互联网金融视角下股权众筹融资的投资风险探析

股权众筹是公司通过出让股份获得资金的一种融资方式,它的出现很大程度上解决了中小型企业融资难、融资贵的问题。但是近年来股权众筹的发展速度逐渐放缓,同时模式本身也暴露出了较高的投资风险。针对这些投资风险,论文从退出机制、外部审计和监管三个层面给出了相应的措施建议。     

汽轮机的运行和故障分析

企业的经营生产离不开电力的供应,而现阶段我国的电力供应依靠发电厂供电,通过汽轮机等一系列机械设备来产生电能。就目前的情形来看,为了保证我国更好地发展,还需要加强对电力设备的保障,而汽轮机则是其中的重要环节。     

铁路枢纽工程咽喉区复杂道岔组织施工技术研究

站场咽喉改造需在不影响铁路运营的前提下在封锁点内完成。如何安全、高效、可行地完成施工任务,关键在于制定详细可行的方案,而施工组织是决定方案是否可行的关键。因此,论文结合哈尔滨站咽喉区组合道岔的施工情况,对施工组织设计及施工技术方案进行了论述。     

风险预控管理体系在煤矿安全管理中的作用

当前我国的煤矿行业迈入了转型发展的重要时期,国家对煤矿行业的安全生产管理提出了越来越高的要求,安全生产标准化成为煤矿企业的重点工作。煤矿生产作业的特殊性决定了在各项生产作业中存在各种安全风险,作业流程的繁多性、要素的多样性加大了煤矿安全管理的难度。煤矿行业现代化的发展趋势下,风险预控管理体系的构建为煤矿安全生产目标的实现提供了保障。     

基于GONE理论的LK公司舞弊动因分析与审计风险防范

继浑水发布做空报告后,LK公司于2020年4月自曝2019年年度审计期间发现相关业务数据巨额造假,引起社会广泛关注.企业战略,尤其是商业模式,已经成为管理层产生财务报表层次重大错报风险的重要诱因.文章以GONE理论作为工具来识别和预判财务舞弊的倾向和风险,解释了企业管理层进行财务舞弊的动因.做空机构基于企业战略层面的潜在风险,有针对性地采取手段并取得了有力证据.注册会计师行业应思考如何发挥职业判断在防范审计风险中的作用,尤其要克服认知偏差对保持职业怀疑的影响,同时应借鉴并改进审计程序,以有效降低审计风险.     

Are gold,USD, and Bitcoin hedge or safe haven against stock? The implication for risk management

This study investigates whether gold, USD, and Bitcoin are hedge and safe haven assets against stock and if they are useful in diversifying downside risk for international stock markets. We propose a combined GO-GARCH-EVT-copula approach to examine the hedge and safe haven properties of gold, USD, and Bitcoin. We then examine the attractiveness of these assets in reducing stock portfolio risk by using downside risk measures estimated by the proposed approach and other competing models. We also evaluate the relative performance of the proposed model in reducing downside risk with the competing models. The findings of the study indicate that the USD is the most valuable hedge and safe haven asset closely followed by gold, while Bitcoin is the least valuable. It is also observed that the proposed combined approach performs best in reducing the portfolio downside risk. The findings of this study are of significance for portfolio managers and individual investors who wish to protect the portfolio value during market turmoil.     

A Bayesian approach for more reliable tail risk forecasts

This paper demonstrates that existing quantile regression models used for jointly forecasting Value-at-Risk (VaR) and expected shortfall (ES) are sensitive to initial conditions. Given the importance of these measures in financial systems, this sensitivity is a critical issue. A new Bayesian quantile regression approach is proposed for estimating joint VaR and ES models. By treating the initial values as unknown parameters, sensitivity issues can be dealt with. Furthermore, new additive-type models are developed for the ES component that are more robust to initial conditions. A novel approach using the open-faced sandwich (OFS) method is proposed which improves uncertainty quantification in risk forecasts. Simulation and empirical results highlight the improvements in risk forecasts ensuing from the proposed methods.     

Labor unemployment risk and firm risk

This paper examines the effect of labor unemployment risk on firm risk. Using unemployment insurance benefits as a proxy for unemployment risk, we find an economically significant positive relation between unemployment risk and firm risk. This positive relation is more pronounced for firms that are more labor-intensive, have a higher layoff propensity and are more financially constrained. While existing literature that employs corporate policy measures such as debt and cash holdings suggests an opposite relationship, our paper presents evidence that the effects stemming from earnings management, earnings quality and reporting quality appear to dominate.     

Forecasting recovery rates on non-performing loans with machine learning

We compare the performance of a wide set of regression techniques and machine-learning algorithms for predicting recovery rates on non-performing loans, using a private database from a European debt collection agency. We find that rule-based algorithms such as Cubist, boosted trees, and random forests perform significantly better than other approaches. In addition to loan contract specificities, predictors that refer to the bank recovery process — prior to the portfolio’s sale to a debt collector — are also shown to enhance forecasting performance. These variables, derived from the time series of contacts to defaulted clients and client reimbursements to the bank, help all algorithms better identify debtors with different repayment ability and/or commitment, and in general those with different recovery potential.     

环境不确定性与企业党员高管的创新“稳定器”效应

本文选取2010—2019年A股上市公司作为研究样本,研究高管党员身份在企业创新面临环境不确定带来冲击时的“稳定器”效应及其内在机制。研究发现：环境不确定性的提升抑制了企业创新,高管党员身份能通过降低研发支出挤出程度和优化融资环境两个渠道有效缓解环境不确定性的创新抑制效应。党员高管的创新“稳定器”效应更多地体现在环境不确定性增加的阶段,在平稳发展时期,应平衡好党组织参与企业治理与企业创新发展自主权的关系。全面从严治党战略的实施使党员高管决策风格更加稳健、保守,降低了企业风险承担,同时强化了面临环境不确定性时高管党员身份的“创新稳定器”作用。在当前企业创新面临高环境不确定性的大背景下,本文研究一方面丰富了党组织参与创新治理的理论依据,另一方面为高不确定性背景下优化企业创新环境提供了可实践路径。