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We analyse a long-term dataset of the Korean equity market from 1983 to 2023 to explore the momentum and reversal effects in both individual stocks and industry sectors. In general, portfolios based on individual stock momentum strategies exhibit a reversal effect, while those based on industry momentum strategies show no significant effects. The reversal effect in individual stocks persists, even when controlling for industry momentum. In certain sub-periods, we observe momentum effects, but overall, reversal effects are dominant. These anomalies persist, even after controlling for various risk factors. [ABSTRACT FROM AUTHOR]

The Korean Emissions Trading Scheme (K-ETS) in its initial stages experiences low market liquidity driven by sellers' supply shortages. We empirically investigate for the first time the informational market efficiency of the K-ETS, specifically how the efficiency varies over time with policy measures taken to increase liquidity, such as individually constrained banking. Our findings indicate that temporary measures taken to improve liquidity in the K-ETS do not ensure informational market efficiency. We also find after the COVID-19 onset, inefficiency does not disappear even with a large surplus of allowances under pre-scheduled constrained banking. This study provides valuable implications for emerging carbon markets, which move forward toward more stringent caps. [ABSTRACT FROM AUTHOR]

This paper is an evaluation of long-term cumulative abnormal returns (CAR's) based on Twitter broadcasts by highly influential market agents. We look at the information content of Elon Musk, CEO of SpaceX, Tesla and Twitter Inc. and the former US President Donald Trump. The principal objectives of this research are twofold: 1.) To assess whether markets are semi-strong form efficient and consequentially whether or not returns can be derived from strategies based on such sporadic tweet releases (abstracting from 'news'). For this purpose, event studies are conducted on multiple companies which were targeted by Musk and Trump tweets. A control group of all Dow Jones companies with earnings releases on Twitter is utilized. We find there appears to be a "pre-post-Twitter-drift" when the release is by exceedingly influential market personalities. The cumulative abnormal returns remain significant over long durations. This indicates that markets are not entirely semi-strong form efficient regarding social media releases and that trading on such tweets may be profitable (even after factoring in varying market phases). 2.) The paper introduces a new theme: long term CAR's of market information events. The paper also notes whether the tweet was during regular market hours or after-market hours. [ABSTRACT FROM AUTHOR]

A manager's prior experience may affect an organization's resource allocation decisions and its performance. I examine this issue in the context of National Football League (NFL) franchises. I find that teams with coaches from an offensive background spend 5.5% points more of their salary cap space on offensive personnel, while a defensive background does not significantly affect the share of resources allocated to defensive personnel. While additional salary resources committed to offensive and defensive personnel do improve team performance in those respective areas, marginal improvements in offensive and defensive performance associated with greater spending are generally unaffected by the coach's background, a finding suggesting that a coach's background does not confer an informational advantage on certain types of personnel. I further find no evidence of significant differences in the effects that spending on offence and defence respectively have on team performance, suggesting efficiency within this labour market. [ABSTRACT FROM AUTHOR]

We examine whether investors display a lack of attention by not incorporating relevant public information into equity valuations. Beginning in 2019, ASC 842 requires the recognition of operating leases, which were previously only disclosed in the financial statement footnotes. This change in accounting standard results in firms with significant operating leases recognizing a considerable increase in debt. We find that firms with significant operating leases, on average, earned negative stock returns around the initial recognition of their operating leases. We find that the negative reaction to operating lease recognition does not vary with firm-level proxies for investor attention, which suggests a pervasive lack of attention to operating lease disclosures prior to ASC 842. Our results provide new evidence consistent with investors suffering from limited attention and equity prices reflecting a lack of fundamental analysis. [ABSTRACT FROM AUTHOR]

Previous research has debated about whether institutionalization could improve market efficiency. We develop a theoretical model under anticipated utility combined with probability weighting to study the impacts of institutionalization on market participation and market efficiency. The prudence attitude towards probability uncertainty leads to limited participation by investors. We find that institutionalization influences the market in two different ways. An increase in the total sector size of institutional investors facilitates price discovery but discourages market participation from naïve investors due to information asymmetry. However, when the top institution has high market power, this large institution trades strategically to induce more participation by naïve traders for risk-sharing at the cost of lowering information efficiency. [ABSTRACT FROM AUTHOR]

This paper studies the dynamic relationship between the parallel and official exchange rates of Chinese Yuan (CNY) to U.S. Dollar (USD). Motivated by recent evidence about Bitcoin as a major channel for capital flight from China, we construct a parallel exchange rate implied by Bitcoin prices in the Chinese and U.S. crypto exchanges. While the dual exchange rates are cointegrated, adjustment to long-run equilibrium is non-linear and depends on policy changes and state of the markets. Results from our Markov Switching Vector Error Correction model suggest the parallel exchange rate responds one-to-one in the long-run with respect to an official exchange rate innovation. However, an unexpected change in the parallel rate is countered by an opposite and state-dependent response in the official exchange rate, suggesting active exchange policy interventions by the Chinese monetary authority. [ABSTRACT FROM AUTHOR]

In this paper, I examine the joint role of the previous game's outcome with and without the spread on wagers' preferences and outcomes in the NFL gambling market. The results show that gamblers are more likely to wager on the home team if they covered the spread in their previous game, while they are less likely to bet on the home team if the visiting team won their last game (not considering the spread). Further results show that teams are more likely to cover the spread if they covered the spread but lost their previous game. Profitable betting strategies are then put forward based on this information. [ABSTRACT FROM AUTHOR]

In this study, we set out to construct a daily frequency climate risk index with the aim to explore the impacts of climate risk on the stock markets of advanced and emerging countries and green stocks. We adopt an approach similar to the Sharpe ratio to demonstrate the pricing of climate risk into stocks and therefore reexamine the (in)efficiency of these markets. We specify an econometric model to evaluate the predictive content of the climate risk index for stock returns. We find compelling evidence of market efficiency when climate risk is priced into the stocks and market inefficiency otherwise. Results from the predictability analyses indicate that about 85% of advanced stock markets, 17% of emerging stock markets, and 100% of green stocks have the capacity to protect investors against climate risk. Forecast evaluations reveal that the climate risk index is a good predictor of the stock returns only after controlling for the macroeconomic environment. We explore several robustness checks and highlight both investment and policy implications. [ABSTRACT FROM AUTHOR]

We use the Hawkes process to model the high-frequency price process of 108 stocks in the Chinese stock market, in order to understand the endogeneity of price changes and the mechanism of information processing. Using a piece-wise constant exogenous intensity, we employ non-parametric estimation, residual analysis, and Bayesian Information Criterion (BIC) to determine that a power-law kernel is the most appropriate for our data. We propose the internal branching ratio to represent endogeneity within a finite interval. The branching ratio tends to be higher after the market opens and before the market closes, with a mean value of around 0.81, suggesting significant endogeneity in price changes. In addition, we explore the relationship between branching ratios and stock characteristics using panel regression. Higher branching ratios are associated with lower levels of price efficiency at high, but not low, frequencies. Finally, the branching ratio increases over time without significant impact from COVID-19. [ABSTRACT FROM AUTHOR]

Sports betting markets are an attractive setting to evaluate the degree to which publicly available information is efficiently incorporated into asset prices. Weather information represents one category of potentially undervalued public data, and we assess its impact on wagering outcomes and market behaviour in American college football. We uncover statistically significant effects of weather characteristics on totals market outcomes, indicating that the market does not appropriately assimilate this data into its forecasts. We also demonstrate that weather characteristics are not statistically significant predictors of totals market line movement magnitude. Together, these results suggest the market systematically undervalues weather data. We then develop simple wagering strategies utilizing only three weather characteristics and illustrate the ability to profit. [ABSTRACT FROM AUTHOR]

We find that investor sentiment restrains the predictability of earnings news on announcement returns but the constraining effect of sentiment on the predictive power of earnings news diminishes as sentiment falls. We document that investor attention works as an important channel in the relation between investor sentiment and announcement returns. Investor attention enhances the immediate price reaction to earnings news by curbing the impact of sentiment on the predictive power of earnings news. Our findings reflect the joint effect of attention and sentiment on the source of excess returns documented in the prior earnings-based market anomaly literature. [ABSTRACT FROM AUTHOR]

This paper probes into the market efficiency and relevant issues of copper options, the first industrial options product launched in China and currently the only non-ferrous metals option. Since its listing on 21 September 2018, the copper options market, developing on the fast track, has become the largest copper options market in the world, and thus it is of important meaning to study its market efficiency. Taking the data of China's copper options market from its debut to 30 April 2022 as a sample, this paper studies the efficiency of this market using three typical risk-free arbitrages such as put-call-future parity arbitrage, box spread arbitrage, and boundary arbitrage strategies. To better reflect the actual situation, this paper, when establishing options arbitrage strategy models, not only took into account various actual trading factors such as transaction costs, market impact costs, liquidity costs, margin, and capital opportunity costs but also combined daily and high-frequency data to present highly practical arbitrage strategies. According to empirical results, there are few arbitrage opportunities with a very low proportion when actual trading factors were considered. Overall, no evidence was found to prove that China's copper options market significantly violates the market efficiency rule. [ABSTRACT FROM AUTHOR]

In this paper, we show that the increasing popularity of machine learning improves market efficiency. By analysing the performance of a set of popular machine learning-based investment strategies, we find that profits from these strategies experience significant declines since the wide adoption of machine learning techniques, especially for profits based on the more preferred method of neural networks. These declines mainly come from long legs. Using the 'machine learning' Google search index as a proxy for machine learning-based trading intensity, we find that returns from the neural networks-based long–short and long-only strategies are weaker following high levels of machine learning intensity, while no relation is found between machine learning intensity and the short-only neural networks-based strategy. [ABSTRACT FROM AUTHOR]

The Shanghai crude oil futures market, as the largest crude oil market in the Asia-Pacific region, is an important complement to the global crude oil market. We use the autoregressive distributed lag model (ARDL) to examine long-term and short-term cointegration relations between the Shanghai crude oil futures market and China's crude oil spot market (Daqing), international (WTI and Brent) benchmarks. Based on the price data of the Shanghai crude oil futures contract covering a long period, we find that, in the long run, the Shanghai crude oil futures price is greatly affected by international crude oil markets. In the short run, both international and China's crude oil spot markets have a significant influence on the Shanghai crude oil futures prices. Moreover, our dynamic simulation results show that there is a significant time lag for the Shanghai crude oil futures market to respond to the shocks from the domestic and international markets. [ABSTRACT FROM AUTHOR]

This study examines the behavior of bank stock prices in Jordan in relation to a significant tax reform event. We analyze a sample of all banks listed on the Amman Stock Exchange to study the market response to the Amended Income Tax Law 2018. In the proposal period, investors were anticipating a mandatory tax increase of 5%, though the enacted law differed from expectations by implementing only a temporary, slight tax increase of 3%. Our findings reveal that there are higher stock returns observed during the post-approval period of the Amended Income Tax Law 2018 compared to the pre-approval period. This holds for both individual stocks and portfolios, indicating a positive market response to the tax reform. This paper contributes to the existing body of literature that examines pricing anomalies. The findings of this study indicate that when a tax bill is passed with a corporate tax rate lower than the proposed level, it creates a positive earnings surprise. However, the market displays inefficiency in promptly revising its expectations, resulting in a delay in the stock return pattern. This suggests that there is a discrepancy between the market's reaction as implied by the efficient market hypothesis and the actual impact of the tax reform on bank stock prices. IMPACT STATEMENT: This study investigates the impact of a significant tax reform event on the behavior of bank stock prices in Jordan. Using event study methodology, the research examines whether the market responds rationally to the earnings news related to the establishment of the National Solidarity Account, comprising 3% of banks' taxable income under the enacted Amended Income Tax Law 2018, compared to a higher increase of 5% of banks' taxable income proposed during the pre-approval period of the tax law. The findings suggest that tax laws influence financial markets and affect stock prices, as stock investors extrapolate their prior negative expectations into the future making it possible to trade based on this macroeconomic event. Investor sentiment, limited attention capacity, overconfidence, and anchoring bias could lead investors to react irrationally to actual statistics on the release date by taking prior forecasts at face value. The study has important implications for academics, practitioners and policymakers. [ABSTRACT FROM AUTHOR]

Differences in the behaviour of asset prices depending on data frequency have not been thoroughly investigated in the literature despite their possible importance. In particular, high-frequency data might contain more information about financial assets because they are updated more rapidly in response to news. This paper explores persistence in high-frequency data (and also daily and monthly ones) in the case of the EuroStoxx 50 futures prices over the period from 2002 to 2018 (720 million trade records) using R/S analysis and the Hurst exponent as a measure of persistence. The results show that persistence is sensitive to the data frequency. More specifically, monthly data are highly persistent, daily ones follow a random walk, and intraday ones are anti-persistent. In addition, persistence varies over time. These findings imply that the Efficient Market Hypothesis (EMH) only holds in the case of daily data, whilst it is possible to make abnormal profits using trading strategies based on reversal strategies at the intraday frequency. [ABSTRACT FROM AUTHOR]

This paper analyses the effects known as the day of the week and the month of the year in the cryptocurrency markets. The closing values of eleven cryptocurrencies have been considered. The study employs dummy variable regression techniques, ANOVA and Friedman tests for assessing two calendar anomalies, the day-of-week and month-of-year effects. To test these calendar effects, we have applied both full sample and rolling-regression techniques for two lengths of the rolling sample intervals. Furthermore, we have examined the existence of long memory in day-of-the- week and month-of-the-year cryptocurrency returns. The results provide evidence about the existence of day-of-the-week and month-of-the-year effects in cryptocurrency returns, in particular, on Thursdays and in November. In addition, it should be added that the general results of the current study show that the calendar effect in the cryptocurrency market is dynamic rather than static, which indicates that the calendar effect is a phenomenon that varies over time. [ABSTRACT FROM AUTHOR]

Despite the presence of arbitrage mechanisms, large premiums (or discounts) for Asia Pacific country ETFs in the US market could still exist in the short run due to the time gap between trading hours of the US and Asia Pacific markets. The price of a country ETF is not solely determined by net asset value but is also affected by information released during US trading hours. In this study, I examine six Asia Pacific country ETFs from 2006 to 2020, using linear regression as well as tree-based ensemble methods to predict the next-day return of the net asset value by analysing information from country ETFs and the S&P 500 Index. The results indicate that the trading hours of local markets significantly influence the predictive power of country ETFs and the S&P 500 Index. The findings suggest that the returns of these ETFs do not necessarily overreact to the US market but instead reflect short-term expectations of the performance of underlying indices. Furthermore, I extend the model to analyse overnight and daytime returns and identify the price correction that occurs during daytime trading hours. [ABSTRACT FROM AUTHOR]

This paper proposes a new investment strategy in the cryptocurrency market based on a two-step procedure. The first step is the computation of the asset's levels of efficiency in an universe of cryptocurrencies. Price returns efficiency degrees are measured by their corresponding levels of multifractality, obtained by the multifractal detrended fluctuation analysis method. The higher the multifractality, the higher the inefficiency in terms of the weak form of market efficiency. Cryptocurrencies are then ranked in terms of efficiency. The second step is the construction of portfolios under the Markowitz framework composed of the most/least efficient digital coins. Minimum variance, maximum Sharpe ratio, equally weighted and (in)efficient-based portfolios were considered. The former strategy is also proposed, where the weights are computed proportionally to the assets levels of (in)efficiency. The main findings are: cryptocurrency price returns are multifractal and their levels of (in)efficiency change over time; returns exhibit left-sided asymmetry, which implies that subsets of large fluctuations contribute substantially to the multifractal spectrum; in bull markets portfolios with the least efficiency assets provided a better risk--return relation; in periods of high volatility and high price depreciation (bear market) a better performance is associated with the portfolios composed by the more efficient cryptocurrencies. [ABSTRACT FROM AUTHOR]

This paper presents a bibliometric review of 2,391 publications on price discovery and hedging in financial assets and commodities. The discipline-wise contribution of publications and journal distribution based on the frequency of relevant research articles are reported. Five overarching themes have emerged from the content analysis, namely: (1) price discovery, (2) hedging in commodities, financial assets, and cryptocurrency, (3) market interconnectedness and volatility spillover, (4) market microstructure in pre- and post-financial crisis, and (5) asset allocation, diversification, and portfolio management. We propose three future research streams, namely predictability in uncertainty, short-term portfolio adjustment, and dynamic trading strategies, with nine research questions that can help investors and stock/commodity exchanges in an active portfolio and derivative contract management. [ABSTRACT FROM AUTHOR]

Decentralized finance, or 'De-Fi', is an emerging sector and movement in finance and the cryptocurrency space that aims to extend the idea of digital currencies to a global decentralized financial system. In many cases, customized 'coins' or 'tokens' are used for applications such as borrowing or lending, providing liquidity, and even voting. Built on the same foundations of traditional cryptocurrencies (e.g. Bitcoin), these tokens possess monetary value and can be traded using fiat currencies on specialized decentralized exchanges. We provide the first analysis investigating the market efficiency of the decentralized finance market through DeFi tokens. Our findings from applying the adaptive market hypothesis (AMH) revealed that the efficiency of the markets varies over time, with the majority of the DeFi token returns exhibit very short days of inefficiency and predictability in their price every year. This is consistent with the AMH, but perhaps unexpected when considering the link between emerging financial markets and market efficiency. We conclude that the majority of investors and practitioners purchase these DeFi tokens for their utility value rather than for investment purposes, hence making the DeFi market more efficient. Further robustness checks on other comparable products in the blockchain ecosystem such as NFTs also reveal similar results. [ABSTRACT FROM AUTHOR]

This paper adopts the fractal analysis approach, specifically a Hurst exponent index in portfolio optimization at the Damascus Securities Exchange (DSE). We construct three portfolios based on the Hurst index from stocks listed on the DSE during the period between 2019 and 2021 and find that these portfolios outperform the market portfolio in terms of returns, Sharpe ratio, Treynor ratio, and alpha. In addition, selecting stocks with high Hurst coefficients further enhances the performance of the portfolio. Importantly, even in out-of-sample tests, the three fractal portfolios continue to outperform the market portfolio. Furthermore, we find that fractal portfolios outperform portfolios formed using the momentum and size strategies demonstrating the superiority of the fractal analysis approach. We conclude that the incorporation of fractal analysis into the portfolio optimization problem allows the creation of a more efficient portfolio. Hence, we recommend that investors consider the Hurst exponent index in their portfolio optimization for better investment decisions. [ABSTRACT FROM AUTHOR]

We determine the amount of information contained in a time series of price returns at a given time scale, by using a widespread tool of the information theory, namely the Shannon entropy, applied to a symbolic representation of this time series. By deriving the exact and the asymptotic distribution of this market information indicator in the case where the efficient market hypothesis holds, we develop a statistical test of market efficiency. We apply it to a real dataset of stock indices, single stocks, and cryptocurrencies, for which we are able to determine at each date whether the efficient market hypothesis is to be rejected, with respect to a given confidence level. [ABSTRACT FROM AUTHOR]

After the crackdown in 2015, Chinese state-owned capital, also called the 'national team' by investors, has become extensively involved in stock market investments. As a form of government direct intervention, state capital in the stock market may have implications for market efficiency and evolution. This study investigates the unbalanced departure of the national team in the aftermath of the crisis: the government no longer directly holds a large number of listed companies' stocks, but its share in the market has declined little. Using a panel regression covering most stock industries, we find a positive association between national team and industry concentration in the stock market. Often, state-funded holdings may inhibit competition and allow the market to evolve in a more concentrated structure. Our study reveals a new potential negative externality of the Chinese government's direct intervention in the stock market. [ABSTRACT FROM AUTHOR]

The recent establishment and popularity of professional esports leagues, coupled with the public listing of the Denmark-based esports team Astralis Group, presents an opportunity to assess whether wins and losses impact a team's stock price in nontraditional sports. We provide empirical evidence that wins in championship matches impact stock returns for Astralis in a regression-based event study. This suggests that investors perceive championship wins as an indicator of future earnings growth of the group. [ABSTRACT FROM AUTHOR]

In this study, we investigate the nature of the accruals anomaly by analyzing the speed of price adjustment to accruals information. Consistent with the mispricing hypothesis, we find that a relatively larger proportion of accruals premium is distributed near the filing dates among low limits-to-arbitrage stocks and during periods of increased arbitrage activity. We also discuss our findings in the context of q-theory. [ABSTRACT FROM AUTHOR]

This paper examines the holiday effect on the Swedish stock market over a 40-year period. We use a regression-based approach on daily price data to ascertain if the holiday effect is present on the Swedish stock market, analyse its historical development using 10-year subsamples, and assess whether its effects vary for different holidays. We find evidence for a positive post-holiday effect using the full sample period. When looking at the subsamples, however, we only find evidence for its existence in the 1990s and 2000s. We do not find evidence for the existence of a pre-holiday effect for any period. No holiday, considered by itself, shows evidence of a pre-holiday effect over the full sample period. For the holidays included, we only find evidence of a post-holiday effect after New Year's. [ABSTRACT FROM AUTHOR]

This study sets out to explore the predictability of global foreign exchange rates vis-à-vis the South African rand using daily nominal exchange rates from January 2010 to February 2018. The estimation techniques include automatic portmanteau test, wild bootstrap variance ratio test, Dominguez–Lobato test for martingale difference hypothesis, and generalized spectral tests. We investigate the time-varying predictability by employing the fixed-length rolling window approach. The full sample results indicate significant predictability of some exchange rates while some suggest no predictability. The rolling window approach established that all the foreign exchange markets go through episodes of significant predictability and episodes of unpredictability. The currency investment space is dynamic and that makes it imperative for market participants to be adaptable. [ABSTRACT FROM AUTHOR]

This study examines how globalization affects stock market quality, whether investor protection serves as a channel in this relationship, and how the channel effect varies depending on the legal system. Our empirical analysis confirms that there is a positive causal relationship between globalization and market quality. Also, since we find that globalization induces stronger investor protection, we disentangle the component of investor protection predicted by globalization. Our analysis shows that the globalization-induced component of investor protection has a significantly positive effect on market quality, which demonstrates the role of investor protection as a channel. Finally, we show that these relationships among globalization, investor protection, and market quality are present in civil law countries but not in common law countries. This illustrates that globalization enhances financial market quality via a stronger ability to effect institutional change and investor protection in civil law countries. [ABSTRACT FROM AUTHOR]

We carry out an in-depth analysis of patterns in stock market returns in seven Latin American countries to identify the presence and persistence of the "sell in May and go away" strategy. We use a predictive ability test to consider data snooping problems and the statistical interference of rules based only on historical asset prices. In line with the efficient market hypothesis, our results show that a trading strategy based on the Halloween effect never offered a significantly superior investment strategy than a "buy and hold" benchmark strategy in Latin American countries. [ABSTRACT FROM AUTHOR]

The 2016 introduction of a Real Estate sector to the Global Industry Classification Standard (GICS) provides a natural experiment for studying how industry classification systems impact firms. This study uncovers significant abnormal returns of 2.31% and 2.49% for real estate investment trusts (REITs) around two distinct announcements of the classification restructuring. This supports the theory of decreasing asymmetric information occurring with the increase in sector transparency. Cross-sectional regressions show higher abnormal returns for REITs of medium cap size, with lower leverage, and with more institutional ownership (IO). The study also tests for changes in IO levels after the event using 13-F filings. A difference-in-difference estimation reveals a lower count of owners and percent of shares held by IOs in the postreclassification period compared to a matched sample of peer firms. Evidence emerges that refutes the common industry refrain of a rise in REIT IO following the classification restructuring. [ABSTRACT FROM AUTHOR]

We study the size-power tradeoff of commonly employed tests of return predictability. For short horizon tests, we show analytically that the indirect dividend test is asymptotically more powerful than the direct return test when dividend growth is less volatile than returns, as appears to be true in the data. The asymptotic power advantages of the dividend test carry over to small samples. Asymptotically, the relative power of the short vs long-horizon return test may depend on size. For empirically relevant parameter values the short-horizon return test is asymptotically more powerful than the long-horizon test at the 1% level but the reverse is true at the 5% and 10% levels. Monte Carlo analysis indicates that, in small samples, the long-horizon return test is more powerful than the short-horizon return test for all sizes. The differences in the relative power of the tests in the small sample case is traced back to the correlation structure of the underlying shocks. [ABSTRACT FROM AUTHOR]

This research tests the Adaptive Market Hypothesis (AMH) regarding calendar anomalies in the Baltic stock markets. Analysis of known calendar anomalies over time is carried out by using sub-sample GARCH (1,1) regression with Kruskal–Wallis statistics and rolling windows. Three calendar anomalies were confirmed in these markets: Friday, MoY (July and January), and ToM (turn-of-the-month). The Baltic stock markets demonstrated behavior supporting the AMH. It was found that the opportunity to earn abnormal returns on investment strategies based on Friday, July, and ToM effects disappeared during the financial crisis of 2007–9. The Friday and the ToM effects follow a more time-varying pattern, while the July effect is less so. [ABSTRACT FROM AUTHOR]

This study investigates the reaction of stock returns to inflation announcements during the inflation switching regime from 2012 to 2018. In this paper, we have compared the broader market index NIFTY 500 vs. narrower market index NIFTY 50, and closing price vs. opening price. The study also checks if the state of the economy influences the stock market reaction. The finding of the study suggests that there are considerable abnormal returns. From a market efficiency perspective, we observe markets have become more efficient post the IT regime for both the stock market indices and also for both sets of prices. [ABSTRACT FROM AUTHOR]

Most studies in the Bitcoin literature are focused on daily data without considering other options. Therefore, it is necessary to analyse Bitcoin features at different frequencies. In this letter, we examine Bitcoin efficiency from 1 min to weekly data using the generalized Hurst exponent. Our results show that Bitcoin is more efficient over time regardless of the frequency. In particular, we observe that, since 2016, daily data are generally the most efficient frequency while 1 min and weekly data are the most inefficient. These results are relevant for investors and scholars since we detect the most profitable frequencies and underline the relevance of analysing different frequencies than daily data. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has raised great attention to the study of its impacts on Bitcoin. We focus on the impacts of the COVID-19 pandemic on the long memory and efficiency of Bitcoin. There exist a few studies on this topic. These studies all ignore the issues of heavy tails and extreme events during COVID-19, which are obstacles to obtaining the reliable continuous time-varying results of long memory and efficiency. After considering the two issues, we first obtain the reliable continuous time-varying results during COVID-19 via sliding window and estimation of Hurst exponent. The other four markets (Ethereum, Binance Coin, S&P 500, and gold spot) are also analysed for comparison. Bitcoin results show that the Bitcoin market keeps efficient during the pandemic and the heavy tails become weaker after the onset of the pandemic. Results of the comparison study show that Bitcoin has similar efficiency with spot gold and is more efficient than Ethereum, Binance Coin, and S&P 500 during the pandemic. This study contributes to current rare literature on the long memory and efficiency of cryptocurrency during COVID-19. [ABSTRACT FROM AUTHOR]

Stock market efficiency has been one of the most investigated topics of the last century. Knowing the efficiency of a market has major implications for both investors and policymakers, as a perfectly efficient market eliminates any arbitrage opportunity and the possibility of actually beating the market. For this reason, this study aims to examine the weak-form market efficiency of the European energy markets using linear and nonlinear unit root tests for the period covering February 2012 to April 2021. The results indicated that while the Augmented Dickey–Fuller test captured the stationarity in only Austria's Oil, and Gas index, using nonlinear tests showed stationarity in 17 of the 20 indices tested. Overall, the European Energy Market can be considered inefficient under the weak form of the Efficient Market Hypothesis. Therefore, there is an indication of profitable arbitrage opportunities among energy stocks. Signs of stationarity also suggest that shocks to energy stocks will have temporary effects. Energy markets of Austria, Finland, France, Greece, Italy, Netherlands, Russia, Spain, Sweden, and the United Kingdom, for this reason, could benefit from policy changes to support increased information flow to achieve more transparency and utilize better trading technologies. [ABSTRACT FROM AUTHOR]

Corporate restructuring is a widely adopted mode of improving efficiency and firm performance and has been studied in different country contexts such as the US, Australia, and Europe. The aim of this paper is to examine the impact of spin-off announcements on the stock prices of parent firms in the Indian context. In addition, we also investigate the price effect anomaly through two subsamples of high-price scripts and low-price scripts. The study is conducted on a sample of 221 Indian firms listed in BSE (Bombay Stock Exchange) from 2003 to 2020 which have announced the spin-offs. We employ event study methodology and find that spin-offs have a significantly positive impact on the stock prices of the parent firm. We observe the highest abnormal return of 1.35% on +1 day post the event. The interval-wise analysis gives the highest CAAR of 2.64% in (+1, +5) interval. The analysis of the price behavior of stocks at different price levels suggests that the low-price script outperformed the high-price script in each event window with a CAAR of 3.90% in high-price script and 7.16% in low-price script for the event window from −10 to +10. [ABSTRACT FROM AUTHOR]

This paper provides insights about the information content and predictive ability of the intrinsic value of the firm in an asset pricing context. The intrinsic value of a firm is of great importance for both the management and the investors of the company. We seek to assess whether the value-to-price (V/P) ratio, estimated with the residual income model (RIM), can explain the cross section of stocks returns. The study enhances the literature in the area of asset pricing by developing a new intrinsic value risk factor, which is a zero-investment portfolio that is neutral to the size, book-to-market equity ratio and the momentum effect. Furthermore, we incorporate in the RIM, for the first time, a time-series model that does not rely on analysts' forecasts for the estimation of the key parameters of the model. A unique dataset from Greece, Italy, Spain and Portugal is utilized, from 31/12/2000 to 30/6/2019, that has a number of idiosyncrasies that are not observable in other developed markets, contributing by this way to the necessary accumulation of non-US research. The results show that the new intrinsic value risk factor absorbs the information content of the HML factor and explains better the cross section of returns, mainly for small size and high book to market value companies. [ABSTRACT FROM AUTHOR]

Information technology (IT) is central to the process execution and management of an ongoing relationship in outsourcing, both of which are fraught with challenges, and often lead to poor business outcomes. Thus, it is important for IT groups in organizations to understand how to deal with such difficulties for improved outsourcing performance. We study whether firms learn over time to deal with these two related but distinct issues in IT and business process outsourcing. Does such learning affect financial value appropriation through outsourcing? We build on the literature in information systems and strategy to investigate whether value creation in outsourcing depends on relational learning that results from prior association with the vendor, and procedural learning that results from prior experience in managing interfirm relationships. We estimate value in terms of long-term abnormal stock returns to the client relative to an industry, size, and book-to-market matched sample of control firms following the implementation of the outsourcing contract. We also analyze announcement period returns and allied wealth effects. Using data from the hundred largest outsourcing deals between 1996 and 2005, we find that whereas relational learning influences value creation in both simple and complex outsourcing engagements, procedural learning impacts value only in complex initiatives. Financial markets are slow to price the value of learning. The results suggest that caution should be exercised when firms without the experience of managing interfirm relationships externalize complex tasks to vendors they have not worked with in the past. Furthermore, IT groups can help improve learning-based outcomes by developing processes and systems that enable a firm to improve outsourcing procedures in a cumulative manner and also to coordinate and collaborate with the vendor. [ABSTRACT FROM PUBLISHER]

This paper evaluates the efficiency of betting market pricing for top league soccer matches played behind closed doors during the COVID-19 pandemic. The removal of the crowd component of home advantage results in substantial improvement in both the market predictions of goal difference and home team wins. [ABSTRACT FROM AUTHOR]

This paper tests for the ability of a variety of technical indicators to generate excess returns at the individual stock level in the seven emerging and frontier markets of the Gulf region. While technical indicators show some early profitability promise, after controlling for the data snooping bias using the False Discovery Rate (FDR) methodology and non-synchronous trading, we fail to find any predictive ability or profitability for technical analysis. We arrive at a similar finding when assessing the risk-adjusted performance of a portfolio composed of stocks chosen based on technical indicators. The findings go to show the failure of technical analysis on the stock level. The findings are also evidence of the Gulf region markets being at least weak-form efficient and carry implications for investors choice of investment tools. [ABSTRACT FROM AUTHOR]

This study is aimed at testing the relationship between investors' uncertainty reflected by market sentiment and herding behavior phenomenon. Using data for 1990–2019 for size-ranked portfolios, the evidence documented here indicates that herding is strongly related to market sentiment as captured by the CBOE's Volatility Index, the VIX. The results indicate that the VIX, which is also recognized as the fear index, has a substantial impact on herding across all groups and subgroups of size-ranked portfolios. Overall, the effect of VIX exists in most of the quantiles of the cross-sectional absolute deviation distribution. In this context, the scale and magnitude of the fear index impact rises toward the highest parts of the herding distribution. We also show that herding behavior is more pronounced when the market is overwhelmed by sentiment. The findings have several practical implications for investment professionals such as portfolio managers, investment officers, analysts, and other market participants. They also provide academic insights for researchers dealing with market efficiency and investors' behavior. [ABSTRACT FROM AUTHOR]

Economists have debated whether market reactions to news depart from the predictions of the efficient market hypothesis (EMH). This article uses the sentiment index and the surprise index from the Thomson Reuters MarketPsych Indices and an ARCH model to investigate the reactions of the return of the Nikkei 225 closing price to different types of news between January 5, 1998 and December 29, 2017, and whether those responses are consistent with the predictions of the EMH. Three sub-periods during the full sample are identified, and the market reactions to the news are then examined and compared among the sub-periods. [ABSTRACT FROM AUTHOR]

Analysing a set of 200 cryptocurrencies over the period from 2015 to 2019, we document a significant return reversal effect that holds at the daily, weekly, and monthly rebalancing frequencies and is robust to controls for differences in size, turnover, and illiquidity. Moreover, the reversal effect persists during both halves of our sample period and following periods of both high and low market implied volatility. Consistent with the effect being driven by a combination of market inefficiency and compensation for liquidity provision, we find reversals are most pronounced among smaller capitalization and less liquid cryptocurrencies. [ABSTRACT FROM AUTHOR]

This study investigates herding behaviour of investors in Thailand under different market conditions, crisis periods, and major market structural changes. The results show that herding behaviour occurs during an extreme market movement of negative or positive returns, in the declining market environment, on days with high trading volume, and during economic downturn as measured by negative GDP output gap. The structural break point analysis and rolling regression technique further shows that herding behaviour gathered heavily around 1997 Asian crisis. The establishments of internet trading platform, bond electronic trading exchange, and future electronic exchanges in Thailand do not make investors herd. [ABSTRACT FROM AUTHOR]

This study examines the dynamics of ten most notable stock market anomalies through 1926–2018 and assesses the joint impact of academic attention, post-publication decay, data-snooping bias, institutional trading, and time trend on their disappearance. It proposes new and simple measures of academic attention attracted by stock market anomalies using the number of articles published on the relevant topic available via Google Scholar or respective citation counts. The study finds that academic attention is the most dominant factor explaining the diminishing abnormal returns of anomaly-exploiting strategies. The approach developed by this study can also be useful in determining whether a stock return regularity is a behavioural anomaly or a systematic risk factor. [ABSTRACT FROM AUTHOR]

In this paper we adopt some ideas from Quantum mechanics, and particularly the well-known Schrödinger's cat (1935) thought experiment in order to present some new views on the big question whether the markets are efficient or not. There are two main conflicting approaches in financial economics: the behavioral approach and the Efficient Market Hypothesis (EMH). The behavioral approach usually uses psychological theories in order to explain what the Efficient Market Hypothesis (EMH) cannot. However, behavioral finance does not have a specific model to suggest, and this is one major counterargument put forth by EMH supporters. Using the well-known CUBA fund case as an example, we show that EMH seems to be in superposition (simultaneously correct and incorrect), but suddenly collapses into one configuration. These dominant economics approaches are supplementary, so it is better for scholars that support either the EMH or behavioral finance to incorporate their ideas into one model, than to continue debating the accuracy of the EMH. The Quantum approach enables us to distinguish the unexpectable from the irrational. Adopting the quantum way of thinking we can build more accurate models and work toward the goal that most scholars pursue: to understand how the world works. [ABSTRACT FROM AUTHOR]

We obtained a unique dataset that covers all trade-based manipulation events identified by the Capital Market Board (CMB) for the period between 2005 and 2013 in order to investigate stock market manipulation and its implications on market quality. Moreover, we examine how manipulators decide which stocks to select for manipulation in an emerging market. We observe that the manipulators select illiquid, underperforming, and less volatile stocks to manipulate in an emerging market. We also demonstrate that stock liquidity, return, and volatility increase throughout the manipulation period and decrease in the post-manipulation period, leading to a deterioration of market quality. [ABSTRACT FROM AUTHOR]