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We present evidence that several popular low-frequency measures of effective spread suffer from a volatility-induced bias and that volatility is the primary driver of the variation of these liquidity proxies. Using data for U.S. equities and major foreign exchange rates, we show that the bias arises when the effective spread is small relative to volatility. We document that the bias has become more acute over time and show that volatility-biased measures fail to replicate some well-known results in empirical finance. We conclude by providing guidance on the choice of low-frequency measures in empirical applications. Authors have furnished an Internet Appendix , which is available on the Oxford University Press Web site next to the link to the final published paper online. [ABSTRACT FROM AUTHOR]

Trading decisions often encounter risk and uncertainty complexities, significantly influencing their overall performance. Recognizing the intricacies of this challenge, computational models within information systems have become essential to support and augment trading decisions. The paper introduces the concepts of trading software agents, investment strategies, and evaluation functions that automate the selection of the most suitable strategy in near real-time, offering the potential to enhance trading effectiveness. This approach holds the promise of significantly increasing the effectiveness of investments. The research also seeks to discern how changing market conditions influence the performance of these strategies, emphasizing that no single agent or strategy universally outperforms the rest. In summary, the overarching objective of this research is to contribute to the realm of financial decision-making by introducing a pragmatic platform and strategies tailored for traders, investors, and market participants in the FOREX market. Ultimately, this endeavor aims to empower people with more informed and productive trading decisions. The contributions of this work extend beyond the theoretical realm, demonstrating a commitment to address the practical challenges faced by traders and investors in real-time decision-making within the financial markets. This multidimensional approach to financial decision support promises to enhance investment effectiveness and contribute to the broader field of algorithmic trading. [ABSTRACT FROM AUTHOR]

Capitalism is a social order that evolves over time. While market exchange, private property, and the profit motive are generic features of capitalist systems, studies of contemporary capitalism aim to highlight what is specific about capitalism today. In this article, we develop the concept of monetary sabotage to pinpoint a phenomenon that has become more pronounced in recent decades, but which has not been sufficiently elaborated so far. Monetary sabotage refers to the utilization and, eventually, manipulation of the monetary infrastructure for private profit, creating instability and perpetuating inequality. Drawing on old institutionalism, with its emphasis on law, and articulating it with contemporary theories of credit and insights from the sociology of money, our analysis highlights the evolution of incorporate and intangible property as premises for financial profit-making at the expense of the public. This institutionalist approach adds new insights to the prevailing financialization literature and complements other critical perspectives. [ABSTRACT FROM AUTHOR]

This study investigates how economic policy uncertainty (EPU) impacts the syndication behaviors of venture capital firms (VCs). Analyzing data from China, we find that EPU boosts the likelihood that VCs take syndicated investments. When facing great EPU, compared with their domestic and private counterparts, foreign and state-backed VCs exhibit a greater propensity for syndication, particularly in collaboration with VCs from distinct capital backgrounds. Further, EPU reduces VCs' risk-taking tendencies and exacerbates inadequate information exchange in the market, thereby making VCs more inclined to syndicate their investments. Finally, EPU adversely affects VCs' exit performance, but syndication helps alleviate this impact. [ABSTRACT FROM AUTHOR]

The interplay of exchange rates among nations significantly influences both international and domestic trade, underscoring the pivotal role of the foreign exchange market (Forex) in a country's economic landscape. Forex fluctuations have a significant impact on the everyday lives of both government agencies and the public population, directly influencing a country's prosperity or misfortune. This work proposes an advanced fuzzy time series model that incorporates domain universe sub-partitioning, parameter adjustment optimization methodologies, and interval forecasting methods. We utilized this model to examine annual exchange rate patterns between the Pakistani rupee (PKR) and the US dollar (US$), comparing its forecast accuracy to that of other models. Our proposed methodology outperformed existing methodologies in terms of forecasting precision, providing stakeholders with valuable insights for making informed, data-driven business decisions that benefit both individual firms and the country overall. [ABSTRACT FROM AUTHOR]

Technological innovation is an important determinant of economic growth, and the Chinese government is trying to create a favourable environment for corporations at both the regulatory and policy levels to improve the innovation level of firms. We use a difference-in-differences model to explore the impact of going public on innovation in small and medium-sized enterprises. A total of 5522 companies listed on the NEEQ from 2013 to 2017 are selected as samples in this study. The main conclusions are as follows: (1) Listing on NEEQ has a significant innovation incentive effect, and compared to unlisted enterprises, the incentive effect has the dynamic characteristics of continuous increase; (2) Further research finds that in the eastern region, where marketisation is higher, as well as the emerging industrial areas, the incentive effect of listing reached 0.4558 and 0.2691 million yuan, respectively, from the perspective of enterprise scale, and listing mainly stimulated the innovation of medium-sized enterprises; (3) Financing constraints and signal transmission partly mediate the relationship between listing and corporate innovation. [ABSTRACT FROM AUTHOR]

Short time series are fundamental in the foreign exchange market due to their ability to provide real-time information, allowing traders to react quickly to market movements, thus optimizing profits and mitigating risks. Economic transactions show a strong connection to foreign currencies, making exchange rate prediction challenging. In this study, the exchange rate estimation between the US dollar (USD) and the Chilean peso (CLP) for a short period, from 2 August 2021 to 31 August 2022, is modeled using the nonlinear Schrödinger equation (NLSE) and calculated with the fourth-order Runge–Kutta method, respectively. Additionally, the daily fluctuations of the current exchange rate are characterized using the Hurst exponent, H, and later used to generate short synthetic fluctuations to predict the USD–CLP exchange rate. The results show that the USD–CLP exchange rate can be estimated with an error of less than 5 % , while when using short synthetic fluctuations, the exchange rate shows an error of less than 10 % . [ABSTRACT FROM AUTHOR]

The objective of this article is to examine the volatility spillover effect between the foreign exchange market and the stock market of Brazil, Russia, India, China and South Africa (BRICS) countries along with Japan as the developed country in the region, affecting the BRICS countries. Generalized Autoregressive Conditionally Heteroscedastic (GARCH) (1,1) method is used to study the volatility between the stock market and the foreign exchange market in selected countries, and asymmetric model, that is, Exponential Generalized Autoregressive Conditional Heteroscedasticity—EGARCH (1,1) is also used to investigate the presence of leverage effects in both stock market and foreign exchange market in selected countries. GARCH findings suggest a two-way volatility spillover between the stock market and foreign exchange markets for India, China and South Africa. In BRICS countries, volatility spillover from the currency market to the stock market is seen as more evident and robust as compared to spillover from the stock market to the currency market. A positive asymmetry in spillover is also observed from the foreign exchange market to the stock market. The findings of the study may provide valuable information to investors for decision-making in international portfolio investment and also for economic policymakers for their financial stability perspective. [ABSTRACT FROM AUTHOR]

This study examined the relationship between exports grouped by technology classification and movements in the real effective exchange rate for emerging markets. Export demand models were estimated for 24 emerging markets, covering high, medium–high, medium–low, and low technology groups from 2010:Q1 to 2021:Q4. Long-term elasticities were estimated using the Augmented Mean Group (AMG) panel estimator. The results indicate that exchange rate uncertainty negatively impacts exports in medium–high and medium–low technology groups, as well as total exports. Mean Group and Common Correlated Effects Mean Group (CCEMG) estimators broadly support these findings. Country-specific analysis revealed a predominantly negative relationship between real exchange rate uncertainty and exports in countries with significant coefficients. Overall, the study highlights the importance of considering country-specific characteristics and technology classifications when studying the link between exchange rate uncertainty and exports. [ABSTRACT FROM AUTHOR]

Macroeconomic and aggregate financial series were shown empirically to share an unconventional form of cyclical and persistent dynamics, whose functional form was obtained from the solution of general-equilibrium models with heterogeneous firms. The econometric modeling of equations that link such series requires a new methodology, as existing parametric techniques can cause paradoxical regression results and omit predictabilities. We provide a solution to disentangle the genuine relation between variables (the parameters linking them) from the unconventional dynamics that drive them. As an application, we show that GBP-USD forward premia have no predictive power for excess returns over 1976–2015 (thus solving this forward-premium puzzle) once the unconventional dynamics of spot rates are modeled. Taking advantage of these dynamics, we uncover a trading strategy which consistently outperforms existing ones in the out-of-sample period 2015–2021, delivering almost treble their profits and yielding a Sharpe ratio of 85%. Hence, even in this heavily traded market, the efficient market hypothesis has been failing for over 45 years as persistent profit opportunities remained unexploited because of the unconventional dynamics of the spot rate. [ABSTRACT FROM AUTHOR]

We study two sources of heteroscedasticity in high-frequency financial data and estimate their contribution to overall volatility by means of a Markov switching (MS) structural VAR model. We achieve identification for all coefficients by assuming that the structural errors follow a GARCH-DCC process. Using transaction data of the EUR/USD interdealer market in 2016, we first detect three regimesof volatility. Then we show that both sources of volatility matter for the transmission of shocks, and that information is channeled to the market mostly through demand shocks. This suggests that, on the EUR/USD market, some liquidity takers (LTs) are better informed than both liquidity providers and those LTs who follow a feedback strategy. [ABSTRACT FROM AUTHOR]

This study sets out to examine the effects of the interaction of subsidy removal on premium motor spirit (PMS) and exchange rate devaluation on macroeconomic instability in Nigeria. In this regard, this study adopted the Bayesian vector autoregressive model (BVAR) identified with sign‐and‐zero restrictions for annual data between 1985 and 2022. The empirical results reveal that both the removal of subsidies on PMS and the devaluation of the naira exchange rate significantly undermine real gross domestic product (GDP) growth and raise inflationary pressures in Nigeria. One important implication of this finding is that the ongoing subsidy reforms in the energy sector and associated devaluation of the naira exchange rate raise the risk of stagflation in Nigeria. Secondly, the simulation shows that simultaneous subsidy removal on PMS and exchange rate devaluation can trigger macroeconomic instability. This finding implies that stabilising PMS price and the exchange rate is key to achieving macroeconomic stability in Nigeria. Thus, this study recommends that Nigeria should be cautious and act quickly to cushion the price of PMS from the vagaries of foreign exchange market fluctuations to improve macroeconomic stability in the country. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to test the effects of enterprise risk management (ERM) on firms' outcomes and the moderating role of knowledge management (KM) on ERM–firms' outcomes relationship. Design/methodology/approach: Data were collected via a questionnaire survey among public listed companies on the principal stock exchange market in Malaysia. A total of 124 questionnaires were received by mail questionnaire. The results were examined through structural equation modelling and partial least squares. Findings: The outcomes specified that ERM has a positive and noteworthy influence on firms' outcomes, and KM has a moderating influence on the correlation among ERM and firms' outcomes. Research limitations/implications: The qualities, procedures and laws of the Malaysian corporations chosen as the sample firms, as well as their regulations, may not be representative of all other countries. Moreover, this study considered only one variable as a moderator, while there are many variables that different studies can consider as moderator or mediators. Practical implications: The results of this research imply that employees' awareness and knowledge of events, opportunities and risk, along with their engagement in the institute's strategy, are critical for risk management and controlling. For the managers, the results of this research can be helpful to their businesses by identifying the effective KM capability that may enhance their positive outcomes. Managers and organizations can use KM as an instrument to increase ERM effect on firms' outcomes. Social implications: KM and ERM are both significant intangible resources that are hard to imitate and are uniquely specified programs, which are important contributors to firm success in the long run. Moreover, the contingency theory of ERM was proved through the results of this study as it was identified in the public companies, that implementation of ERM as a strategic management practice, by organizations along with an effective KM may enhance the achievement of objectives and outcomes. Originality/value: This study helps to measure ERM comprehensively and how intangible assets such as KM can affect the comprehensive risk management process and its effectiveness. [ABSTRACT FROM AUTHOR]

The foreign exchange (FX) market has evolved into a complex system where locally generated information percolates through the dealer network via high-frequency interactions. Information related to major events, such as economic announcements, spreads rapidly through this network, potentially inducing volatility, liquidity disruptions, and contagion effects across financial markets. Yet, research on the mechanics of information flows in the FX market is limited. In this paper, we introduce a novel approach employing conditional transfer entropy to construct networks of information flows. Leveraging a unique, high-resolution dataset of bid and ask prices, we investigate the impact of an announcement by the European Central Bank on the information transfer within the market. During the announcement, we identify key dealers as information sources, conduits, and sinks, and, through comparison to a baseline, uncover shifts in the network topology. [ABSTRACT FROM AUTHOR]

Despite interest in preindustrial markets, archaeological discussions have largely been limited to proposing methods to determine the presence or absence of market exchange in ancient societies. While these contributions are important, methodological limitations have prevented theoretical considerations of the emergence and evolution of marketplaces and market exchange in prehistory. We propose that agent-based modeling provides a window to explore physical conditions and agent behaviors that facilitate the emergence of customary exchange locations and how such locations may evolve into socially embedded institutions. The model we designed suggests that simple bartering rules among agents can generate concentrated locations of exchange and that spatial heterogeneity of resources is the most important factor in facilitating the emergence of such locales. Furthermore, partner-search behaviors and exchange of information play a key role in the institutionalization of the marketplace. The results of our simulation suggest that marketplaces can develop, even with the absence of formalized currency or central planning, as a consequence of collective strategies taken up by agents to reduce exchange partner-search costs and make transactions more frequent and predictable. The model also suggests that, once established as a social institution, marketplaces may become highly conservative and resistant to change. As such, it is inferred that bottom-up and/or top-down interventions may have often been required to establish new marketplaces or relocate marketplaces to incorporate new resources, resolve supply–demand imbalances, or minimize rising economic costs that arise as a result of social, political, and economic change. [ABSTRACT FROM AUTHOR]

Purpose: The present study aimed to examine the effect of received remittance inflows on the price level ratio of the purchasing power parity conversion factor to the market exchange rate in 36 developed and developing countries from 2004 to 2020. Design/methodology/approach: The panel data conducted a comparative analysis and used panel least squares, regression with Driscoll-Kraay standard errors of fixed effect, random effect, feasible generalised least squares and maximum likelihood robust least squares to overcome the heterogeneity issue. Furthermore, the two-step difference generalised method of moments to overcome the endogeneity issue. Diagnostic tests were used to increase robustness. Findings: In the studied countries, there was a statistically significant negative relationship between received remittance inflows and the price-level ratio of the purchasing power parity conversion factor to the market exchange rate. This relationship explains why remittance flows depreciate the real exchange rate. The study's results also indicated that attracting investments can improve the quality of institutions despite high tax rates, leading to low tax revenue. Originality/value: The current study findings enrich the understanding of policies of how governments should minimise tariff rates on capital imports and introduce export-oriented incentive programmes. The study also revealed that Dutch disease can occur due to differences in the demand structure and manufacturing development policy. [ABSTRACT FROM AUTHOR]

The foreign exchange market is the most liquid financial market globally, attracting investors looking for lucrative investment opportunities. Despite numerous techniques developed for forecasting foreign exchange trends, accurate and reliable models remain scarce. This article presents a novel approach that combines fundamental and technical analysis to predict exchange rates for the USD-CNY, EUR-USD, and GBP-USD currency pairs. Additionally, we extend the model's architecture by using China CSI300 stock index futures (CIFc1) instead of VIX, LSTM instead of GRU, and adding data pre-processing. The results show that our method is more accurate and stable than other approaches mentioned above, including traditional methods based on fundamental analysis. This study highlights the importance of the idea of combing fundamental information with deep learning, and underscores the effectiveness of integrating technique analysis and fundamental analysis, and lays the groundwork for further extensions and experimentation in foreign exchange forecasting. [ABSTRACT FROM AUTHOR]

The objectives of this paper are to analyse the presence of multifractality in daily exchange rates of the US dollar (USD), British Pound (GBP), Euro (EUR), and Japanese Yen (JPY) relative to the Indian Rupee (INR) for a specific period (1999–2018) and to investigate the source of the observed multifractality in these exchange rates. The research examines the multifractal spectra of logarithmic returns (daily price changes) for the four currencies. To investigate the origins of this multifractality, we conduct two transformations on the return series: (a) random shuffling of the original time series of logarithmic returns which disrupts any long-range correlations within the data. And (b) application of phase randomisation on the unaltered series which aims to preserve frequency information while altering timing-related characteristics of the data. We then look at the impact of these transformations on the multifractality. Our findings indicate that all four exchange rates exhibit multifractal characteristics in their return series. The source of multifractality differs between currencies: The USD is primarily driven by the "fat tail" of the distribution (extreme fluctuations). For the GBP and EUR, a combination of long-range correlations and fat tails contributed to multifractality. The JPY is mainly influenced by the broad tail of the distribution (more frequent but smaller fluctuations). These results have implications for policymakers and market participants. Based on these findings, policymakers should consider the specific characteristics of each currency when designing risk management strategies or regulatory interventions. [ABSTRACT FROM AUTHOR]

Horizontal, multilateral and polycentric forms of governance, albeit important in reality, represent a challenge for the now dominant use of the 'market and hierarchy' continuum of structural alternatives. This paper proposes a broader characterisation of both poles of the continuum of governance forms that would enhance the understanding of both intra- and inter-organisational governance. One side of the continuum would encompass examples of ' societas ', for example, legal entities (among which firms) unifying property rights and deliberately coordinating actions through a wide set of voice-based mechanisms, including non-hierarchical ones. The other side of the continuum would encompass 'polyarchies', that is, forms of decentralised coordination among nodes deciding autonomously, but not necessarily linked by transactions of goods and services coordinated by prices, such as market exchanges. This paper uses several cases from the agri-food sector to show that many 'strange' unclassified forms can be described, explained and assessed as hybrids between polyarchy and societas. The final section of the paper proposes some refinements in the independent variables to be used in the comparative assessment of organisation forms and new propositions that can be derived for future research. [ABSTRACT FROM AUTHOR]

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

The Covid-19 Global Health Pandemic introduced a number of economic challenges to countries around the world. Notably, most policymakers implemented greater fiscal spending and monetary stimulus. For the first time, 15 emerging market economies experimented quantitative easing. Most were not constrained by the zero-lower-bound condition, and the degree of financial depth, central bank independence, and central bank transparency varied significantly. This research yields three critical findings. First, emerging markets experienced declines in capital flows and depreciation pressure stemming from quantitative easing. Second, quantitative easing in advanced economies had a more sizable and significant effect than domestic policies. Finally, the degree of financial development and central bank independence are key drivers in how quantitative easing impacts exchange rates specifically. More developed financial systems and greater central bank independence correspond to dampening the effect of quantitative easing on exchange rates. [ABSTRACT FROM AUTHOR]

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The global foreign exchange (FX) market represents a critical and sizeable component of our financial system. It is a market where firms and investors engage in both speculative trading and hedging. Over the years, there has been a growing interest in FX modeling and prediction. Recently, machine learning (ML) and deep learning (DL) techniques have shown promising results in enhancing predictive accuracy. Motivated by the growing size of the FX market, as well as advancements in ML, we propose a novel forecasting framework, the MVO-BiGRU model, which integrates variational mode decomposition (VMD), data augmentation, Optuna-optimized hyperparameters, and bidirectional GRU algorithms for monthly FX rate forecasting. The data augmentation in the Prevention module significantly increases the variety of data combinations, effectively reducing overfitting issues, while the Optuna optimization ensures optimal model configuration for enhanced performance. Our study's contributions include the development of the MVO-BiGRU model, as well as the insights gained from its application in FX markets. Our findings demonstrate that the MVO-BiGRU model can successfully avoid overfitting and achieve the highest accuracy in out-of-sample forecasting, while outperforming benchmark models across multiple assessment criteria. These findings offer valuable insights for implementing ML and DL models on low-frequency time series data, where artificial data augmentation can be challenging. [ABSTRACT FROM AUTHOR]

This study assesses the global and cross-regional influence of China's currency, the renminbi (RMB). We first develop a theoretical framework to determine the channel through which progress in RMB internationalization can be mapped onto the market influence of the RMB exchange rate on that of other currencies. Using a volatility connectedness approach, we then construct a series of spillover indices reflecting the international influence of the RMB. We find that the RMB's influence is worldwide but is smaller than that of major international currencies, such as the US dollar. Overall, the RMB has basically become a peripheral currency in Greater China, Central Asia, Eastern Europe, and some South Asian economies. Because of the Belt and Road initiative, regionalization of the RMB has also progressed in developing economies; however, China still has far to go in fully achieving internationalization of its currency. [ABSTRACT FROM AUTHOR]

We apply a time-varying parameter VAR (TVP-VAR) extended joint connectedness approach, in addition to the generalized connectedness approach, to understand the connectedness of crude oil futures price and exchange rates of major oil-dependent countries. We find time-varying nature of pair-wise and total connectedness that are usually elevated during events such as COVID-19, Brexit, European sovereign debt crisis and global financial crisis. Both joint and generalized connectedness approaches confirm that Japanese Yen and Russian Ruble are the leading net receiver of the shocks, though the two approaches provide mixed results for some other currencies. Moreover, there is strong evidence of time-varying and bi-directional shock transmissions between oil and foreign exchange markets. We also show that oil price volatility and gold price have predictive power on the connectedness. Lastly, we analyse the policy and portfolio implications. [ABSTRACT FROM AUTHOR]

Violations of no-arbitrage conditions measure the shadow cost of intermediary constraints. Intermediary asset pricing and intertemporal hedging together imply that the risk of these constraints tightening is priced. We describe a "forward CIP trading strategy" that bets on CIP violations shrinking and show that its returns help identify the price of this risk. This strategy yields the highest returns for currency pairs associated with the carry trade. The strategy's risk substantially contributes to the volatility of the stochastic discount factor, is correlated with both other near-arbitrages and intermediary wealth measures, and appears to be consistently priced across various asset classes. Authors have furnished an Internet Appendix , which is available on the Oxford University Press Web site next to the link to the final published paper online. [ABSTRACT FROM AUTHOR]

The article analyzes the main changes in the Russian currency market in the context of modern realities — unprecedented geopolitical pressure, changes in the financial, currency and payment landscape under the influence of sanctions. The purpose of the article is to study the directions of ruble settlements, financial integration and trade in currencies of friendly countries in response to structural changes in the Russian currency market. A significant decrease in the share of the dollar in international payments, reserves and transactions in the foreign exchange market is noted. Much attention is paid to the current trends of dedollarization and diversification of financial markets, which the exchange infrastructure has developed under the influence of difficult external conditions. The authors conducted a study to answer the debatable question of whether the rise in popularity of national currencies was natural or accidental. They support their conclusions with historical statistical data on transactions in the foreign exchange market.

The article shows the impact of external economic sanctions on the Russian financial market. Special attention is paid to the currency, commodity and derivative markets of the Moscow Stock Exchange. The main focus of the work is the analysis of changes in market dynamics and pricing under the influence of political and economic constraints. Methodologically, the study is based on a comprehensive analysis of trade session data, including statistical processing and modeling of market reactions. The use of actual analytical methods made it possible to identify nonlinear dependencies and hidden patterns of behavior of market participants. The results of the study demonstrate that sanctions have had a significant impact on volatility, liquidity and market structure. The authors show the influence of political factors on financial instruments in a crisis, as well as develop new methodological approaches to analyzing financial market data. The results of the work can be used to coordinate trading strategies, develop market regulation policies and assess risks in conditions of political instability. The study also provides a basis for further analysis of the consequences of economic sanctions and the development of strategies to adapt to changing market conditions.

This study takes the foreign exchange rates of Taiwan, Hong Kong and Japan as the research issue, and utilises the VEC GJR-Asymmetric GARCH model to analyse the interaction among spot exchange rates of these three countries. The empirical results prove that the average returns of all foreign exchange markets have their own- and cross-spillovers, and the volatility of the return rate exists ARCH and /or GARCH effects. In addition, using Japanese forward premium/discount as information variable, empirical results find that Japanese forward premium/discount have important explanatory power for the links of Taiwan, Hong Kong, and Japanese spot exchange rates, and the original volatility spillover effect has disappeared, indicating that Japanese forward premium/discount is indeed an information variable. In terms of the volatility asymmetry effect, the results show that the estimated coefficients of asymmetry in Taiwan and Japan are positively significant, indicating that under the impact of bad news, their own market volatilities will be greater than good news. We also justify that the foreign exchange rates of Taiwan and Hong Kong, Taiwan and Japan, and Hong Kong and Japan are more closely linked to each other in the face of the two major events. The US-China trade war and the COVID-19 outbreak have triggered risk contagion, with a crisis in one country quickly spreading to another, intensifying the link between the foreign exchange markets of Taiwan, Hong Kong, and Japan. Our findings may help investors and policymakers find responses to such foreign exchange market turbulence.

Modeling implied volatility (IV) is important for option pricing, hedging, and risk management. Previous studies of deterministic implied volatility functions (DIVFs) propose two parameters, moneyness and time to maturity, to estimate implied volatility. Recent DIVF models have included factors such as a moving average ratio and relative bid-ask spread but fail to enhance modeling accuracy. The current study offers a generalized DIVF model by including a momentum indicator for the underlying asset using a relative strength index (RSI) covering multiple time resolutions as a factor, as momentum is often used by investors and speculators in their trading decisions, and in contrast to volatility, RSI can distinguish between bull and bear markets. To the best of our knowledge, prior studies have not included RSI as a predictive factor in modeling IV. Instead of using a simple linear regression as in previous studies, we use a machine learning regression algorithm, namely random forest, to model a nonlinear IV. Previous studies apply DVIF modeling to options on traditional financial assets, such as stock and foreign exchange markets. Here, we study options on the largest cryptocurrency, Bitcoin, which poses greater modeling challenges due to its extreme volatility and the fact that it is not as well studied as traditional financial assets. Recent Bitcoin option chain data were collected from a leading cryptocurrency option exchange over a four-month period for model development and validation. Our dataset includes short-maturity options with expiry in less than six days, as well as a full range of moneyness, both of which are often excluded in existing studies as prices for options with these characteristics are often highly volatile and pose challenges to model building. Our in-sample and out-sample results indicate that including our proposed momentum indicator significantly enhances the model's accuracy in pricing options. The nonlinear machine learning random forest algorithm also performed better than a simple linear regression. Compared to prevailing option pricing models that employ stochastic variables, our DIVF model does not include stochastic factors but exhibits reasonably good performance. It is also easy to compute due to the availability of real-time RSIs. Our findings indicate our enhanced DIVF model offers significant improvements and may be an excellent alternative to existing option pricing models that are primarily stochastic in nature. [ABSTRACT FROM AUTHOR]

The financing costs of green asset-backed securities (ABS) are deeply affected by the increased information asymmetry and greenwashing risk resulting from risk transferring in securitization. To attract potential investors, many ABS issuers obtain external certifications, yet it is unclear whether they pay off financially. Based on a sample of 588 green ABS issued in China for 2016–2022, this paper examines the impact of external certification in the form of green certification and reputation of financial intermediaries involved in the issuance on the yield discount of green ABS over the paired non-green ABS. The empirical findings show that both external certifications lower the greenium of green ABS by serving as favorable signals and mitigating greenwashing concerns, especially in non-financial industry and the securities exchange market. Moreover, the information asymmetry and credit risk of issuers enhance the pricing effect of financial intermediary certification but undermine that of green certification. Our findings provide valuable implications to facilitate the financing efficiency of green financial markets and promote global low-carbon transition. [ABSTRACT FROM AUTHOR]

This article proposes a structural framework for the joint estimation of tourists' daily personal expenditures (intensity) and length of stay (extensity). We reconceptualize commonly accepted exogeneous determinants of both outcomes into a set of exogenous antecedents pre-existing the travel decision and a set of endogenous mediators that capture the role of market exchange after the travel decision and corresponding choices are made. Findings reveal that the effects of some exogenous factors, such as gender, income, and motives on total spending are fully mediated within the intensity and extensity components, absent of any direct impacts. Other factors, such as nationality, appear not to influence spending due to offsetting mediated effects. As these forces are difficult to discern via reduced-form modeling, the proposed structural framework provides tourism managers with deeper insight into the footprints of established expenditure determinants, potentially improving upon the efficacy of marketing strategies. [ABSTRACT FROM AUTHOR]

We examine changes in market liquidity when several popular U.S. retail brokers restrict client trading in GameStop stock over a six-day period in early 2021 due to higher clearinghouse deposit requirements. When retail investor participation in a high-attentionstock becomes restricted, trading activity declines and trading venue shifts occur – there is less trading in dark markets and more fragmented trading across U.S. stock exchanges. We also find that when a stock order flow mix becomes comprised of fewer retail investors and a higher concentration of institutional investors, the quoted bid-ask spread widens, and trading cost measures rise significantly. [ABSTRACT FROM AUTHOR]

Using the nonlinear autoregressive distributed lag (NARDL) method, the current study explores the effects of exchange rate variations on commodities trade between Pakistan and the United Kingdom. The current study contends that the limiting assumption of symmetry between the exchange rate and the trade flows may have hampered the empirical results, despite the fact that earlier studies primarily used the symmetric cointegration approach. From 1980 to 2020, the study examines the symmetric and asymmetries effects of exchange rate variations on 35 sectors in Pakistan that import from the UK and 35 industries that export to the UK. The findings suggest that there is evidence of a considerable influence of asymmetric exchange rate variations on trade flows in both the short and long term in over half of the importing and exporting industries that participate in trade with the UK. By highlighting the significance of taking into account asymmetry in the analysis and exposing the sector-specific effects of exchange rate changes on trade flows, the study adds to the body of current work. [ABSTRACT FROM AUTHOR]

The study of the dynamics of foreign exchange rates is of paramount importance to economic policy makers for developing countries like India that depend on foreign exchange to meet a large part of their import obligations. This paper uses the concepts of entropy to study the regularity/irregularity of the returns from the Indian Foreign exchange (forex) markets particularly during periods of economic instability. We use the Approximate Entropy and Sample Entropy statistics which measure the level of repeatability in the data are used to quantify the randomness in the forex returns for four major currencies namely the US Dollar, the British pound, the EURO and the Japanese Yen with respect to the Indian Rupee from the time period 2006 to 2021. These statistics are chosen as they are both statistical measures for assessing the randomness or regularity of time series data and enable researchers to objectively evaluate the degree of randomness present in the returns series and understand the crucial underlying patters or behaviors. In this research we look at two periods of major financial upheavals, the subprime crisis also known as the Global Financial Crisis (GFC) during 2006-2007 and the recent Covid-19 pandemic during 2020-2021. Our empirical results overwhelmingly confirm our working hypothesis that regularity in the returns of the major Indian foreign exchange rates increases during times of financial crisis. This is evidenced by a decrease in the values of the sample entropy and approximate entropy before and after/during the financial crisis period for the majority of the exchange rates. Our empirical results also show that Sample Entropy is a better measure of regularity than Approximate Entropy for the Indian forex rates which is in agreement with the theoretical predictions. Understanding the returns from foreign exchange rates during financial crises has important policy implications for various stakeholders, including market participants, policymakers, and regulators. It enables them to formulate better risk management and hedging strategies. It also helps policy makers in crisis management and contingency planning and safeguard the stability of the financial system. Exchange rate movements are interconnected across global markets, and crises often have cross-border implications. Collaborating on crisis management strategies across countries can help foster stability in international markets. [ABSTRACT FROM AUTHOR]

This paper investigates the nonlinear risk transmission from the oil and natural gas markets to the foreign exchange markets of five energy importers and one major energy exporter. We separate conditional volatility into the transitory (short-term) and permanent (long-term) parts, and then these volatilities are embedded in an elaborate robust linear quantile regression model. We find that the risk spillover effect is relatively low in Central and Eastern European countries (CEECs) probably because they pursue a managed float exchange rate regime. On the other hand, this effect is higher for Turkey and Russia, which is especially true for the effect from oil to the rouble at the highest quantile. This happens because Russia receives the largest amount of foreign currency from oil exports. The results indicate that the short-term risk spillover effect is notably stronger than the long-term one, which means that the exchange rate volatility is mainly determined by market sentiment. The rolling regression results coincide very well with the estimated quantile parameters. [ABSTRACT FROM AUTHOR]

The level of currency exchange security is an important indicator of the effective functioning of the currency exchange market. An imbalance in the domestic currency exchange market intensifies financial instability and makes it impossible to maintain an adequate level of currency security. The purpose of the research is to estimate the level of currency security of Ukraine in the conditions of currency market imbalance to determine the main reasons for its inadequate level and to make proposals for improving the methodology of calculation of the integral index of currency security. The article offers the author's interpretation of the essence of the concept of "currency security". The integral index of currency security during 2008 - 2022 was calculated in accordance with the "Methodical recommendations for calculating the level of economic security of Ukraine" and recommendations were suggested for improving this methodology in order to improve the situation on the currency market. It was proved that certain indicators make an impact on the level of currency security of Ukraine: movement of capital, negative trade balance, sufficient level of international reserves, dollarization of the economy, and high level of public debt. Ways to ensure an adequate level of currency security were proposed. Macroeconomic indicators that can act as indicators of currency security are considered and the correlation between them and the level of currency security was investigated. The expediency of introducing an additional indicator for the integral assessment of currency security is substantiated: the ratio of state and state-guaranteed debt to GDP. It allows to calculate the level of currency security more reliably. It is well-founded that the proposed indicator has a close stochastic connection with the exchange rate, therefore, if it is used with existing indicators of currency security calculation, it allows to detect negative trends of decreasing of the level of currency security. [ABSTRACT FROM AUTHOR]

Due to the strong nonlinearity and high complexity of foreign exchange rate data, how best to accurately analyze their trends and forecast them is regarded as a challenging research topic. While such research has developed rapidly and a large number of publications have appeared, few programmatic quantitative and qualitative overviews have been compiled in the field of exchange rate. By integrating bibliometric methods with network visualization based on CiteSpace software, this study analyzed 4999 publications of exchange rate research from the Web of Science (WoS) Core Collection database during 1992 to 2021. The study summarizes the major development in exchange rate determination since Meese‐Rogoff puzzle, from New Open‐Economy Macroeconomics (NOEM) and the Foreign Exchange Market Micro‐Structure Hypotheses, to determination model based on relationship between exchange rate and commodity price. Through the study's statistical analysis, co‐occurrence, co‐citation, and co‐keywords analysis, the influential authors, research institutions, countries and regions, journals, research hotspots, and future trends in the field of exchange rate are intellectually identified over the past 30 years. As a complement to existing literature, this paper provides theoretical and practical reference for researchers and practitioners in the field of exchange rate. [ABSTRACT FROM AUTHOR]

This document outlines the analysis, design, implementation, and benchmarking of various neural network architectures in a short-term frequency prediction system for the FOREX market. Our objective is to emulate the decision-making process of a human expert (technical analyst) through a system that swiftly adapts to market condition changes, thereby optimizing short-term trading strategies. We have designed and implemented a series of LSTM neural network architectures that take exchange rate values as input to generate short-term market trend forecasts. Additionally, we developed a custom ANN architecture based on simulators for technical analysis indicators. We performed a comparative analysis of the results and came to useful conclusions regarding the suitability of each architecture and the cost in terms of time and computational power to implement them. The ANN custom architecture produces better prediction quality with higher sensitivity using fewer resources and spending less time than LSTM architectures. The ANN custom architecture appears to be ideal for use in low-power computing systems and for use cases that need fast decisions with the least possible computational cost. [ABSTRACT FROM AUTHOR]

This paper analyses how limits to the complexity of statistical models used by market participants can shape asset prices. We consider an economy in which the stochastic process that governs the evolution of economic variables may not have a simple representation, and yet, agents are only capable of entertaining statistical models with a certain level of complexity. As a result, they may end up with a lower-dimensional approximation that does not fully capture the intertemporal complexity of the true data-generating process. We first characterize the implications of the resulting departure from rational expectations and relate the extent of return and forecast-error predictability at various horizons to the complexity of agents' models and the statistical properties of the underlying process. We then apply our framework to study violations of uncovered interest rate parity in foreign exchange markets. We find that constraints on the complexity of agents' models can generate return predictability patterns that are simultaneously consistent with the well-known forward discount and predictability reversal puzzles. [ABSTRACT FROM AUTHOR]

In the present paper, we investigate the complex dynamics arising from a behavioral exchange rate discontinuous model with heterogeneous agents. Unlike previous works explaining the emergence of chaos in the exchange rate models as the resulting of nonlinearity, our model is able to produce endogenous exchange rate dynamics due to the presence of discontinuity induced by a sentiment index, which affects the way investors take their trading decisions. In particular, it affects the level of optimism/pessimism of fundamentalists regarding their perception on the value of fundamental. Moreover, it also affects the strength to which one kind of chartists places her buying/selling orders. We show that our model, represented by a two-dimensional discontinuous map, has the ability to produce interesting endogenous exchange rate dynamics. In addition, when each component of the map is buffeted by a stochastic component, the model closely replicates the stylized facts of the EUR/USD and EUR/JPY exchange rate markets. [ABSTRACT FROM AUTHOR]

This paper examines the dynamic evolution and volatility spillovers between China's green bond market and conventional financial markets (bond, stock, commodity, and foreign exchange markets) using time and frequency connectedness measures. The empirical findings are as follows: firstly, there is a significant volatility spillover effect between the green bond market and other traditional financial markets, with the spillover effect showing clear time‐varying characteristics. The total spillover effects among all markets increase notably during extreme market conditions. Secondly, the green bond market primarily acts as a net risk spillover transmitter in most periods. Thirdly, compared to the stock, foreign exchange, and commodity markets, the green bond market has a more significant spillover effect on the traditional fixed‐income market. Finally, the volatility spillover effect of the green bond market on other markets exhibits a time‐frequency evolution, predominantly driven by short‐term factors. However, as market maturity increases, the influencing factors of the spillover effect gradually shift from short‐term to medium and long‐term factors. These findings offer insights for portfolio and risk management. [ABSTRACT FROM AUTHOR]

Exchange rate market play an important role as a measure to deal with monetary and currency crises and control its effects on the economy. The purpose of this study is to investigate the relationship between exchange market pressure, inflation rate, oil price and economic uncertainty in Iran using the VAR-DCC-GARCH model during the period of the first quarter of 1991 to the third quarter of 2021. Based on the results of the research, there is a dynamic conditional correlation between the variables, and volatilities of the inflation rate, oil price and economic uncertainty index lead to volatilities of the exchange market pressure. Also, the spillover effect of inflation rate, oil price and economic uncertainty index on exchange market pressure is positive and significant, which shows the important influence of these variables on exchange market pressure. Therefore, according to the correlation structure between the exchange market pressure and the macroeconomic variables, it is possible to control the effects of macroeconomic variables on the currency market by implementing appropriate policies in line with economic stability. [ABSTRACT FROM AUTHOR]

This paper aims to find an answer to the questions of "whether chief executive officers (CEOs) are compensated for market risk", and "how the combined interaction of board size and CEO duality moderates this relationship" from the tenets of agency theory and managerial power theory. Even though the contracting view of agency theory posits that agents are neither to be punished nor rewarded for events that go beyond their direct control (market risk), the research findings in the corporate governance domain are contradictory. It was found that Chinese and American executives were paid for market risk, including oil prices and exchange rates, which was explained by retention risk and weaker corporate governance systems. To shed light on previous inconclusive research, this paper investigates the topic further in a new country setting, that of Switzerland, because the previous results were mostly related to Anglo-Saxon countries. Switzerland is also one of the exemplary countries for executive compensation. Furthermore, it investigates the combined (cascaded) interaction effects of the board size and CEO duality on CEO compensation and market risk from the perspective of managerial power theory, which has not been previously analyzed in the literature to date. For the direct effect, in contrast to previous findings in Anglo-Saxon countries, it has been found that CEOs were not paid for market risk in Switzerland, which confirms agency theory's contracting prediction. This finding outlines the future comparative research area in this domain. For the combined interaction effect, it has been found that board size incorporated with CEO duality is the significant cascaded moderator, and large boards with CEO duality are significantly more effective in controlling asymmetric compensation, which confirms the efficacy of large boards with CEO duality in coping with asymmetric compensation and managerial entrenchment (managerial power theory). These results have both practical and academic implications for boards of directors, Human Resources and corporate governance literature, agency theory, and managerial power theory, by providing further evidence on previous inconclusive findings on board size, CEO duality, and the role of market risk in the CEO pay structure. [ABSTRACT FROM AUTHOR]

The foreign exchange rate market is one of the most liquid and efficient. In this study, we address the efficient analysis of this market by verifying the day-of-the-week effect with fractal analysis. The presence of fractality was evident in the return series of each day and when analyzing an upward trend and a downward trend. The econometric models showed that the day-of-the-week effect in the studied currencies did not align with previous studies. However, analyzing the Hurst exponent of each day revealed that there a weekday effect in the fractal dimension. Thirty main world currencies from all continents were analyzed, showing weekday effects according to their fractal behavior. These results show a form of market inefficiency, as the returns or price variations of each day for the analyzed currencies should have behaved similarly and tended towards random walks. This fractal day-of-the-week effect in world currencies allows us to generate investment strategies and to better complement or support buying and selling decisions on certain days. [ABSTRACT FROM AUTHOR]

The success of an investment portfolio is not only related to its yield, but is also influenced by market risks, especially the contagion risks that may exist between assets. Therefore, effective portfolio optimization requires first studying the risk contagion relationship between financial assets. We selected a total of six financial assets from different stock and exchange rate markets as the research objects, and explored the risk contagion relationships of various assets in the investment portfolio through Vine Copula. Research has shown that there is often a structural mutation in one or some assets of an investment portfolio, leading to significant fluctuations in investment returns. The Vine Copula model can effectively measure the risk contagion between assets caused by asset structural mutations. [ABSTRACT FROM AUTHOR]

Credit and debt are more than just material exchanges within a market economy, they are also social constructs embedded in moral judgments about the character of the agents involved. During the recent European Sovereign Bond crisis, some commentators noted how a similarly loaded moral media discourse juxtaposed "virtuous" Northern European countries on the one side, and "spendthrift, lazy" Southern European ones on the other side. In this article, I provide a quantitative large-N empirical assessment of this phenomenon. I employ a dictionary-based approach inspired by research in social psychology to measure moral content. Upon analyzing more than 14,000 articles published in the Anglo-American and German financial press between 2004 and 2019, I show the extent to which Greece was described in negative moral language. After the initial "shock" in the fall of 2009, the average moral tone turns negative, and more so in the German financial press relative to its Anglo-American counterpart. Moreover, by most measures, it never completely reverts to pre-crisis levels, thus suggesting how "sticky" economic narratives can become. Against the original expectations, though, there is no evidence that the financial press framed the last and most acute phase of the Greek crisis in 2015 in increasingly moral terms. [ABSTRACT FROM AUTHOR]

Our study focused on exploring the volatility spillover between foreign currency and stock markets, as well as the price dynamics of financial instruments traded in South Asian countries. We use daily data from 2001 to 2021 on the closing exchange rates of local currency to the US dollar and closing stock price indices of these countries. To capture the volatility spillover effect, we utilized the GARCH-BEKK model and used Granger Causality test results to test the price dynamics of these markets. Our findings revealed that the own volatility shocks significantly affect current market behavior and volatility effects spill over bi-directionally between foreign exchange rates and stock price indices in these countries. This study provides valuable insights for both domestic and international investors to understand the South Asian stock and foreign exchange markets, enabling them to make more efficient investment decisions based on the best market conditions. [ABSTRACT FROM AUTHOR]

This study examines the long memory properties in the volatility of the foreign exchange markets of Egypt, Ghana, Kenya, Nigeria and South Africa. Applying the FIEGARCH model to daily data from June 2, 1997, to December 31, 2021, we find long memory in the second moment of return innovations across all five countries' foreign exchange markets and significant first-order positive autocorrelation. To isolate spurious long memory, we perform a structural break test and find that structural breaks in all five foreign exchange markets do not affect long memory. The findings may have implications for risk management. Historical volatility-based investment methods can generate risk-adjusted returns innovations. Long memory may indicate unexploited profit for risk-seeking speculators and international investors in these countries' financial assets. Also, official intervention should be random and rule-changing to reduce currency market predictability. [ABSTRACT FROM AUTHOR]