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In the servicization business model, a service-oriented manufacturer sells the service derived from its products. Because of the special compensation method, a service-oriented manufacturer is more likely to be underfunded. A Stackelberg game is formulated to investigate the interaction among a bank, a manufacturer, and an operator, in which two financing strategies are considered: bank financing and guaranteed (internal) financing. The difference between these two strategies is who bears the bankruptcy risk of the manufacturer. With bank financing, the bank bears the risk and determines the interest rate, while under guaranteed financing, the operator sets a guaranteed financing interest rate. We find that under bank financing, the low operating efficiency of the manufacturer increases the bank's share of the supply chain benefits. In particular, the service-oriented manufacturer can rarely be financed if the bankruptcy risk is high. However, under guaranteed financing, the operator may, interestingly, even subsidise a manufacturer with high operating efficiency. In this situation, a high bankruptcy risk could incentivize the manufacturer to improve its operating efficiency for the sake of the subsidy. Practically, guaranteed financing could coordinate the supply chain through interest rate adjustments or subsidies when facing different risk levels, which could improve both firms' benefits. [ABSTRACT FROM AUTHOR]

We estimate short-term dividend strip prices from 27 years of S&P 500 index options data (1996-2022). We use option-implied interest rates when estimating strip prices and longer holding period returns to mitigate measurement error. We find that Sharpe ratios for short-term strips are similar to or higher than Sharpe ratios for the market. Short-term strips also have a low market beta and a positive alpha. Over the business cycle, realized term premiums (ie, the difference between market and strip returns) and the term structure of Sharpe ratios move countercyclically, whereas the term structure of alphas moves procyclically. [ABSTRACT FROM AUTHOR]

We present a theory in which the interaction between limited sharing of idiosyncratic labor income risk and labor adjustment costs (that endogenously arise through search frictions) determines interest rate dynamics. In the general equilibrium, the interaction of these two ingredients relates bond risk premiums, cross-sectional skewness of income growth, and labor market tightness. Our model rationalizes an upward-sloping average yield curve and predicts a negative relation between labor market tightness and bond risk premiums. We provide evidence for our theory's mechanism and predictions. [ABSTRACT FROM AUTHOR]

During the first half of 2020, the difference in savings from mortgage refinancing between high- and low-income borrowers was 10 times higher than before. This was the result of two factors: high-income borrowers increased their refinancing activity more than otherwise comparable low-income borrowers and, conditional on refinancing, they captured slightly larger improvements in interest rates. Refinancing inequality increases with the severity of the COVID-19 pandemic and is characterized by an underrepresentation of low-income borrowers in the pool of applications. We estimate a difference of $5 billion in savings between the top income quintile and the rest of the market. [ABSTRACT FROM AUTHOR]

This article studies how the rise of financial technology (Fintech) lending affects credit access, interest rates, and social welfare. We consider a lending competition model with two incumbent banks and a Fintech lender, which use different information and technologies to assess borrower creditworthiness. We show that Fintech lending could negatively affect high-quality borrowers' access to credit when the Fintech lender's screening accuracy is superior to that of the banks. Furthermore, Fintech lending may worsen the allocative efficiency of credit and reduce social welfare under some conditions. Analytical and numerical results suggest that Fintech lending mostly reduces the expected interest rates. [ABSTRACT FROM AUTHOR]

The emergence of blockchain creates a new possibility to solve the fraudulent problem of financial supply chain. We construct a game model to verify the strategic choice of the financial supply chain in an uncertain environment. We derive the equilibrium results and investigate the strategic choice of blockchain service for the financial supply chain. We also study the product price, product quantity, financing interest rate, and supply chain risk transmission, respectively. Specifically, when the blockchain is not considered, the financial model of supply chain led by core enterprises depends on firms' reputation. The retail and wholesale prices increase when fraud occurs or consideration payment increases. Besides, the market stability reduces price performance. In the blockchain environment, the strategic choices are divided into two cases: when choosing the core enterprise model and the third-party service model, the third-party service model is the equilibrium strategy; when choosing the third-party service model and the platform model, the platform model is the equilibrium strategy. [ABSTRACT FROM AUTHOR]

How do inaccurate priors about the distribution of interest rates affect search and outcomes in consumer credit markets? Consumer credit markets feature large amounts of within-borrower price dispersion in interest rates; if consumers are unaware of the extent of this price dispersion, they may shop less and take out loans at higher interest rates than they would otherwise. We conducted a randomized controlled trial with 112,063 loan seekers in Chile where we showed treated participants a price comparison tool that we built using administrative data from Chile’s financial regulator. The tool shows loan seekers a conditional distribution of interest rates based on similar loans obtained recently by similar borrowers, using data on the universe of consumer loans merged with borrower characteristics. We also cross-randomized whether we asked participants their priors about the distribution of interest rates. We find that consumers thought interest rates were lower than they actually were, and the price comparison tool caused them to increase their expectations about the interest rate they would obtain by 56%. Consumers also underestimated price dispersion, and our price comparison tool caused them to increase their estimates of dispersion by 69%. The price comparison tool did not cause people to search or apply at more institutions, but it did cause them to receive 13% more offers and 11% lower interest rates, and to be 28% more likely to negotiate with their lender and 4.7% more likely to take out a loan. In contrast, merely asking participants their expectations about interest rates led them to search at 4% more institutions and obtain 9% lower interest rates.

We develop a quantitative model with imperfections in domestic and international financial markets that generates strong effects of U.S. monetary policy on emerging markets (EMs). Financial imperfections prevent arbitrage both between local EM lending and borrowing rates, and between local-currency and dollar borrowing rates. An adverse feedback effect between financial health and external conditions amplifies the domestic "financial accelerator," leading to large cross-border spillovers of U.S. monetary policy shocks. The model implies a link between uncovered interest parity violations and local credit spreads, a prediction we show the data strongly supports. 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]

Do different loan application formats affect consumer loan requests? Six studies show that when consumers are asked to provide a preferred monthly payment (MP) (vs. loan amount [LA]), they request different principal amounts. This is because these loan application formats differ in the scale-compatible information they bring to consumers' mind. When LAs are elicited, consumers think of and request the cost of the expenditure they seek to finance. When MPs are elicited, however, consumers think of their monthly budget slack to construct and then request MPs they perceive to be affordable. For lower cost loans with a given term and interest rate, the MP (vs. LA) format results in larger principal requests. This effect reverses for higher cost acquisitions because individuals' budget slack caps out around $500 per month. These studies provide insight into how consumer loan application formats can affect consumer borrowing, as well as the psychological underpinnings responsible for the effect. Theoretical, managerial, and consumer welfare implications of the findings are discussed. [ABSTRACT FROM AUTHOR]

After exogenous demand shocks caused by natural disasters, FinTech lenders are more responsive to increased demand for reconstruction mortgages than traditional banks and non-FinTech shadow banks. Both FinTech and traditional banks increase credit supply, but FinTech supply is more elastic without increases in risk-adjusted interest rates or delinquency rates. Comparing lending supply channels, banks respond to regulatory incentives to lend to damaged areas, whereas FinTech lenders supply more credit when traditional banks rely more on balance sheet financing and physical branch networks. Compared to traditional banks, FinTech lenders increase supply elasticity more aggressively in response to local competitive pressure. [ABSTRACT FROM AUTHOR]

While the causal impact of limited attention to macroeconomic news is difficult to detect, this article proposes one solution: exploiting when foreign investors are "distracted" by risk factors in their home markets. I demonstrate that financial activity in the average foreign investor's home market decreases foreign attention paid to 21 emerging economies, measured using Google search volume for economy-specific financial terms that emanate from outside each economy's border. Exploiting this effect using an instrumental variables approach, I find that an exogenous increase in foreign attention preceding a scheduled monetary policy rate announcement raises preannouncement stock returns and announcement day turnover. [ABSTRACT FROM AUTHOR]

This article investigates spillovers from foreign economies to the U.S. through changes in long-term Treasury yields. We document a decline in the contribution of U.S. domestic news to the variance of long-term Treasury yields and an increased importance of overnight yield changes, a proxy for foreign shocks' contribution to U.S. yields. A model that identifies U.S., Euro area, and U.K. shocks that move global yields suggests that foreign shocks account for at least 20% of the daily variation in long-term U.S. yields in recent years. We also document the predictability of long-term U.S. yields by the U.S.–foreign yield spread. [ABSTRACT FROM AUTHOR]

In this third and final article, foundational elements of a premium-financed indexed universal life insurance sales strategy will be explored through a series of forecast outcomes. Foundational elements include indexed interest crediting rates, loan interest charges, and the amount and timing of borrowed funds. Determining appropriate indexed interest rates to illustrate using life insurance company software will be informed by historical cap and participation rates. Determining appropriate loan interest rates to forecast will be informed by historical 12-month LIBOR rates. Given that the dominant theme of these articles is to explore what it means for a financial service professional to act ethically and responsibly within the context of premium-financed indexed universal life insurance sales strategies where the insurance policy is viewed as the sole source of loan repayment, it is hoped that the financial service professional will gain a better understanding of how to talk about and present such strategies so that their clients have a more complete perspective when deciding whether to adopt this type of strategy and, if so, in what manner they should proceed. [ABSTRACT FROM AUTHOR]

This study provides novel evidence regarding the effects of loan-to-value (LTV) limits on housing choices. Using a detailed loan-level dataset, I exploit the introduction of LTV limits in Israel. I find that the LTV limits led borrowers to choose housing units that were more affordable, farther from the central business district, and in lower socioeconomic neighborhoods. Additionally, these LTV limits increase interest rates and decrease loan amounts. The findings of this study indicate that macroprudential policies, which focus on the stability of the financial system, have micro implications on location choices, commuting costs, and movement to less-advantaged areas. [ABSTRACT FROM AUTHOR]

Many of the Federal Reserve's (the Fed's) monetary policy operations involve trading with primary dealers. We find that, for agency MBS, dealers charge 2.5 cents (per $100 face value) higher selling to the Fed than to non-Fed customers. Controlling for the same dealer, same security, and same trading time, this discriminatory pricing likely arises from dealers' market power rather than inventory costs. Further, matching trade size reduces the price differential by more than half, implying that dealers' market power greatly relates to the Fed's purchases in large amounts, whereas the Fed's limited breadth of counterparty choice also plays some role. [ABSTRACT FROM AUTHOR]

By studying the relationship between shadow banking activities of commercial banks in China and the pricing of deposits and loan interest rates, we find that shadow banking promotes the liberalization of commercial bank interest rate pricing. Further research finds commercial banks' shadow banking businesses improve their liquidity. Compared with state-owned banks, the development of shadow banking promotes the liberalization of the deposit and loan interest rate pricing of non-state-owned banks to a greater extent. Therefore, we believe China should support the development of shadow banking to promote the liberalization of interest rates and monetary policy transformation. [ABSTRACT FROM AUTHOR]

A novel methodology to investigate the fine structure of interest rates based on Machine Learning techniques is discussed. The aim is to capture in an unsupervised way the common stochastic structure that drives the dynamics of interest rates of different maturities. The proposed approach is based on the Wasserstein barycenter, a powerful tool of analysis that allows us to construct, from a set of assigned probability distributions, a single probability distribution that captures the essential features of the whole set. To identify common stochastic factors, a Gaussian Mixture Model is fitted to the Wasserstein barycenter by maximum likelihood using the Expectation-Maximization algorithm with an initialization strategy based on Graph Machine Learning techniques. A fine-tuning of single-maturity interest rates is discussed in an attempt to capture maturity-specific stochastic factors. The proposed analysis also gives us the opportunity to test the hypothesis of a market segmentation into a short-term segment, the money market, and a long-term segment, the capital market, each with its own segment-specific stochastic factors. The methodology is tested on the US zero-coupon Treasury yield curve. The results obtained seem to show that most of the stochastic nature of the dynamics of the US zero-coupon yield curve can be captured by a three-component Gaussian Mixture Model describing the Wasserstein barycenter of the short-term segment of the yield curve. [ABSTRACT FROM AUTHOR]

This study aims to investigate a financial system consisting of four ordinary differential equations associated with the rate of interest, investment demand, price index, and the density of financial information gained by the population. The equilibrium and local stability of the system are investigated numerically. The impact of saving amounts and the rate of investment demand increases after getting financial information on the system are discussed. The findings of the study are verified graphically. It is found that the system becomes stable if the rate of investment demand increases after getting financial information kept at a certain level, such that the savings amount is maintained at a higher level. Also, the bifurcation diagrams of the system for various significant parameters that affect the system's stability have been depicted. [ABSTRACT FROM AUTHOR]

This paper applies a novel time series-based additive nonparametric quantile regression technique to stress test the credit risk of conventional and participation banks in Turkey. We particularly examine the effects of the exchange rate, unemployment rate, the policy interest rate, and the public debt-to-GDP ratio on the non-performing loan ratio (NPL) of Turkish banks at distinct quantile levels. We find that their effects are heterogeneous and significantly vary across different types of banks and quantiles. Overall, participation banks are more vulnerable to negative scenarios associated with the exchange rate, unemployment rate, and public debt ratio than conventional banks. [ABSTRACT FROM AUTHOR]

This paper investigates the driving forces of shadow banking in 27 EU Member States, using annual data for 1999–2020. To account for heterogeneity, the panel is split into two sub-groups labeled "old" Europe and Eastern Europe. The estimations provide evidence that bank assets, insurance corporation assets, interest rate spreads, and regulatory quality significantly determine shadow banking growth. Financial development also has a considerable influence. The strong link between shadow banking entities and insurance corporations highlights the need to create a framework to test the interconnectedness of financial institutions at the EU level. [ABSTRACT FROM AUTHOR]

We study a large-scale Brazilian loan subsidy program to expand long-term credit. The government subsidizes banks' funding costs for lenders, who then allocate credit to firms at regulated interest rates below a maximum ceiling. We propose and test a mechanism allowing banks to circumvent the rate caps and capture part of the subsidy. We show that when issuing a subsidized loan, lenders with market power use a cross-product pricing strategy, whereby they increase the price of other products to the same client. Our results have important policy implications for the design and effectiveness of government interventions in credit markets. (JEL G21, H81, E43) [ABSTRACT FROM AUTHOR]

We analyze the role of international reserves and sovereign debt in the determination and international transmission of interest rates. We develop a model that describes the money market equilibrium with capital account openness. It predicts that higher levels of international reserves lead to lower interest rates whereas the effect of higher government debt is ambiguous. We then test empirically these predictions on a panel of 128 countries over 1985–2019. We find that: (i) the transmission of U.S. interest rates to domestic interest rates is stronger in emerging market economies (EMEs) than in advanced economies (AEs) for short‐term interest rates (STIR), and vice versa for long‐term interest rates (LTIR); (ii) international reserves help counteract the transmission of the U.S. policy rate on STIR in EMEs; (iii) a higher sovereign debt level is associated with lower interest rates in EMEs (liquidity effect), but higher interest rates in developing economies (risk premium effect). [ABSTRACT FROM AUTHOR]

This study investigates the issue of trilemma versus dilemma in relation to monetary autonomy. We construct a long‐term interest rate independence index (LRI) apart from the conventional monetary policy independence evaluated on the basis of the short‐term interest rate independence index (SRI). LRI intends to capture the independence of domestic financial conditions and the monetary policy in a broad sense. Empirical results are as follows. On the basis of SRI, trilemma holds well, in which trade‐offs between SRI and international capital mobility and between SRI and exchange rate stability are found. This outcome is consistent with the findings of many past studies that support trilemma. However, on the basis of LRI, dilemma holds after the global financial crisis because only the trade‐off between LRI and international capital mobility exists. This result is consistent with the conclusion of Rey (2013), which emphasized the huge effects of the global financial cycle on the domestic financial condition owing to the integration of international financial markets. Empirical results settle the issue between trilemma and dilemma. [ABSTRACT FROM AUTHOR]

The name of Schumpeter is not among those of the precursors of post‐Keynesian monetary theory. This seems understandable when considering Schumpeter's ferocious criticism of The General Theory. However, in recent years various authors have highlighted significant points of contact between Schumpeter's monetary theory and that of Keynes and of post‐Keynesians. The objective of this work is not only to indicate the similarities between Schumpeter's monetary theory and that of the post‐Keynesians, but rather to show that Schumpeter's approach to money and credit allows making post‐Keynesian monetary theory more solid. In particular, we will show that Schumpeter's monetary theory enables to develop an explanation of the principle of effective demand sounder than that based on the simple presence of endogenous money and on the liquidity preference theory. [ABSTRACT FROM AUTHOR]

Blockchain technology (BCT) has the potential to revolutionize the supply chain financing (SCF) system and mitigate the detrimental effects of demand volatility on SCF. As one of the first to examine the effects of BCT implementation in SCF from the perspective of demand volatility, we focus on the impacts of BCT on equilibrium and whether the retailer has the incentive to adopt BCT. We perform a comparative analysis of the Stackelberg game involving three parties under scenarios with and without BCT adoption. We find that when the demand volatility reduction coefficient is sufficiently large, BCT can facilitate a reduction of the ordering quantity while still sustaining the same service level, thus avoiding excessive inventory, and reducing the associated risk of bankruptcy. Additionally, the decreased bankruptcy risk enabled the bank to reduce interest rates. The adoption of BCT can improve the profit of the retailer when the adoption cost of BCT is sufficiently low. Our findings provide management insights into when the small and medium‐sized enterprises should adopt BCT and the interactive decision‐making of all parties in the SCF business after BCT adoption. [ABSTRACT FROM AUTHOR]

Capital constraints are one of the major challenges for the supplier to invest in activities to enhance environmental and social responsibility (ESR) in production. Responsible buyer direct financing has emerged as an important solution to motivate supplier ESR by pegging the interest rate to the supplier's ESR level. Motivated by real practices, we develop game‐theoretical models to explore the value of conducting blockchain‐assisted due diligence to inspect the borrowing supplier's ESR qualification in a two‐tier supply chain structure where the downstream buyer directly finances the capital‐constrained supplier. Conventional wisdom tells us that driving greater supplier transparency (e.g., conducting blockchain‐assisted due diligence) will motivate the supplier to strengthen environmental and social compliance. However, we identify the necessary and sufficient "backfiring condition" under which the blockchain‐assisted due diligence may "backfire" by reducing the supplier's ESR efforts. The supplier devotes more ESR efforts if and only if the due diligence cost is sufficiently high. Our result implies that the heavy cost of adopting blockchain technology is not necessarily bad from the responsibility perspective as long as the backfiring condition does not hold. Moreover, we identify the Pareto zone in which conducting blockchain‐assisted due diligence could benefit both supply chain members. We extend our model by examining the impact of a shift from profit orientation to social welfare orientation. Our findings provide managerial insights into the implementation of blockchain‐assisted due diligence to enhance supplier ESR and improve supply chain members' profits. [ABSTRACT FROM AUTHOR]

We study the problems of consistency and the existence of finite-dimensional realizations for multi-curve interest rate models of Heath–Jarrow–Morton type, generalizing the geometric approach developed by T. Björk and co-authors for the classical single-curve setting. We characterize when a multi-curve interest rate model is consistent with a given parameterized family of forward curves and spreads and when a model can be realized by a finite-dimensional state process. We illustrate the general theory in a number of model classes and examples, providing explicit constructions of finite-dimensional realizations. Based on these theoretical results, we perform the calibration of a three-curve Hull–White model to market data and analyse the stability of the estimated parameters. [ABSTRACT FROM AUTHOR]

We develop and implement a non-parametric method for joint exact calibration of a local volatility model and a correlated stochastic short rate model using semimartingale optimal transport. The method relies on the duality results established in Joseph et al. (Calibration of local volatility models with stochastic interest rates using optimal transport, 2023). and jointly calibrates the whole equity-rate dynamics. It uses an iterative approach which starts with a parametric model and tries to stay close to it, until a perfect calibration is obtained. We demonstrate the performance of our approach on market data using European SPX options and European cap interest rate options. Finally, we compare the joint calibration approach with the sequential calibration, in which the short rate model is calibrated first and frozen. [ABSTRACT FROM AUTHOR]

Agents' beliefs regarding future monetary policy changes influence their current decisions. However, these expectations may not always materialize in the future. This study shows that the monetary fundamental shocks (exogenous changes consistent with expectations) stabilize output and inflation, while the noise shocks (biased beliefs that fail to be realized in the future) increase economic fluctuations. Moreover, factors that amplify financial frictions—the spread between the capital return of entrepreneurs and the risk‐free interest rate of a central bank—can increase anticipation effects associated with these two types of monetary policy shocks. [ABSTRACT FROM AUTHOR]

The valuation of equity-linked annuity (EIA) has been extensively studied, while few papers consider the impact of long-range dependence (LRD) features on financial and mortality dynamics in EIAs' valuation. To characterise the LRD feature, we adopt the fractional Brownian motion (FBM) in modelling the dynamics of asset prices and mortality intensities, in which clustering jumps are captured by the compound Hawkes process. Besides, the interest rate dynamic is driven by the FBM and correlates to the asset price dynamic. Numerical analyses show that ignorance of the LRD feature and the jump component in the modelling framework could lead to a potential deficiency in the reserve and solvency capital of EIA policies. [ABSTRACT FROM AUTHOR]

Following the end of the coronavirus pandemic, the European Central Bank (ECB) was confronted with an unprecedented increase in energy prices. This led to consumer price inflation in the euro area far beyond the ECB's inflation target of two percent, at times up to 10 percent. At the same time, the euro area economy was threatened by a recession, which resulted in the ECB facing conflicting objectives of stabilizing the economy and combating inflation. Estimates show that while the ECB's policy strategy of maintaining a low level of interest rates did improve the economy, it also exacerbated the rise in energy prices. The empirical analysis demonstrates that an interest rate hike at the beginning of the energy crisis would have stabilized inflation more effectively. Tightening monetary policy would have curbed energy demand and caused the euro to appreciate, which would have led to a more rapid decline in energy prices. In this counterfactual scenario, the euro area would have had to endure a brief recession, but the overall economic situation would have stabilized by the fourth quarter of 2023. The ECB would likely have been better able to follow its price stability mandate if a capital markets and fiscal union existed in the euro area. [ABSTRACT FROM AUTHOR]

AbstractWith the development of financial markets, the trading of financial derivatives has become more flexible. To meet the demands of investors, over-the-counter (OTC) trading of options has also become increasingly frequent, raising concerns about accurately pricing vulnerable options. This study investigates the pricing problem of European vulnerable options under the sub-mixed fractional jump-diffusion (SMFJ) model. Firstly, the underlying asset price model and the counterparty company value model are established under the SMFJ model with a sub-mixed fractional Vasicek stochastic interest rate. Then, analytical solutions for the European vulnerable options are obtained using the quasi-martingale measure transformation and the risk-neutral pricing method. Additionally, the accuracy of the pricing formula is verified through the Monte Carlo simulation method. Finally, the rationality and validity of the established model are confirmed by numerical simulations, and the influence of key parameters on the pricing models is analyzed. [ABSTRACT FROM AUTHOR]

As the second largest bond market in the world, China's bond market has attracted extensive attention in recent years. Given its importance in facilitating financing arrangements and informing investment decisions, accurate bond coupon prediction is valuable. This paper proposes an ensemble model combining TabNet, DeepFM, and XGBoost for predicting the coupons of investment-grade corporate bonds. Specifically, to optimize the hyperparameters of the proposed model, an improved butterfly optimization algorithm incorporating the concepts of good point sets, refraction opposition-based learning, switching probability adjustment, and Solis & Wets search strategies is developed. Extensive experiments using data on China's investment-grade corporate bonds demonstrate the superior performance of the proposed model in the accuracy of bond coupon predictions. Additionally, the importance of various features has been discussed. The results show that the base interest rate for valuation and term to maturity are important to bond coupon predictions obtained by the proposed model. [ABSTRACT FROM AUTHOR]

To address marketing challenges in the agricultural sector, provide financial support for small-scale farmers over marketing seasons, manage price risks of agricultural products, and enhance the functioning of agricultural mercantile exchanges, it is attainable to implement an efficient and compliant warehouse receipt system (WRS) that aligns with the legal, institutional, social, and economic-financial conditions of a country. The aim of this study is to design, simulate, and assess the feasibility of an innovative WRS in the agricultural sector. To achieve this, a WRS was designed and evaluated for maize crop in Iran. The research methodology of this study is divided into three main parts: design, simulation, and feasibility assessment of the WRS. The design process incorporated the FAO-provided (2009) warehouse receipt system development, considering the experiences of various countries and the institutional and financial regulations specific to Iran. Additionally, a dynamic programming model was used to simulate the system, and an agent-based model was utilized for system feasibility assessment. The study results demonstrated that it is possible to design an innovative and efficient WRS by involving five key actors, including farmers, buyers (maize traders), banks, mercantile exchange market, and the warehouse (governmental institution), and establishing clear communications among them. Based on simulation results using dynamic programming model, it was evident that four parameters, namely the annualized loan interest rate, the valuation coefficient for loan collateral, price volatility of the product over the marketing season, and the warehouse cost-to-product value ratio, significantly impact the adoption of the WRS by farmers. In conclusion, the findings from the agent-based model revealed that setting the annualized loan interest rate at 8%, a collateral valuation coefficient of 85%, price fluctuations over the non-harvest time at 60%, and a warehouse cost-to-product value ratio of 2% can result in the participation of nearly 100% of farmers in the proposed WRS. [ABSTRACT FROM AUTHOR]

The article "Climate-Related Financial Stability Risks for the United States: Methods and Applications" examines various models used to study climate-related financial stability risks (CRFSRs) in the U.S. It discusses the strengths and weaknesses of ten types of models and their suitability for assessing CRFSRs, noting a high level of uncertainty in current assessments. The text also delves into the methodology of natural capital analysis, emphasizing the importance of measuring firms' exposure to natural resource degradation and the impacts on business models. It concludes by suggesting ways to combine existing methodologies for a more comprehensive understanding of climate risks and vulnerabilities, highlighting the need for further research in integrating climate-related risks into modeling frameworks. [Extracted from the article]

Complex Machine Learning (ML) models used to support decision-making in peer-to-peer (P2P) lending often lack clear, accurate, and interpretable explanations. While the game-theoretic concept of Shapley values and its computationally efficient variant Kernel SHAP may be employed for this aim, similarly to other existing methods, the latter makes the assumption that the features are independent. The assumption of uncorrelated features in credit risk management is fairly restrictive and, thus, prediction explanations coming from correlated features might result in highly misleading Shapley values, even when considering simple models. We therefore propose an evaluation of different dependent-feature estimation methods of Kernel SHAP for classification purposes in credit risk management. We show that dependent-feature estimation of Shapley values can improve the understanding of true prediction explanations, their robustness and is essential for better identifying the most relevant variables to default predictions coming from black-box ML models. RESEARCH HIGHLIGHTS: We propose estimation of feature-dependent Shapley values for P2P credit risk management We consider different linear and non-linear predictive models with varying degrees of dependence Dependent feature estimation of Shapley values can improve prediction explanations and their robustness Loan amount and interest rate are the most determinant features to loan default prediction explanations [ABSTRACT FROM AUTHOR]