言用的跨学科概念平台—信用的基本问题研究系列之一

各学科的信用研究一直没能实现很好的进展。一个重要根源是，传统的信用解释不能为各学科的信用研究提供一个统一的概念平台，以促成各个学科的研究形成合力。通过对信用本身特性的分析可以发现，信用的本质性规定可重新界定为“信用即信任之效用”。这一新界定能够使多学科的信用概念找到一个统一的基础，能够消解传统信用概念使用中的矛盾，能够很好地理顺信用与其他相关概念的关系，从而可以成为多学科信用研究的概念平台。     

Deciphering big data in consumer credit evaluation

This paper examines the impact of large-scale alternative data on predicting consumer delinquency. Using a proprietary double-blinded test from a traditional lender, we find that the big data credit score predicts an individual’s likelihood of defaulting on a loan with 18.4% greater accuracy than the lender’s internal score. Moreover, the impact of the big data credit score is more significant when evaluating borrowers without public credit records. We also provide evidence that big data have the potential to correct financial misreporting.     

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.     

Pure jump models for pricing and hedging VIX derivatives

Recent non-parametric statistical analysis of high-frequency VIX data (Todorov and Tauchen, 2011) reveals that VIX dynamics is a pure jump semimartingale with infinite jump activity and infinite variation. To our best knowledge, existing models in the literature for pricing and hedging VIX derivatives do not have these features. This paper fills this gap by developing a novel class of parsimonious pure jump models with such features for VIX based on the additive time change technique proposed in Li et al., 2016a, Li et al., 2016b. We time change the 3/2 diffusion by a class of additive subordinators with infinite activity, yielding pure jump Markov semimartingales with infinite activity and infinite variation. These processes have time and state dependent jumps that are mean reverting and are able to capture stylized features of VIX. Our models take the initial term structure of VIX futures as input and are analytically tractable for pricing VIX futures and European options via eigenfunction expansions. Through calibration exercises, we show that our model is able to achieve excellent fit for the VIX implied volatility surface which typically exhibits very steep skews. Comparison to two other models in terms of calibration reveals that our model performs better both in-sample and out-of-sample. We explain the ability of our model to fit the volatility surface by evaluating the matching of moments implied from market VIX option prices. To hedge VIX options, we develop a dynamic strategy which minimizes instantaneous jump risk at each rebalancing time while controlling transaction cost. Its effectiveness is demonstrated through a simulation study on hedging Bermudan style VIX options.