Artigo Revisado por pares

SEASONALITY IN THE VIETNAM STOCK INDEX

2015; Volume: 9; Issue: 1 Linguagem: Inglês

ISSN

2157-0698

Autores

H. Swint Friday, Nhung Hoang, University-Corpus Christi,

Tópico(s)

Market Dynamics and Volatility

Resumo

ABSTRACTThis study examines seasonality in the Vietnam Stock Market Index over 10 years, since the market's establishment on July 28th, 2000 until December 31st, 2010. The study found significant positive returns in April and significant negative returns in July for the VN-Index. Also, the or Go away in May come back Halloween Day effect is observed in the Vietnam Stock Market Index. The authors posit these results are partially driven by the rainy season in Vietnam where monthly rainfall reaches up to 1000 mm.JEL: G11, G14KEYWORDS: Halloween Effect, January Effect, Seasonality, Vietnam Stock MarketINTRODUCTIONGlobal stock market anomalies persist as a challenging puzzle for researchers. The more wellknown phenomenon examined in numerous empirical studies include the January Effect and other seasonality anomalies such as the Halloween Effect. This analysis provides additional insight into this line of literature by examining seasonality in the Vietnam stock index specifically looking at the January Effect and the Halloween Effect. In addition, we provide evidence that rainfall especially in the rainy season is a possible explanation for the Halloween Effect we find in this market index.The Efficient Market (EMH) is one of the most important hypotheses in applied finance with far reaching implications to the way traders and investors direct resources and allocate investment assets. The EMH holds that on average investors cannot consistently earn excess returns because financial markets incorporate information in an unbiased manner. In other words, new information will be nearly instantaneously incorporated into asset prices pushing markets to new equilibriums moment by moment (Efficient Market Hypothesis 2008).However, the existence of seasonality in stock returns violates the EMH assumption if traders can use historical information to consistently earn excess returns. Nageswari and Selvam (2011) stated that the presence of seasonality including the Halloween effect, January effect, and 'Day of the Week Effect' in stock returns violates in particular the Weak Form of the EMH because investors can predict and time the markets based on past price patterns. Using historical data, investors and market participants may devise trading strategies and making abnormal profits. For instance, buying on Mondays and selling on Fridays or 'Selling in May and going away until Halloween day' are trading strategies where investors may make excess profits in stock markets.We take the next step and test the Semi-Strong form of the EMH to determine if external fundamental factors are driving the seasonality widely documented in these markets. First, this study employs monthly historical returns of the VN-Index to determine the presence of seasonal patterns and abnormality of monthly stock returns from the Index's inception to 2010. In addition, we also hypothesize that weather and especially monthly rainfall levels are a possible explanation for the seasonal effects detected in the VN-Index. This particular vein of analysis has not been examined in previous studies. This research will also provide evidence on the possible need to introduce new derivatives into these emerging markets to hedge against meteorological uncertainty similar to the weather derivatives traded in the US market.PREVIOUS LITERATUREEvidence of different seasonal effects has been observed in international markets around the world. Some of the more prominent effects include the January Effect and the Halloween effect. Wachetel (1942) was the first to document the January effect in stock returns. The phenomenon garnered little attention until Keim (1983) again reported observing abnormal January returns for New York Stock Exchange (NYSE) and American Stock Exchange (AMEX) common stocks over the period 1963-1979. Three proposed explanations for the January effect include the tax-lossing hypothesis (Roll 1983) and the gamesmanship hypothesis (Haugen and Lakonishok 1987). …

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