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I develop a model revealing the interplay between a stock's liquidity and the policies and value of the issuing firm. The model shows that bid-ask spreads increase not only the firm's cost of capital but also the opportunity cost of cash, then lowering cash reserves, increasing liquidation risk, and reducing firm value. These outcomes are stronger when internalized by liquidity providers, simultaneously leading to a wider bid-ask spread. A two-way relation between the firm and the liquidity of its stock arises, implying that shocks arising within the firm or in the stock market have more complex implications than previously understood. [ABSTRACT FROM AUTHOR]

This article studies the relationship between credit provision and stock trading behavior. We collect every stock transaction of the three major British companies during the 1720 South Sea Bubble and link stock trading to margin loan positions with the Bank of England. We give insights in the selection of traders into the loan facility by comparing the trading behavior and realized returns of borrowers to other traders. We find that loan holders are more likely to buy following high returns and document strong underperformance of borrowers. [ABSTRACT FROM AUTHOR]

Our paper reexamines whether 29 variables from 26 papers published after Goyal and Welch 2008 , as well as the original 17 variables, were useful in predicting the equity premium in-sample and out-of-sample as of the end of 2021. Our samples include the original periods in which these variables were identified, but end later. More than one-third of these new variables no longer have empirical significance even in-sample. Of those that do, half have poor out-of-sample performance. A small number of variables still perform reasonably well both in-sample and out-of-sample. [ABSTRACT FROM AUTHOR]

Retail order imbalance positively predicts returns, but on average retail investor trades lose money. Why? Order imbalance tests equal-weighted stocks, but retail purchases concentrate on attention-grabbing stocks that subsequently underperform. Long–short strategies based on extreme quintiles of retail order imbalance earn dismal annualized returns of −14.8% among stocks with heavy retail trading but earn 6.6% among other stocks. Our results reconcile the literatures on the performance of retail investors, the predictive content of retail order imbalance, and attention-induced trading and returns. Smaller retail trades concentrate more on attention-grabbing stocks and perform worse. [ABSTRACT FROM AUTHOR]

Copyright of Contemporary Accounting Research is the property of Canadian Academic Accounting Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article introduces a new holding horizon measure of active management and examines its relation to future risk-adjusted fund performance (alpha). Our measure reveals a wide cross-sectional dispersion in mutual fund investment horizons, and shows that long-horizon funds exhibit positive future long-term alphas by holding stocks with superior long-term fundamentals. Further, stocks largely held by long-horizon funds outperform stocks largely held by short-horizon funds by more than $ 3\% $ annually, adjusted for risk, over the following 5-year period. We also find a clientele effect: to reduce liquidity costs, long-horizon funds attract more long-term investors through share classes that carry load fees. [ABSTRACT FROM AUTHOR]

Collecting large asset managers' capital market assumptions, we revisit the relationships between subjective equity premium expectations, equity valuations, and financial portfolios. In contrast to the well-documented extrapolative expectations of retail investors, asset managers' equity premium expectations are countercyclical: they are high (low) when valuations are low (high). We find that asset managers' portfolios reflect their heterogeneous expectations: allocation funds of asset managers with larger U.S. equity premium expectations invest significantly more in U.S. equities. The sensitivity of portfolios to expectations seems to be muted by investment mandates and is smaller than the one predicted by a standard portfolio choice model. [ABSTRACT FROM AUTHOR]

Sophisticated investors frequently choose to publicly disclose private information, a phenomenon inconsistent with most theories of speculation. We propose and test a model to bridge this gap. We show that when a speculator cares about both short-term portfolio value and long-term profit, a disclosure mixing asset fundamentals and her holdings is optimal by inducing competitive dealership to revise prices toward those holdings while alleviating adverse selection. We find that when mutual fund managers have stronger short-term incentives, the frequency of strategic non-anonymous disclosures about their stocks by market-worthy newspaper articles increases and those stocks' liquidity improves, consistent with our model. [ABSTRACT FROM AUTHOR]

Using the exclusion of business development companies (BDCs) from stock indexes, this paper studies the effectiveness of market discipline in the direct lending space. Amid share sell-offs by institutional investors, a drop in BDCs' valuations limits their ability to raise new equity capital. Following this funding shock, BDCs do not adjust their capital structure. At the same time, they are reducing the risk exposure of their portfolios. We document a greater reduction in risk for BDCs subject to stronger market discipline from their debtholders. BDCs pass through the capital shock to their portfolio firms by reducing their investment intensity. [ABSTRACT FROM AUTHOR]

We propose a loglinear present-value identity in which investment ("scale"), profitability ("yield"), and discount rates determine a firm's market-to-book ratio. Our identity reconciles existing influential market-to-book decompositions and facilitates novel insights from three empirical applications: (1) Both investment and profitability are important contributors to the value spread and stock return news variance. (2) Any cross-sectional return predictability has a mirror image in cash-flow fundamentals, providing asset pricing theories with additional moments to match. (3) The investment spread significantly improves the predictability of time-series variation in the value premium and justifies the poor performance of value in recent years. [ABSTRACT FROM AUTHOR]

Momentum profits depend mainly on the short leg and therefore on barriers to short sales. Our research indicates that the decline in momentum profitability in the past 2 decades is driven partly by a contemporaneous growth in stock options trading. Stock options offer an alternative to short selling, augmenting the stock lending market, and thereby contributing to improved pricing efficiency. The resulting reduction in barriers to short sales contributes to lower returns to momentum trading from the short leg. Our results persist after matching stocks with and without options based on different firm-level characteristics. [ABSTRACT FROM AUTHOR]

We develop a dynamic model of costly stock short-selling and lending market and obtain implications that simultaneously support many empirical regularities related to short-selling. In our model, investors' belief disagreement leads to shorting demand, whereby short-sellers pay shorting fees to borrow stocks from lenders. Our main novel results are as follows. Short interest is positively related to shorting fee and predicts stock returns negatively. Higher short-selling risk can be associated with lower stock returns and less short-selling activity. Stock volatility is increased under costly short-selling. An application to GameStop episode yields implications consistent with observed patterns. [ABSTRACT FROM AUTHOR]

Restricted stock units (RSUs) are a type of equity compensation that many companies offer to attract top talent and to incentivize their executives to remain employed. RSUs generally have the potential of resulting in the transfer of substantial value to the executive, without a lot of complexity associated with that outcome. To make the most of an executive's RSUs, the financial service professional should make sure that the executive understands how much value they have and should devise a plan for addressing the taxation and cash flow needs following the vesting of the RSUs. [ABSTRACT FROM AUTHOR]

This article investigates the impact of heterogeneous foreign investment on home market stock price informativeness. Evidence from China's nascent A-share market shows non-segmented foreign investment reduces firms' stock return synchronicity, while segmented foreign investment does not. Using the Shanghai (Shenzhen)–Hong Kong Stock Connect program as a natural experiment that exogenously increases non-segmented foreign ownership, we find that synchronicity drops significantly for program stocks relative to the control stocks. Our results are most consistent with an "informed trading" explanation, rather than a "learning" or "governance" explanation. These results have policy implications for stock market liberalization programs. [ABSTRACT FROM AUTHOR]

This paper introduces novel mathematical optimisation models for the 2-Dimensional guillotine Cutting Stock Problem with Variable-Sized Stock that appears in a Spanish company in the honeycomb cardboard industry. This problem mainly differs from the classical cutting stock problems in the stock, which is considered variable-sized, i.e. we have to decide the panel dimensions, width, and length. This approach is helpful in industries where the stock is produced simultaneously with the cutting process. The stock is then cut into smaller rectangular pieces that must meet the customers' requirements, such as the type of item, dimensions, demands, and technical specifications. Furthermore, in the problem tackled in this paper, the cuts are guillotine, performed side to side. The proposed mathematical models are validated using real data from the company, obtaining results that drastically reduce the produced material and leftovers, reducing operation times and economic costs. [ABSTRACT FROM AUTHOR]

Copyright of Contemporary Accounting Research is the property of Canadian Academic Accounting Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Contemporary Accounting Research is the property of Canadian Academic Accounting Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study selects the quarterly data of all equity and equity-oriented hybrid open-end funds in China from 2007 to 2022 as the research sample, and examines the impact of fund style drift on fund returns through a two-ways fixed effect model. Our results show that overall style drift tends to improve fund performance. However, after differentiating the type of style drift, we find that fund drift based on stock picking abilities enhanced performance, whereas fund drift based on chasing market trends reduced fund performance. This study presents a new measurement method based on industry allocation, providing an empirical foundation for research on industry-specific theme funds. It also offers fund managers insights for optimizing performance evaluation and incentive systems, while serving as a reference for regulators to develop flexible, effective policies for market stability. [ABSTRACT FROM AUTHOR]

Herding behavior has become a familiar phenomenon to investors, with potential dangers of both undervaluing and overvaluing assets, while also threatening market stability. This study contributes to the literature on herding behavior by using a recent dataset, covering the most impactful events of recent years. To our knowledge, this is the first study examining herding behavior across three different types of investment vehicle and also the first study observing herding at a community (subset) level. Specifically, we first explore this phenomenon in each separate type of investment vehicle, namely stocks, US ETFs and cryptocurrencies, using the Cross-Sectional Absolute Deviation model. We find mostly similar herding patterns for stocks and US ETFs. Subsequently, the same experiment is implemented on a combination of all three investment vehicles. For a deeper investigation, we adopt graph-based techniques including the Minimum Spanning Tree and Louvain community detection to partition the combination into smaller subsets to detect herding behavior for each subset. We find that herding behavior exists at all times across all types of investment vehicle at a subset level, although perhaps not at the superset level, and that this herding behavior tends to stem from specific events that solely impact that subset of assets. Lastly, we explore herding by examining the financial contagion effects between these types of investment vehicle. Results show that US ETFs not only have a tendency to propagate similar trading behaviors in stocks and especially cryptocurrencies but also show self-reinforcing herding behavior, acting as drivers of their own trends. [ABSTRACT FROM AUTHOR]

Our study is based on the hypothesis that stock exchanges, being nonlinear, open and dissipative systems, are capable of self-organization to the edge of a phase transition. To empirically support the hypothesis, we find segments in hourly stock volume series for 3,000 stocks of publicly traded companies, corresponding to the time of stock exchange's stay to the edge of a phase transition. We provide a theoretical justification of the hypothesis and present a phenomenological model of stock exchange self-organization to the edge of the first-order phase transition and to the edge of the second-order phase transition. In the model, the controlling parameter is entropy as a measure of uncertainty of information about a share of a public company, guided by which stock exchange players make a decision to buy/sell it. The order parameter is determined by the number of buy/sell transactions by stock exchange players of a public company's shares, i.e., stock's volume. By applying statistical tests and the AUC metric, we found the most effective early warning measures from the set of investigated critical deceleration measures, multifractal measures and reconstructed phase space measures. The practical significance of our study is determined by the possibility of early warning of self-organization of stock exchanges to the edge of a phase transition and can be extended with high frequency data in the future research. [ABSTRACT FROM AUTHOR]

The impact of U.S. monetary policy (USMP) on domestic interest rates and goods markets in Emerging Market Economies (EMEs) remains a subject of ongoing debate. We investigate the fluctuations in U.S. interest rates across 17 inflation-targeting EMEs with flexible exchange rates from 2000–2020. Our findings reveal asymmetric contagion effects, with U.S. interest rate decrease having a more significant short-term impact than rate hikes. Long-term U.S. rates minimally influence EMEs' domestic rates. Resilience is observed in EMEs with robust GDP growth and favorable trade balances, while increased capital inflows and stock market surges heighten contagion risks. Focusing on the short-term contagion effect on goods markets through international trade drivers, we find that global capital flows and US dollar fluctuations, combined with a rise in the FED rate, contribute to the deterioration of EMEs' trade balance. The study underscores the need for EMEs to monitor and respond to U.S. monetary policy changes for financial stability and advocates for enhanced international dialogue among policymakers. [ABSTRACT FROM AUTHOR]

In reliability analysis, the residual life of a component or system plays a key role in explaining a component's present condition as well as how long it will continue to function as intended under specific circumstances, thereby preventing premature failure and saving money. Based on this, Nair and Rajesh [Geometric vitality function and its applications to reliability. IAPQR Trans. 2000;25(1):1–8] proposed a new measure called the geometric vitality function that explains the system's failure pattern. In the present study, we have introduced the geometric vitality function in the context of order statistics by means of the relevation transform and also analysed the monotone and ordering properties of the proposed measure. The application of the proposed measure in the stock markets are explored in the present study. Finally, to estimate the proposed measure using a real life data set, a simple estimator has been introduced as well. [ABSTRACT FROM AUTHOR]

This study advances the understanding of cleantech commercialisation by adopting a market validation approach to analyse equity capital's role in navigating the 'Valley of Death'. Focusing on the three core financial milestones – revenue generation, profitability and retained earnings – we investigate 354 UK cleantech firms over 10 years and employ Cox proportional hazard models to explore whether equity capital speeds or slows the achievement of these three financial milestones. We conclude that equity capital-backed firms are slower across the Valley of Death. We discuss the implications of our findings for cleantech firms and those seeking to support the financing of cleantechs. [ABSTRACT FROM AUTHOR]

Considering the frequency domain and nonlinear characteristics of financial risks, we propose a VMD-Vine copula-CoVaR framework to study the dependence structures and risk spillovers among international financial markets at different time scales. Furthermore, a mean-variance optimization technique has been applied to evaluate the performance of the optimal cross-market portfolios. The empirical results show that: (1) The R-Vine copula is superior to the C- and D-Vines; (2) Compared with the Asian stock markets, the European stock markets are more correlated with each other. The correlations between the markets at the long-term scale are greater than those at the short- and medium-term ones; (3) The optimal pair copulas are combined with the CoVaR to estimate the systemic spillover risks among the markets. The downside and upside spillover risks across the markets are not always symmetric. Moreover, the ΔCoVaRs at the medium-term scale are the highest and the lowest at the short-term one; and (4) The optimal cross-market portfolio constructed by our framework perform better than the benchmarks by annualized return, Sharpe ratio, and maximal drawdown. The findings have direct implications for portfolio managers and investors to prevent extreme risks and take better international investment decisions based on the knowledge of optimum portfolio. [ABSTRACT FROM AUTHOR]

Choosing the appropriate method to identify turning points is critical for investors and policymakers. We propose a novel hybrid model combining dual long memory with structural breaks in the mean to identify the turning points of the stock market in China and the United States. The results show that models accounting for long memory and structural break perform well in the turning point detection. Notably, the proposed hybrid model generates superior in-sample turning point matching and out-sample forecasts for SSECI over those obtained from the competing ARFIMA models. In contrast, DJIA is better explained by the dual memory model with structural breaks in volatility. Finally, our analysis extends to encompass FTSE, HSI, IBOVESPA, and SENSEX30. The results demonstrate the superior performance of the hybrid model in markets exhibiting fractal characteristics. Such heterogeneity indicates differences in investor risk preference across stock markets and offers elaborate international evidence to the adaptive market hypothesis. [ABSTRACT FROM AUTHOR]

This paper proposes a theoretical model based on traditional ICAPM and dividend growth models but with variance-belief formation features such as overextrapolation and sticky expectation to link the macroeconomic uncertainty (MU hereafter) and stock excess returns. We predict a nuanced, possibly negative, intertemporal MU-return trade-off and a negative contemporaneous relationship between the change in MU and excess returns. The empirical analysis utilizing panel data from 46 stock markets validates our model but also reveals the heterogeneity across markets with different economic levels, financial development, and national culture. The impact of MU is amplified during global and country-specific financial crises. In addition, we also suggest that MU indeed is a significant source of realized variance of excess returns in stock markets. [ABSTRACT FROM AUTHOR]

This study empirically examines the impact of noncontrolling large shareholders (NCLSs) on short‐term debt for long‐term investment (SDFLI) using a sample of Chinese A‐share firms listed on the Shanghai and Shenzhen Stock Exchanges from 2005 to 2021. The findings suggest that NCLSs reduce the level of SDFLI; however, asset collateralizability mitigates the negative relationship between NCLSs and SDFLI. Conversely, stock liquidity reinforces the governance effect of NCLSs in mitigating SDFLI. The mechanism analysis suggests that improving agency efficiency is an important channel through which NCLSs influence SDFLI. This study deepens the understanding of the factors driving the SDFLI of listed Chinese firms and provides insights into how to mitigate this problem. Additionally, it provides empirical support for the governance role NCLSs play in listed firms. [ABSTRACT FROM AUTHOR]

This paper studies the effect of board reforms on stock liquidity using data from 37 countries. We document that board reforms significantly increase stock liquidity: the effective spread on average decreases by 12.7% after a board reform. As information asymmetry is a key determinant of stock liquidity, we further find that board reforms decrease information asymmetry, and the treatment effect of board reforms on stock liquidity is stronger for firms with ex ante higher information asymmetry. Finally, board reforms facilitate healthy stock market development, with the effect being stronger for countries with lower aggregate stock market liquidity prior to reforms. (JEL G14, G15, G18) [ABSTRACT FROM AUTHOR]

This paper examines the inflation-hedging capability of listed real estate (LRE) companies in the US from 1975 to 2023, and in three other economies—the UK, Japan, and Australia—from 1990 to 2023. By using a Markov switching vector error correction model (MS-VECM), we identify that the short-term hedging ability moves towards being negative or zero during turbulent periods. In stable periods, LRE provides good protection against inflation. In the long term, LRE offers a good hedge against expected inflation and shows a superior inflation hedging ability than stocks. Additionally, we identify inflation-hedging portfolios by minimizing the expected shortfall. This inflation-hedging portfolio allocation methodology suggests that listed real estate stocks should play a significant role in investor portfolios. [ABSTRACT FROM AUTHOR]

China's stock market has many stock indexes that provide performance benchmarks of listed companies. Employing the staggered difference-in-differences (DID) method, this study examines the effect of inclusions in stock index on firm operation and performance. We confirm that inclusions in the CSI 500 significantly decrease firm performance and the results are robust across several tests. We provide direct evidence of a channel through which inclusion affects firm performance; specifically, we find that stock price informativeness experiences a significant decrease after inclusion in an index. Further, we find that the effect of stock index inclusions is also significant for firms in developed markets. Overall, these results shed light on the effect of stock index inclusions on a firm's real operation. [ABSTRACT FROM AUTHOR]

In this study, we extend the existing literature around dividend signaling theory and calendar anomalies by addressing the question of whether calendar anomalies, including Halloween, Turn-of-the-Month (TOM), January, Monday, and Friday effects, have any influence on the relationship between stock returns and dividend announcements. Previous studies have primarily focused on demonstrating the impact of calendar anomalies on overall stock market returns. Our main aim is to investigate whether the Cumulative Abnormal Returns (CARs) associated with dividend announcements made by firms listed in the FTSE 350 index exhibit deviations from the norm due to these calendar anomalies. Our findings reveal a notable asymmetry in the reactions to dividend increase and decrease announcements. Specifically, the timing of dividend increase announcements appears to have no significant effect on their associated CARs. However, dividend decrease announcements made during periods characterized by seasonality exhibit CARs that differ significantly from those observed during normal times. Importantly, these findings remain robust across various alternative economic model specifications, including interaction models, binary models, and GMM estimations. Consequently, our results suggest that calendar anomalies, such as Halloween, January, and Friday effects, play a key role in shaping the association between stock returns and dividend announcements. [ABSTRACT FROM AUTHOR]

The correction notice addresses errors in various sections of the article "Will a Small Subcontractor Internalize Its Export Marketing Resources?" published in the Journal of Business-to-Business Marketing. The study examines the impact of market-based resources on small subcontractors' adoption of internalization of export marketing resources, focusing on factors like exploration orientation and relational ties. The research presents statistical data on market share status, asset specificity, and independent variables in business-to-business marketing, highlighting significant relationships between these factors and firm capabilities. The findings suggest that exploration orientation and relational ties are key determinants of business success in a competitive market setting. [Extracted from the article]

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]

Climate change has heightened the need to understand physical climate risks, such as the increasing frequency and severity of heat waves, for informed financial decision-making. This study investigates the financial implications of extreme heat waves on stock returns in Europe and the United States. Accordingly, the study combines meteorological and stock market data by integrating methodologies from both climate science and finance. The authors use meteorological data to ascertain the five strongest heat waves since 1979 in Europe and the United States, respectively, and event study analyses to capture their effects on stock prices across firms with varying levels of environmental performance. The findings reveal a marked increase in the frequency of heat waves in the 21st century, reflecting global warming trends, and that European heat waves generally have a higher intensity and longer duration than those in the United States. This study provides evidence that extreme heat waves reduce stock values in both regions, with portfolio declines of up to 3.1%. However, there are marked transnational differences in investor reactions. Stocks listed in the United States appear more affected by the most recent heat waves compared to those further in the past, whereas the effect on European stock prices is more closely tied to event intensity and duration. For the United States sample only, the analysis reveals a mitigating effect of high corporate environmental performance against heat risk. This study introduces an innovative interdisciplinary methodology, merging meteorological precision with financial analytics to provide deeper insights into climate-related risks. [ABSTRACT FROM AUTHOR]

Brain tumors develop when abnormal cells grow within or near the brain. Determining the extent of the tumor is crucial for effective treatment. Magnetic Resonance Imaging (MRI) has emerged as a non-ionizing radiation tool for diagnosing brain tumors. Segmenting brain tumors manually is a tedious process so the performance depends on the experience of the operator. To overcome the above-mentioned problem, in this research project, brain tumor detection is classified by the proposed Shepard Convolutional Quantum Neural Network (ShCQNN) using MRI images. Initially, pre-processing of the input image is carried out with a Mean filter and the process of segmentation is executed by LinkNet. Here, the proposed Chicken Swarm Stock Exchange Trading Optimization (CSSETO) is used to train LinkNet. This CSSETO is formed from Stock Exchange Trading Optimization (SETO) and Chicken Swarm Optimization (CSO). Further, image augmentation includes rotation, random erasing, brightness or contrast adjustment, and shearing. Moreover, the extraction of features is done next to image augmentation, where some important features such as Local Ternary Pattern (LTP), Convolutional Neural Network (CNN), and Local Optimal Oriented Pattern (LOOP) are obtained. In the last stage, a brain tumor is detected using ShCQNN which is the amalgamation of Shepard Convolutional Neural Network (ShCNN) along with Quantum Neural Network (QNN). The two benchmark datasets, namely Multimodal Brain Tumor Segmentation Challenge 2018 (BraTS2018) database and the Figshare dataset are used to assess the performance of the proposed model using performance measures, such as specificity, accuracy, and sensitivity. Also, the performance of the proposed method has been compared with existing models, such as VGG Stacked Classifier Network (VGG-SCNet), Whale Harris Hawks Optimization (WHHO), CNN model, and EfficientNet-B0 and the results revealed that the proposed method provided superior performance than other existing methods. The proposed method obtains the accuracy of 0.925, sensitivity of 0.915, and specificity of 0.915. Regarding the accuracy, the performance improvement of the devised ShCQNN technique is 19.14%, 18.60%, 10.81%, and 2.70% higher than the existing methods VGG-SCNet, WHHO, CNN model, and EfficientNet-B0. [ABSTRACT FROM AUTHOR]

Capital market stability is important for safeguarding investors' interests and promoting the healthy development of enterprises. Based on the data of Chinese-listed companies from 2008 to 2019, this paper explores whether corporate political connection building can reduce stock price volatility from the perspective of government–enterprise relationship. We find that corporate political connection building can significantly reduce stock price volatility, and the higher the political uncertainty, the more significant the effect of corporate political connection building in reducing corporate stock volatility. It is further found that information transparency plays a mediating role in the reduction of stock price volatility by corporate political connection building, and the effect of corporate political connection building in reducing stock price volatility is significant in the samples of non-state-owned enterprises and those with a low degree of marketization. This paper provides a reference for the realistic path to reduce stock price volatility and realize the stable development of capital market from the perspective of government–enterprise relations. [ABSTRACT FROM AUTHOR]

In this article, we extend the Proportion Portfolio Insurance (PPI) strategy by a life-cycle adjusted multiplier to adapt to the scenario of multi-period investment with continuous cash inflows, such as variable annuity with minimal guarantees. Using variational methods, we establish the closed-form optimal risk multiplier that determines the proportion of risky assets. It is negatively correlated with the life-cycle phase and previous performance but positively correlated with market conditions. We test the effectiveness of the life-cycle adjusted PPI strategy in a discrete-time framework for application considerations. In the U.S. and China stock markets, the life-cycle strategies outperform benchmark strategies under various measurements with robust results. Variable annuity investors who are less risk-averse or accept a lower guarantee ratio can benefit most from our strategy. [ABSTRACT FROM AUTHOR]

This study investigates the weak-form efficiency and asymmetric multifractal scaling behavior of rare earth stock indices in the global, U.S. and Chinese markets during the trade war and the COVID-19 period. We examine the scaling behavior across overall, upward (bullish), and downward (bearish) market states from 2013 to 2021, employing an asymmetric multifractal detrended fluctuation analysis approach. Our findings indicate asymmetric multifractality in U.S. rare earth stock prices, caused by fat tails and long-range correlations. Weak-form price inefficiency and asymmetry in U.S. rare earth stock prices are prominent during market downturns, such as the trade war and COVID-19 periods. Chinese rare earth stocks demonstrate greater efficiency than U.S. and global stocks; thus, the latter markets provide arbitrage opportunities during upward and downward trends. [ABSTRACT FROM AUTHOR]

Investing in cryptocurrencies is progressively becoming a norm; however, these assets are excessively volatile and often decrease or increase in value instantly. Thus, rational investors holding cryptocurrencies for extended periods firmly search for assets that can diversify their risk, preferably with assets other than cryptocurrencies. In this study, we consider the two most studied cryptocurrencies with the highest capitalization and trading volume/value, namely Bitcoin and Ethereum. Specifically, we examine whether high-performing leading US tech stocks (Facebook, Amazon, Apple, Netflix, Google [FAANG]) can provide any diversification benefits to cryptocurrency investors. To do so, we employ dynamic conditional correlation (DCC), asymmetric DCC, time-varying parameter vector autoregression-based connectedness measures, dynamic correlation-based hedge and safe-haven regression analyses, portfolio optimization and hedging strategies, time- and frequency-based wavelet coherence, and high-frequency 10-min intraday data from January 1, 2018 to January 31, 2023. We find that FAANG stocks can be considered (at least weak) safe havens for Bitcoin and Ethereum during the sample period. Our subperiod analyses reveal that the safe-haven role of FAANG stocks, specifically for Bitcoin, has noticeably increased. While the safe-haven property of Facebook is the most promising, for Netflix it is blurred between a weak–safe-haven and a hedge. Our findings may help investors, policymakers, and academicians to invest in cryptocurrencies, formulate relevant investment guidelines, and extend the literature on cryptocurrencies, respectively. [ABSTRACT FROM AUTHOR]

This study investigates whether analysts provide informative forecasts for stocks issued by firms with greater information uncertainty. As firm-specific information uncertainty is not directly observable, the research highlights the role of analysts forecasts and reports in offering valuable insights to investors. It also investigates whether forecast quality is sufficiently captured by forecast bias. The findings indicate that forecast quality tends to be lower for firms with greater information uncertainty and that forecast bias alone does not fully reflect the informational content of analysts' forecasts. Overall, the results suggest that analysts forecasts possess positive informational value. [ABSTRACT FROM AUTHOR]

This paper selects daily stock market trading data of RCEP member countries from 3 December 2007 to 9 December 2024 and employs the Time-Varying Parameter Vector Autoregression (TVP-VAR) model and transfer entropy to measure the time-varying volatility spillover effects among the stock markets of the sampled countries. The results indicate that the signing of the RCEP has strengthened the interconnectedness of member countries' stock markets, with an overall upward trend in volatility spillover effects, which become even more pronounced during periods of financial turbulence. Within the structure of RCEP member stock markets, China is identified as a net risk receiver, while countries like Japan and South Korea act as net risk spillover contributors. This highlights the current "fragility" of China's stock market, making it susceptible to risk shocks from the stock markets of economically developed RCEP member countries. This analysis suggests that significant changes in bidirectional risk spillover relationships between China's stock market and those of other RCEP members coincided with the signing and implementation of the RCEP agreement. [ABSTRACT FROM AUTHOR]

The capital asset pricing model (CAPM) is a foundational asset pricing model that is widely applied and holds particular significance in the globally influential Chinese stock market. This study focuses on the banking sector, enhancing the performance of the CAPM and further assessing its applicability within the Chinese stock market context. This study incorporates a heterogeneous autoregressive (HAR) component into the CAPM framework, developing a CAPM-HAR model with time-varying beta coefficients. Empirical analysis based on high-frequency data demonstrates that the CAPM-HAR model not only enhances the capability of capturing market fluctuations but also significantly improves its applicability and predictive accuracy for stocks in the Chinese banking sector. [ABSTRACT FROM AUTHOR]

Top management team (TMT) social capital plays an important role in obtaining innovation resources and improving enterprise innovation performance (EIP). However, there are few literatures on the impact of different dimensions of TMT social capital on EIP, especially in the digital era. Taking the listed companies disclosed by Shanghai Stock Exchange in 2008–2019 as samples, based on resource-based view and social network theory, a moderated mediation model is constructed. This paper examines the mechanism of TMT social capital affecting EIP, the mediating role of digital technology and the moderating role of network position. The results show that, TMT overseas capital and academic capital have significant positive effects on EIP; digital technology mediates the relationship between overseas capital, academic capital and EIP; network position moderates the relationship between academic capital and digital technology. Furthermore, the mediating role of digital technology in the relationship between academic capital and EIP is moderated by network position. The research conclusion enriches the research on TMT social capital, digital technology and EIP, and provides helpful guidance for enterprises to make full use of TMT social capital to manage digital technology and improve EIP. [ABSTRACT FROM AUTHOR]

The decision of the Federal Court of Justice (BGH) on January 31, 2024 confirms the use of the stock market price to estimate the value of a company, as in the case of the acquisition of K. AG by V. AG. The courts justified the appropriate compensation for the shareholders based on the stock market value of K. during certain reference periods. The decision concerned the valuation of company shares in the context of a takeover offer and was based on the stock market value as a basis. The appeal was rejected as unfounded, and the costs were imposed on the applicants. [Extracted from the article]

As investors select stocks more efficiently to form portfolios that meet their objectives, they should be grouped based on their time-varying risk levels. One of the clustering approaches is time series clustering with a model-based approach using hierarchical and K-means clustering algorithms. The distance calculation is based on the estimated parameters of the model used; in this case, the GARCH (1,1) model is used. This paper proposes a modified Piccolo distance that uses the absolute value between two GARCH (1,1) models, which is a development of the Manhattan distance. The modified Piccolo distance improves robustness to outliers and simplifies calculations, resulting in more accurate and efficient time series cluster analysis. Applying hierarchical and K-means clustering with modified Piccolo distance will be compared with other model-based distance modifications for clustering applied to simulated data and case studies using stock data incorporated in the Indonesia Stock Exchange. A measure of cluster validity is calculated using the C index. From the simulated data and case studies, it is found that clustering with Piccolo distance modification and other distance modifications between two GARCH (1,1) models produce clusters with a small C index, both for simulated data and case studies. A small C index value in the clustering results indicates good clustering quality, where the clusters formed have high similarity and are well separated from others. Furthermore, the clusters formed will be considered in making a good portfolio, so it is expected to reduce the risk in the stock portfolio. [ABSTRACT FROM AUTHOR]