Academic journal article International Journal of Management

Investigating Seasonal Anomalies in Asian Stock Market Prices: A Stochastic Dominance Approach

Academic journal article International Journal of Management

Investigating Seasonal Anomalies in Asian Stock Market Prices: A Stochastic Dominance Approach

Article excerpt

In this research, we examine the possible January effect on some Asian stock market price, namely Singapore, Taiwan and Hong Kong. In spite of the non-normal nature of stock returns, most previous studies have employed the mean-variance criterion or Capital Asset Pricing Model (CAPM) statistics, which rely on the normality assumption and depend only on the first two moments, to test for calendar effects. To overcome this drawback, in this paper, we use the stochastic dominance approach and the Davidson and Duelos test to examine the existence of January effects for some Asian markets using daily data for the period from 1990 to 2007. Our empirical results support the existence of monthly seasonality effects in these Asian markets but suggest that first order stochastic dominance for the January effect has largely disappeared.

(ProQuest: ... denotes formulae omitted.)

Introduction

According to the Efficient Market hypothesis, past prices of shares should have no predictive power of future prices. In effect, prices should be random. However, numerous studies have shown that market inefficiencies do exist and that anomalies may be in terms of seasonal effects over the day of the week, the months of the year or over specific years. This will negate the notion of efficiency in markets since traders will be able to earn abnormal returns just by examining patterns monthly returns and setting trading strategies accordingly. Essentially, this will entail an inefficient market situation where returns are not proportionate with risk.

Several studies such as Keim (1983), Ariel (1987), and Jaffe and Westerfield (1989) have pinpointed out the existence of a monthly effect on the US and other international markets. Findings from these studies suggest that investors can exploit calendar anomalies to earn abnormal returns and cast doubt on the market efficiency hypothesis. However, some recent studies such as Cheung and Coutts (1999), Davidson and Faff (1999), Coutts and Sheikh (2000), and Gu (2003), using data mainly from the 1990s, reveal a weakening and/or disappearance of calendar effects. Most of the existing literature has employed the mean-variance (MV) criterion (Markowitz, 1952) or the capital asset pricing model (CAPM) statistics (Sharpe, 1964; Treynor, 1965 and Jensen, 1969). Both approaches use parametric statistics, which rely on the normality assumption and depend only on the first two moments to test for calendar effects. These approaches result in missing crucial information contained in the data such as higher moments. To overcome these limitations, some of the more recent studies apply a non-parametric stochastic dominance (SD) approach, which is free of assumption, to investigate calendar effects.

Specifically, we examine the existence of January effects for Hong Kong, Singapore, and Taiwan markets using daily data for the period 1990 to 2007. Our objective is to test whether investors can increase their wealth as well as their utility by exploiting calendar anomalies in their portfolios.

Prior Research

Calendar effects and seasonal anomalies have been the most discussed studies by many academics and professionals in the security/stock market since decades. Among other studies in that particular field; (1) the month of the year effects, (2) day of the week effects, (3) turn of the month effects, (4) turn of the year effects, and (5) holiday effects are those in which more resources and time have been invested. This paper concentrates on the first- mentioned anomaly.

One of the most common and interesting finding from the researches carried out in the month of the year effects anomaly is the so-called January effect. The January effect is the anomaly that common stock returns are larger in January than in other months. Several explanations have been offered for the January effect. Ogden (1990) suggests it is due to end-of-year transactions of cash or liquidity. …

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