Financial Anomalies: Examination of Chinese B‐share Markets from 1993 to 2006 (original) (raw)
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Financial Anomalies: Evidence from Chinese A-share Markets
International Journal of Economics and Finance, 2011
The analysis of broad samples of equal-weighted and value-weighted returns of the Chinese security markets documents that abnormally high rates of return on small-capitalization stocks are to be observed during the month of March on both Shanghai and Shenzhen A-share markets. Different to the international experience of the January effect, the March effect can be seen as the turn-of-the-year effect in the Chinese security market as the national economic background and cultural background delay the turn-of-the-year from February to March.
A new perspective on financial anomalies in emerging markets: the case of China
Http Dx Doi Org 10 1080 09603100701735946, 2008
Financial anomalies in emerging markets can be caused by very different reasons than that in mature markets. In a GARCH model, we examine financial anomalies in emerging markets from a new perspective, which focuses on heavy political interventions. In the context of China, we show that political consideration of the government can be a critical force that drives the monthly anomaly in the stock market. The Chinese case indicates that usual explanations for the month anomaly or the January effect may become invalid in an environment where political intervention is a dominant force in the stock market. Typical of a policy-driven market that prevails in emerging economies, results indicate no evidence for the January effect in China, neither its mirror version, the Chinese New Year effect. Rather, returns abnormality is found to occur in March when China is in the political high season. This March effect is likely a result of political manoeuvre by the government to make the appearance of a stable and thriving stock market, which serves the political purpose of preventing social resentment in a politically sensitive time. This shows political window dressing can be an important cause of financial anomalies, which has been largely neglected in the literature.
Anomalies in Asia Pacific Stock Markets: A Re-Examination of the Turn-of-the-Year Effect
Asian Journal of Economic Modelling
This paper examines the turn-of-the-year (TOY) effect in fifteen Asia Pacific stock indices by using an updated dataset. The analysis utilizes the daily datasets spanning from 2000 to 2018. Applying the Ordinary Least Square (OLS) and the Exponential Generalized Autoregressive Conditional Heteroskedastic (EGARCH) approach, the results of this paper suggest that the TOY effect becomes detectable again after the Global Financial Crisis (GFC) in developed markets with the tax year not ending in December. Furthermore, the magnitude of this anomaly diminishes in emerging markets after the GFC, which is consistent with the Efficient Market Hypothesis (EMH). The evidence of the leverage effect in the market volatility shows in negative shocks that it is considerably higher than that of positive shocks for all markets. This phenomenon is more evident in mature markets compared to emerging markets. The positive connection between the leverage effect and stock market volatility is seen with d...
Calendar effects in Chinese stock market
Annals of Economics and Finance, 2005
Our paper examines calendar effects in Chinese stock market, particularly monthly and daily effects. Using individual stock returns, we observe the change of the calendar effect over time. In Shanghai and Shenzhen, the year-end effect was strong in 1991 but ...
The Impact of Seasonal Anomalies on MSCI’s Selected Economies’ Stock Index Returns
Reviews of Management Sciences, 2020
This article explores the effect on four developing Asian financial markets on the day of this week (volatility). Methodology: Regular market return data are gathered in their specific index from MSCI's selected economies, such as China, India, Malaysia and Pakistan. Yahoo's financial platform gathered index info. The selected sampling duration is between 2 May 2013 and 29 November 2017. The observational study was undertaken and the findings were concluded by the usage of a regression model to analyze day of consequence and the GARCH model to monitor conditional variance. Findings: These findings suggest that all stock returns and volatility are substantially impacted by the day of the week in three nations, but both the return and the volatility result in each of the four cases are not similar. An investor may make abnormal gains by betting on a previously accessible information-based approach and investors may obtain invaluable insights into investment decisions. Conclusion: If investors are conscious of this, they will adjust their investments in view of these shifts in stock returns.
Universiti Teknologi MARA, 2021
The existence of market anomalies for the return reveals the inefficiency in the market that could affect investor investment strategy, portfolio selection, and profit management. It is due to the unpredictable movement of the stock market return that will affect the decision of investors later. As such, this study intends to investigate day of the week effect, a month of the year effect, and a quarter of the year effect on the Malaysian Stock Exchange, namely the Kuala Lumpur Composite Index (KLCI) on data from 2nd January of 2015 until 31st December 2018. Based on the findings from Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model analysis, it is found that the daily effect on returns was insignificant. Possible reasons for the insignificant return could be due to the lack of time-series data. However, the significant monthly effect on returns of May, November, and December while the quarterly effect on the returns is found significant in the first quarter. This study also concludes that volatility shock is persistent in the returns for all those three market anomalies.
The Month-of-the-Year Effect in the European, American, Australian and Asian Markets
Economies, 2021
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 predotcom-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.
January Effect Revisited: Evidence from Borsa Istanbul and Bucharest Stock Exchange
International Journal of Economics and Finance, 2017
Any siginificant deviation from fundamental value observed in a market is acctepted to be an anomaly. As one of the most commonly referred anomalies in markets, January effect may be used to explain abnormal stock returns observed in January. The aim of this paper is to examine the January effect in two emerging markets for the time period between 2000 and 2014 using daily closing prices with power ratios analysis. Our results indicate that January effect is persistent for both Borsa Istanbul (BIST-100) and Bucharest Stock Exchange (BET).