Performance assessment of ensemble learning systems in financial data classification

Financial data classification plays an important role in investment and banking industry with the purpose to control default risk, improve cash and select the best customers. Ensemble learning and classification systems are becoming gradually more applied to classify financial data where outputs from different classification systems are combined. The objective of this research is to assess the relative performance of existing state‐of‐the‐art ensemble learning and classification systems with applications to corporate bankruptcy prediction and credit scoring. The considered ensemble systems include AdaBoost, LogitBoost, RUSBoost, subspace, and bagging ensemble system. The experimental results from three datasets: one is composed of quantitative attributes, one encompasses qualitative data, and another one combines both quantitative and qualitative attributes. By using ten‐fold cross‐validation method, the experimental results show that AdaBoost is effective in terms of low classification error, limited complexity, and short time processing of the data. In addition, the experimental results show that ensemble classification systems outperform existing models that were recently validated on the same databases. Therefore, ensemble classification system can be employed to increase the reliability and consistency of financial data classification task.     

The Bank Lending Channel Revisited

A central proposition in research on the role of banks in the transmission mechanism is that monetary policy imparts a direct impact on deposits and that deposits act as the driving force of bank lending. This paper argues that the emphasis on policy‐induced changes in deposits is misplaced. A reformulation of the bank lending channel is proposed that works primarily through the impact of monetary policy on banks’ balance sheet strength and risk perception. Such a recasting implies, contrary to conventional wisdom, that greater reliance on market‐based funding enhances the importance of the channel.     

The productivity of agricultural credit in India

This study examines the nature of the relationship between formal agricultural credit and agricultural Gross Domestic Product (GDP) in India, specifically the role of the former in supporting agricultural growth, using state level panel data covering the period 1995–1996 to 2011–2012. The study uses a mediation analysis framework to map the pathways through which institutional credit relates to agricultural GDP relying on a control function approach to tackle the problem of endogeneity. The findings from the analysis suggest that over this period, all the inputs are highly responsive to an increase in institutional credit to agriculture. A 10% increase in credit flow in nominal terms leads to an increase by 1.7% in fertilizers (N, P, K) consumption in physical quantities, 5.1% increase in the tonnes of pesticides, 10.8% increase in tractor purchases. Overall, it seems quite clear that input use is sensitive to credit flow, whereas GDP of agriculture is not. Credit seems therefore to be an enabling input, but one whose effectiveness is undermined by low technical efficiency and productivity.     

Usury laws and private credit in Lima,Peru. Evidence from notarized records

I examine the impact of usury laws on the Peruvian credit market between 1825 and 1852. Using a new data set of nearly 2,000 loans from archival sources, I show that the repeal of colonial anti-usury laws in early 1833 had an important effect on the allocation of credit in Lima. It increased interest rates and promoted access to credit. Furthermore, lenders made loans with greater maturities after the repeal of usury laws.     

我国消费金融业务的发展困境及对策刍议

根据2009年银监会文件成立的四家消费金融公司，是我国在拓展内需促进经济发展模式转型过程中作出的有益尝试，在前期发展过程中体现出自身的价值。文章针对消费金融公司前期发展过程中出现的业务发展较慢等问题，进行了简要的分析评述，并结合2014年开始施行的《消费金融公司试点管理办法》，针对发展困境提出了对策与建议。     

Credit Rating and Monetary Policy Transmission to Equity Markets: Evidence from the Emerging Market

This study empirically estimates credit channel of the monetary policy and corporate stock return using daily stock return data including the sample with non-financial firms listed in Korea stock exchange (KOSPI). Empirical results support that changes in the basis rate turn out to increase equity returns in case of the firms with higher credit rating compared to the previous year. The estimation results confirm the conjecture that monetary policy has a significant impact on stock market through the channel of changes in credit rating.     

对称性交易：破解农村信贷供需衔接困局的内在逻辑——基于山东农村金融创新案例的分析

摘要：在现有农村土地产权制度下，土地及依附于其上的各类生产要素不具有充分交易的条件，进而因缺乏合格的交易客体而使农村金融交易呈现非对称状态。人民银行济南分行立足于满足枣庄流转土地和寿光蔬菜订单的需求，在谋求对称农村金融交易主体上寻求突破，较好顺应了农村土地规模化和集约化经营的主流趋势，对破解农村金融交易困境有一定借鉴意义。     

Is ex-post credit risk affected by the cycles? The case of Italian banks

The objective of this research is to empirically examine if both credit and business cycle affect the ex-post credit risk (i.e. non-performing loans) in the banking system of Italy for the period 1995Q1–2014Q1. The increase in NPLs post-2008 has put into question the robustness of many European banks and the stability of the whole sector. It still remains a serious challenge, especially in Italy which is one of the countries that hit by the financial crisis. By employing fixed and random effects and a dynamic GMM estimation as econometric methodologies I find results that underline common causes for NPLs. Higher NPLs in Italy are mostly due to worse macroeconomic conditions (i.e. bad phase of business cycle) and due to excess credit. Through a Granger causality test, my arguments found even more support. Such findings can be helpful when designing macro-prudential as well as NPL resolution policies.     

Bond finance,bank credit,and aggregate fluctuations in an open economy

Corporate sectors in emerging markets have noticeably increased their reliance on foreign financing, presumably reflecting low global interest rates. The evidence also shows a rebalancing from bank loans towards bonds. To study these developments, we develop a dynamic open economy model where these modes of finance are determined endogenously. The model replicates the stylized facts following a drop in world interest rates; in particular, rebalancing towards bonds occurs because bank credit becomes relatively more expensive, reflecting the scarcity of bank equity. More generally, the model is suitable for studying interactions between modes of finance and the macroeconomy.     

Fluctuating levels of personal role engagement within the working day: A multilevel study

In this diary study, we examined a theoretical model in which the psychological conditions of meaningfulness, availability, and safety serve as mechanisms through which the work context during discrete situations within the workday influences “state” engagement. We further theorised that a person's “trait” level of engagement would exert cross‐level effects on the state level relationships. Multilevel analyses based on a sample of 124 individuals in six organisations and 1,446 situational observations revealed that meaningfulness and availability (but not safety) mediated the relationships between perceptions of the work context and state engagement. High levels of trait engagement strengthened the within‐person relation between availability and state engagement, yet weakened the within‐person relation between meaningfulness and state engagement, suggesting two different processes may be at play. Overall, the findings advance our understanding of engagement as a multilevel and temporally dynamic psychological phenomenon and promote a contextually based HRM approach to facilitating engagement.