Modelling the iron ore price index: A new perspective from a hybrid data reconstructed EEMD-GORU model

As iron ore is the fundamental steel production resource, predicting its price is strategically important for risk management at related enterprises and projects. Based on a signal decomposition technology and an artificial neural network, this paper proposes a hybrid EEMD-GORU model and a novel data reconstruction method to explore the price risk and fluctuation correlations between China’s iron ore futures and spot markets, and to forecast the price index series of China’s and international iron ore spot markets from the futures market. The analysis found that the iron ore futures market in China better reflected the price fluctuations and risk factors in the imported and international iron ore spot markets. However, the forward price in China’s iron ore futures market was unable to adequately reflect the changes in the domestic iron ore market, and was therefore unable to fully disseminate domestic iron ore market information. The proposed model was found to provide better market risk perceptions and predictions through its combinations of the different volatility information in futures and spot markets. The results are valuable references for the early-warning and management of the related enterprise project risks.     

Early labor market outcomes of university graduates: Does time to degree matter?

Using university administrative and survey data drawn from the AlmaLaurea Consortium, we analyze the effect of time to degree on the early labor market performance of Italian graduates. The empirical strategy allows identifying separately the impact of elapsed time to degree on the transition from university to work and on earnings from other determinants specific to the academic path completed. Findings suggest that delayed graduation reduces the employment probability (0.8% points for each year of delay), and this effect is still persistent five years after graduation. Once employed, graduates not completing their degree within the minimum period are also penalized in their net monthly earnings, even five years after graduation. The most penalized groups are women and graduates in non-scientific fields.     

Predicting housing prices in China based on modified Holt's exponential smoothing incorporating whale optimization algorithm

The forecast of the real estate market is an important part of studying the Chinese economic market. Most existing methods have strict requirements on input variables and are complex in parameter estimation. To obtain better prediction results, a modified Holt's exponential smoothing (MHES) method was proposed to predict the housing price by using historical data. Unlike the traditional exponential smoothing models, MHES sets different weights on historical data and the smoothing parameters depend on the sample size. Meanwhile, the proposed MHES incorporates the whale optimization algorithm (WOA) to obtain the optimal parameters. Housing price data from Kunming, Changchun, Xuzhou and Handan were used to test the performance of the model. The housing prices results of four cities indicate that the proposed method has a smaller prediction error and shorter computation time than that of other traditional models. Therefore, WOA-MHES can be applied efficiently to housing price forecasting and can be a reliable tool for market investors and policy makers.     

Financial statement comparability and bank risk-taking

This study examines the relationship between financial statement comparability and bank risk-taking. Our analysis of a sample of publicly listed U.S. banks over the 1994–2019 period shows that banks with more comparable financial statements are related to significantly less risk-taking. We also find that the negative relationship between comparability and risk-taking is more pronounced for firms with more severe moral hazard and agency problems. Our documented findings are robust across alternative measures of comparability and risk-taking and considering change analysis, after controlling for strength of corporate governance and using propensity score matching and two-stage least squares estimation to address endogeneity concerns. Our analysis also shows that the relationship between financial statement comparability and bank risk-taking is stronger for smaller banks than for larger banks. Overall, this study provides unique insights into the role of financial statement comparability in curbing risk-taking in the banking sector.     

It makes me feel vulnerable! The impact of public self-disclosure on online complaint behavior

Genuine reviews are essential for financial performance and for customer trust. In the case of a negative experience, withholding negative reviews may lead to biased online information. This paper aims to investigate two factors that may prompt customers to withhold their complaints (i.e., identity disclosure and locus of control). The study adopts a sequential exploratory mixed-method approach. An exploratory interview phase compares public vs anonymous online environments, and explores the reasons why dissatisfied customers might decide not to complain. An experiment then shows that vulnerability is a key mechanism preventing negative reviews. This effect is exaggerated when customers perceive that they do not have control over the events happening in their lives (i.e., external locus of control). Our work uncovers an important determinant of online complaint behavior, vulnerability. It also offers practical suggestions, such as improving confidentiality, to increase a customer's willingness to complain following a negative experience.     

A critical overview of privacy-preserving approaches for collaborative forecasting

Cooperation between different data owners may lead to an improvement in forecast quality—for instance, by benefiting from spatiotemporal dependencies in geographically distributed time series. Due to business competitive factors and personal data protection concerns, however, said data owners might be unwilling to share their data. Interest in collaborative privacy-preserving forecasting is thus increasing. This paper analyzes the state-of-the-art and unveils several shortcomings of existing methods in guaranteeing data privacy when employing vector autoregressive models. The methods are divided into three groups: data transformation, secure multi-party computations, and decomposition methods. The analysis shows that state-of-the-art techniques have limitations in preserving data privacy, such as (i) the necessary trade-off between privacy and forecasting accuracy, empirically evaluated through simulations and real-world experiments based on solar data; and (ii) iterative model fitting processes, which reveal data after a number of iterations.     

中国金融系统风险溢出效应研究——基于溢出指数和波动溢出网络

文章基于溢出指数和波动溢出网络方法，从静态和动态分别度量我国金融系统不同子市场间的风险联动水平及变动趋势。研究结果表明，我国金融系统风险溢出效应整体水平较高，各市场间联动性较强；市场内部滞后效应大于市场之间溢出效应，两两有向溢出效应具有强不对称性；作为我国金融系统的风险中心，货币市场始终处于风险溢出方，但在金融危机时期，其对外风险溢出效应相对减弱，而大宗商品市场、资本市场、房地产市场等其余市场的风险溢出效应相对增强。值得注意的是，当前我国金融系统整体风险溢出水平较高，市场间风险相关性较强，需要进一步加强系统性风险的监测与防范。     

金融资源配置、技术进步与经济高质量发展

随着我国发展阶段及内外部条件的变化,科技创新已成为新时代引领我国经济高质量发展的核心驱动力。本文以金融驱动技术进步的视角,构建内生增长DSGE模型,分析金融资源配置、技术进步和经济增长之间的关系。研究佐证了我国技术创新的逆周期性,并发现金融资源在企业生产性投资与创新投资之间的分配,可以通过改变生产要素投入规模和技术进步率两种途径影响经济增长,且这两种影响之间存在“跷跷板”关系,但后者更具主导性。在此基础上,诠释了金融、技术与经济的动态传导机制:经济扩张期,企业生产规模扩张,金融资源对生产性投资的支持增加,对创新的投入相对减少,技术进步率放缓;经济收缩期,企业缩减生产规模,金融资源对生产性投资的支持减少,对创新的投入相对增加,技术进步率提升。本研究的政策启示为,面对当前发展新矛盾、新挑战,应把握发展新格局、新机遇,进一步深化金融改革,优化金融资源配置机制,鼓励创新投资,充分发挥股权市场对企业研发创新的支持作用,并辅以稳健适度的宏观调控政策,为企业创新提供良性的宏观环境,激活企业创新需求,促进技术进步,推动经济高质量发展。     

基于快铁融合的上海铁路集装箱快运站选址研究

快铁融合可以充分发挥快递企业和铁路运输的优势,有效提升物流作业效率,达到运输资源分配平衡的效果,是多元化运输的发展方向。在既有和计划建设的铁路货运站中选择铁路集装箱快运站与快递企业集散网络衔接,以快递企业时间满意度和集散运输成本为目标,构建基于时间满意度的铁路集装箱快运站选址模型,以上海铁路集装箱快运站为例进行实证分析,提出保证铁路集装箱快运站与快递企业合理衔接的对策,为铁路集装箱运输融入快递市场提供决策支持,加速快铁融合的实施。     

东道国金融发展对中国企业对外直接投资的影响:二元边际与生产率门槛

文章基于中国上市企业2008-2015年对外直接投资数据，分析东道国金融发展在扩展边际和集约边际上对企业对外直接投资决策以及投资所需生产率水平的影响。研究发现，在不同生产率的企业中东道国金融发展的影响是异质性的。较高的金融发展水平会系统性地降低投资所需的生产率水平，进而促进中国企业对外直接投资的概率、次数和规模。进一步的研究还发现，在经济发展水平比中国高的东道国金融发展的生产率效应更显著，投资所需生产率下降得更多。尽管如此，高经济发展水平东道国的最低生产率门槛仍然高于低经济发展水平的东道国。控制了金融发展指标和企业全要素生产率的内生性后，结果依然稳健。