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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]

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]

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]

The paper explores the concept of cash refund capital reductions (CRCR) in the context of firms listed on the Taiwan Stock Exchange Corporation (TSEC) and GreTai Securities Market (GTSM). CRCR is a distinct and increasingly vital financial tool used by these firms. Taiwan stands alone in adopting CRCR, making it a challenge to establish both a theoretical framework and gather empirical evidence on this subject. In this study, we examined 205 CRCR announcements made between 2002 and 2022, delving into their impact on both bull and bear markets. Our investigation reveals that the market responses to CRCR announcements were more significant during bull markets compared to bear markets. Additionally, we delve into the crucial factors influencing market responses in these varying market conditions. The findings underscore the importance for firms announcing CRCR to carefully consider the prevailing market conditions. [ABSTRACT FROM AUTHOR]

This paper investigates international monetary spillovers to stock prices in Bangladesh, a frontier market that has been excluded from prior studies in the literature. Using daily stock price data for over 300 publicly traded firms in a high‐frequency event study framework, we find that contractionary monetary shocks originating from the US, euro area, and China lower stock prices, with Chinese monetary shocks having the largest impact. Contractionary shocks originating from India, on the other hand, lead to a statistically significant increase in stock returns. The positive response is driven by a small number of policy decisions. When these outlier decisions are removed from the sample, contractionary Indian monetary shocks lead to a decline in stock prices in line with spillovers from the other countries. [ABSTRACT FROM AUTHOR]

This paper discusses the evolution of central bank communication, focusing on recent efforts by central banks to engage with a wider audience via social media. We document the social media presence of major central banks and discuss how analyzing Twitter content by and about monetary policy makers can inform about the effectiveness of communication in influencing beliefs. We focus on recent techniques employed in analyzing social media content in order to understand how central bank communication affects expectations and, subsequently, behavior in financial markets. [ABSTRACT FROM AUTHOR]

This paper defines a variety of game theoretic solution concepts in the language of soft set theory. We begin by defining the Nash equilibrium in pure strategies. We assume that the gains of the players are totally ordered and non‐desirable alternatives are absent. Moreover, we introduce the notions of strong and semi‐strong utility. These two completely new notions, serve as a mechanism for converting non‐ordered gains into totally ordered ones. We define the Nash equilibrium in mixed strategies in a general framework by introducing the notion of an extended game and strategy space. We finally define the Nash solution to cooperative bargaining games within the framework of soft set theory, illustrate a practical application to an over‐the‐counter financial market, and provide a detailed numerical example. [ABSTRACT FROM AUTHOR]

The article discusses a special issue of the journal Financial Markets, Institutions & Instruments, which focuses on the topic of climate risk and its impact on policy, financial markets, and corporate risk management. The special issue includes five papers that were selected through a rigorous review process. The papers cover a range of topics, including the effect of climate policy risk on syndicated bank loans, the relationship between corporate pollution and reputational exposure, the association between air temperature and sovereign bond returns, the moderating effect of carbon dioxide emissions on the relationship between corporate social responsibility and stock valuation, and the relationship between environmental performance and stock price crash risk. The authors provide detailed analyses and findings for each paper, contributing to the emerging literature on climate and finance. [Extracted from the article]

Focussed upon the U.S. stock market, the paper investigates the role of dividend policy, its level and (in)stability in generation of relative corporate value and relative stock price. Whilst relative corporate value is proxied by Tobin's q and relative stock price is operationalised by the four most frequent multiples (P/E, P/B, P/S and P/FCF), the dividend policy is represented by three popular metrics measuring the propensity to pay dividends. Controlling for operating and macroeconomic conditions, panel data techniques in a simultaneous equations framework are employed to 115,837 quarterly observations for 1466 firms represented in the S&P 1500 Composite Index over the period 1989–2022. The findings reveal that dividend policy matters, albeit the response of Tobin's and multiples to dividend policy is asymmetric. In particular, corporate value of U.S. firms is found to increase with per‐share dividend amounts but decreases relative to the dividend payout ratio and yield. The established empirical evidence reaffirms claims against dividend neutrality and is useful in developing pre‐selection investing strategies that relate practices in dividend policy to fundamental screening based on multiples. [ABSTRACT FROM AUTHOR]

The London Assurance Company (LA), which incorporated during the bubble of 1720, experienced more dramatic price movements in its shares than the South Sea Company. This paper examines how incorporating during the bubble affected its long run performance. We show that the bubble in the Company's share price was partly attributable to changes in market structure during the share issuance process. As a result of the bubble, the Company's original subscribers, who had been curated for expertise and political connections, overwhelmingly exited during 1720 and were replaced by unsuccessful speculators. Analysis of LA shareholder behaviour up to 1737 suggests that this loss of shareholder expertise had detrimental consequences for the Company's performance. These results demonstrate how a bubble in the shares of a newly created company can lead to an exodus of value‐adding investors, damaging the company's long‐term prospects. [ABSTRACT FROM AUTHOR]

This paper investigates the causal relationships and volatility spillovers between the BSE Bankex index and the stock prices of five major Indian banks (Axis Bank, HDFC Bank, ICICI Bank, Kotak Bank, and SBI). Daily data from January 2, 2018 to March 8, 2023 are used, and statistical techniques such as descriptive statistics, Unit Root test, Cointegration test, Ganger Causality test, OLS regression, and GARCH model are employed. The study finds bidirectional causal relationships between the bank stocks and BSE Bankex returns, suggesting that the movement of the bank stocks significantly affects the overall market returns and vice versa. The study also finds significant volatility spillovers between the bank stocks and BSE Bankex returns, implying that the shocks in the bank stocks affect the market returns and vice versa. The study's outcomes have practical implications for investors and policymakers. Investors can use the results to make informed investment decisions in the Indian stock market, while policymakers can use the findings to monitor the financial stability of the banking sector and design appropriate policy interventions to address any potential financial crises. Overall, the study's findings suggest that policymakers should proactively monitor and manage market risks to safeguard overall financial stability. [ABSTRACT FROM AUTHOR]

Globalization has brought larger spillovers of global risks across borders since the 2000s. Specifically, global policy risk has sharply increased due to policy uncertainty in major countries in the recent decade as are shown in the Brexit, the US‐China trade friction and the COVID‐19 pandemic. This paper empirically investigates effects of both global policy risk and global financial risk on macroeconomy and financial markets in eight major countries from January 1997 to June 2020. We employed a structural vector autoregressive framework to obtain interesting empirical results. First, global risks have recessionary effects on the macroeconomy, reducing production, deteriorating employment, lowering long‐term interest rates, depressing prices and reducing global trade. Second, global risks also have recessionary effects on financial markets, plunging stock prices, appreciating the safe‐haven currencies and depreciating the other currencies. Third, the macroeconomies and the financial markets respond to the global financial risk more significantly than the global policy risk. Fourth, the recessionary effects of global risks vary depending on countries. [ABSTRACT FROM AUTHOR]

We explore evolving research trends and hotspots in financial contagion through keywords co‐occurrence and co‐citation network analyses. 2,071 articles have been collected from Web of Science Core Collection database from 2005 to 2021 and been analyzed by using bibliometric methods. The results indicate a tremendous growth in research on financial contagion, especially following the Global Finance Crisis. The current research mainly focuses on understanding the causes and consequences of past financial crises and recessions, examining the network effects of banks and other important financial institutions on risk contagion, developing new systematic approaches to modelling financial contagion, and providing empirical evidences for financial contagion among various asset classes and across different countries and regions. We find that there is still no consensus regarding the causes and measures of financial contagion, however, new promising perspectives have emerged to expand research in this area. We also propose several future directions for studies on financial contagion based on the research gap identified in this review. [ABSTRACT FROM AUTHOR]

This study investigates the spillover dynamics among 10 Australian sectoral indices and their connectedness to global factors, including the WTI crude oil price, oil market volatility, Australian exchange rate, U.S. stock market volatility index and Infectious Disease Tracker Index. Using data from May 14, 2007 to March 31, 2022, this study applies the time‐varying parameter vector autoregressive model to study their static and dynamic connectedness, wavelet coherence analysis to investigate the time‐frequency co‐movement of global macroeconomic factors with Australian sector stock indices and wavelet decomposition‐based Granger causality. The results show that aggressive stocks (Industrials, Consumer Discretionary and Financials) are net transmitters, while defensive stocks (Health, Information Technology, Communication and Utilities) are net receivers of spillovers. The coronavirus pandemic has increased systemic risk, causing radical changes in net connectedness. Additionally, global macroeconomic factors drive the connectedness of the Australian sectoral indices, with oil and exchange rates moving in phase, and oil volatility, stock volatility and the Infectious Disease Tracker Index moving in antiphase. Global stock and oil market volatility has a significant impact on the Australian sector's returns over short‐, medium‐ and long‐term horizons. This study provides valuable insights to investors and policymakers by carefully examining the relationships between global factors and Australian sectoral indices. [ABSTRACT FROM AUTHOR]