Modelling the Term Structure of Hong Kong Inter-Bank Offered Rates （HIBOR）

Different single-factor models are used to estimate the term structure of Hong Kong Inter-Bank Offered Rates （HIBOR）. These models use stochastic differential equations which effectively reflect market characteristics of short- and long-term interest rates, such as capability of mean reversion and interest rate level fluctuation. For the period from 2005 to early 2007, the economy of Hong Kong had been relatively stable with pretty low volatilities in interest rate. However, starting from 2008 to beginning of 2012, the Hong Kong and the world economies had been steering from relatively stable to fluctuations, the 2008 financial tsunami initiated by the U,S. had been causing financial instability globally. With the U.S： government taking quantitative easing monetary policy, U.S. interest rates fluctuated and submerged rapidly. Volatility of HIBOR was extremely sensitive to fluctuation of U.S. interest rates, since Hong Kong dollar exchange rate has been pegged with U.S. dollar. In short, during the period of early 2008 to early 2012, volatility of short-term interest rate was extremely sensitive. Obviously, the term structure of interest rate for these two periods had made major shift, combining the two periods would lead to unfavorable econometric results.

P2P network lending in the credit risk rating of the individual

P2P lending network is person to person lending network, lnternet-based applications, individuals lending financial model to others through the network intermediary,＇ platform. Currently P2P lending network has developed rapidly, but the P2P network lending platform also are lacing increasing risks, the biggest risk is credit risk. This article from the credit rating perspective, comparative analysis of the existing credit rating methodology, Analysis to establish a relatively sound credit rating mechanisms, thus reducing credit risk.

Track correlation algorithm based on CNN-LSTM for swarm targets

The rapid development of unmanned aerial vehicle(UAV) swarm, a new type of aerial threat target, has brought great pressure to the air defense early warning system. At present, most of the track correlation algorithms only use part of the target location, speed, and other information for correlation.In this paper, the artificial neural network method is used to establish the corresponding intelligent track correlation model and method according to the characteristics of swarm targets.Precisely, a route correlation method based on convolutional neural networks (CNN) and long short-term memory (LSTM)Neural network is designed. In this model, the CNN is used to extract the formation characteristics of UAV swarm and the spatial position characteristics of single UAV track in the formation,while the LSTM is used to extract the time characteristics of UAV swarm. Experimental results show that compared with the traditional algorithms, the algorithm based on CNN-LSTM neural network can make full use of multiple feature information of the target, and has better robustness and accuracy for swarm targets.

民间借贷利率司法管制上限的检视与重构——以对中小企业融资的影响为切入

实施4倍LPR上限旨在调低借贷利率,降低中小企业综合融资成本。但LPR自公布以来整体呈现下降态势,且有进一步下调空间,现有利率上限低于我国长期历史利率与市场平均利率,其“一刀切”的规制模式亦忽略了民间借贷的多元性,由此引发的金融抑制效应可能造成借贷资金供给减少,进而加剧中小企业的融资困境。分类调整可以优化现有的司法管制模式,区分生产经营类借贷与生活消费类借贷,适度放松对前者的管制以缓解借贷人“惜贷”的情况;基于利息期限结构的特征区分短期、中期和长期借贷,允许5年以上的长期借贷准用5年期4倍LPR的上限。通过实现司法管制的精细化与差异化,弥补因4倍LPR上限调整方式给中小企业融资所造成的负面溢出效应。

Predicting COVID-19 fatality rate based on age group using LSTM

Objective: To predict the daily incidence and fatality rates based on long short-term memory(LSTM) in 4 age groups of COVID-19 patients in Mazandaran Province, Iran.Methods: To predict the daily incidence and fatality rates by age groups, this epidemiological study was conducted based on the LSTM model. All data of COVID-19 disease were collected daily for training the LSTM model from February 22, 2020 to April 10, 2021 in the Mazandaran University of Medical Sciences. We defined 4 age groups, i.e., patients under 29, between 30 and 49, between 50 and 59, and over 60 years old. Then, LSTM models were applied to predict the trend of daily incidence and fatality rates from 14 to 40 days in different age groups. The results of different methods were compared with each other.Results: This study evaluated 5 0826 patients and 5 109 deaths with COVID-19 daily in 20 cities of Mazandaran Province. Among the patients, 25 240 were females(49.7%), and 25 586 were males(50.3%). The predicted daily incidence rates on April 11, 2021 were 91.76, 155.84, 150.03, and 325.99 per 100 000 people, respectively;for the fourteenth day April 24, 2021, the predicted daily incidence rates were 35.91, 92.90, 83.74, and 225.68 in each group per 100 000 people. Furthermore, the predicted average daily incidence rates in 40 days for the 4 age groups were 34.25, 95.68, 76.43, and 210.80 per 100 000 people, and the daily fatality rates were 8.38, 4.18, 3.40, 22.53 per 100 000 people according to the established LSTM model. The findings demonstrated the daily incidence and fatality rates of 417.16 and 38.49 per 100 000 people for all age groups over the next 40 days. Conclusions: The results highlighted the proper performance of the LSTM model for predicting the daily incidence and fatality rates. It can clarify the path of spread or decline of the COVID-19 outbreak and the priority of vaccination in age groups.

One-year follow-up study of Helicobacter pylori eradication rate with ^(13)C-urea breath test after 3-d and 7-d rabeprazole-based triple therapy

AIM: To investigate the long-term role of a 3-d rabeprazole-based triple therapy in patients with Helicobacter pylori (H pylori)-infected active peptic ulcers. METHODS: We prospectively studied 115 consecutive patients with H pylori-infected active peptic ulcers. H pylori infection was confirmed if any two of H pylori DNA, histology, and rapid urease test were positive. Patients were assigned to either an open-labeled 3-d course of oral amoxicillin 1 000 mg b.i.d., clarithromycin 500 mg b.i.d., and rabeprazole 20 mg b.i.d., or 7-d course of oral amoxicillin 1 000 mg b.i.d., clarithromycin 500 mg b.i.d., and rabeprazole 20 mg b.i.d. Subsequently, all patients received oral rabeprazole 20 mg once daily until the 8th wk. Three months after therapy, all patients were followed-up endoscopically for the peptic ulcer, H pylori DNA, histology, and rapid urease test. One year after therapy, H pylori infection was tested using the 13C-urea breath test. RESULTS: The ulcer healing rates 3 mo after therapy were 81.0% vs 75.4% for the 3-d and 7-d groups [intention-to-treat (ITT) analysis, P=0.47] respectively, and 90.4% vs 89.6% for the 3-d and 7-d groups [per-protocol (PP) analysis, P=0.89] respectively. The eradication rates 3 mo after therapy were 75.9% vs 73.7% for the 3-d and 7-d groups (ITT, P=0.79) respectively, and 84.6% vs 87.5% for the 3-d and 7-d groups (PP, P=0.68) respectively. One year after therapy, seventy-five patients returned to receive the 13C-urea breath test, and the eradication rates were 78.4% vs 81.6% in 3-d and 7-d groups (PP, P=0.73) respectively. CONCLUSION: Our study showed the eradication rates against H pylori infection 3 and 12 mo after triple therapy were not different between the 3-d and 7-d rabeprazole-based groups. Therefore, the 3-d rabeprazole-based triple therapy may be an alternative treatment for peptic ulcers with H pylori infection.

Study on Relation Between Dynamic Pattern of Regional Vertical Strain Rate and Several Strong Earthquakes such as Lijiang(M_s7.0)and Menyuan(M_s6.4)Earthquakes

Making use of the method of obtaining regional vertical strain rate from regional preciseleveling data and gaining dynamic pattern combining with deformation data on spanningfaults, the regional vertical strain dynamic evolution characteristics of several moderatelystrong earthquakes such as Lijiang (M_s 7.0) and Menyuan (M_s 6.4) earthquakes occurredin crustal deformation monitoring areas located in the western Yunnan and Qilianshan-Hexiregion. Based on the above-mentioned facts, by studying the time-space nonhomogeneity andstrain energy accumulation status, some criteria for judging the medium. and short-termstrong seismic risk regions according to the regional vertical strain rate dynamic informationare proposed.

LPR新机制下利率锚的最优选择

贷款市场报价利率LPR改革作为疏通货币政策传导路径的关键手段,最大特点是引入中期借贷便利(MLF)作为“利率锚”。以LPR新机制改革为切入点,运用OLS、TVP-VAR模型验证以MLF为“利率锚”的有效性,构建VAR模型探究市场化“利率锚”的最优选择问题。结果表明:LPR新机制下从贷款基准利率到MLF政策利率的“换锚”改革仅仅实现初步市场化,“利率锚”的市场化程度对货币政策传导作用尤为重要;从基准性和稳定性两个方面比较分析Shibor、Repo和DR 007三种备选利率,确定DR 007为市场化“利率锚”的最优选择,加深“利率锚”市场化程度,提高货币政策利率传导机制有效性,促进实体经济发展。

流动性创造、市场利率预期与银行利率动态调整

在银行体系局部流动性问题频发的现实背景下,深入把握流动性创造对银行利率动态调整的影响机理,是理顺我国货币政策传导的重要微观基础.本文从理论与实证上研究了流动性创造如何影响银行利率对市场利率及其预期的动态调整,并考虑了忽略预期市场利率可能产生的遗漏变量问题.研究发现:1)流动性创造对银行利率动态调整具有负向的影响,且考虑流动性创造后市场利率对存款利率的传导相对较低.2)流动性创造对银行利率动态调整的影响具有异质性,市场利率对国有及全国性股份制银行的传导不够顺畅.3)预期能够在一定程度上改善市场利率的短期传导,但无法从根本上纠正市场利率的长期传导,尤其是对于国有及全国性股份制银行而言.4)在流动性创造对银行利率动态调整的影响机制中,同业拆借具有部分中介效应,进一步验证了市场利率异质性传导的原因在于流动性创造在同业市场中存在外部融资约束效应.基于此,建议从实现存款利率并轨、提高中小银行同业市场参与度、加强预期管理着手,疏通货币政策传导渠道,优化货币政策跨周期调节.

民间借贷法律规制对犯罪的影响——基于利率上限调整和高利贷入罪的实证研究

民间借贷时常引发犯罪行为,这是民间借贷利率管制和高利贷入罪的重要理由。本文采用中国裁判文书网刑事一审判决书的犯罪数据,基于民间借贷利率上限调整和高利贷入罪的准自然实验,利用双重差分模型实证检验了民间借贷法律规制对犯罪的影响。结果显示,民间借贷利率上限提高会增加非法吸收公众存款罪、集资诈骗罪、诈骗罪、合同诈骗罪和赌博罪,而高利贷入罪不但没有遏制民间借贷相关犯罪,反而增加了非法吸收公众存款罪、诈骗罪、合同诈骗罪、强迫交易罪和敲诈勒索罪。进一步分析发现,小额贷款公司对民间借贷相关犯罪和高利贷入罪所引发的犯罪具有抑制作用。基于溯因推理,对于这三方面事实的最佳解释是,民间借贷引发犯罪的重要机制在于民间资金需求无法得到满足。因此,防治民间借贷相关犯罪问题的主要政策措施应是缓解资金供需矛盾。

放开贷款利率管制对企业创新投资的影响研究

基于中国贷款利率市场化的准自然实验,利用沪深A股制造业上市公司2007—2020年数据,对放开贷款利率管制后的企业创新投资行为进行了研究。实证结果表明,放开贷款利率管制显著提升了企业创新投资水平,而这种提升作用主要通过增加企业长期贷款规模来实现。同时,相对于融资约束较小、技术水平较低的企业,放开贷款利率管制对企业创新投资的促进作用在融资约束较大、技术水平较高的企业中更为明显。

地方政府债券发行如何影响贷款利率?

基于2015—2021年31个省(区、市)的面板数据,采用时间和个体双向固定效应模型实证检验地方政府债券发行如何影响贷款利率。结果发现,地方政府债券发行会通过影响上海银行间同业拆放利率(Shibor),促进贷款利率下行,尤其在西部欠发达地区的影响效应最为明显。鉴于此,应注重积极的财政政策与稳健的货币政策协调配合,合理安排地方政府债券发行的规模和频次,同时做好市场预期引导,增强货币政策调控效果。

吉林省法人银行贷款让利空间测算分析

随着LPR形成机制的改革完善,LPR充分发挥了方向性和指导性作用,打破了贷款利率隐性下限,畅通了利率传导渠道,促进了企业贷款利率明显下行。近三年,吉林省银行业金融机构对实体经济让利取得了显著成效,但吉林省地方法人银行贷款利率明显高于全国性银行,是推动降低实体经济贷款成本的重点。为探究省内法人银行机构让利空间,本文根据商业银行存贷款利率定价机制和资产扩张受资本充足率约束等基本原理,构建贷款利率下降空间测算模型,测算出2022年吉林省地方法人银行实际贷款利率下降空间为50个基点左右。

ADS-B Reception Error Correction Based on the LSTM Neural-Network Model

Standard automatic dependent surveillance broadcast (ADS-B) reception algorithms offer considerable performance at high signal-to-noise ratios (SNRs). However, the performance of ADS-B algorithms in applications can be problematic at low SNRs and in high interference situations, as detecting and decoding techniques may not perform correctly in such circumstances. In addition, conventional error correction algorithms have limitations in their ability to correct errors in ADS-B messages, as the bit and confidence values may be declared inaccurately in the event of low SNRs and high interference. The principal goal of this paper is to deploy a Long Short-Term Memory (LSTM) recurrent neural network model for error correction in conjunction with a conventional algorithm. The data of various flights are collected and cleaned in an initial stage. The clean data is divided randomly into training and test sets. Next, the LSTM model is trained based on the training dataset, and then the model is evaluated based on the test dataset. The proposed model not only improves the ADS-B In packet error correction rate (PECR), but it also enhances the ADS-B In terms of sensitivity. The performance evaluation results reveal that the proposed scheme is achievable and efficient for the avionics industry. It is worth noting that the proposed algorithm is not dependent on conventional algorithms’ prerequisites.

我国民间借贷利率规制的演进、评析与优化路径

民间借贷的蓬勃发展使法律对其核心要素——利率进行规制。1991年和2015年关于民间借贷司法解释、《民法典》及2020年司法解释对民间借贷利率规制在自由放任、管控、适度放开与再度收紧之间徘徊。在对民间借贷利率规制的制度演进进行梳理的基础上,对演进各阶段进行评析,总结利率规制反复与回归的态势,以及利率规制伴随着打击高利贷制止犯罪的特点,进而指出利率规制存在的问题与不足:利率规制难以适应民间借贷负外部性可能引发的公共风险;政府监管部门对利率规制的态度摇摆与暧昧;司法对利率规制的效果仍有待提升等。为此,应当转变利率规制理念,树立“疏”主“禁”辅的理念;建立健全放贷人制度规则,平衡借贷双方权益;探索制定民间借贷利率分类动态指引,提升司法治理效果;引入激励相容法律规制,创新民间借贷监管模式。

基于最小二乘法的网络借贷模型

网络借贷是近年来出现的新兴事物,研究网络借贷中借款用途对借贷成功率的影响.通过使用美国最大的P2P网络借贷Prosper网站2007年以来的数据,以单一变量原则建立数学模型,并使用最小二乘法进行参数估计,回归实证研究表明:同等条件下,学生借款比其他种借款成功率低3.4%,分析其原因发现学生还款率并不比其他的低,因此对学生存在直觉歧视.通过类似的方法,还发现用于汽车或者其他方面的债务更容易借到钱.同时,实证研究还得出了其他若干因素,如借款金额、利率等对借款成功率的影响.

零借阅中文图书出版社分析与馆藏优化策略研究

通过对上海海事大学图书馆2010—2012年入藏的可供借阅中文图书的出版社分析发现,低零借阅率中文图书出版社的特征为:符合大量读者阅读需求,出版图书品质高,出版品种较集中;高零借阅率中文图书出版社的特征为:专业读者数量有限,出版品种多且分散,出版图书同质化严重。根据统计分析结果,图书馆可从以下方面入手优化馆藏:在采访上,圈定不适宜出版社、优质出版社和核心出版社;在典藏流通上,进行复本剔除或密集排架、开展阅读推广服务。

借款描述对P2P网络借贷行为影响的实证研究

以P2P网络借贷行业的领军者——人人贷的交易观测作为研究样本,研究借款描述对P2P网络借贷行为的影响。结果发现:借款人信用等级越低,越倾向于添加借款描述,以降低借贷双方的信息不对称问题;在控制了其他变量的情况下,借款描述展示的人格数量越多,越能吸引投标人,满标用时越快,借款人越容易获得借款且借款违约率越低;进一步分析借款描述中展示的不同人格对借贷行为影响的程度,发现"勤奋"人格对借款成功率和投标人数的影响最大,而"成功"人格对投标完成时间和借款违约率的影响最大,其余的人格也都对借贷行为产生不同程度的影响。

非完全利率市场化下网络借贷的利率定价有效吗--来自“人人贷”的微观借贷证据

P2P作为传统融资模式的有效补充,对缓解长尾人群的融资约束、实现金融的普惠职能有十分重要的促进作用。不同于国外P rosp e r的利率竞价机制,我国P2P的借款利率是由借款人设定的,在信息不对称和非完全市场化双重因素作用下形成的利率是否有效?本文借助"人人贷"上的借款订单数据,从订单达成的时间、满标参与人数、订单完成度和参与人数比例四个维度检验其有效性。本文发现借款利率并没有起到明显的违约风险信号的作用,投资者首先注重收益而后才会意识到风险,因此借款人往往设定较高的利率以减少订单达成的时间和提高投资者的参与度。进一步本文发现,借贷双方经过多次利率博弈后建立的声誉可以缓解借款人的融资约束。

地域差异如何影响P2P平台借贷的行为——基于“人人贷”的经验证据

本文以人人贷平台的借贷交易数据为样本,分别从各省经济水平、金融生态环境、教育程度和正规金融普及程度等四个角度,考察了地域差异对P2P网络借贷行为的影响。研究结果表明:我国P2P借贷市场上,不同地域之间的借款成功率存在显著的差异,地域歧视已经存在于互联网金融领域。具体而言,经济水平越高、金融生态环境越好、教育程度越高的省份的借款人更容易获得借款;而正规金融普及程度对借款成功率有负向影响,表明P2P网络借贷是正规金融的有效补充。本文的结果为深入理解互联网金融地域歧视背后的原因,以及创造公平和谐的网络借贷环境提供了启示。