. Results reveal the significant Halloween effect for cotton (driven by the January effect) and the significant reverse Halloween effect for sugar. It brings implications useful to the main actors in the market. They may apply trading strategies generating satisfactory profits or providing hedging against unfavourable changes in soft commodities prices.

AN ANOMALY WITHIN AN ANOMALY: THE HALLOWEEN EFFECT IN THE LONG-TERM REVERSAL ANOMALY

In this paper, we investigate the presence of the Halloween effect in the long-term reversal anomaly in the US. When we examine the cross-sectional returns of winner-minus-loser portfolios formed on prior returns over the time period of 1931-2021, we find evidence of stronger returns during winter months versus summer months. In particular, the effect appears to be driven by very strong winter-summer seasonality in the portfolio of small-capitalisation losers, and lack of Halloween effect in the portfolio of large-capitalisation winners. Our finding is robust to alternative measures of long-term reversal, differing sub-periods, the inclusion of the January effect and outlier considerations, as well as within small and large-sized companies.

The Month-of-the-Year Effect in the European, American, Australian and Asian Markets

This paper examines the existence of the month-of-the-year effects in four different continents, namely Europe, Asia, America, and Oceania. Nine indexes were analyzed in order to verify differences between monthly returns from January 1990 to December 2013, followed by an examination of the January effect, Halloween effect, and the October effect, testing for statistical significance using an OLS linear regression in order to verify whether those effects offer consistent opportunities for investors. Investors with globally diversified portfolios benefit from the Halloween effect, with a 1.2% average monthly excess return in winter and spring, while the pre-dotcom-bubble period had a better performance than the post-dotcom-bubble period. In the global post-dotcom-bubble period, there is statistical evidence for 1.60% and 1% lower average monthly returns in January (the January effect) and in months other than October (the October effect), respectively, contradicting the literature. The dotcom bubble seems to be responsible for the January effect differing from what might otherwise have been expected in the later period. There is no consistent and clear impact on continental incidence. The Halloween effect is revealed to be a fruitful strategy in the FTSE, DAX, Dow Jones, BOVESPA, and N225 indexes taken one-by-one. The January effect excess average return was only statistically significative for the pre-dotcom-bubble period for globally diversified portfolios. This paper contributes to a wider global and comparable view upon month-of-the-year effect.

The calendar anomalies on Warsaw Stock Exchange in 2015-2020

The article is devoted to the subject of popular calendar anomalies. According to the theory of finance, if investors act rationally, the market can be considered efficient. In such a situation, achieving an above-average rate of return is impossible, as securities reflect all available information about them. However, on the basis of many studies and assumptions of behavioral economics, numerous exceptions to this rule have been discovered, which have been called market anomalies or stock anomalies. Such a deviation is the "January effect" and "January barometer" described in this work. The aim of the article is to investigate whether there is a deviation on the Warsaw Stock Exchange in 2015-2020 called the "January effect" and also whether the return rate in January can be a good prognosis for the rest of the year. In the results of the analysis, the occurrence of the title calendar effects in the studied sample was not unequivocally stated.

January anomalies on CEE stock markets

Numerous studies show that stock markets are often impacted by various calendar anomalies that disrupt the “random walk” behavior of stock prices. These anomalies contradict the Efficient markets theory and can be exploited to generate abnormal returns. This paper investigates the presence of two of them, namely the January effect and the January barometer, on the stock markets of 12 Central and Eastern European (CEE) countries. The paper examines the statistical significance of differences in returns recorded over the month of January and returns recorded over the other months (the January effect), as well as the statistical significance of differences between returns recorded during the remainder of year after a positive January return and after a negative January return (the January barometer). The results show, among other things, that the statistically significant January effect affects the Estonian, Lithuanian, Czech, Romanian, and Latvian stock markets. On the Romanian and Lithuanian stock markets, statistically significantly higher January returns are accompanied by statistically significantly higher January price volatility. On the other hand, we can speak of a statistically significant January barometer only in the case of the Latvian, Lithuanian, and Ukrainian stock markets. The presence of these anomalies is contrary to the Efficient market theory. It can be assumed that proper investment strategies based on these calendar anomalies should be able to generate abnormal returns. AcknowledgmentThis paper is an outcome of the science projects VEGA (1/0613/18) and VEGA (1/0221/21).

January Effect di Indonesia Periode 2017 – 2019

The January Effect is one of the seasonal anomalies, which reveals that stock returns in January tend to be higher than in months other than January. This study aimed to examine and analyze the existence of the January effect using abnormal return and trading volume activity (TVA) variables. The presence of the January Effect was researched on companies listed on the Indonesia Stock Exchange (IDX) and continues to be included in the Investor33 Index during 2017-2019. The samples studied were 25 companies. It was selected using purposive sampling method. The results of the normality test showed that the data was not normally distributed. Thus, only the non-parametric test, namely the Wilcoxon Signed Rank Test, can be used as a data analysis technique. Based on the analysis conducted, it was found that there was a significant difference in abnormal returns and no significant difference in TVA in January and other than January. Therefore, it can be concluded that statistically, the January Effect occurred in Indonesia during the test period indicated by abnormal returns. Keywords: January Effect; Abnormal Return; TVA.

Return Anomalies in the Kuwaiti Stock Market

This paper intends to investigate the existence of daily return anomalies and the weekend effect within Boursa Kuwait, Kuwait’s stock exchange. Kuwait as an economy has continued to be opened up to foreign investment and as foreign funds being to flood into the market; return anomalies akin to those within international markets begin to materialize, bringing new opportunities for abnormal returns and arbitrage. The premise of this paper is the existence of the January effect and the Weekend effect, and uses econometric methods in support of their existence, bringing into question the challenges to market efficiency and the changing landscape for investors and their strategies.

An examination of calendar anomalies: evidence from the Thai stock market

PurposeThe study examines the existence of calendar anomalies, including the day-of-the-week (DOW) effect and the January effect, in the Stock Exchange of Thailand.Design/methodology/approachUsing daily stock returns from March 2014 to March 2019, the study performs regression analysis to examine predictable patterns in stock returns, the DOW effect and the January effect, respectively.FindingsThere is strong evidence of a persistent monthly pattern and weekday seasonality in the Thai stock market. Specifically, Monday returns are negative and significantly lower than the returns on other trading days of the week, and January returns are positive and significantly higher than the returns on other months of the year.Practical implicationsThe findings offer managerial implications for investors seeking trading strategies to maximize the possibility of reaching investment goals and inform policymakers regarding the current state of the Thai stock market.Originality/valueFirst, the study investigates calendar anomalies in the Thai stock market, specifically the DOW effect and the January effect, which have received relatively little attention in the literature. Second, this is the first study to examine calendar anomalies in the Thai stock market across different groups of companies and stock trading characteristics using a range of composite indexes. Furthermore, the study uses data during the period 2014–2019, which should provide up-to-date information on the patterns of stock returns in Thailand.