A New Approach to Predict Financial Failure： Classification and Regression Trees （CART）

The increase of competition, economic recession and financial crises has increased business failure and depending on this the researchers have attempted to develop new approaches which can yield more correct and more reliable results. The classification and regression tree （CART） is one of the new modeling techniques which is developed for this purpose. In this study, the classification and regression trees method is explained and tested the power of the financial failure prediction. CART is applied for the data of industry companies which is trade in Istanbul Stock Exchange （ISE） between 1997-2007. As a result of this study, it has been observed that, CART has a high predicting power of financial failure one, two and three years prior to failure, and profitability ratios being the most important ratios in the prediction of failure.

Short-Term Financial Time Series Forecasting Integrating Principal Component Analysis and Independent Component Analysis with Support Vector Regression

Financial time series forecasting could be beneficial for individual as well as institutional investors. But, the high noise and complexity residing in the financial data make this job extremely challenging. Over the years, many researchers have used support vector regression (SVR) quite successfully to conquer this challenge. In this paper, an SVR based forecasting model is proposed which first uses the principal component analysis (PCA) to extract the low-dimensional and efficient feature information, and then uses the independent component analysis (ICA) to preprocess the extracted features to nullify the influence of noise in the features. Experiments were carried out based on 16 years’ historical data of three prominent stocks from three different sectors listed in Dhaka Stock Exchange (DSE), Bangladesh. The predictions were made for 1 to 4 days in advance targeting the short term prediction. For comparison, the integration of PCA with SVR (PCA-SVR), ICA with SVR (ICA-SVR) and single SVR approaches were applied to evaluate the prediction accuracy of the proposed approach. Experimental results show that the proposed model (PCA-ICA-SVR) outperforms the PCA-SVR, ICA-SVR and single SVR methods.

An Early Warning Model of Financial Distress Prediction Based on Logistic-AHP-BP Neural Network Model

Ever since the appearance of"Implementation Measures for Suspending and Terminating the Listing of Loss-making Companies"in 2001,the delisting system has emerged.However,the proportion of delisted companies in China has never exceeded 1% each year.The number of delisted companies in the security market is far less than the number of companies with financial distress.The capital market lacks a good delisting system and investors lack risk identification capabilities.Financial risk is directly related to delisting risk.Therefore,an early warning model of financial distress prediction for China.s stock market can provide guidance to stakeholders such as listed companies and capital markets.This paper first explains the immature delisting system of China.s capital market and the overall high risk of listed companies.financial distress.Then,the paper further elaborates previous research on financial distress prediction model of listed companies and analyzes the advantages and disadvantages of different models.This paper chooses the Analytic Hierarchy Process(AHP)to screen out the main factors that affect the risk of financial distress.The main factors are included in Logistic regression model and BP neural network model for predicting financial distress of listed companies.The overall effect of two models are assessed and compared.Finally,this paper proposes policy implications according to empirical results.

Analysis of the Impact of Asian Financial Crisis on Shanghai's Utilization of Foregin Direct Investment

The Asian financial crisis has increasingly shown its in-fluence on the utilization of foreign direct investment inShanghai. To further explain this, the main factors thatplay important roles in the decision of foreign direct in-vestment in Shanghai are analyzed. The extent of influ-ence is measured according to the changes of those decis-ive factors. A simple linear regression model is intro-duced to help the analysis.

Forecast of steel cord demand after the financial crisis

To analyze the production and marketing of China automobile in Year 2009,and also the development of China automobile and steel cord in those 11 years.The single-element regression mathematics model was set up to analyze the steel cord demand and automobile production.It predicted that automobile production would up to 15 170 000,16 690 000 and 18 360 000 respectively from 2010 to 2012,with the confidence as of 95%,the steel cord consumption in those three years will be 1 180 000 - 1 370 000 t, 1 320 000 - 1 520 000 t and 1 470 000 - 1 680 000 t.As to the policy of China stimulation,The role of Chinese tire has converted from the export-oriented to domestic consumer smoothly,so the effect of US special protectionist tariffs is limited in China.

Fuzzy Varying Coefficient Bilinear Regression of Yield Series

We construct a fuzzy varying coefficient bilinear regression model to deal with the interval financial data and then adopt the least-squares method based on symmetric fuzzy number space. Firstly, we propose a varying coefficient model on the basis of the fuzzy bilinear regression model. Secondly, we develop the least-squares method according to the complete distance between fuzzy numbers to estimate the coefficients and test the adaptability of the proposed model by means of generalized likelihood ratio test with SSE composite index. Finally, mean square errors and mean absolutely errors are employed to evaluate and compare the fitting of fuzzy auto regression, fuzzy bilinear regression and fuzzy varying coefficient bilinear regression models, and also the forecasting of three models. Empirical analysis turns out that the proposed model has good fitting and forecasting accuracy with regard to other regression models for the capital market.

At what levels of financial development does information sharing matter?

Background:The purpose of this study is to investigate how an increase in information-sharing bureaus affects financial access.Methods:We employed contemporary and non-contemporary interactive quantile regressions in 53 African countries for the period 2004–2011.Information-sharing bureaus are proxied with public credit registries and private credit offices.Financial development dynamics involving depth(at overall economic and financial system levels),efficiency(at banking and financial system levels),activity(from banking and financial system perspectives),and size are used.Results:Two key findings are established.First,the effect of an increase in private credit bureaus is not clearly noticeable on financial access,probably because private credit agencies are still to be established in many countries.Second,an increase in public credit registries for the most part improves financial allocation efficiency and activity(or credit)between the 25th and 75th quartiles.Conclusions:As a main policy implication,countries in the top and bottom ends of the financial efficiency and activity distributions are unlikely to benefit from enhanced financial allocation efficiency as a result of an increase in public credit registries.

Impact of Financial Development on the Environmental Quality in Iran

In recent decades, undesirable environmental changes, such as global warming and greenhouse gases emission, have raised worldwide concerns. In order to achieve higher growth rate, environmental problems emerged from economic activities have turned into a controversial issue. The aim of this study is to investigate the effect of financial development on environmental quality in Iran. For this purpose, the statistical data over the period from 1970 to 2011 were used. Also by using the Auto Regression Model Distributed Lag （ARDL）, short-term and long-term relationships among the variables of model were estimated and analyzed. The results show that financial development accelerates the degradation of the environment; however, the increase in trade openness reduces the damage to environment in Iran. Error correction coefficient shows that in each period, 53% of imbalances would be justified and will approach their long-run procedure. Structural stability tests show that the estimated coefficients were stable over the period.

Can Financial Shared Services Improve Business Performance?Evidence from Chinese A-share Listed Corporations

Taking Chinese A-share listed corporations as sample,this paper studies whether the implementation of financial shared service center,an IT-based financial management practice,can significantly improve the business performance.We conduct Wilcoxon rank sum test and OLS regression model.The results show that there is a significant difference in business performance between the corporations without financial shared service center and the matching samples which have implemented financial shared service.In addition,the positive effect of financial shared services on business performance has a time-lag.As the corporations become adept on financial shared services,their business performance such as profitability,operating ability and growth could be improved steadily.Our study provides suggestions on whether corporations’might upgrade their financial system and how to evaluate the implementation results.

Correlation Analysis of Fiscal Revenue and Housing Sales Price Based on Multiple Linear Regression Model

This paper selects seven indicators of financial revenue and housing sales price in recent 19 years in China,and uses SPSS and Excel to carry out descriptive statistics,independent sample t-test,correlation analysis and regression analysis to comprehensively study the correlation between financial revenue and housing sales price in China,and establishes the relationship between financial revenue and housing sales price When the average selling price of commercial housing increases by one unit,the fiscal revenue will increase by 27.855 points.

金融监管与非银行金融部门系统性风险传染

近年来,中国系统性金融风险呈现跨部门传导效应,尤其是非银行金融部门风险传染可能成为威胁金融市场稳定的重要挑战。本文基于非银行金融部门的微观数据,采用弹性网分位数回归构建尾部风险网络,利用复杂网络分析方法动态捕捉非银行金融机构系统性风险溢出水平的演变特征,研究金融监管对非银行金融部门系统性风险传染的政策效应。研究结果显示:第一,金融部门的系统性风险溢出总水平主要来自非银行金融部门的系统性风险溢出水平,其中多元金融部门的系统性风险溢出尤为突出,证券部门和多元金融部门存在较为密切的双向系统性风险溢出;第二,2017年金融监管改革后,金融公司之间的风险网络结构密度有所降低,跨部门系统性风险溢出水平显著降低;第三,金融监管对非银行金融部门系统性风险溢出水平的影响具有明显的时变性特征,2016—2017年金融监管明显降低了系统性风险溢出水平,2018年后政策效果因受到外部冲击而有所弱化;第四,不同非银行金融部门的系统性风险溢出水平对政策冲击的响应存在差异,金融监管政策在短期内降低多元金融部门和证券部门的系统性风险溢出水平效果更为明显。本文的研究结论对完善中国金融风险防范体系、防止金融资本“脱实向虚”和健全相应的风险监管制度具有一定的参考价值。

制造业企业扩大金融活动能否推动企业价值增长?——基于上市制造业企业面板数据门限回归分析

利用随机最优控制理论模型,将制造业企业资产配置决策引入企业价值产生及波动机制,剖析了资本积累中产业资本与金融投资的动态配置决策及其与企业价值的非线性关系,并基于2003-2020年上市制造业企业面板数据进行了检验。理论分析论证了在资本配置中制造业企业的金融投资规模与其价值增长整体呈现的非线性关系。实证结果显示,资本积累初始分配时适度增加金融投资对企业价值增长具有正效应,且强度呈现由弱到强的变化趋势。采用动态指标刻画企业扩大金融活动的行为并进一步检验,结果表明:企业价值与动态金融资产配置存在双门限效应,企业扩大金融活动存在适度区间,其动态调整与期初资本配置及产业投资与金融投资的相关性有关。在缓慢增长阶段金融投资增长率较低时企业扩大金融投资可促进企业价值增长,在再分配时可反哺产业资本;当金融投资增长率超过拐点时,企业扩大金融活动将对企业价值产生负效应;而当金融投资增长率超过第二个门限值时,金融投资将对企业价值增长再次产生促进效应。

航空制造业升级的金融支撑作用研究

航空制造业作为高端制造业的代表,不仅是国家综合实力的象征,也是推动产业升级和经济转型的关键力量,同时,航空制造业的转型升级需要强有力的金融支持。金融作为现代经济的核心,其发展水平与效率直接影响到产业资本的形成、配置与运用,进而对航空制造业的升级进程产生较为深远的影响。基于此,本文在梳理评述国内外金融发展与航空制造业升级的相关理论研究的基础上,辨析金融支持航空制造业发展的作用机理,利用2008-2021年间我国18个省市的面板数据进行面板回归与门槛回归,实证检验金融发展对制造业升级的影响,并从金融发展的不同维度进行分析,根据结果确定金融支持航空制造业升级的关键着力点与弱项,最后结合理论分析与实证结果提出相关建议。

本地-流动儿童的义务教育结果公平与教育财政投入、家庭教育支出的研究

本地-流动儿童的义务教育结果公平涉及流动人口的社会融入与以人为核心城镇化进程,故值得学术研究深入探讨的议题。本文利用中国教育追踪调查数据,实证检验了教育财政投入、家庭教育支出对不同儿童义务教育结果表现的影响,结果发现:(1)基准估计揭示了教育财政投入、家庭教育支出与本地-流动儿童的学业表现间可能存在负相关性的关系,但未有明显证据表明本地儿童的学业表现优于流动儿童,稳健性检验则发现似不相关回归更富估计效率;(2)利用分样本回归的异质性分析,发现生均财政经费拨款有利于提高流动儿童和贫困家庭子女的义务教育结果表现;(3)利用分位数回归发现本地儿童在各分位点上的学业表现高于流动儿童,但估计结果并不显著,进一步利用MM分解发现本地-流动儿童的义务教育结果不平等具有“天花板效应”的鲜明特征。

金融科技对上市金融机构风险影响研究

金融科技能够显著提高金融机构服务效率,但也给金融机构带来了更多的不确定性和潜在风险。文章基于TENET网络模型构建上市金融机构风险网络,从风险输入和溢出两个层面探究金融科技对上市金融机构的影响及作用机制。研究发现,金融机构间风险输入和溢出强度存在时变特征,金融机构风险网络具有时变特征。金融科技可以抑制机构间风险输入,金融机构发展金融科技可以帮助其抵御外来风险,但发展金融科技也会增加机构间的风险溢出。金融机构间C2B、分布式计算、金融科技、网贷等发展水平差距的扩大可以减少机构间风险传染,机构间C2C、人工智能和网上支付等发展水平差距的扩大则会增加机构间风险传染。此外,机构的关联交易差距扩大也会增加机构间风险传染。

金融科技对黑龙江省居民消费水平的影响

随着科技的进步,金融科技逐渐成为推动经济发展的重要力量,对居民消费水平也产生了影响。通过实证研究,分析金融科技不同维度对黑龙江省居民消费水平的具体影响。采用回归分析方法构建了4个模型,分别考察了金融科技、金融科技发展宽度、金融科技发展深度及数字化水平对居民消费水平的影响。结果表明,金融科技指数、发展宽度和发展深度均对居民消费水平具有显著的正向影响,而数字化水平的影响不如前者显著。黑龙江省应深化金融科技发展,注重均衡性,加强风险防控,利用金融科技发展机遇推动金融服务创新,为提升居民消费水平和经济发展注入新动力。

金融科技发展的股票市场系统性风险研究

防范化解股票市场系统性风险是维护中国金融市场稳定的重要内容。以2012-2021年125家涉及14个业务部门的金融科技上市公司作为研究样本,基于分位数回归的CoVaR模型测算股票市场金融科技板块系统性风险,利用网络爬虫技术(Python)通过百度高级搜索功能爬取金融科技相关词频,构造地级市层面金融科技发展水平指标,实证检验金融科技对其股票市场系统性风险的影响。研究发现,金融科技有效抑制其股票市场系统性风险,并通过提高市场交易信息透明度、提升企业风险承担两条路径,从而降低其股票市场系统性风险。进一步研究发现,不同时间段、市场态势、市场化程度下金融科技抑制其股票市场系统性风险的程度不同。金融科技抑制其股票市场系统性风险存在时间上的异质性,金融科技虽产生风险的累积作用,但存在阶段性特征,在样本期间随着时间的推移抑制作用由弱变强,大于累积作用进而呈现总体抑制,亦可见中国金融科技监管实行的有效性;金融科技对股票市场中市场化程度较高的企业风险抑制作用较强,并在“熊市”表现更为明显。研究结论对防范化解金融科技板块系统性风险、推进金融科技良性发展提供了有益启示。

Infinite Loop?What Is Behind the Ongoing Turmoil in the Banking Sector?

The war in Ukraine is unfortunately not over,to add insult to injury,Silicon Valley Bank collapses and Credit Suisse acquired by UBS under the Swiss emergency legislation.The merger of Credit Suisse with UBS,Switzerland’s biggest bank,has also raised concerns about the proliferation of more institutions deemed“too big to fail”.Through the study of four financial crises in the past 100 years,this paper believes that behind this potential financial crisis is still the real estate bubble,but the significant problems in the United States are the most worrying.Post-financial crisis recessions are costlier and last longer than normal recessions.When credit booms are superimposed with asset price bubbles,financial crises are highly likely and economic recovery will be slower.In this paper,relative data and regression model are used to analyze the causes of the crisis;further this paper discusses the reasons behind the financial crisis and related conjectures and gives relevant development speculations.

土地流出对农村老年人健康水平的影响研究

基于2018年中国健康与养老追踪调查(CHARLS)数据,运用Ologit回归模型,实证检验土地流出是否显著改善了农村老年人的健康水平及其对健康影响的作用路径。结果显示:(1)土地流出对农村老年人身体健康有正向促进作用,但对其心理健康有消极影响。(2)子女经济支持在土地流出对老年人身体健康的影响机制中发挥了完全中介效应,对老年人心理健康的中介效应有显著负作用。(3)异质性分析结果表明,土地流出对老年人的健康影响存在区域性差异,对东部地区农村老年人健康的积极作用更为明显。因此,应进一步规范土地流出制度,加大对土地流出市场的培育和完善;建立健全社会保障体系和养老保障制度;加大对公共医疗资源的投入力度,重点关注老年人的身心健康,加强对老年人的情感关怀。

数字普惠金融、农业低碳生产与绿色全要素生产率

充分发挥数字经济的潜力,助推高质量绿色经济的发展,是实现“双碳”目标的重要路径。为此,深入考察数字普惠金融对绿色全要素生产率的影响具有重要意义。选取2011—2021年间中国各省数字普惠金融与绿色全要素生产率相关数据,采用双向固定效应模型,分析数字普惠金融、农业低碳生产与绿色全要素生产率之间的关系。研究发现,数字普惠金融的发展能够显著提高绿色全要素生产率,数字普惠金融在促进生态友好型农业实践中发挥了关键作用,特别是通过促进农地流转、提供土地交易的金融支持的方式以实现规模经营以及促进农业低碳生产,从而最终提高绿色全要素生产率。异质性分析发现,由于数字普惠金融举措的实施,处于金融基础设施初级阶段的地区在绿色全要素生产率方面显示出更明显的进步,在培育数字普惠金融指数的同时,需完善农业土地流转政策,推动农地流转标准化,制定符合地方实际情况的数字普惠金融政策。