Narrow Results

In this paper using the global Hurst exponent, the impact of privatization of public companies in Iran on the degree of efficiency in Tehran Stock Exchange is assessed. The results show that selling public companies' share in Tehran Stock Exchange (TSE) leads to a structural break in degree of market development. To model this phenomenon a catastrophe approach is used and it is demonstrated that this structural break can be better explained by a cusp catastrophe model.

Chong and Lam and Chong et al. show that SETAR(200) and MA(50) outperform other rules in both the U.S. and the Chinese stock market. This paper investigates the synergy of combining SETAR(200) and MA(50) rules in ten U.S. and Chinese stock market indexes. It is found that the SETAR rule performs better in the U.S. market, while the MA rule performs better in the Chinese market. In addition, we find evidence that a new strategy combining the two rules together is able to create synergy. An immediate implication of our result is that investors are able to improve the performance of their portfolios by combining existing profitable trading rules.

Since the existence of market memory could implicate the rejection of the efficient market hypothesis, the aim of this paper is to find any evidence that selected emergent capital markets (eight European and BRIC markets, namely Hungary, Romania, Estonia, Czech Republic, Brazil, Russia, India and China) evince long-range dependence or the random walk hypothesis. In this paper, the Hurst exponent as calculated by R/S fractal analysis and Detrended Fluctuation Analysis is our measure of long-range dependence in the series. The results reinforce our previous findings and suggest that if stock returns present long-range dependence, the random walk hypothesis is not valid anymore and neither is the market efficiency hypothesis.

In this paper, we use a time-frequency domain technique, namely, wavelet squared coherency, to examine the associations between the trading volumes of three agricultural futures and three different forms of these futures' daily closing prices, i.e. prices, returns and volatilities, over the past several years. These agricultural futures markets are selected from China as a typical case of the emerging countries, and from the US as a representative of the developed economies. We investigate correlations and lead–lag relationships between the trading volumes and the prices to detect the predictability and efficiency of these futures markets. The results suggest that the information contained in the trading volumes of the three agricultural futures markets in China can be applied to predict the prices or returns, while that in US has extremely weak predictive power for prices or returns. We also conduct the wavelet analysis on the relationships between the volumes and returns or volatilities to examine the existence of the two "stylized facts" proposed by Karpoff [J. M. Karpoff, The relation between price changes and trading volume: A survey, J. Financ. Quant. Anal.22(1) (1987) 109–126]. Different markets in the two countries perform differently in reproducing the two stylized facts. As the wavelet tools can decode nonlinear regularities and hidden patterns behind price–volume relationship in time-frequency space, different from the conventional econometric framework, this paper offers a new perspective into the market predictability and efficiency.

We propose a novel stock market model and investigate the effectiveness of trading breaks. Our nonlinear model consists of two types of traders: while fundamentalists expect prices to return towards their intrinsic values, chartists extrapolate past price movements into the future. Moreover, chartists condition their orders on past trading volume. The model is able to replicate several stylized facts of stock markets such as fat tails and volatility clustering. Using the model as an artificial stock market laboratory we find that trading breaks have the power to reduce volatility and — if fundamentals do not move too strongly — also mispricing.

Share repurchases have become an increasingly popular method for companies to distribute cash to its shareholders as many countries have removed restrictions related to this activity. By using a new and unique data set with complete information of each repurchase program, the long-run share price performance following actual share repurchases and whether managers trade strategically are examined for a sample of Swedish firms. I find that the announcement effect surrounding the first repurchase date is small but that repurchasing firms on average outperform several benchmarks during the first three years and thereby exhibit superior information of the stock price. Evidence of strategic trading is documented in small market cap firms. Finally, I document that Swedish firms repurchase more in the first half compared to the second half of the program and also that a higher completion rate is associated with high abnormal return.

The literature has recently begun to investigate the properties of cryptocurrency markets to identify key drivers for the use of cryptocurrencies in investment strategies. This paper provides a comprehensive review on the financial applications of Bitcoin. The focus is on three lines of research: price formation, detection of market inefficiency, and diversified portfolio construction. Topics such as market micro-structure and the interplay between different cryptocurrencies are only touched on briefly. We observe that many empirical studies find that Bitcoin markets are inefficient, with huge price fluctuations and long-range memory, and that these markets are heavily influenced by news and sector-specific events, or by infrastructure conditions such as volume trading and market liquidity. Nevertheless, astonishing price appreciations and modest correlation values versus other asset classes have contributed significantly to motivate applications of Bitcoin to investment and diversification. Future research may address practical implementations of such solutions and investigate the long-term sustainability and viability of these investment strategies.

There is a huge literature on whether forward rates of interest provide unbiased estimates of future interest rates. In most studies econometric evidence is presented which is apparently inconsistent with market efficiency; but more rarely is the economic, as opposed to statistical, significance of deviations from efficiency investigated. This paper uses accurate, up-to-date information on short term money market rates, from a common source, for all the major economies to assess efficiency and profit opportunities. The economic significance of deviations from the conditions required for efficiency are assessed by testing various trading rules.

The paper explores the potential to make profits from money market transactions based on simple rules derived from econometric analysis of the relation between current and future interest rates. We find that in many cases there are systematic divergences between forward rates and future spot interest rates for various currencies quoted on the London interbank market.

We examine the pricing of instalments receipts ("IRs") issued on the New Zealand stock market that trade concurrently with the underlying shares. An IR is a security that has identical entitlements to dividends receipts as the holder of an ordinary share but allows the holder to acquire the ordinary share with fixed pre-scheduled payments spread over a period of time. Similar to Charupat and Prisman (2004) for IRs traded in the Canadian market, we find that IRs of secondary offerings in the New Zealand market trade at an economically significant premium in the immediate period following their initial issue. The premium then declines over time and becomes negative in the period prior to the final instalment payment date. Our study suggests the benefits of IRs are not unique to one institutional environment and that issuers can increase the demand for new securities by overcoming investors' borrowing restrictions.

This paper is concerned with the potential profit opportunities in trading calendar spreads of 90-day Bank Accepted Bill (BAB) futures contracts on the Sydney Futures Exchange (SFE) during the 1990s. It is shown that statistically significant gross profits can be generated by a naïve strategy for most of the considered holding periods ranging from 3 months to 18 months. However, after the deduction of generous transaction costs, the net profits are statistically significant only for the 6-month holding period returns. The implications of the profits produced by calendar spread trading methodology on the efficiency of the BAB futures market are also addressed. The empirical results reveal that the efficiency market hypothesis for the BAB futures market cannot be universally accepted in the 1990s.

We investigate the effectiveness of two recent regulatory policy changes on market efficiency in the Chinese A- and B-share markets. Overall, the opening of the B-share market to domestic Chinese investors and the limited opening of the A-share market to foreign investors increase market efficiency. The opening of the B-share market significantly reduces the price differential between A- and B-shares. Furthermore, there is no longer feedback in returns between the two markets in recent years. Our results provide evidence that there is no detrimental effect to market efficiency by integrating Chinese investors to international markets and foreign investors to the Chinese stock markets.

The main purpose of this paper is to examine the impact that the introduction of exchange traded derivative warrants has on the underlying securities' price, volume and volatility in the Australian market. The impact that derivative trading has on the underlying security is essential to our understanding of security market behaviour and important in the fields of market efficiency and pricing of derivatives. The major findings of significant negative abnormal returns, reduction in skewness, no change in beta and small changes in variance are consistent with recent research findings in the US, UK and Hong Kong. However, the findings of derivative warrant listing resulting in decreased trading volume is in contrast with most prior research in the field. The results of this research, showing a negative price impact, decreased volume and no change in risk, and other recent empirical findings such as Mayhew and Mihov (2000) or Faff and Hillier (2003), indicate a requirement for further development of the theoretical frameworks.

Cooper et al. (2006) find support for the "other January" effect in the US market over the period from January 1940 to December 2003 whereby the 11-month holding period returns following positive January returns are on average higher than those 11 months following negative January returns. Under this scenario, January returns can predict the subsequent 11-month holding period returns implying the potential for abnormal profits. We revisit this "anomaly" in the US stock market using the extended period from July 1926 to January 2012. Over the shorter period of 1940–2003 used by CMO, the results are supportive of the "other January" effect and they do so for several alternative holding periods. However, this alleged "other January" effect disappears once we expand the period. Moreover, we find similar and perhaps stronger anomalies for non-January months, particularly February and September. The evidence we uncover in this paper suggests that this alleged "other January" effect is likely sample-period sensitive and further, it is not specific to the month of January.

This study examines the Russian stock market efficiency from two perspectives. First, we document that for the sample of Russian firms cross-listed on the Main Market of the London Stock Exchange (LSE) as Global Depositary Receipts (GDRs), the return series obtained from both the local market and the LSE are time-invariant and hence, predictable. This suggests that the market is inefficient with respect to pricing Russian GDRs and that investors are likely to make systematic nonzero profits. Second, we document profitable arbitrage opportunity surrounding the announcement to adopt IFRS, which is an additional evidence of market inefficiency. The significant pricing spread observed on this key date was due to the differential market reaction to IFRS adoption — neutral on the local MICEX exchange dominated by individual traders and significantly negative on the LSE dominated by institutional investors. This finding can be explained by (i) informational advantages of the local investors due to geographic proximity, (ii) differential expectations with respect to governance norms and listing requirements, and (iii) difference in portfolio composition of the two investor groups.

We build upon social movement and investor attention theories to investigate the effect of “taking a knee” protests on the abnormal stock returns of NFL sponsoring companies. The study is conducted in two phases. Employing event study methodology in the first phase, we measured the abnormal returns and trading volumes of the companies during a four-year period from 2016 to 2020. While the results for abnormal returns are economically small, we found that there is 13.42% increase in trading volume in [0,$+$5], 61.28% in [0,$+$15], and 160.01% in [0,$+$30] event windows. There was also information leakage prior to the events as indicated by the 36.08 increase in trading volume in the [$-$30, $-$2] event window. We ran multiple regression models in the second phase to further examine the degree to which the unique circumstances surrounding the protests explain variations in abnormal returns. Companies that had higher brand values and the negative emotional tone of the comments made by the President of the United States about the protests were positively associated with abnormal returns. The results are also robust to methodological changes using abnormal returns adjusted for trading volume. Overall, the findings suggest that social activism by athletes is likely to affect investor attention and sentiment, thereby garnering a spillover effect on sponsoring companies’ stock prices and trading volumes.

The ongoing COVID-19 shocked financial markets globally, including China’s crude oil future market, which is the third-most traded crude oil futures after WTI and Brent. As China’s first crude oil futures are accessible to foreign investors, the Shanghai crude oil futures (SC) have attracted significant interest since launch at the Shanghai International Energy Exchange. The impact of COVID-19 on the new crude oil futures is an important issue for investors and policy makers. Therefore, this paper studies the short-term influence of COVID-19 pandemic on SC via multifractal analysis. We compare the market efficiency of SC before and during the pandemic with the multifractal detrended fluctuation analysis and other commonly used random walk tests. Then, we generate shuffled and surrogate data to investigate the components of multifractal nature in SC. And we examine cross-correlations between SC returns and other financial assets returns as well as SC trading volume changes by the multifractal detrended cross-correlation analysis. The results show that market efficiency of SC and its cross-correlations with other assets increase significantly after the outbreak of COVID-19. Besides that, the sources of its multifractal nature have changed since the pandemic. The findings provide evidence for the short-term impacts of COVID-19 on SC. The results may have important implications for assets allocation, investment strategies and risk monitoring.

Based on the China Securities Index 300 (CSI 300 index) futures trading restrictions in 2015, this paper uses the multifractal detrending moving-average cross-correlation analysis method (MF-X-DMA) to investigate the effect of introducing futures trading restrictions on the market efficiency of CSI 300 index spot and futures markets. We begin by using multifractal detrending moving-average analysis (MF-DMA) and find that the futures trading restrictions improve spot market efficiency but decrease futures market efficiency. Moreover, we examine the cross-correlation between spot and futures markets and the information transmission process. MF-X-DMA analysis shows an increase in the level of persistent cross-correlation between spot and futures markets, and a decrease in the multifractality degree of cross-correlation, suggesting that the relationship between spot and futures markets becomes stronger and less complicated after the futures trading restrictions. Moreover, the nonlinear Granger causality test shows that futures returns do not Granger cause spot returns after the restrictions. Therefore, the futures trading restrictions may mitigate the harmful effect of speculative trading in the futures market and thus improve spot market efficiency.

The daily price limits in the ChiNext stock market were relaxed from $\pm 10$% to $\pm 20$% on 24 August 2020. Using the multifractal detrended moving average cross-correlation analysis (MF-X-DMA) method, we find that relaxing daily price limits leads to a greater degree of multifractality of the ChiNext stock market, suggesting that the relaxation of daily price limits harms stock market efficiency. In addition, the positive cross-correlation between ChiNext and Chinese main board stock markets becomes weaker, i.e., relaxing daily price limits also decreases the connection between ChiNext and other stock markets. Moreover, there is an increase in the degree of the cross-correlation multifractality between ChiNext and Chinese main board stock markets, suggesting that the linkage of ChiNext and other stock markets is more complicated and risky after the relaxation of daily price limits. Our findings fulfill related literature from the perspective of multifractality and have important implications for investors.

The Efficient-Market Hypothesis (EMH) is one of the important theories in financial markets. Under this hypothesis, developing a robust profitable strategy is infeasible because the market price fluctuates immediately following any new information and is thus unpredictable. However, many empirical studies have shown that certain trading strategies in the financial markets are profitable, and the Momentum Strategy is one of the major strategies among them. With four momentum strategies, this paper uses the real-world data points (intra-day data of one-minute time frame) for back-testing the Taiwan Stock Exchange Capitalization Weighted Stock Index Futures (TAIEX Futures) during the period from January 04, 2010 to March 25, 2015. Numerical comparisons among the four strategies reveal that there exist market inefficiencies in Taiwan stock market. We verified the momentum effect of Taiwan Index Futures market through different stop-loss and stop-profit mechanisms. In conclusion, the management of stop-loss and stop-profit is crucial in the profit/loss of the trading strategy. The technique can be applied to many trading methodologies in improving the quality of strategies. Money management provides another path for strategy planning other than purely focusing on the technical mechanisms.

Reasoning that private firm-specific information causes firm-specific return variation that drives down market-model R²s, [Morck et al., 2000, The Information Content of Stock Markets: Why do Emerging Markets have Synchronous Stock Price Movements? Journal of Financial Economics, 58, 215–260] begin a large body of research which interprets R² as an inverse measure of price informativeness. Low-R²s or "synchronicity," as it is called in this literature, signal that prices more efficiently incorporate private firm-specific information, and high R²s indicate less. For this to be true, we would expect that low-R² stocks have characteristics that facilitate private informed trade, i.e., lower information costs and fewer impediments to arbitrage. However, in this paper we document the opposite: Low-R² stocks are small, young, and followed by few analysts, and have high bid-ask spreads, high price impact, greater short-sale constraints and are infrequently traded. In fact, microstructure measures suggest that private-information events are less likely for low-R² stocks than high, and that differences in R² are driven as much by firm-specific volatility on days without private news as by firm-specific volatility on days with private news. These results call into question prior research using R² to measure the information content of stock prices.