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In this future directions in finance article, I discuss several topics that I believe are promising areas for research. The topics fall into three areas: the microstructure of fixed income markets, equity market microstructure, and short selling. Both theoretical and empirical work is needed in these areas. [ABSTRACT FROM AUTHOR]

The paper "Corporate managers, price noise and the investment factor" investigates the impact of flows between the bond and equity funds on investment factors over the period 1984 to 2015. The paper "To jump or not to jump: momentum of jumps in crude oil price volatility prediction" finds a phenomenon, "momentum of jumps" (MoJ) and proposes a strategy that significantly outperforms the individual models and a series of competing strategies to enhance the predictability of crude oil price volatility. The paper "A theory of very short-time price change: security price drivers in times of high-frequency trading" analyzes and identifies four parameters considered to affect price changes. [Extracted from the article]

This paper's objective is to examine the asymmetric cointegration and asymmetric effects of financial development and monetary policy on monetary transmission mechanisms in the Nigerian context using annual data spanning the period from 1986 to 2023. This study pushes the frontiers of knowledge by providing information on the nonlinear impacts of monetary policy and financial sector innovations on monetary transmission mechanisms in Nigeria to help policymakers tailor their strategies to local conditions, enhancing the effectiveness of monetary interventions in the economy. To achieve this, this paper adopted nonlinear ARDL models to understand how changes in the direction of monetary policy and developments in the financial system induce changes in the transmission of monetary policy. The findings document the existence of asymmetries in both the short and long run, revealing that the impacts of financial development and monetary policy on the different monetary policy channels are not uniform. These asymmetries indicate that the responses of various economic variables to monetary policy actions differ depending on the level of financial development. These findings underscore the complexity of the monetary transmission mechanism and the necessity for a nuanced understanding of how financial development and monetary policy interact in different contexts. Consequently, this finding is symptomatic of some characteristics of those financial markets on their way toward advanced developments. As the financial system matures, monetary policy may have a greater impact on the cost of short-term funding for banks without having any discernible effect on the rates at which businesses and households access funding. Therefore, this paper recommends focusing on the policies that will foster the financial system across the banking sector, capital market, bond market, and overall financial sector to improve the efficiency of the monetary transmission process. [ABSTRACT FROM AUTHOR]

Copyright of Max-Planck-Institut für Gesellschaftsforschung Discussion Papers is the property of Max Planck Institute for the Study of Societies and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The rapid development of supply chain finance (SCF) has significantly alleviated the financing difficulties of small and medium-sized enterprises (SMEs). However, it is important to recognize that within the accounts receivable financing segment of the SCF credit market, the credit risk associated with SMEs poses a serious challenge and potential threat to the stability, health, and sustainable development of the SCF system. This paper pays special attention to the stability of the two-party evolutionary game between SMEs and financial institutions (FIs) within the context of the Chinese SCF credit market. To identify a pathway to reduce credit risks for SMEs while simultaneously enhancing system stability, this paper adopts the stochastic evolutionary game (SEG) model and combines the fixed-point method to determine the conditions that satisfy the stability of the system's index p mean square of the system. This study has made attempts in various aspects, such as the innovative construction and investigation of a nonlinear SEG model, the endeavor to study the stability of SEG systems using fixed-point methods, and the innovative construction of a more realistic two-player SEG system. The data and simulation results generated from hypothetical scenarios show that the conclusions of the article are credible and feasible. Through the study, we conclude that the higher credit ratio from FI and the higher penalty intensity from core enterprises (CEs) will accelerate the stability of the system. Based on solid data and modeling analysis, insights into the regulation of FI are provided. [ABSTRACT FROM AUTHOR]

Overconfidence (hubris or overestimation of one's ability to perform) has been viewed in the finance literature as a character trait that is stable over time, e.g., assuming that if a manager is overconfident, he/she is overconfident all the time. In this paper, we aim to show that managerial overconfidence can be state-contingent, i.e., the level of managerial overconfidence could be influenced by an external economic shock such as the global financial crisis in 2008. A novelty of this paper is to provide evidence for and application of the concept of state-based managerial overconfidence, which is new in the finance literature. Two empirical studies were reported. In the first study (Study 1), we analyzed real market data by linear regression. We found that managerial overconfidence could vary according to changes in the state of the macroeconomy or tightening of corporate governance policies. In the second study (Study 2), we conducted a lab experiment simulating how external manipulations could alter participants' confidence level. Both our empirical studies provide strong evidence of state-contingent overconfidence by Student's t-test and contribute to the current finance literature, which assumes overconfidence as a personality trait. Our findings have important practical implications for the credit market. According to the state-contingent overconfidence hypothesis, creditors might reduce the loan amount or the loan duration (or other loan contract terms) too excessively by more than the efficient level during an economic downturn if the offsetting effect of state-contingent overconfidence is ignored. [ABSTRACT FROM AUTHOR]

As highlighted by Pop & Georgescu (2024), the Romanian academic literature concerning municipal bonds is sparse, while the investigations regarding the factors that can influence the sub-sovereign bond trading at Bucharest Stock Exchange is quasi non-existent, to the best of authors’ knowledge. The present paper continues the work of Pop & Georgescu (2024) by trying to identify which of the public available information regarding various interest rates and Bucharest Stock Exchange (henceforth BVB) indices returns influence the trading activity of municipal bond market segment. The correlations presented within this paper imply that the modest profile of municipal bond segment at BVB is related to a relative small number of individual investors that dominate the transactions, using mostly observed data to decided when to trade and what to trade. The scarce correlations that appear in relation with the trading volume and trading value point toward the idea that only a small portion of the listed municipal bonds are owned by individual investors. [ABSTRACT FROM AUTHOR]

This paper examines the dynamic linkages among economic policy uncertainty (EPU), the green bond market, the carbon market, and the macroeconomy using the time-varying parameter vector autoregressive (TVP-VAR) model with monthly data spanning from January 2016 to December 2021. Additionally, it assesses the robustness and accuracy of the empirical results through the Bayesian vector autoregressive (BVAR) model. The findings indicate that EPU negatively affects the green bond market in the short term but has a positive impact in the medium and long term. Conversely, EPU has a positive impact on the carbon market in the short term but a negative impact in the medium and long term. Furthermore, the green bond market negatively influences the carbon market in both the short and medium to long term. These results suggest that emerging markets, such as the green bond and carbon markets, are influenced by EPU. The adverse impact of the green bond market on the carbon market, however, contributes to expediting China's attainment of its low-carbon objectives. Appropriate economic policies can play a vital role in accelerating the transition to a low-carbon economy. The study also reveals that the US-China trade war has expedited the development of green capital markets in China, despite its impact on the green economic transition in the country. These findings provide insights for the government and investors to formulate suitable strategies for risk mitigation. [ABSTRACT FROM AUTHOR]

This paper describes the growth of local-currency bond markets in Emerging Asia and the institutional and policy challenges facing the region's economies for their further development. It presents an empirical analysis of the relationship between local-currency government bond (LCGB) market development and the components of financial development, using panel data for selected Emerging Asian economies. The analysis seeks to identify the key determinants for the development of LCGB markets. The results show that the depth of and access to both financial markets and financial institutions have a significantly positive impact on LCGB market development. Critical factors associated with local-currency bond market depth include macroeconomic variables, the exchange-rate regime, capital account openness and creditor rights. Based on these results, the paper offers policy directions for fostering the development of local-currency bond markets in the region. [ABSTRACT FROM AUTHOR]

This paper examines if incorporating changes in financial market risk perception improves the predictive power of an early-warning system for systemic banking crises. In explaining systemic banking crises, the existing literature identifies inflating stock and real estate bubbles, credit booms, and surges in net capital inflows as the common drivers. Employing panel logit models to predict the postwar systemic banking crises in advanced economies to occur within three–four years, the paper's key finding is that, even after controlling for the effects of surges in asset and credit markets and net capital inflows that are above the long-run trends for an extended period, market participants' increasing underestimation of downside risks is a significant predictor of these crises. Incorporating changes in risk perception improves the prediction accuracy of the model significantly. This finding is robust across alternative prediction horizons, systemic crisis definitions, and risk-perception measures. Consistent with the recent theoretical developments in the form of the diagnostic expectations hypothesis for financial markets, the interpretation is that recent recurring good news about financial markets and the broader economic trends for sufficiently long periods lead to growing neglect of tail risks and riskier financial transactions, raising systemic risk and the likelihood of a financial crisis. The finding suggests monitoring financial market risk perception, in addition to the conventional indicators, to predict and avert systemic banking crises. [ABSTRACT FROM AUTHOR]

The process of global integration has accelerated, and the international financial market has become increasingly closely linked. The financial risks that come with them are becoming more complex and difficult to guard against. Multimedia modeling in Health Cloud biometric authentication and data management systems can be applied to the analysis of financial markets. Most of the current financial risk analysis models are based on a single time, and the models are relatively simple and cannot adapt to the current complex multidimensional mixed financial risk environment. Therefore, this paper aimed to analyze the spatial spillover effect of financial risk contagion based on the directed asymmetric (DAI) spatial econometric model. This paper proposed to transfer entropy information weight information and introduce the GARCH (generalized auto-regressive conditional heteroskedasticity) model to improve the traditional econometric model. By constructing a DAI measurement model, the spatial contagion of multidimensional mixed financial risks was analyzed, and on this basis, a generalized multidimensional economic space was established to analyze spatial spillover effects and analyze the specific path of spatial spillover effects. The model results in this paper showed that the degree of correlation between the stock and bond market varied greatly between countries. Among them, the change coefficient W s ⟶ b r s D of the event period was judged to have a large degree of negative change in the United Kingdom, Germany, and France in the European Union, which were −0.9885, −0.9876, and −0.9748, respectively. This showed that the model in this paper had a good and reliable ability to cope with the current multidimensional mixed complex financial risk environment and could be used as a reference for financial risk-related research. At the same time, it also proved that multimedia modeling in health cloud biometric authentication and data management system could provide a role in financial risk contagion analysis. [ABSTRACT FROM AUTHOR]

The green bond market has significantly improved in recent years thanks to the development of financial instruments and the rising climate change concerns. Given this backdrop, this paper investigates the effects of returns in different financial markets, i.e. the United States Treasury Bonds, the Standard & Poor's stock market, the United States Dollar, Gold, Crude Oil, and Bitcoin on the Green Bond returns (the Standard & Poor's Green Bond Index) from September 17, 2014, to September 1, 2022. The results from the robust linear and machine learning estimators indicate that the returns of the United States Treasury Bonds and the United States Dollar are negatively related to the Green Bond returns. Meanwhile, Gold returns positively affect Green Bond returns. The quantile regression estimations of Machado–Santos Silva also show that these findings are valid in different quantiles. The paper also discusses policy implications related to climate change and the development of financial instruments to promote green investments. [ABSTRACT FROM AUTHOR]

Market freezes are an interesting and theoretically challenging phenomenon —they are observed empirically, but cannot occur in standard models. This paper develops a formal theory of recurrent freezes emphasizing liquidity and self‐fulfilling prophecies. While it is well understood how to get hot and cold spells, where prices and quantities fluctuate, we get asset market freezes and thaws where trade completely stops and starts. The simplest specification gets this using negative asset returns. Other specifications use information frictions or fixed costs. We also consider credit freezes, analyze the extent to which the decentralized nature of trade matters, and discuss policy implications. [ABSTRACT FROM AUTHOR]

This study delves into the temporal dynamics within the equity market through the lens of bond traders. Recognizing that the riskless interest rate fluctuates over time, we leverage the Black-Derman-Toy model to trace its temporal evolution. To gain insights from a bond trader's perspective, we focus on a specific type of bond: the zero-coupon bond. This paper introduces a pricing algorithm for this bond and presents a formula that can be used to ascertain its real value. By constructing an equation that juxtaposes the theoretical value of a zero-coupon bond with its actual value, we can deduce the risk-neutral probability. It is noteworthy that the risk-neutral probability correlates with variables like the instantaneous mean return, instantaneous volatility, and inherent upturn probability in the equity market. Examining these relationships enables us to discern the temporal shifts in these parameters. Our findings suggest that the mean starts at a negative value, eventually plateauing at a consistent level. The volatility, on the other hand, initially has a minimal positive value, peaks swiftly, and then stabilizes. Lastly, the upturn probability is initially significantly high, plunges rapidly, and ultimately reaches equilibrium. [ABSTRACT FROM AUTHOR]

The article describes several reports published within the issue, such as one by Louis Bachelier on the bond market.

In this paper, we study the pricing of contracts in fixed income markets under volatility uncertainty in the sense of Knightian uncertainty or model uncertainty. The starting point is an arbitrage-free bond market under volatility uncertainty. The uncertainty about the volatility is modeled by a G-Brownian motion, which drives the forward rate dynamics. The absence of arbitrage is ensured by a drift condition. Such a setting leads to a sublinear pricing measure for additional contracts, which yields either a single price or a range of prices and provides a connection to hedging prices. Similar to the forward measure approach, we define the forward sublinear expectation to simplify the pricing of cashflows. Under the forward sublinear expectation, we obtain a robust version of the expectations hypothesis, and we show how to price options on forward prices. In addition, we develop pricing methods for contracts consisting of a stream of cashflows, since the nonlinearity of the pricing measure implies that we cannot price a stream of cashflows by pricing each cashflow separately. With these tools, we derive robust pricing formulas for all major interest rate derivatives. The pricing formulas provide a link to the pricing formulas of traditional models without volatility uncertainty and show that volatility uncertainty naturally leads to unspanned stochastic volatility. [ABSTRACT FROM AUTHOR]

In this paper, we explore a novel model for pricing Chinese convertible bonds that seamlessly integrates machine learning techniques with traditional models. The least squares Monte Carlo (LSM) method is effective in handling multiple state variables and complex path dependencies through simple regression analysis. In our approach, we incorporate machine learning techniques, specifically support vector regression (SVR) and random forest (RF). By employing Bayesian optimization to fine-tune the random forest, we achieve improved predictive performance. This integration is designed to enhance the precision and predictive capabilities of convertible bond pricing. Through the use of simulated data and real data from the Chinese convertible bond market, the results demonstrate the superiority of our proposed model over the classic LSM, confirming its effectiveness. The development of a pricing model incorporating machine learning techniques proves particularly effective in addressing the complex pricing system of Chinese convertible bonds. Our study contributes to the body of knowledge on convertible bond pricing and further deepens the application of machine learning in the field in an integrated and supportive manner. [ABSTRACT FROM AUTHOR]

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]

This paper assesses the extent to which carry trade operations affect the performance of equity and bond markets in a target country, South Africa, by considering the US and the euro area as the funding countries. A two- and three-factor capital asset pricing model (CAPM) is employed to assess whether the pricing of equity and bond markets in South Africa depends on the US dollar/rand and euro/rand carry trade returns. Moreover, the paper uses the quantile regression technique to assess whether this pricing varies with the distribution of the equity and bond returns. The findings support that the US- and euro-funded carry trade are essential factors for the pricing of equity and bond markets in South Africa. Moreover, the results of the two-factor model show a negative relationship between the equity excess return and the US-carry trade returns at lower quantiles of the equity market returns. The positive relationship is observed in the upper quantiles of the equity market. The negative relationship means that carry trade activities reduce equity market returns during a bear market as investors close out their position when conditions in the equity market become unfavourable. The results of the three-factor model, controlling for the global volatility or uncertainty, show that carry trade investors exit the equity market to invest in the bond market when global uncertainty rises. This finding shows that carry trade investors choose less risky assets during rising global uncertainty. [ABSTRACT FROM AUTHOR]

In China's rural credit system, the problem of credit constraints is prominent. Due to the imperfect credit market, a large number of rural residents have credit constraints. Rural credit constraint is a serious problem restricting China's rural economic development. Aimed at solving the rural credit constraints, this paper makes an optimization analysis on the rural credit system and loan decision-making. To more reasonably evaluate customers' borrowing ability, the credit risk based on farmers' data on the big data platform is evaluated in this paper. The stacked denoising autoencoder network is improved by adopting the deep learning framework to improve the accuracy of credit evaluation. For improving the loan decision-making ability of rural credit system, a loan optimization strategy based on multiobjective particle swarm optimization algorithm is proposed. The simulation results show that the optimization ability, speed, and stability of the proposed algorithm have achieved good results in dealing with the loan portfolio decision-making problem. [ABSTRACT FROM AUTHOR]

The current study explores the problem of illiquidity in the corporate bond market globally and proposes a solution to enhance liquidity by studying various dimensions of liquidity. Purpose: The purpose of this paper is to propose a solution to the global issue of illiquidity in the corporate bond market. The problem has been identified by many researchers and this paper attempts to find a viable solution in the "fungibility route" as an alternative to the "liquidity route". Design/Methodology: An analysis of a sample size of 234,772 trade data of corporate bonds and a sample size of 2,00,607 trade data of G-securities is performed to identify the problem. Findings/Solution proposed: A mathematical model based on the credit risk differential and sensitivity differential is proposed to find out the fair value at which an illiquid bond can be exchanged with a liquid bond. To arrive at the fair value of the illiquid bond, we have calculated the risk-adjusted yield (RAY) using the modified duration and a credit risk differential. Originality: This research is a pioneering effort in addressing the worldwide issue of corporate bond illiquidity by proposing a novel solution. The proposed strategy aims to improve the liquidity of the bond indirectly, by utilizing the fungibility route. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the effect of geopolitical risks on financial development (measured by domestic credit to the private sector) in a panel dataset of 18 emerging markets over the period 1985-2018. The results from the fixed-effects estimations indicate that an increase in geopolitical risks leads to a lower level of domestic credit to the private sector. The findings from the bias-corrected least-squares dummy variable estimations also confirm that geopolitical risks impacts negatively on domestic credit to the private sector. In terms of controls, we have found that per capita income and broad money are positively associated with domestic lending. Further, external imbalances were found to suppress domestic credit in emerging markets. Various additional controls were then included to address potential omitted variable bias. Moreover, we utilized multiple robustness checks, such as excluding countries from different continents as well as extracting outlier observations. According to the findings from these robustness checks, the negative impact of geopolitical risks on domestic lending is statistically and economically robust. To the best of the author's knowledge, this paper is the first to provide evidence for the negative impact of geopolitical risks on financial development in emerging markets, the economic performance of which can slow down as competitiveness deceases due to concomitant threats. [ABSTRACT FROM AUTHOR]

This paper investigates the extent of volatility or risk spillovers between the currency carry trade and asset markets, namely the equity and bond markets, in South Africa to infer the extent of the connectivity between the two markets. The carry trade operation examined in this paper involves two strategies, both of which use the South African rand as the investment currency, with the U.S. dollar and the Japanese yen as the funding currencies. The vector autoregressive BEKK-Generalised Autoregressive Conditional Heteroscedastic (multivariate VAR-BEKK-GARCH) model is used to this end. Moreover, the paper assesses the dynamic correlation between each currency carry trade and asset markets to infer the time-varying dependence between the two markets. The results of the empirical analysis show evidence of volatility spillover between the carry trade returns and the two asset market returns. The extent of the spillover depends on the choice of the funding currency, with the U.S. dollar-funded strategy transmitting more shocks to the South African equity market compared to the bond market. Moreover, the synchronisation of the dynamic correlation between each asset market and the currency carry trade returns shows that any possibility of arbitrage is precluded in the currency carry trade market. [ABSTRACT FROM AUTHOR]

Purpose: This paper investigates the influence of three different sentiment indicators on the time-varying stock–bond correlation of 15 countries during the global crisis period of the coronavirus disease 2019 (COVID-19) pandemic. Design/methodology/approach: The author uses the time-varying correlation estimated using the autoregressive moving average -dynamic conditional correlation - generalised autoregressive conditional heteroskedasticity (ARMA-DCC-GARCH) model to achieve this aim. The impact of investor sentiment on the stock–bond correlation was analysed using the Markov regime-switching regression. Findings: The study results show that the sentiment indicators of fear, uncertainty and distress have a pronounced negative impact on the stock–bond correlation. They further provide evidence of a strong regime effect on the stock–bond correlation with sentiment indicators. Practical implications: The paper has a relevant impact on policymakers and fund managers. First, the policymakers now have more insightful evidence of how the stock and bond markets react during crises. Second, the fund managers need to focus on behavioural variables as they may be driving factors in crisis periods that may impair portfolio management. Originality/value: To the best of my knowledge, the paper is the first to throw light on the behaviour of the stock–bond correlation for 15 countries during the COVID-19 period. [ABSTRACT FROM AUTHOR]

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

Because of its creditor's rights, equity, and options, convertible bonds have been developed rapidly since its emergence and have become one of the main tools in the financial market. One of the core problems of convertible bonds is pricing. The research on the pricing model of convertible bonds in China is relatively late. Most of them use foreign technologies, but they are quite different from the actual situation in China, and most of the models are characterized by a single factor. Therefore, this paper puts forward the nonarbitrage pricing model in the stock market and the application of the finite element numerical solution in the value of convertible bonds. The biggest innovation of this paper is to design a combined pricing model by using the model of nonarbitrage pricing theory and finite element numerical solution. The model combines the advantages of the nonarbitrage pricing theory and finite element numerical solution, and through the design of this paper, the model effectively improves the calculation accuracy and is suitable for most of the current market environment. While improving the comprehensive performance of the pricing model, it also simplifies the calculation methods and steps. In order to further verify the actual effect of the pricing model in this paper, the traditional binary tree model is taken as the experimental contrast object, including the comparative analysis of the market price and the theoretical price of the convertible bond, the comparative experiment of the prediction effect between the model and the binary tree model, and the analysis of the relative price error of the convertible bond. The results show that the comprehensive performance of the pricing model in this paper is significantly better than the traditional binary tree model. This study has achieved ideal results and can be widely recommended. [ABSTRACT FROM AUTHOR]

This paper investigates (i) the return-volatility spillover between Bitcoin, Ethereum, Ripple, and Litecoin, (ii) the interdependence between cryptocurrencies' volatility and the US equity and bond markets' volatility, and (iii) the impact of the Covid-19 outbreak on the cryptocurrencies' return-volatility. A two-step estimation approach is considered where Univariate General Autoregressive Conditional Heteroskedastic models are estimated to model the volatility of the four cryptocurrencies then a Simultaneous Equation Model is estimated to model the interconnection between the cryptocurrency volatilities, the US equity and bond markets' volatility, and Covid-19 outbreak. We show that return-volatility spillovers exist among Bitcoin, Ethereum, and Litecoin while Ripple is the main transmitter of shocks. We find that the cryptocurrency market is detached from the US stock market but not from the US bond market. Finally, we show that a high economic and financial uncertainty in the US stock market due to pandemic outbreaks affects the price of Litecoin, Bitcoin, and Ethereum. However, shocks are short-lived. Our findings have practical implications; as the evidence of volatility spillovers among cryptocurrencies and their relative isolation from the majority of mainstream assets should be factored into the valuation and portfolio diversification strategies of investors. In crisis times such as those induced by Covid-19, investors who seek protection from downward movements in bond markets could benefit from taking a position in Ethereum. Policymakers can also rely on our findings to time their intervention to stabilize markets and control uncertainties inherent to stressful periods. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has given rise to a spike in financial market volatility. In this paper, we attempt to assess the effects of financial & news-driven uncertainty shocks in growing Asian economies, using country-specific bond volatility shocks as a measure of local interest rate uncertainty. Also, we contrast the effects of local uncertainty with global stock market uncertainty. Using bond market data from nine Asian markets, we uncover a transmission mechanism of uncertainty shocks via the bond market. The mechanism works as a crowding-out effect due to government-led excessive market borrowing with supply-side consequences for the private sector, as opposed to economic policy or global stock market uncertainty which works more like a demand shock as in the literature. We conclude that countries with growing fiscal deficits that entail a larger government bond market or higher current account deficits, tend to experience an increase in the cost of borrowing due to this bond market volatility or interest rate uncertainty shocks. [ABSTRACT FROM AUTHOR]

This paper aims to explore the effect of financial innovation on economic growth in 28 transition countries from 2004 to 2021. Financial innovation is categorized based on the structure of the financial system, including commercial banks, non-commercial banks and financial markets. By applying difference GMM estimation, the research demonstrated a significant positive effect of financial innovation in commercial banks and non-commercial banks on economic growth. The results show that a greater number of financial innovations in terms of products and services, processes, technology and function in commercial banks and non-commercial banks would result in higher economic growth in transition countries. In contrast, financial innovation in financial markets indicates significantly negative effects on economic growth. Introducing complex products in stock and bond markets in underdeveloped financial markets probably lead to the volatility and fragility, reducing economic growth. The results of this research contribute to issuing crucial policies that employ financial innovation as an impulse for spurring economic growth in transition countries. [ABSTRACT FROM AUTHOR]

This paper explores the informational role of the Loan Only Credit Default Index (LCDX) on the pricing of syndicated loans. Despite an extensive body of research on credit indices and loan pricing, limited studies have comprehensively assessed the complex relationship between the LCDX and individual loan spreads. Contrary to indices like the CDX, which are largely linked to corporate bonds, the LCDX directly pertains to the syndicated secured loan market, offering valuable insights about the overall credit default market and the cost of credit risk insurance. Preliminary results reveal a pronounced positive correlation between the LCDX spread and the syndicated loan spread, particularly noticeable amongst borrowers with lower credit quality. The paper highlights the LCDX's pivotal role in conveying secondary credit market information, with critical implications for credit risk management and financial regulations. [ABSTRACT FROM AUTHOR]

Investing in green bonds has been recognized as a strategy that not only promotes environmental performance but also offers attractive investment returns. However, macroeconomic factors, such as geopolitical risk (GPR), climate policy uncertainty (CPU), and global economic policy uncertainty (GEPU), play a substantial role in shaping green bond returns. Using the returns of US green bonds as a proxy for the returns of green bonds, we argue in this paper that these heterogenous uncertainty measures might have asymmetric impacts on the returns of green bonds (GB). By employing monthly data from January 2016 to August 2022, we apply the nonlinear autoregressive distributed lags model (NARDL) to examine the asymmetric impact of these heterogenous uncertainty measures on the returns of GB. The NARDL findings reveal evidence of short-run asymmetric impacts of GPR, GEPU, and CPU on the returns of green bonds. In the long run, there is an asymmetric impact of GPR and CPU on the returns of GB. However, there is a symmetric impact of CPU on the returns of GB in the long run. Specifically, in the short run, we found that a positive CPU shock causes a decline in the returns of green bonds. A similar magnitude of negative CPU shock causes an increase in the returns of green bonds. Moreover, a positive shock to GPR increases the return of green bonds, while a comparable negative shock to GPR reduces the return of GB. Furthermore, only negative shocks to GEPU have an impact on GB returns in the short run. Specifically, a negative GEPU shock reduces GB returns. In the long term, the returns of GB are positively impacted by negative shocks in GPR and both positive and negative shocks in GEPU, whereas positive shocks in GPR affect the returns of GB negatively. [ABSTRACT FROM AUTHOR]

Green finance is a sustainable force in promoting green development. China's social financing structure determines the key role that green credit plays in sustainable development. Under the dual pressure of future economic downturn and huge capital gaps, it is worth exploring whether to continue promoting green credit that conforms to the long-term market mechanism. From the perspective of Chinese commercial banks, this paper analyzes whether promoting green credit is compatible with the incentives and their profit maximization goals. To this end, the research in this paper is based on the following three aspects: (1) Based on financial analysis, this paper reveals the different pricing of green industries in the capital market and credit market and explains the mechanism through which green credit policies improve the operating conditions of commercial banks; (2) combined with the conclusions from the literature and financial analysis, the influence of different index types on the modeling results is analyzed, and it is determined that the main reasons causing a decline in the return on assets are the excessive expansion of capital and the decline in internal resource-use efficiency; (3) a data envelopment model (more accurately, SBM-DDF) with undesirable outputs is established to dynamically analyze the operating efficiency of Chinese commercial banks, and the role of green credit in improving efficiency is studied. The main conclusions of this paper are as follows: if Chinese commercial banks increase their proportion of green credit, they can not only increase their profit scale but also improve and optimize the allocation of their internal resources, thus improving their operating efficiency. The main sample of this study comprises 43 commercial banks in China from 2007 to 2020. [ABSTRACT FROM AUTHOR]

This paper analyzes recent developments in the British and European government bond markets with reference to the UK's decision to leave the European Union. The two main goals of the study are, firstly, to examine whether the Brexit referendum result has affected the risk premium and, secondly, whether there are any changes in risk pricing following the referendum. The paper finds a significant impact of the Brexit referendum on the risk premium in selected economies. Furthermore, the results suggest that there is a considerable change in risk pricing after the announcement of the referendum result. Credit default risk and the risk aversion play a much important role in the post-referendum period than they did prior to the vote, particularly in the UK. [ABSTRACT FROM AUTHOR]

In recent years, the new agricultural business entities have grown rapidly in all parts of the country and have become an effective carrier to achieve the basic stability of China's rural family operation system and moderate-scale agricultural operation. However, the systemic defects of rural financial market and the credit rationing of formal financial institutions make the capital needs of rural areas unsatisfied for a long time. Financial demand determines the direction of supply reform. Therefore, in order to improve rural financial supply and promote the transformation and development of agricultural economy under the current situation, it is necessary to effectively understand the formal credit demand and the impact factors of accessibility of the new agricultural business entities, which represents the direction of China's agricultural development in the future. Based on back propagation (BP) neural network, this paper constructs the farmers' formal credit availability prediction model and studies the formal credit demand and the impact factors of the availability of new agricultural business entities. The experimental results show that the farmers' formal credit availability prediction model has good performance in prediction accuracy, prediction time, and mean squared error. [ABSTRACT FROM AUTHOR]

Research background: According to the World Bank (2020), about 60% of adults in developing countries do not use formal financial services. Furthermore, according to the Polish Association of Loan Institutions (2022), about 3 million Poles use loans, most of them obtained online. Among the reasons for more than a decade of growth of interest in the non-bank consumer lending market there are the development of modern technology applications in finance and the establishment of the Lendtech sector. Purpose of the article: The main goal of the paper is to verify the role played by the Lendtech (LT) sector in the consumer credit market in the context of household financial exclusion. The following research questions were asked: Do credit-excluded households take advantage of LT services and, if so, to what extent? What are the behaviours and preferences of those who use consumer credit offered by LT? Do socio-demographic characteristics determine consumer use of loans offered by LT and, if so, what are they? Is the use of loans offered by LT due to credit exclusion or other factors? What action should be taken by participants in the digital consumer loan market interested in its inclusive direction? Methods: The paper uses the following methods: critical analysis of the literature, Kruskal-Wallis test, Mann-Whitney test, and nonparametric regression algorithm: k-nearest neighbors, as well as inductive inference methods. The data used is primary in nature and comes from a nationwide survey, September 2022 (CAWI method) of 1,200 Poles, of whom 200 respondents are Lendtech customers. The quota selection applied made it possible to reflect characteristics corresponding to the population of customers of lending institutions registered in BIK databases. Findings & value added: The article is a pioneering study based on an independent scientific survey, devoted to the Polish LT services market considered in terms of its relationship with one of the types of financial exclusion: credit exclusion. The most important conclusion is that people at risk of credit exclusion find a financing substitute in the LT sector, and thus it plays an important role in reducing financial exclusion, while maintaining the principle of creditworthiness verification. [ABSTRACT FROM AUTHOR]