This paper analyzes the statistical and economic significance of the calendar anomalies to propose appropriate strategies or recommendations. Studying the calendar anomalies in Vietnam also diversifies the research scope and validates some hypotheses in the past. | Efficient market hypothesis and calendar effects Empirical evidences from the Vietnam stock markets Accounting 6 2020 Contents lists available at GrowingScience Accounting homepage ac Efficient market hypothesis and calendar effects Empirical evidences from the Vietnam stock markets Pham Dan Khanha and Pham Thanh Datb aSchoolof Advanced Education Programs National Economics University 207 Giai Phong Road Hanoi Vietnam b School of Banking and Finance National Economics University 207 Giai Phong Road Hanoi Vietnam CHRONICLE ABSTRACT Article history Vietnam s stock market although has small scale without a long history of development but the Received March 7 2020 exchange has just started for a massive development. There have also been a number of anomalies Received in revised format March suggested that the market is not efficient. Therefore there is a possibility that active investors with 10 2020 right strategy can consistently achieve higher profit than the market portfolio. This paper analyzes the Accepted May 8 2020 Available online statistical and economic significance of the calendar anomalies to propose appropriate strategies or May 8 2020 recommendations. Studying the calendar anomalies in Vietnam also diversifies the research scope and Keywords validates some hypotheses in the past. In this research the authors just analyze the monthly effects and Seasonal effect the experimental results of this study may have significant implications not only for financial managers Stock return financial advisers and investors but also for government to implement policy on stock market. Calendar effect Dummy Variable Regression EMH 2020 by the authors licensee Growing Science Canada 1. Introduction Calendar effect produces higher or lower yields depending on the nature of the time series Ariel 1990 . These effects are called market abnormalize since these abnormalize cannot be explained by traditional asset pricing models. Examples of some
