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As China's carbon market continues to develop, its close connection with the financial and energy markets is becoming increasingly apparent. A systematic study of the spillover effects between markets is important, as it can help prevent excessive fluctuations in carbon prices. With this in mind, this study proposes a time‐varying parameter vector autoregression with Lanne–Nyberg decomposition extended joint connectedness approach to analyze quantitatively the spillover effects in the "carbon–energy–financial" system. Empirical results show that a bidirectional spillover effect exists among markets. Not only does the carbon market have the most pronounced return (volatility) linkages with the natural gas (clean energy) market, but the information connected with the energy markets is also more closely linked than with the financial markets. We also find that market fluctuations, caused by the China–US trade conflict and the COVID‐19 pandemic, have increased spillovers in the system. [ABSTRACT FROM AUTHOR]

Auction rate preferred stock (ARPS) is often regarded as an alternative to other near-cash instruments such as commercial paper while the dividend exclusion for ARPS offers tax advantages to corporate purchasers. The mean default risk premium for ARPS, relative to commercial paper, is estimated at 83 basis points during stable financial markets. This default premium appears to surge during unstable equity markets, having jumped by 192 basis points in November 1987. Lower-rated ARPS shows even larger changes, with yields 40-50 basis points above yields on high-rated ARPS, adjusted for the normal risk premium differential. The perceived risk change of ARPS underscores how quickly market participants re-evaluate default risk, and even the importance of the priority order among debt and equity claimants. Findings suggest ARPS and commercial paper are not an acceptable substitute for commercial paper during times of unsettled equity markets. [ABSTRACT FROM AUTHOR]

The Chinese capital market has attracted increasing academic attention due to its rising global influence, ongoing regulatory reforms, and distinct institutional background. In this paper, we review scholarly accounting and finance research pertaining to the Chinese capital market in Mainland China published in Tier 1 and Asia‐Pacific regional journals during the 1999–2018 period. Our review is based along four dimensions: top‐cited articles, main research fields, frequently contributing authors, and emerging research trends. We find that the increasing presence of China in global capital markets, along with its ongoing economic reforms, provides academics with opportunities to investigate distinct institutional environments and utilize natural experiments. This has led to the formulation of novel accounting and finance research questions, greatly advancing our understanding of accounting and finance research. [ABSTRACT FROM AUTHOR]

It is rather unusual to find all the papers presented in one of these sessions adhering so closely to the session title. I am taking note of this point to emphasize the unusual commonality of the two papers. Namely, both papers use the two parameter CAPM as their basic framework, and both papers investigate (or better, reinvestigate) classic, fundamental corporate finance issues. These are not trivial or second order issues undertaken in the two papers--capital budgeting, capital structure and dividend policy have always been at the core of corporation finance. But there is even a third similarity between these two papers; and that is, they both use numerical examples and solutions to illustrate some very difficult conceptual and analytical problems and to draw general conclusions. In many of the topics or cases studied in the two papers, analytical solutions were extremely complex or impossible, so that the usefulness of numerical examples was clearly demonstrated. [ABSTRACT FROM AUTHOR]

This paper investigates the all important issue of diagnostic tests, including unit roots and cointegration, in the tourism demand modelling literature. The origins of this study lie in the apparent lack in the tourism economics literature of detail concerning the diagnostic test aspect. Study of this deficiency has suggested that previous literature on tourism demand modelling may be divided into two categories: the pre-1995 and post-1995 studies. It was found that the pre-1995 and some post-1995 studies have ignored unit root tests and co-integration and, hence, are vulnerable to the so-called ‘spurious regression’ problem. In highlighting the key diagnostic tests reported by post-1995 studies, this paper contends that there is no need to report the autoregressive conditional heteroskedasticity (ARCH) test, which is applicable only to financial market analysis where the dependent variable is return on an asset. More generally, heteroskedasticity is not seen as a problem in time-series data. However, the reporting of a greater than necessary range of diagnostic tests — some of which do not have any theoretical justification with regard to tourism demand analysis — does not diminish the precision of the results or the model. This paper should appeal to scholars involved in tourism demand modelling. Copyright © 2003 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper analyses the dynamics of financial deepening and the volatility of business cycle in the United Arab of Emirates (UAE). We use cointegration tests of regime‐shift with one and two endogenous structural breaks, respectively, using Gregory and Hansen, Oxford Bulletin of Economics and Statistics, 1996, 58, 555–560 and Hatemi‐J, Empirical Economics, 2008, 35, 497–505 approaches. The asymmetry in the underlying relationship of the concerned variables are examined following NARDL model over the period 1974–2016. The findings suggest the presence of regime shifts in the cointegrating relationship and asymmetry between growth volatility and financial deepening. Furthermore, the paper provides evidence of a significant difference in the response of business cycle to negative or positive changes in the financial deepening, which are more pronounced in the short run. Therefore, the obtained asymmetry suggests that business cycle responses are quick and adverse to changes in the financial system in the UAE. The empirical findings of this paper have potential policy implications in this emerging country that is aiming to establish an international reputation in its financial market and become a regional financial hub. [ABSTRACT FROM AUTHOR]

Under the background of effectively building the legal system of the capital market and strengthening investor protection, an evaluation of whether China's legal system's reformations have improved investor protection is of great significance. Based on the lawsuits of 663 listed companies from 1997 to 2021, this paper finds the average annual proportion of listed companies punished by the China Securities Regulatory Commission and prosecuted by the investors is 40%, and since 2017, it has stabilized at around 70%. This paper also finds the "head effect" of the number of investors and claims in the misrepresentation cases over the years and the advantages of China Securities Investor Services Center's support in investor protection. Then, the negative binomial regression method is used to empirically find that investor protection gets better and better with the reformation of China's laws. Reformations in the legal system and key provisions have all led to an increase in the number of sued investors and claims. However, the time of legal proceedings only depends on the reform of the entire legal system. Finally, to reduce litigation costs and make all investors actually receive compensation after being infringed, we should establish the class action mechanism in the future reformation of China's legal system. [ABSTRACT FROM AUTHOR]

This paper explores whether environmental management activities and corporate commitment to tackle climate change concerns play a role in hedging a company's market valuation after a political or economic shock. Based on the literature on corporate social responsibility (CSR) and insurance‐like effects, this study advances knowledge on the impact of companies' engagement to tackle climate change on share price variation after the 2016 Brexit Referendum. The study also contributes to the limited number of studies using a difference‐in‐differences (DID) methodology in the CSR and climate change research area. Specifically, it uses DID, a natural experimental research design, and a multi‐variate regression analysis. The paper concludes that companies' concrete commitment to climate change has a buffer role in mitigating uncertainty related to Brexit. As the study found that financial markets reward companies that pay attention through the adoption of concrete actions and best practices on environmental issues during uncertain periods with respect to those that do not, the findings are in line with previous literature suggesting that corporate environmental commitment plays a buffering role during troubling periods. Results on the buffer role played by screenings, assessments, or disclosure activities to address environmental issues are unclear. We thus argue that during uncertain times, markets sustain companies taking proactive actions to tackle climate change. [ABSTRACT FROM AUTHOR]

This paper primarily aimed at examining the level, and determinants of financial inclusion in Tanzania, comparing it with other East African Region member countries using the Global Findex (2017) database. The study reports some insightful findings. The results show that, financial inclusion is less developed in Tanzania than in other East African countries contrary to expectations. According to expectations from development finance theories financial inclusion directly relates to economic development. However, Tanzania having better GDP than its neighbour countries ranks behind other countries with lower GDPs. One may say that weak financial system, inappropriate policy and poor financial instruments hamper significant effect of finance on growth. The paper argues that regardless of a significant economic growth reported in Tanzania inability of the financial system to reach majority of the population may be considered as a major reason behind the unexpected link between economic growth and financial inclusion. Furthermore, the study shows that financial inclusion is positively related to the income level and education level of the households, and negatively relates to gender. Moreover, a non‐linear relationship between age and financial inclusion is reported‐ that is the relation is positive at a certain age level, and change to negative at a higher age level.Consequently, the study recommends promoting equal participation in both labor and financial markets, and that East African's Governments to fully capture the dynamics of markets and track informal as well as formal economic activities to attract inclusive economy which will, ultimately, match with financial inclusion agenda. [ABSTRACT FROM AUTHOR]

The existing literature on the volatility forecasting less considered the co‐movement among stock markets from the spatial dimension. This paper builds the hybrid convolutional neural networks (CNNs)–gated recurrent unit (GRU) model for volatility forecasting under high frequency financial data based on transaction information and the topological characteristics constructed through the complex network of multi‐market symbol patterns. The hybrid neural network CNN‐GRU combines the advantages of CNN automatically extracting features for the input indicators and GRU processing long and short‐term serially dependent features, which can better improve the forecasting accuracy. The empirical results show that with the integration of topological characteristics as the indicators based on complex network, the deep learning model has a significant improvement of one‐step and multi‐step volatility forecasting accuracy for the China's and the US stock markets. The research in this paper provides a complete index system from the spatial dimension and a more accurate and robust volatility forecasting method under the high‐frequency financial data. [ABSTRACT FROM AUTHOR]

This article presents the author's comments on a paper that examined expected returns on stocks. The author suggests that the paper did an excellent job evaluating variance-bound literature; however, he believes that the analysis conducted was partial and failed to highlight the conclusions reached by other prominent researchers on volatility. The author also is skeptical of the conclusion drawn in the paper that suggests turning to nonstandard models for expected returns to explain stock price volatility. The author notes that the field has come a long way in understanding the statistical traps involved with volatility and pushes for more research.

This paper discusses the pricing of assets in an intertemporal rational-expectations model when real production and inflation evolve according to first-order autocorrelated processes. The focus is on the structure of the various intertemporal discount rates (yields) exhibited by this economy. Yield curves are identified for consumption claims, indexed bonds, and nominally riskless bonds and can be extended to any claim that can be approximated by a (finite) linear combination of such securities. The model demonstrates that, if the average term structure for nominally riskless securities is upward sloping, then the yield curve for consumption (market) claims is downward sloping, suggesting that conventional methods for computing long-term discount rates err by not accounting for maturity factors. The paper also explores the relationship between the intertemporal equilibrium and its embedded single-period equilibria. The single-period risk measures in this economy are derived and shown to be (generally) functions of maturity. A model of nominal bond betas is constructed along these lines. It is shown that bond betas that are increasing functions of maturity do not necessarily imply an upward-sloping term structure. [ABSTRACT FROM AUTHOR]

The paper documents that, over the period 1999–2011, Economic Notes made a further step forward in becoming a professional outlet for high‐quality academic research by moving under the production and distribution by an international publisher (Blackwell, later on, Wiley). The Journal cultivated research on the challenges posed by an environment of financial innovation and security‐market expansion, which posed new economic policy and bank management issues. Accordingly, it refocused on compelling financial, banking and monetary topics, as epitomized by adopting its current subtitle 'Review of Banking, Finance and Monetary Economics'. On balance, the Journal's long‐standing editorial policy of being open to a variety of contributions in the field of economics was retained, but a noticeable shift toward financial themes took shape over the 1999–2011 period. This focus, inspired by the events of the period, helped the Journal to remain relevant to the research interests of many scholars at the time. Notably, the Journal included topics in applied research that had a potential impact on the management of financial institutions, such as risk management and asset pricing, as well as the analysis of financial regulations. Those years proved fertile for both editorial policy and the dissemination of the Journal. [ABSTRACT FROM AUTHOR]

As an emerging financing model in the carbon financial market, carbon asset pledge financing (CAPF) has received extensive attention from governments and firms with the advance of low‐carbon economy. Since enterprises, banks, third‐party carbon asset evaluation agencies (TCAs), governments, etc, are involved in the operation of CAPF, driven by information asymmetry and the interaction among different stakeholders, rent‐seeking behavior is easy to occur in CAPF. This paper develops an evolutionary game model to investigate the rent‐seeking behavior in CAPF among different stakeholders. In addition, the risk‐sharing and penalty mechanisms are also taken into account. Subsequently, we examine the effect of relevant parameters on the dynamic evolution strategy of all parties in CAPF rent‐seeking through numerical examples. The results show that the governance of rent‐seeking behavior in CAPF needs the cooperation of different participating entities, the improvement of carbon financial market can reduce the occurrence of rent‐seeking behavior in CAPF. Compared with firms, TCAs are more susceptible to opportunism. Additionally, both the risk‐sharing mechanism and the penalty mechanism can effectively reduce the occurrence of rent‐seeking behavior. This paper contributes to the management of CAPF, and managerial insights for the governance of rent‐seeking behavior in CAPF are also provided. [ABSTRACT FROM AUTHOR]

Monetary spillovers are heterogeneous in two ways: how central banks generate them and how countries receive them. First, the Fed is mostly unique in its ability to affect other countries' financial markets, among ten developed central banks. This is noteworthy given the lack of data on other central banks' spillovers. This paper makes public a novel data set of these ten central banks' monetary shocks to support future research. Second, the Fed affects recipient countries in different ways, with the bonds and currencies of countries with high‐interest rates reacting differently than those of low‐rate countries. This can help shed light on theories around the Fed's spillovers, and this paper demonstrates how the exact pattern is inconsistent with models in which developed central banks react to the Fed. [ABSTRACT FROM AUTHOR]

Based on the question of the representability of economy and economics in audiovisual media, developments on the financial markets have often been discussed as a depiction problem. The abstractness and complexity of economic interrelations seem to defy classical modes of storytelling and dramatization. Nevertheless, public opinion about economic changes and dependencies crucially relies on audiovisual media. But how can the public communicate in images, sounds, and words about forces that are out of sight and out of reach, and can supposedly only be adequately grasped by experts? In a case study on audiovisual images of the global financial crisis (2007–), this paper tracks and analyzes a recurring motif: the staging of expert knowledge as close‐ups of expressive faces vis‐à‐vis computer screens in television news, documentaries, as well as feature films. It draws on the use of digital tools for corpus exploration (reverse image search) and the visualization of video annotations. By relating and comparing different staging strategies by which these "broker faces" become embodiments of turbulent market dynamics, the paper proposes to not regard them as repeated instantiations of the same metaphor, but as a developing web of cinematic metaphors. Different perspectives (news of market developments or historical accounts of crisis developments) and affective stances toward the global financial crisis are expressed in these variations of the face‐screen constellation. The paper thus presents a selection of different appearances of "broker faces" as a medium for an audiovisual discourse of the global financial crisis. A concluding analysis of a scene from Margin Call focuses on its specific intertwining of expert and screen as an ambivalent movement figuration of staging insight. Between the feeling of discovery (of a potential future threat) and the sense of being haunted (by a menacing force), the film stages the emergence of a "broker face" in an atmospheric tension between suspense and melancholy. We argue that the film thereby reframes the motif and poses questions of agency, temporality, and expert knowledge. [ABSTRACT FROM AUTHOR]

The article lists names of several papers which are to be published by the periodical based on topics like Trading Networks; Market Selection; and Financial Market.

The article presents a critique of the study "On the Politics of Accounting Disclosure and Measurement: An Analysis of Economic Incentives," by Nils H. Hakansson. It comments on the numerous claims made by Hakansson about generalizability, and his failure to offer analytics about how the results would obtain if the assumptions were relaxed. The article demonstrates that relaxing certain assumptions leads to different results. The author cites some inconsistencies between the assumptions and results of Hakansson's study.

Examining stock price crash risk in emerging economies is important since emerging equity markets are characterized by excessive volatility and weak corporate governance. This paper investigates the association between foreign ownership and crash risk using a data sample of firms listed on the Ho Chi Minh City Stock Exchange over the period 2007–2015. Employing a number of econometric techniques for panel data analysis, the paper shows that foreign investors are positively associated with future stock price crash risk. Importantly, this finding highlights the critical problem of information asymmetry in emerging markets. This paper has strong implications for portfolio investment and risk management. The paper is also relevant for financial market supervisory body in maintaining safe and sound financial markets. [ABSTRACT FROM AUTHOR]

The article comments on two articles published within the issue; "Some Notes on Financial Incentive-Signalling Models, Activity Choice and Risk Preferences," by S. Ross, and "Welfare Aspects of Options and Supershares," by N. Hakansson. The author notes that both Hakansson and Ross are prominent figures in literature which focuses on the power of options to complete financial markets. The author views the basic premise of Hakansson's paper to be the normative desirability of introducing derivative assets which complete the financial market. He feels that Hakannson's work establishes conditions under which the market portfolio can play the powerful role which is assigned in Ross' paper. The author notes that, if the conditions described by the authors were realized, financial markets could be completed by an institution facilitating trades in options written on the market portfolio.

Accurate prediction of financial market trends can have a great impact on maximizing profits and avoiding risks. Conventional methods, e.g., regression or SVR, or end-to-end training approaches, coined as deep learning algorithms, have restraints as a consequence of capturing noisy and unnecessary data. Financial market’s data are composed of stock’s price time series that are correlated, and each time series has both global and local dynamics. Inspired by recent advancements in disentanglement representation learning, in this paper, we present a promising model for predicting financial markets that learn disentangled representations of features and eliminate those features that cause interference. Our model uses the informer encoder to extract features, capturing global–local patterns by using the time and frequency domains, augmenting the clean features with time and frequency-based features, and using the decoder to predict. To be more specific, we adopt contrastive learning in the time and frequency domains to learn both global and local patterns. We argue that our methodology, disentangling and learning the influential factors, holds the potential for more accurate predictions and a better understanding of how time series move and behave. We conducted our experiments using the S&P 500, CSI 300, Hang Seng, and Nikkei 225 stock market datasets to predict their next-day closing prices. The results showed that our model outperformed existing methods in terms of prediction error (mean squared error and mean absolute error), financial risk measurement (volatility and max drawdown), and prediction net curves, which means that it may enhance traders’ profits. [ABSTRACT FROM AUTHOR]

This paper compares several methods for constructing weekly nowcasts of recession probabilities in Italy, with a focus on the most recent period of the Covid-19 pandemic. The common thread of these methods is that they use, in different ways, the information content provided by financial market data. In particular, a battery of probit models are estimated after extracting information from a large dataset of more than 130 financial market variables observed at a weekly frequency. The accuracy of these models is explored in a pseudo out-of-sample nowcasting exercise. The results demonstrate that nowcasts derived from probit models estimated on a large set of financial variables are, on average, more accurate than those delivered by standard probit models estimated on a single financial covariate, such as the slope of the yield curve. The proposed approach performs well even compared with probit models estimated on single time series of real economic activity variables, such as industrial production, business tendency survey data or composite PMI indicators. Overall, the financial indicators used in this paper can be easily updated as soon as new data become available on a weekly basis, thus providing reliable early estimates of the Italian business cycle. [ABSTRACT FROM AUTHOR]

This paper investigates effects of contagion in sub‐Saharan African stock markets by examining both crisis and non‐crisis contingent theories. Specifically, the paper examines cross‐market linkages through heteroskedasticity bias‐adjusted correlation in asset returns and assesses the impact of regional macroeconomic fundamentals on stock market volatility using GARCH‐MIDAS technique. The crisis contingent results reveal that there is no evidence of contagion in sub‐Saharan African markets from crises in global developed markets (the UK and the US). However, there is evidence of contagion from emerging market crises (China, South Africa, and Kenya). The non‐crisis contingent analysis underscores the significance of regional economic fundamentals, especially inflation and the GDP, on stock market volatility in South Africa, Nigeria, and Kenya. [ABSTRACT FROM AUTHOR]

The effects of government bailouts have been extensively examined in the literature. This paper is one of the first to empirically examine the bailout funds established in China in 2018, which aimed to mitigate firms' liquidity squeeze risk caused by share pledges. Utilising a hand‐collected dataset of government bailout funds, this paper finds that stock prices increased when government introduced the bailout fund plan, especially for non‐state‐owned enterprises (SOEs) and firms with small size and share pledges. Long‐term performance of bailed out firms increased as well. Overall, our results provide new evidence that government bailouts have positive effects on financial markets. [ABSTRACT FROM AUTHOR]

This paper examines nonlinear and time‐varying dependence structures between a pair of stochastic variables, using a novel approach which combines regime‐switching models and local Gaussian correlation (LGC). We propose an LGC‐based bootstrap test for examining whether the dependence structure between two variables is equal across different regimes. We examine this test in a Monte Carlo study, where it shows good level and power properties. We argue that this approach is more intuitive than competing approaches, typically combining regime‐switching models with copula theory. Furthermore, LGC is a semi‐parametric approach, hence avoids any parametric specification of the dependence structure. We illustrate our approach using financial returns from the US–UK stock markets and the US stock and government bond markets, and provide detailed insight into their dependence structures. [ABSTRACT FROM AUTHOR]

Summary: This paper examines the impact of data rescaling and measurement error on scoring rules for distribution forecast. First, I show that all commonly used scoring rules for distribution forecasts are robust to rescaling the data. Second, the forecast ranking based on the continuous ranked probability score is less sensitive to gross measurement error than the ranking based on the log score. The theoretical results are complemented by a simulation study aligned with frequently revised quarterly US gross domestic product (GDP) growth data, a simulation study aligned with financial market volatility, and an empirical application forecasting realized variances of S&P 100 constituents. [ABSTRACT FROM AUTHOR]

In this paper, we investigate house price shocks on the macroeconomic variables (financial market, inflation, and real sector) of the G7 economies. We use the GVAR to capture the spillover effects from the U.S. housing market and oil prices on these economies from 1991M3–2022M10. We identify the U.S. house price shock using the Structural Generalized Impulse Response Function, house supply and demand variables, and regional divergence. We find that the domestic stock markets and industrial production are the most sensitive to house price shocks. We further compare the importance of house and oil prices on domestic fluctuations. The estimates reinforce the previous findings: U.S. house prices are responsible for a quarter of the domestic volatility of the stock markets and industrial production. In the other macroeconomic segments, the effects of house prices are present, but in lower values. Our results show that house prices provoke more domestic fluctuations than oil prices. Finally, we also found that short and long‐term credit markets, as well as stock markets, transmit the house price shock to industrial production. Consequently, we provide potential channels to comprehend the spillover effect of U.S. house prices on international markets. [ABSTRACT FROM AUTHOR]

For most of the past decade, unconventional monetary policies (UMPs) have affected the wealth of savers, renters and younger generations. These policies, which enlarge central bank balance sheets – supporting credit expansion in the economy – but have no reliable mechanism for reversal, raise the simultaneous risk of higher inflation and deflation. In this paper, we critique UMPs by drawing on extant literature and empirical data that elucidate the undesired economic effects they cultivate. In particular, we focus on the implications of UMPs on efficient portfolio holdings by proposing an intuitive ex‐ante measure of dynamic efficiency loss that has applications for future research. [ABSTRACT FROM AUTHOR]

Stock forecasting is difficult because of its complexity and uncertainty. To better predict stock prices and then provide stockholders with reasonable suggestions, this paper proposes an improved time convolution network (TCN) model for predicting stock prices. The model used can make up for some of the shortcomings of the traditional neural network, use the trading data in the stock market, and put the preprocessed data of financial news into the model for training to improve the accuracy of prediction. Using the Shanghai Securities Exchange (SSE) 50 Index (Shanghai Securities Exchange 50 Index selects the most representative 50 stocks with large scale and good liquidity in Shanghai stock market as sample stocks) and news text crawled from financial web pages as samples, predict the direction of the SSE 50 Index's rise and fall. After using different network structure hyperparameters to adjust the model structure, the prediction effect is compared with other models, and it is found that the proposed improved TCN model can effectively improve the effect of predicting the rise and fall of the SSE 50 index, and can complete the model training and predict the stock price faster. [ABSTRACT FROM AUTHOR]

This paper applies the Random Forest (RF) method for the robust modelling of credit default prediction. This technique has been proven as an efficient classifier and can provide better interpretability in comparison to other classifiers. Using Chines micro‐enterprise credit data set, this study emphasizes the multidimensional analysis of credit risk, such as the whole sample, subsample, and the incremental effect of the group of predictors. To that end, relative variable importance (RVIs) has been presented for all predictors according to the contribution in the prediction accuracy so that to ensure interpretability of the model. The empirical findings confirm that RF technique is reliable and efficient across all of the criteria used in this study. In addition, the examined experimental analysis indicates that non‐traditional variables have a significant effect on the classification accuracy. Thus, this paper recommends some alternative predictors like the legal representative's basic information, internal non‐financial factors, along with traditional financial variables for sustainable model development. The performance is compared from the perspective of five different performance measures. This modelling algorithm can be used by different financial markets participants to measure systematically credit default prediction of individual and institutional customers. [ABSTRACT FROM AUTHOR]

This paper is an empirical attempt to assess the relations among business cycles, financial cycles, and economic uncertainty for India during the period January 2003 to January 2020. Empirical findings from the vector autoregression model suggest a bidirectional causal relationship between the real and financial markets. Further, the aforementioned markets are found to influence the uncertainty index in India. We employ the Granger causality test in the frequency domain which exhibits the dynamic nature of causal relations, while our novel fractal connectivity approach reveals the long‐run correlation structure among all three variables. [ABSTRACT FROM AUTHOR]

Our understanding of why corporations pay dividends is currently unsatisfactory. On the one hand, received theory tells us that dividends are irrelevant (in the sense that any two arbitrarily chosen dividend policies have equivalent consequences), both in the absence of taxes (Miller and Modigliani) and in their presence (Miller and Scholes). On the other hand, dividends continue to flood the empirical world with cash as regularly and as consistently as the sun scorches the desert, and one is hard put to characterize this pattern (currently at an annual rate of about $63 billion) as being founded on irrelevance. Not surprisingly, the attendant anomaly has led some, notably Black, to suggest that we really don't know why companies pay dividends. Something is clearly amiss. The present paper will look to the information content of dividends as a substantive (although not necessarily complete) explanation for the prevalence and persistence of positive dividend policies in market economies. The notion that dividends may constitute a source of information is, of course, not new (see e.g., Miller and Modigliani, Black, Stern). The basic idea is that the raising and lowering of dividends communicates information over and beyond what is provided by (mandated and nonmandated historical cost-based) earnings reports, forecasts, and other announcements. By in effect merging extant dividend theory with the theory of public information, the present paper generates several noteworthy consequences. [ABSTRACT FROM AUTHOR]

This article presents a discussion on an article that examines the effects of volatility on market efficiency. In observation of the work in the paper the author notes that since several variances are directly used in the usual tests of regression parameters and orthogonality, the relations between the volatility bounds and the standard set statistics should be more fully explored. He also notes that violations of the variance constraints should be attributed to the inappropriateness or inadequacy of the model tested rather than to market efficiency.

The article presents commentary about a paper written by Paul Griffen entitled "Competitive Information in the Stock Market: An Empirical Study of Earnings, Dividends and Analysts' Forecasts," which was published in the May, 1976 edition of the "Journal of Finance." The author observes that of the three hypotheses Griffen tests, two are operationally equivalent and none has been supported with adequate evidence. However, he believes that Griffen's investigation of the marginal and joint effects of earnings, dividends, and analysts' forecasts is a worthy endeavor.

The article presents commentary about a paper written by Robert K. Eskew and William F. Wright (E&W) entitled "An Empirical Analysis of Differential Capital Market Reactions to Extraordinary Accounting Items," which appeared in the May, 1976 edition of the "Journal of Finance." The author does not believe that E&W's work represents a significant contribution because its two main findings appeared in previous research. He also raises several issues with E&W's approach, including their assumption that a security's risk remains fixed over a given 12-month period.

As previously mentioned, there has been relatively little work concerning the effect of public information on the allocation of consumption. To fill this gap, the present paper examined the social value of public information in a pure exchange economy under different types of markets and utility functions. A model with time-independent utility functions and complete capital markets is a common one in the financial literature. Our paper yields the surprising result that public information has no value in this model. Conversely, the dissemination of information may affect consumption decisions and, hence, may have social value when either capital markets are incomplete or utility functions are time-dependent. This paper is intended as a first step toward assessing the social value of public information. The models presented here are limited by some restrictive assumptions. Among them, we assumed a pure exchange economy, information release after an initial equilibrium, homogeneous expectations, and specific utility functions. It is hoped that future research will relax these assumptions so that the theory of public information may become as rich as the theory of private information. [ABSTRACT FROM AUTHOR]

One important attribute of an efficient capital market is that current market prices fully reflect all available information and, thus, capital market equilibrium is conditional upon this information. There is, however, nothing in the efficient capital market model that provides theoretical insights on the nature or properties of the mechanism through which this conditioning information becomes available. In this paper, some properties and implications of one scheme for information-production were examined. The assumptions underlying this scheme are consistent with those that imply capital market efficiency. The production arid dissemination of information for use by capital market agents was handled via market game theory. Insofar as information about the allocation of real resources is concerned, it was shown that a Pareto optimal competitive solution (in the game-theoretic sense) is attained.[22] And, from the definition of this solution, one knows that the solution involves nonzero expenditures on information so long as at least one group of agents finds it desirable to invest in information-production. Moreover, it was shown that the returns (from information-production) to each agent converge to that agent's competitive allocation (in the classical sense). A basic idea used was as follows. The value of information to an individual was expressed in terms of a certainty equivalent. The certainty equivalents for the members of a coalition defined the payoff vector for that coalition. Then, it was shown that a core for the information- production game exists. The effects of information-production on the equilibrium production-investment decisions of firms whose securities are traded in the capital market were also examined. [ABSTRACT FROM AUTHOR]

This paper analyzes how mutual fund performance relates to past performance. These tests are based on a multiple portfolio benchmark that was formed on the basis of securities characteristics. We find evidence that differences in performance between funds persist over time and that this persistence is consistent with the ability of fund managers to earn abnormal returns. [ABSTRACT FROM AUTHOR]

In this paper, we document regularities in trading patterns of individual and institutional investors related to the day of the week. We find a relative increase in trading activity by individuals on Mondays. In addition, there is a tendency for individuals to increase the number of sell transactions relative to buy transactions, which might explain at least part of the weekend effect. [ABSTRACT FROM AUTHOR]

This paper presents an integrated overview of the literature linking institutions, financial development, and economic growth. From the large body of research on institutional development, the paper first selects those contributions that make it possible to study the role of institutional arrangements in ameliorating/worsening the information frictions and transaction costs that characterize the development of financial markets. The paper then investigates the theoretical mechanisms by which these specific frictions affect economic growth and presents the stock of empirical evidence quantifying the impact of institutions on growth through financial development. [ABSTRACT FROM AUTHOR]

One has to be impressed with the potential importance of the data base which Professors Cohn, et al. have been able to assemble and begin to analyze. The first report of their ongoing study, which was presented a year ago at these meetings, tantalized our expectations for learning more about the investment behavior of individuals--for long a relatively forgotten segment of the securities markets. A subsequent paper presented additional information on portfolio objectives, investor attitudes, decision processes, and portfolio composition--as well as insights on how these aspects of individual investors are interrelated. The issue of the present paper is straightforward: as individuals acquire greater wealth beyond their consumption needs, what do they do with it? Absolute and relative risk aversion are formal measures of what they do, and thus are often discussed in theoretical papers. While some theorists have proceeded without specification of investor utility functions beyond the sign of their first and second derivatives, other theorists have postulated additional properties, such as absolute and relative risk aversion, and even the functional form in some instances. In addition to its theoretical implications, the findings of this study by Professors Cohn, et al. should be of general interest to anyone teaching investment courses at any level. [ABSTRACT FROM AUTHOR]

This paper empirically explores dynamic risk impact of extreme volatility between stock and foreign exchange markets in emerging markets. Based on CoVaR analysis, we construct networks to investigate the nonlinear and dynamic evolution characteristics of risk contagion. The results show that stock and foreign exchange markets exhibit asymmetric tail dependence. All networks present small world network characteristics. The risk tolerance impact is more noticeable than risk overflow and stock markets are more sensitive to risk contagion. In the minimum spanning tree (MST), Korean stock market and foreign exchange markets of India and China are critical nodes in the minimum path of risk overflow. [ABSTRACT FROM AUTHOR]

This paper aims to examine the information game in an artificial financial market. The main objective of this work is to implement an agent‐based model that simulates complex stock markets. Similar existing simulation models address the buying and selling of assets but do not investigate the information exchange process. We extend the previous model by investigating the information exchange process during the transaction process. In this research, we simulate an asynchronous marketplace where interacting and heterogeneous agents exchange information and assets simultaneously. We study the effect of heterogeneous and cumulative information setup on the volume of transactions and the price dynamics during market sessions. We argue that the right interpretation of relevant information is conducive to rational decision‐making by the simulated agents. Our simulation shows that stock market results are sensitive to the type of information about agents. Our model will enhance the exchange decisions in the markets, which will lead to more efficiency. [ABSTRACT FROM AUTHOR]

This paper uses a new textual data index for predicting stock market data. The index is applied to a large set of news to evaluate the importance of one or more general economic‐related keywords appearing in the text. The index assesses the importance of the economic‐related keywords, based on their frequency of use and semantic network position. We apply it to the Italian press and construct indices to predict Italian stock and bond market returns and volatilities in a recent sample period, including the COVID‐19 crisis. The evidence shows that the index captures the different phases of financial time series well. Moreover, results indicate strong evidence of predictability for bond market data, both returns and volatilities, short and long maturities, and stock market volatility. [ABSTRACT FROM AUTHOR]

The growth of precarious employment coupled with declining social safety nets has increased economic insecurity among many households, leaving them without key resources to weather financial hardships like those brought on by the COVID‐19 pandemic. This has been especially true for people whose disabilities, health statuses, and already precarious economic situations have made them extra vulnerable. We combine survey (N = 1,027) and interview (N = 50) data for Canadians with disabilities and chronic health conditions to explore how mobilizing four types of institutional supports connected to labor markets, financial markets, family, and government influenced perceptions of current and future insecurity during crisis. Because employment income was only available to about half of our respondents, many relied on a combination of savings, family supports, and government programs to make up the difference. This paper demonstrates how marginalized groups make use of different supports within liberal welfare states during times of crisis. [ABSTRACT FROM AUTHOR]

This paper examines the relationship between the overconfidence expressed by the chair of the US Federal Reserve and financial market expectations. I first use a media‐based proxy to compute a measure of Fed chair's overconfidence for the period 1999M01–2017M07, the overconfidence indicator. The overconfidence indicator provides a quantitative measure of the overconfidence expressed by the Fed chair, which is covered by the media, and thus, perceived by financial market participants. I relate this variable to inflation and unemployment expectations of market participants. Our results show that an overconfident Fed chair is significantly associated with higher inflation expectations and lower unemployment expectations. These findings are robust to (i) the macroeconomic forecasts used to extract the exogenous component of the media‐based proxy reflecting Fed chair's overconfidence (the Survey of Professional Forecasters and the Greenbook forecasts) and (iii) an alternative proxy of inflation expectations. These findings shed some new light on the impact of central bankers' communication on financial market expectations, and thus, on the effectiveness of their monetary policy decisions. [ABSTRACT FROM AUTHOR]

In this paper, we study the power of moment‐based normality tests which include Jarque Bera (JB) test and D′Agostino and Pearson (DP) omnibus tests. Power comparison were obtained via Monte Carlo simulation of sample data generated from four alternative distributions like Uniform, Logistic, Student t and Gamma distribution. Our simulation results show that for Uniform distribution, DP test has better power compared to JB test. For Logistic, Student t and Gamma distributions, we find JB normality test to be powerful compared to DP test. We further apply the moment‐based normality tests empirically on the Indian stock market indices (NSE Nifty 50 and BSE Sensex) for different frequencies (daily, weekly, monthly and quarterly) during the period from 2010 to 2020. We find that daily returns of Indian stock indices are non‐normal whereas weekly, monthly and quarterly returns are normally distributed. [ABSTRACT FROM AUTHOR]