金融衍生品与企业风险承担——基于我国制造业上市公司的经验证据

以我国沪深A股上市的制造业企业2007-2012年数据为基础,剖析了金融衍生品对企业个体风险和系统风险的影响。研究表明,无论是整体的衍生品还是不同合约类型的衍生品,对个体风险和系统风险均产生了抑制效应。进一步分析显示,衍生品对个体风险的抑制效应在显著性水平上存在着结构性差异,其中外汇衍生品的影响在统计上显著,而商品衍生品和利率衍生品则不显著。此外,还发现整体衍生品和单一衍生品对系统风险的抑制效应均不显著。     

Earthquake risk and housing prices in Japan: Evidence before and after massive earthquakes

The hedonic pricing approach is used to examine whether homeowners and/or renters alter their subjective assessments of earthquake risks after massive earthquakes. Using nation-wide household panel data coupled with earthquake hazard information and records of observed earthquakes, we find that there are some modifications of individuals' assessments of earthquake risk in both cases. We have carefully taken into consideration the bias stemming from the use of objective risk variables as a proxy for individual risk assessments. Our results suggest that the price discount from locating within a quake-prone area is significantly larger soon after earthquake events than beforehand. We argue that the most likely interpretation for this result is that households tend to underestimate earthquake risk if there has not been a recent occurrence.     

Public-private partnerships and scale efficiency in Brazilian ports: Evidence from two-stage DEA analysis

This paper assesses the impacts of public-private partnerships on major Brazilian public ports. It is proposed that these kinds of arrangements with private terminal operators could help achieving higher levels of scale efficiency by enhancing coordination processes, providing more adequate information technologies, and higher connectivity with other transportation modes. Methodology relies on factor extraction of inputs/outputs as a first step to compute DEA efficiency estimates, followed by truncated bootstrapped regression analysis to test different contextual variables. Results indicate a strong positive impact of public-private partnerships on port scale efficiency, corroborating their impacts in relation to the most productive scale size.     

Dynamic and asymmetric effects between carbon emission trading,financial uncertainties,and Chinese industry stocks: Evidence from quantile-on-quantile and causality-in-quantiles analysis

This paper investigates the dynamic and asymmetric effects between carbon emission trading (CET), financial uncertainties, and Chinese stocks in different industries over the period from 19th December 2013 to 21st March 2022. We utilized a novel quantile framework including rolling window quantile regression method, quantile-on-quantile method, and causality-in-quantiles method to implement this research more comprehensively and accurately. Our contributions and findings, empirical in nature, are as follows: (i) In the early establishing stage of the carbon market, with a bullish market situation, carbon emission trading has a negative impact on most industry stocks. In the developing and improving stage of the carbon market, different industries have different impact situations. (ii) We find that the effects of financial uncertainty on stocks are stronger than CET on stocks. We also find that the dependence structures between CET, financial uncertainty, and industry stocks are asymmetric in most industries, and there are many mutation structures with significant risks in extreme situations. (iii) Carbon emissions trading, crude oil volatility, and US stock volatility all have strong causal relationships with Chinese industry stocks. (iv) We also provide policy suggestions to relevant countries to balance carbon market and stock markets and avoid risks from financial uncertainty in different industries.     

Analysis of the cross-region risk contagion effect in stock market based on volatility spillover networks: Evidence from China

This article uses the stock market regional indexes of 31 provinces (include Province-level municipalities and Minority Autonomous Regions) in mainland China as a sample, and constructs an inter-regional volatility spillover network of China’s stock market based on the GARCH-BEKK model. Through network centrality analysis, Diebold and Yilmaz's spillover index method and block model analysis, we comprehensively analyze the risk contagion effect among different regions in China’s stock market. The empirical results show that: (i) The risk contagion intensity (risk reception intensity) in various regions of China’s stock market has a typical “core-periphery” distribution characteristic due to regions’ different levels of economic development. (ii) There are obvious risk spillover effect in China’s stock market, among which the economically developed regions along the southeastern coast of China, such as Beijing, Shanghai, Zhejiang and Jiangsu, are the main risk transmitters, while the economically undeveloped regions in the Midwest of China, such as Xinjiang, Xizang, Gansu, Nei Menggu and Qinghai are the main risk receivers. (iii) Each region is divided into 4 blocks according to their respective roles in the risk spillover process in China’s stock market. Block 1 that is composed of the economically underdeveloped regions in the Midwest is the “main benefit block”, it acts as a “receiver”. Block 2 that is composed of regions with strong economic growth vitality in the Midwest is a “Bilateral spillover block”, it both plays the role of “receiver” and “transmitter”. Block 3 that is composed of developed regions along the southeast coast, it acts as a “transmitter”; Block 4 that is composed of the relatively fast-growing regions in the Southwest is the “brokers block”, it serves as a “bridge”. The results of this article can provide some reference for investors in financial institutions and decision makers in financial regulators.     

Risk management in life insurance companies: Evidence from Taiwan

The solvency issue of life insurance companies has become more important in recent years as business risks turn increasingly greater. This study examines the relationship among investing risk, underwriting risk, and the capital ratio during the post risk-based capital regulation period of 2004–2009 in Taiwan. In addition to the two-stage least square regression (2SLS), we also adopt the two-stage quantile regression (2SQR) to capture the effects of low capital (or risk) levels and high capital (or risk) levels. 2SLS do not fully explain the capital-risk relation. Contrary to previous evidence reported in the U.S., our findings in 2SQR model indicate that the relationship between capital and underwriting risk is positive, while the relationship between investing risk and capital shows a reverse pattern. Overall, the 2SQR provides stronger evidence than the 2SLS.     

Factors influencing bank risk in Europe: Evidence from the financial crisis

We use a dynamic panel data model to analyze bank-specific and macroeconomic determinants of bank risk for a large sample of commercial banks operating in the euro area. The selected time span, from 2001 to 2012, considers the impact of the on-going financial and economic crisis on the Eurozone banking system. Our results indicate that capitalization, profitability, efficiency and liquidity are inversely and significantly related to bank risk. However, the recourse to wholesale funding by banks seems to increase their risk. We also find that less-concentrated markets, lower interest rates, higher inflation rates and a context of economic crisis (with a falling GDP) increase bank risk.     

Managing risk in the formative years: Evidence from young enterprises in Europe

This paper empirically investigates aspects of risk management in young small enterprises? effort to survive and grow. We use a new dataset on several thousands small businesses in their “formative age” (2–8 years old) in 10 European countries and 18 sectors. Firms across all types of sectors use internal risk mitigation strategies to manage technology risk and operational risk. Financial risk is managed by tapping formal and informal networks. Market risk appears less amenable to internal management action. Formal network participation (strategic alliances) is a strategy cutting across all kinds of risk with the exception of operational risk. Firms in knowledge-intensive sectors (high-tech manufacturing and KIBS) engage in risk management activities more extensively. Firms led by more educated entrepreneurs and/or operating in demanding volatile markets tend to network more and to use internal risk mitigation strategies more extensively.     

The role of neighborhood characteristics in mortgage default risk: Evidence from New York City

Using a rich database of non-prime mortgages from New York City, we find that census tract level neighborhood characteristics are important predictors of default behavior, even after controlling for an extensive set of controls for loan and borrower characteristics. First, default rates increase with the rate of foreclosure notices and the number of lender-owned properties (REOs) in the tract. Second, default rates on home purchase mortgages are higher in census tracts with larger shares of black residents, regardless of the borrower’s own race. We explore possible explanations for this second finding and conclude that it likely reflects differential treatment of black neighborhoods by the mortgage industry in ways that are unobserved in our data.     

Project success and project team management: Evidence from capital projects in the process industries

Efficient project execution is a key business objective in many domains and particularly so for capital projects in the process industries, but existing project management research gives little direction about how project team factors influence three important capital project outcomes: cost, schedule, and operability. After an extensive cross-disciplinary review of the general team and project management literatures, we constructed and tested a theoretically based, five-dimensional model of organizational context, project team design, project team leadership, project team processes, and project outcome factors. We examined the model by means of an empirical study of 56 newly completed capital projects executed by 15 Fortune 500 companies in the process industries. The results indicate the value of disaggregating project outcomes for research purposes. Different bundles of project team factors were found to drive project cost, schedule, and operability. Project team efficacy, cross-functional project teams, autonomous project team structure, and virtual office usage were the strongest predictors of project cost effectiveness. Continuity of project leadership, cross-functional project teams, and project manager incentives were the strongest predictors of project construction schedule. In contrast, clear project goals and an office design to facilitate effective communication were the main predictors of plant operability. Implications of these findings for researchers and project practitioners are discussed. One major practical implication of our findings is that project managers need to clearly focus and prioritize their goals for each project so they can adopt the appropriate bundles of project team practices that will facilitate their goal achievement.