Affect Market Efficiency Research Articles

How do stock markets react to dividend announcements during the COVID-19 pandemic? Evidence from the GCC markets

PurposeThis study aims to investigate how stock markets responded to corporate dividend policy changes during the COVID-19 pandemic in the Gulf Cooperation Council (GCC) countries. Likewise, it explores how efficiently market prices incorporate the news by examining the speed of stock price adjustment to various dividend announcements.Design/methodology/approachThe sample includes 741 dividend announcements from 2017 to 2021 made by 326 firms listed in the stock markets of the GCC countries. A series of regression analyses examine how dividend announcements influence the market reaction during the COVID-19 pandemic, controlling for other well-documented firm characteristics.FindingsThis study reveals an adverse stock price reaction to all the dividend announcements in most GCC markets. The findings also show strong asymmetric effects of COVID-19 on how the markets react to different dividend changes. Likewise, the authors show that investors tend to underreact to the good news of dividend increases amid hard times of crises due to prevailing uncertainty and bearish sentiment. Besides, regression results reveal that firms with dividend reductions during the pandemic experience less adverse market reactions than dividend-decreasing firms prepandemic.Practical implicationsFor firms, the findings confirm the role that corporate dividend policy can play in conveying signals to investors, especially during hard times of crises and turbulences, thereby affecting their share price. For policymakers, the results substantially affect market efficiency and firm valuation in the GCC markets.Originality/valueThis study is not only one of the first few attempts to scrutinize how the pandemic has affected the market reaction to changes in corporate dividend policies but also, to the best of the authors’ knowledge, it is the first to examine how corporate dividend policy could affect stock markets during COVID-19 in the context of GCC markets.

Fintech platforms and information service quality from the perspective of investor cognition

Fintech platforms serve the financial information market as a new player in corporate finance along with traditional analysts, and individual investors' preferences for these two service providers will affect market efficiency. This paper focuses on the financial information service industry in the context of the COVID-19, and discusses the information service quality of financial information service providers (fintech platforms vs. analysts) from the perspective of individual investors' cognition. Based on the theory of organizational information processing, through survey method, it has been found that investors believe that the information service quality of fintech platforms is higher than that of analysts, and is mediated by information planning comprehensiveness. It was also found that economic environment uncertainty moderates the mediating information service providers and information service quality through information planning comprehensiveness. Specifically, in a low economic environment uncertainty (Non-Lockdown Policy), investors believe that financial technology platforms have higher information planning comprehensiveness and higher quality of information services compared to analyst; In a high economic environment uncertainty (Lockdown Policy), the aforementioned impact is weakened. Robustness results indicate that the above main effects remain when considering the sub-sample and investors' Internet search behaviour. In addition, the heterogeneity results indicate that the more economically developed the region, the higher the investors' evaluation of the quality of financial information services. This study promotes the understanding of fintech substitution effect from the perspective of investor perception and reveals the psychological mechanism of individual investors, which provides micro ideas for the governance of fintech platforms for new participants in startups' financing and regional fintech development.

The time-varying effects of liquidity and market efficiency of the European Union carbon market: Evidence from the TVP-SVAR-SV approach

We use the time-varying parameter structural vector autoregression stochastic volatility (TVP-SVAR-SV) and causality-in-quantiles methods to explore the linkage between market liquidity and efficiency in the European Union Emissions Trading Scheme (EU ETS) during Phase III. Our findings indicate that two-way causality existed under normal and lower market conditions. Additionally, the linkage between liquidity and efficiency exhibits time-varying characteristics. Except in cases of extremely high market liquidity, the pass-through effect of liquidity on efficiency is mostly positive in the long run. The linkage is particularly stronger in the medium and long term. However, the response of liquidity to efficiency shocks is more complicated. Market efficiency generally has an overall inhibitory effect on liquidity in the short term and a promoting effect in the medium and long term. Furthermore, we investigate the impulse response during the COVID-19 period and the war between Russia and Ukraine and find that improvements in efficiency will permanently damage liquidity. Overall, the abilities of market makers and arbitrage traders, impacted by multiple factors, play an important role in the process by which liquidity affects market efficiency. By revealing and explaining the dynamic relationship between liquidity and efficiency, this research provides valuable information for policymakers and various market participants.

The tail wagging the dog: How do meme stocks affect market efficiency?

During the GameStop frenzy, Robinhood Markets Inc. made an unprecedented move by pausing the purchase of meme stocks, which represent a small segment of the market, from January 28th to February 5th, 2021. To evaluate the impact of this ban on market efficiency, we created two meme stock indices based on the lists of restricted stocks and conducted robust tests utilizing daily changes in these indices and the S&P 500 index. Our analysis suggests that meme stock trading does not have a negative impact on market efficiency. Furthermore, upon analyzing hourly data, we identified some puzzling correlations during the trading ban period. Specifically, we noticed that the illiquidity and volatility of both the meme stock market and S&P 500 increased, which raises concerns about a wider, unintended impact of the ban.

Unobservable investments, trade efficiency and search frictions

AbstractInformation structure can affect market efficiency by influencing participants' investment incentives. In this case, the entrants' type distribution and the market trade efficiency are both affected by the information structure, so they are jointly determined and correlated. In order to investigate the effects of asymmetric information, this paper uses a random search model of ex ante investments and trade efficiency, assuming that the amount of investment remains the investor's private information. I show that the ex ante payoffs are equivalent to the equilibrium payoffs when investments are observable. In the unique steady state equilibrium, non‐degenerate investment distribution and price distribution emerge simultaneously with ex ante identical agents. The investments motivated by unobservability fail to improve social welfare due to the mismatches caused by unobservability. Allocating positive bargaining power to investors alleviates the mismatch problem and improves social welfare.

Digitization, Prediction, and Market Efficiency: Evidence from Book Publishing Deals

Digitization has given creators direct access to consumers as well as a plethora of new data for suppliers of new products to draw on. We study how this affects market efficiency in the context of book publishing. Using data on about 50,000 license deals over more than 10 years, we identify the effects of digitization from quasi-experimental variation across book types. Consistent with digitization generating additional information for predicting product appeal, we show that the size of license payments more accurately reflects a product’s ex post success, and more so for publishers that invest more in data analytics. These effects cannot be fully explained by changes in bargaining power or in demand. We estimate that efficiency gains are worth between 10% and 18% of publishers’ total investments in book deals. Thus, digitization can have large impacts on the allocation of resources across products of varying qualities in markets in which product appeal has traditionally been difficult to predict ex ante. This paper was accepted by Joshua Gans, business strategy.

The Tail Wagging the Dog: How Do Meme Stocks Affect Market Efficiency?

The Tail Wagging the Dog: How Do Meme Stocks Affect Market Efficiency?

Factors affecting market efficiency of unhusked rice in Central Java

The purpose of this study was to analyze marketing distribution, factors affecting marketing, and margins of unhusked rice in Undaan Sub-District, Kudus Regency. The survey was conducted from October to November 2018 in Undaan Sub-District, Kudus Regency. The data of marketing margin and marketing efficiency were descriptively analyzed using multiple linear regression analysis. The result showed that there were two patterns of marketing channels of unhusked rice; first, farmers’ → rice mills and second, farmers’ → middleman → rice mills. The marketing margin of the first pattern was Rp. 0.00, while the marketing margin of the second pattern was Rp. 525.93 at the middleman level. The marketing efficiency of the two patterns was efficient in term of farmers’ share. The result of the multiple linear regression showed that the channel pattern and the selling price as independent variables were the factors influencing marketing efficiency.

An Efficient Hybrid TLBO-PSO Approach for Congestion Management Employing Real Power Generation Rescheduling

In the present deregulated electricity market, power system congestion is the main complication that an independent system operator (ISO) faces on a regular basis. Transmission line congestion trigger serious problems for smooth functioning in restructured power system causing an increase in the cost of transmission hence affecting market efficiency. Thus, it is of utmost importance for the investigation of various techniques in order to relieve congestion in the transmission network. Generation rescheduling is one of the most efficacious techniques to do away with the problem of congestion. For optimizing the congestion cost, this work suggests a hybrid optimization based on two effective algorithms viz Teaching learning-based optimization (TLBO) algorithm and Particle swarm optimization (PSO) algorithm. For binding the constraints, the traditional penalty function technique is incorporated. Modified IEEE 30-bus test system and modified IEEE 57-bus test system are used to inspect the usefulness of the suggested methodology.

Constrained Dealers and Market Efficiency

We analyse how constraints on dealers’ risk bearing capacity affect market efficiency in the foreign exchange (FX) market. Dealers support market efficiency by accommodating their customers’ trading demands through elastic liquidity provision in normal times but when they face constraints their elasticity of liquidity provision weakens. Episodes of tight dealer constraints – for instance, due to high leverage, Value-at-Risk, and funding costs – in turn go hand in hand with price inefficiencies due to law of one price deviations and elevated trading costs. We rationalise our novel empirical findings with a tractable model that sheds light on the key mechanisms of how market efficiency can deteriorate when dealers are more constrained.

Two‐sided service markets: Effects of quality differentiation on market efficiency

Determining the effects of quality differentiation on the efficiency of two‐sided service markets is challenging. The presence of private information on both market sides and the heterogeneity of sellers can lead to substantial economic inefficiencies. Hence, this paper investigates how quality‐differentiated sellers affect market efficiency from the perspective of mechanism design theory. First, we characterize second‐best mechanisms for matching buyers and sellers. We then propose a heuristic algorithm for approximating the welfare‐maximizing match outcomes. Based on empirical data, our simulation study suggests that an increased quality differentiation can reduce market efficiency; however, this inefficiency vanishes as the market size increases.

Crypto Covered Interest Parity Deviations

Studying deviations from covered interest rate parity (CIP) in the Bitcoin/US-Dollar (BTC/USD) market, we find large CIP deviations of up to 15% until Q1/2018. Afterwards, CIP deviations have been subdued, which we attribute to the market entry of high-frequency traders (HFTs). We argue that these market entries have increased efficiency of cryptocurrency markets with respect to CIP as well as liquidity, volatility, and bid-ask spreads. Remarkably, these efficiency gains are larger for the less liquid cryptocurrency Litecoin. Employing a difference-in-differences design, we show that the launch of the BTC/USD future at the Chicago Mercantile Exchange (CME) did not affect market efficiency. Finally, remaining CIP deviations after Q1/2018 seem mostly related to increased credit risk of certain crypto exchanges.

Social media, interaction information and stock market efficiency: evidence from the Shenzhen stock exchange easy interaction platform in China

ABSTRACT This paper studies the impact of interaction between investors and listed companies on market efficiency from two perspectives of earnings expectation and information asymmetry. We conduct an empirical analysis of the Shenzhen Stock Exchange Easy Interaction (SSEEI) platform. The interactive text is used to build interactivity indicators showing that the platform provides an important way to increase stock market efficiency. We further study how the interaction affects market efficiency using the emotion dictionary and the Latent Dirichlet Allocation (LDA) model. The results show that both good and bad news discussed on the platform are significant to market efficiency.

Do the performance and efficiency of China's carbon emission trading market change over time?

Whether or not China can succeed at the forefront of international development in the coming decades will largely hinge on its ability to adapt to low-carbon economic development and its efforts to promote the Unified National Emission Trading System (UNETS). To understand the evolution of China's carbon market, this paper firstly divides the development of China's regional carbon markets into three phases: pilot construction (phase 1, before 31 May 2015), preparation for the UNETS (phase 2, 1 June 2015-19 December 2017), and formal construction of the UNETS (phase 3, 20 December 2017-present). Then this research reviews the trading performance and employs four robust variance ratio (VR) tests to capture structural changes and examine the efficiency of China's eight regional carbon markets in different periods. Results show that compared to phase 1, smaller price volatility, larger daily trading volume, and higher market liquidity are more frequent at the later stages of majority markets. Despite these improvements, results from the VR tests indicate that the statistic in majority of China's regional carbon markets is insignificant in any given period and, therefore, they are not weak-form efficient. The additional detrended cross-correlation analysis demonstrates that market liquidity affects market efficiency in the Hubei market only, which implies that Hubei, where the market liquidity reaches almost 100% in phase 3, is highly likely to be weak-form efficient shortly. Finally, several recommendations are provided to improve the efficiency and maturity of China's carbon markets, including strengthening legislation, improving the market design, and constructing information platforms.

Sophisticated investors and market efficiency: Evidence from a natural experiment

We study how sophisticated investors, when faced with shocks to information environment, change their information acquisition and trading behavior, and how these changes in turn affect market efficiency. We find that, after exogenous reductions of analyst coverage due to closures and mergers of brokerage firms, hedge funds scale up information acquisition, trade more aggressively, and earn higher abnormal returns on the affected stocks. The hedge fund participation also mitigates the impairment of market efficiency caused by coverage reductions. Overall, in a causal framework, our findings suggest a substitution effect between sophisticated investors and public information providers in facilitating market efficiency.

Stock Price Overreaction to ESG Controversies

There has been substantial growth in the incorporation of environmental, social and governance (ESG) issues into investment decisions, and this trend has been motivated by the societal benefits that are achieved when socially responsible firms have access to cheaper capital. While the benefits with ESG investing are apparent, we investigate the possible downside of the trend towards ESG by examining how this approach to investing might affect market efficiency. ESG is now a highly salient aspect of an investor’s information set and, given cognitive limitations, investors might devote substantial resources to examining ESG characteristics to the detriment of other firm fundamentals. Consistent with salience theory, we report that this over-emphasis on ESG results in the market overreacting to news about ESG controversies. This over-reaction is more pronounced within smaller firms and stocks that were held by more transient investors before the announcement. Contrarian investors are likely able to profit from the unpopular strategy of buying stocks after bad ESG news is released.

Insider trading laws and price informativeness in emerging stock markets: The South African case

We test the view that insider trading deters informativeness and, thereby, provide empirical evidence on the ramifications of insider trading legislation, particularly in an emerging market, that has hitherto received no research attention. Using the difference-in-differences identification strategy, we find that “effective insider trading law” improves stock price informativeness, a reflection of market efficiency, and that this efficiency is robust to both economic factors that affect market efficiency and the choice of control. Importantly, our results support the hypothesis that prohibition of insider trading elicits efficiency enhancement, particularly in emerging markets which are often characterized by weaker requisite institutional infrastructure than developed markets.

Price transmission of Arabica coffee between North Sumatra with state main export purpose (America-Europe)

Fluctuations in North Sumatra Arabica coffee prices can affect market efficiency and transmission prices of North Sumatra Arabica coffee with the main export destination countries. This can be used as an opportunity by market participants, especially those who have the power to influence prices to manipulate prices. This research was conducted to analyse the transmission price of North Sumatra Arabica coffee with the main destination countries of America and Europe, and analysis of the factors forming the price of Arabica coffee in North Sumatra. The method used in this study is the Asymmetric Error Correction Model (AECM) model which is used for analysis of Arabica coffee price transmission and the Error Correction Model (ECM) model which is used to analyse the factors forming coffee prices with. The results showed that there was an asymmetric relationship between the transmission price of Arabica coffee in North Sumatra and the main destination country in the short run whereas in the long run the price transmission occurred symmetrically. In the analysis of the factors forming the price of North Sumatra Arabica coffee both in the short term and long term are significantly affected by all variables used.

How Does Benchmarking Affect Market Efficiency? The Role of Learning Technology

How Does Benchmarking Affect Market Efficiency? The Role of Learning Technology

Dealers' Search Intensity in U.S. Corporate Bond Markets

Are dealers' search efforts endogenous in decentralized markets? How do dealers' search efforts affect market efficiency? We propose a model with dealers choosing idiosyncratic search intensities, and estimate the model using transaction data on U.S. corporate bonds. We find that: [1] with dealers ranked by their private valuations for a bond, the middle-type dealer chooses the highest search intensity, and she reallocates bond positions from lower-type dealers to higher-type dealers; [2] the estimated model predicts that the search costs and bond mis-allocation in current OTC markets generate 13.7% welfare loss relative to a counterfactual friction-less market.