A Cooperative Dynamic Approach to Pairs Trading

Based on recent works on stocks comovement, Pairs Trading’s strategy is enhanced by reducing the stock universe to the stocks with the lower volatility on a given date. From this universe of low volatility stocks, pairs are selected by looking for pairs whose series present a high degree of antipersistence. Finally, a “reversion to the mean” strategy is applied to these pairs. It is shown that, with this approach to Pairs Trading, positive results can be obtained for stock from the Nasdaq stock exchange, mainly during bull markets and low volatility periods.

Market Trends and Options Trading: Viewpoint, Probability and Implications

In Dow theory, market trends are classified as secular trends for long-term frames, primary trends for medium-term frames, and secondary trends for short-term frames. For the long and medium terms, they can consist of major bull (bear) markets and minor bear (bull) markets; for the short terms, they may have corrections and bear rallies. These definitions of market trends are not very helpful to options traders because in practice, options trading is often done on a short-term time frame and options have a unique property of time value. Even in a bull market, there is a possibility of losing all money for buying call options; in a bear market, there is a probability of earning money for buying call options. This inconsistency often troubles options traders deeply. From the viewpoint of options trading, we introduce a new concept of analyzing the market trends and propose new methods for estimating the probabilities of the market trends since at any time the future prices are unknown. By simplifying the market trends into three concepts of uptrend, downtrend, and neutral trend, it will have consistent implications for options trading. JEL classification numbers: C13, G10, G13. Keywords: Market trends, Options trading, Trend probability, Estimation methods, Trading implications.

COVID-19 PANDEMIC AND HERDING BEHAVIOUR IN CRYPTOCURRENCY MARKET

In this paper, we examine the presence of herding in cryptocurrency market for four distinct sub-periods (Pre and During COVID-19 period, bear and bull markets) using daily closing prices of 5 largest cryptocurrencies by market capitalization (Bitcoin, Ethereum, XRP, Stellar and Tether) from April 20, 2019 to January 31, 2021. The study employs cross-sectional absolute deviations (CSAD) model to test herd behavior and the results of the study provide evidence of herd behavior in the whole market for the selected period under study. The study also proofs the presence of herding during COVID-19 period and in positive market returns. These indicate that, investors in the cryptocurrency market, during COVID-19 periods, and in bullish market are inclined to the investment behavior of other peer investors in the market. The study is significant to investors, regulators and players in the cryptocurrency market so as to deepen their understanding of herding behavior since herding is thought to increase the volatility of the market. The study is significant to investors, regulators and players in the cryptocurrency market so as to deepen their understanding of herding behavior since herding is thought to increase the volatility of the market.

Investigating the Dynamics of Exchange Traded Funds Across the Bear and Bull Markets: Evidence from Indian Equity ETFs

The present study attempts to examine the tracking ability of Indian equity exchange traded funds (ETFs) across the bearish and bullish market regimes. Also, ETFs’ sensitivity to their respective underlying indices across the two market conditions is examined so as to gain an insight into the differences in risk exposure under the two regimes using DBM. The results found that the tracking error (TE) of ETFs varies across the two market regimes with it higher during the bullish regime. At the same time, ETFs’ responsiveness to their underlying indices is found to be higher during the bearish market regime, which justifies the existence of lower TE during the bearish regime. NIFTYBEES, KOTAKNIFTY and BANKBEES emerged to be the top three performers in terms of tracking efficiency. Further, NIFTYBEES, BANKBEES and JUNIORBEES are reported to provide significantly positive excess returns during the bullish regime. As such, investors considering investment in equity ETFs can opt for the top performing funds where they also stand a chance to earn excess return (in few cases). Also, it is observed the beta coefficients of ETFs varied significantly from unity. It suggests that the ETFs and their respective underlying indices are not subject to similar systematic risk.

Price-Volume Granger Causality Tests in the Egyptian Stock Exchange (EGX)

Using weekly Egyptian stock exchange data on the 34 most active companies stretching from 2011 to 2017, this study finds that price changes Granger cause trading volume up to 8 weeks (lags), supporting the sequential information arrival model in the EGX. We also find a robust contemporaneously positive asymmetric relationship between price change and trading volume, confirming two well-documented characteristics of the price-volume relationship as well as two major adages of Wall Street: “it takes volume to move prices” and “volume in bull markets is heavier than volume in bear markets”. Overall, our results imply that although there is some sequential diffusion of information, the EGX’s efforts at improving its microstructure through initiatives such as the 2009 Presidential Degree on structure and governance, appear to have helped in improving instantaneous access to information – as exemplified by our evidence of strong contemporaneous positive price-volume relationship.

Cross-Sectional Relationship Between Beta and Realized Returns in Emerging Markets

This paper examines the conditional risk-return relationship caused by the impact of using realized returns as a proxy for expected returns, which requires a separation of negative and positive market premiums. Following the methodology of Pettengill et al. (1995), we test the cross sectional relationship between beta and realized returns on the Amman Stock Exchange (ASE) for ten beta sorted portfolio over the period of January 1993 to December 2016. The empirical results suggest that the traditional two-pass approach produces an insignificant relationship between beta and realized returns in most of the sample period. However, when adjusting for negative market premiums, the results show a significant and consistent relationship for all the testing periods and samples. However, a guaranteed reward for holding extra risk occurred only in the period 2001 –2008, which suggests an assurance of positive risk-return tradeoff during bull markets. JEL Classifications: G11, G12, G15, C21 Asset Pricing, Emerging Markets, Conditional Relationship, Beta, Market Premium

Driving factors of merger momentum in China: empirical evidence from listed companies

Purpose The purpose of this paper is to study merger momentum and its driving factors in China by sampling 376 listed bidders from 2008 to 2013. Design/methodology/approach The empirical model captures the dependency of market reaction on recent merger and stock market states. The independent variables are designed from two dimensions, i.e. at the level of market-wide as an integral and bidder-specific as individuals. Furthermore, both the market and bidding firms contain merger momentum and market momentum, respectively. Findings The empirical results show that there is merger momentum in the market. Particularly, merger momentum is significant both in short run and long run for the mergers with cash payment, which supports the synergy effect. It also implicates the mergers with stock driven by investor sentiment. Besides, investors’ over-optimism is significant in the bull markets while managerial hubris is found in the bear markets. Research limitations/implications The driving factors for merger momentum in China are complex. Three impacts with different effects interact with one another. They are investor sentiment and managerial hubris with negative effects resulting in reversal abnormal return in the long run, and synergies with positive shocks resulting in no reverse at all. The limitation of the paper is insufficient analysis of the mergers financed by stocks, which will be the focus for future study. Practical implications The conclusions of the study help to intensify the understanding of the immature and unnormalized capital market in China. The empirical analyses give some inspiration and suggestions to three parties in the market, i.e. investors, bidding firms and regulators, respectively. Originality/value There are three contributions. The first one is to provide a novel model to identify how these different effects work on the merger momentum. The second one is the measurement of investor sentiment from different perspectives. The last but most important one is the new findings with novel explanations, which proves that the impacts on merger momentum are complex.

Benchmark-Based Preferences Make Investors Loss Averse in Bull Markets and Gain Seeking in Bear Markets

Recent empirical studies have shown that investors are far more likely to be loss averse during bull markets than during bear ones. The aim of this short note is to give solid foundations to this empirical evidence. Using the benchmark-based preference method we establish a direct connection between the individual perception of the market trend and the individual risk preferences. Then we develop a novel definition of loss aversion and gain seeking which intuitively captures the human attitudes described by the quotes “losses loom larger than gains” and “gains loom larger than losses”, respectively. Our findings have also practical applications. In fact they may offer a solid explanation to the disposition effect. According to this cognitive bias in bull markets investors are driven by loss aversion and tend to sell winners too early; whereas in bear markets investors are driven by gain seeking and tend to hold losers too long.