Asymmetric effects of housing wealth on college enrolment

We investigate the impact of housing wealth, credit availability and financial distress on college enrolment decisions. We find that housing wealth is negatively related to enrolment in public schools and positively related to enrolment in private schools. This evidence suggests that, on average, students substituted away from private schools towards public institutions during the recent financial crisis.     

Dynamic response of bank-intermediated trade finance to a global liquidity shock

This paper investigates the bank-level responses of a bank-intermediated instrument of trade finance to a negative global liquidity shock in Korea. Using a factor-augmented vector autoregression approach, the results show that there exists significant heterogeneity in bank-level trade-finance responses to a global liquidity shock. In addition, we find that the source of the heterogeneity is the bank-level foreign currency liquidity condition; banks with a better foreign currency liquidity condition may dampen the negative impact of a global liquidity shock on trade-finance.     

Market impact: a systematic study of the high frequency options market

This paper deals with a fundamental subject that has seldom been addressed in recent years, that of market impact in the options market. Our analysis is based on a proprietary database of metaorders—large orders that are split into smaller pieces before being sent to the market—on one of the main Asian markets. In line with our previous work on the equity market [Said, E., Bel Hadj Ayed, A., Husson, A. and Abergel, F., Market impact: A systematic study of limit orders. Mark. Microstruct. Liq., 2018, 3(3&4), 1850008.], we propose an algorithmic approach to identify metaorders, based on some implied volatility parameters, the at the money forward volatility and at the money forward skew. In both cases, we obtain results similar to the now well-understood equity market: Square-Root Law, Fair Pricing Condition and Market Impact Dynamics.     

互联网金融规制与市场有效性改善*——来自中国网络借贷行业的证据

中国的互联网金融经历了一个先创新发展后监管规制的过程，本文通过对网络借贷行业的实证研究，分析监管规则的出台实施对新型互联网融资市场有效性的影响。实证结果表明，网络借贷平台资金的银行存管、持有ICP证等强制性规定缓解了投资者、平台企业与借款人之间的信息不对称，对克服早期平台间通过竞相承诺高回报率来吸引投资者导致的“柠檬市场”问题、对解决网贷市场上缺乏平台风险性高低有效信号的问题都起到了正向作用，有助于互联网融资市场的有效性提高。     

Drivers of eWOM engagement on social media for luxury consumers: Analysis,implications, and future research directions

The rapid industrialization and growth across the world have fostered the consumption of luxury fashion brands. Electronic word-of- mouth on social media (eWOM) is fast becoming an effective and germane strategy to engage luxury consumers through posting pictures, sharing reviews, and communicating information on platforms like Facebook, Instagram, and TikTok. Extant research has not examined the antecedents and drivers that lead to eWOM behavior. We leverage self-congruity theory and through its focal lens, our study addresses this research gap through a survey conducted with 453 consumers in Mexico, Latin America's fastest growing market. Our results indicate that need for status, susceptibility to normative influence, and luxury brand involvement, moderated by authentic pride and social media influencers lead to eWOM behavior on social media. We also demonstrate that luxury brand involvement and susceptibility to normative influence mediate the relationship between need for status and eWOM behavior on social media. The study provides important implications to managers and researchers by suggesting long-term actionable strategies for growth that can help luxury firms develop a sustainable competitive advantage over rivals and competitors.     

刑事涉财产执行中的案外人权益救济——以案外人权益救济程序的当事人构造为视角

刑事涉财产执行程序因采取移送执行模式而被误认为不存在申请执行人，使得刑事涉财产执行程序及其衍生的案外人权益救济程序过分依赖执行法院的职权主义。在刑事附带民事诉讼裁判、追缴或责令退赔违法所得并返还被害人判项、责令被免予刑事处罚的被告人赔偿被害人损失判项的执行程序中，案外人权益救济程序原则上应以被害人为申请执行人，并参照适用民事强制执行程序中的案外人权益救济制度。其他刑事涉财产执行程序应以检察机关为申请执行人。除非出现被执行人逃避执行或者案外人对执行标的提出排除执行请求等特殊情形，作为申请执行人的检察机关通常无须现实参加执行程序。     

Machine learning for financial transaction classification across companies using character-level word embeddings of text fields

An important initial step in accounting is mapping financial transfers to the corresponding accounts. We devised machine-learning-based systems that automate this process. They use word embeddings with character-level features to process transaction texts. When considering 473 companies independently, our approach achieved an average top-1 accuracy of 80.50%, outperforming baselines that exclude the transaction texts or rely on a lexical bag-of-words text representation. We extended the approach to generalizes across companies and even across different corporate sectors. After standardization of the account structures and careful feature engineering, a single classifier trained on 44 companies from 28 sectors achieved a test accuracy of more than 80%. When trained on 43 companies and tested on the remaining one, the system achieved an average performance of 64.62%. This rate increased to nearly 70% when considering only the largest sector.     

A multivariate distance nonlinear causality test based on partial distance correlation: a machine learning application to energy futures

This paper proposes a multivariate distance nonlinear causality test (MDNC) using the partial distance correlation in a time series framework. Partial distance correlation as an extension of the Brownian distance correlation calculates the distance correlation between random vectors X and Y controlling for a random vector Z. Our test can detect nonlinear lagged relationships between time series, and when integrated with machine learning methods it can improve the forecasting power. We apply our method as a feature selection procedure and combine it with the support vector machine and random forests algorithms to study the forecast of the main energy financial time series (oil, coal, and natural gas futures). It shows substantial improvement in forecasting the fuel energy time series in comparison to the classical Granger causality method in time series.     

我国物流业转型升级研究综述

中国经济已经到了只有转型升级才能持续健康发展的关键阶段,产业转型升级在国家政策文件和研究文献中出现的词频较高。文章以我国物流业为研究对象,从现有涉及到物流业转型升级方面的文献挖掘有效信息,梳理我国物流业转型升级研究的历史脉络,从供应链与价值链、产业集群、现代科学技术应用和产业联动四个视角对现有的物流业转型升级文献进行了总结和归纳,并从物流业转型升级的动力研究、阶段性划分研究和演进规律研究三个方面指出了现有文献的研究不足和以后可能的研究方向。其中,供应链与价值链视角侧重于物流企业的纵向角度,产业集群视角侧重于物流企业的横向角度。文章对于物流企业战略设计、政府政策的制定和理论研究具有一定的参考作用。     

正交实验设计方法在B to B电子商务体系质量改进中的应用

电子商务在全球快速地发展，中国企业面临着由B to C方式向B to B方式的转变，本文采用正交实验设计的方法来解决已建成电子商务体系的质量，以满足新的需求。