Stock market volatility forecasting: Do we need high-frequency data?

The general consensus in the volatility forecasting literature is that high-frequency volatility models outperform low-frequency volatility models. However, such a conclusion is reached when low-frequency volatility models are estimated from daily returns. Instead, we study this question considering daily, low-frequency volatility estimators based on open, high, low, and close daily prices. Our data sample consists of 18 stock market indices. We find that high-frequency volatility models tend to outperform low-frequency volatility models only for short-term forecasts. As the forecast horizon increases (up to one month), the difference in forecast accuracy becomes statistically indistinguishable for most market indices. To evaluate the practical implications of our results, we study a simple asset allocation problem. The results reveal that asset allocation based on high-frequency volatility model forecasts does not outperform asset allocation based on low-frequency volatility model forecasts.     

严监管背景下农信社合规风险管理体系建设

2018年,银行业监管环境进一步趋严,不但强调对银行的监管,更提出了对监管人员职责的监管,这种严格的外部监管环境对农信社的合规风险管理带来了极大的挑战。农信社合规风险管理体系的建设和完善已势不容缓。论文提出了农信社合规风险管理体系建设要从战略定位、文化渗透、防线搭建、专业专职化、考核和追究六个维度入手,推进合规风险管理长效机制的建设。     

The mechanism of credit risk contagion among internet P2P lending platforms based on a SEIR model with time-lag

The credit risk contagion of Internet peer-to-peer (P2P) lending platforms is an important part of Internet financial risk management and supervision. This study analyzes the contagion path of credit risk in Internet P2P lending. Based on complex network theory and the theory of infectious disease dynamics, the characteristics of Internet P2P lending development are combined to construct a SEIR model of credit risk transmission among Internet P2P lending platforms with time lag, and the robustness of the model is analyzed and proven. The influence of platform correlations, the susceptible immune rate, the platform elimination rate, contagion latency, the saturation coefficient, and the susceptibility input rate on credit risk contagion behavior among Internet P2P lending platforms is analyzed, using the equilibrium point and threshold value. The impact of each variable is analyzed by simulation. Corresponding countermeasures and suggestions are proposed to prevent and control credit risk contagion among these platforms.     

互联网平台下商业模式创新的路径、经验和启示

互联网经济快速发展,基于互联网平台的企业创新行为具有鲜明的特色。纵向研究了三家企业的创新过程,发现互联网环境下,企业商业模式创新有三个特点:以客户为中心的战略准则,价值创造由企业转向客户;企业打破边界,加强合作伙伴之间的协同和柔性,大幅提高创新效率;企业提高管理不确定的能力,领导者、企业文化、管理模式帮助企业应对不确定性。同时,提出当前创新模式存在核心技术缺乏、生产端缺乏创新的潜在风险,并提出创新发展的建议:加强生产端互联网的建设,提高创新质量;深化完善商业生态系统建设,提高商业系统整体的创新能力。     

碳排放交易制度的节能减排路径：效率提升还是结构转型？——来自中国省级数据的准自然实验

以中国2013年以来实行的碳排放交易试点政策作为准自然实验事件，基于2000-2017年中国30个省市的面板数据，运用双重差分法实证检验碳排放交易制度的节能减排效应及影响机制。研究发现，碳排放交易制度有利于实现中国经济“节能”与“减排”的双重目标，并通过了一系列稳健性检验；作用机制检验表明，能源效率提升和能源结构转型都是碳排放交易制度实现节能减排目标的重要路径；能源效率提升在碳排放交易制度实现“节能”和“减排”中分别发挥了10.19%和5.93%的作用，而能源结构转型分别发挥了48.87%和52.95%的作用。这意味着中国碳排放交易制度实现节能减排的主要动力来自能源结构转型，而非能源效率提升。能源结构转型涉及问题更加宏观和深层，这为中国加快推进节能减排进程，特别是完成2030年碳达峰和2060年碳中和的国际承诺提供政策启示。     

高校跨学科创新团队知识互动程度评价研究

知识互动程度评价对改善高校跨学科创新团队知识互动具有重要意义。在界定高校跨学科创新团队知识互动及知识互动程度内涵的基础上，创新性地从知识互动深度、互动广度、互动时间3个维度建立知识互动程度评价指标体系。进一步地，采用三角模糊权重、熵权和模糊积分相结合的方法，构建知识互动程度评价模型。最后，选取一所高校跨学科创新团队进行实例分析，验证评价模型的可操作性，可为高校跨学科创新团队知识互动程度评价提供一个新视角。     

Determinants of students’ entrepreneurial intention to compete in a fast-pitch competition

Despite the heightened popularity of entrepreneurship education, there remain open questions regarding best practices in co-curricular programs. Using the theory of planned behavior, the authors examine how students’ intention is shaped to increase the likelihood of participation in entrepreneurship co-curricular programs. To the best of the authors’ knowledge, this study is the first to examine the relation between entrepreneurial identity and entrepreneurial intention theory. They find the popular personality trait, openness, is related to ambition, which reveals the interaction between personal elements (personality/identity) and contextual elements (aspirations to success/intention), a novel finding in the literature. This further illustrates the interconnectedness between the theory of planned behavior and the entrepreneurial event model     

Evolution of indigenous tourism among the Lacandon of Chiapas: an application of Weaver’s model

ABSTRACT

In this paper, Weaver’s six-stage indigenous tourism model is applied to the Lacandon Maya (Hach Winik) of Chiapas, Mexico. Based on a comprehensive review of the anthropological and historical literature on this indigenous group, combined with longitudinal ethnographic and collaborative research performed with tourism entrepreneurs, the Lacandon tourism experience is assessed from the pre-European period until present. By analysing a case study of indigenous tourism in Mexico, a developing country in another geographical region and with a different colonial past, this work supplements Weavers’ perspective. The results show that the fourth and fifth stages of Weaver’s model coincide in this case study, while the sixth stage is still incomplete. Although the Lacandon case has its peculiarities and bearing in mind that several different factors should be considered in the Latin American context, the model proves to be an interesting tool for indigenous tourism analysis in developing countries.     

A hybrid information approach to predict corporate credit risk

This study proposes a hybrid information approach to predict corporate credit risk. In contrast to the previous literature that debates which credit risk model is the best, we pool information from a diverse set of structural and reduced‐form models to produce a model combination based on credit risk prediction. Compared with each single model, the pooled strategies yield consistently lower average risk prediction errors over time. We also find that while the reduced‐form models contribute more in the pooled strategies for speculative‐grade names and longer maturities, the structural models have higher weights for shorter maturities and investment grade names.     

Estimating yield curves of the U.S. Treasury securities: An interpolation approach

Following the approach of interpolation, this paper proposes the multiple exponential decay model to fit yield curves for both the U.S. TIPS market and the conventional Treasury security market. Several estimation methods, including the unconstrained/constrained nonlinear minimization, quadratic programming, and the iterative linear least squares, are applied to estimate the unknown parameters according to different curve‐fitting purposes. Comparisons between the proposed model and the alternatives show that the multiple exponential decay successfully (1) adapts to a variety of shapes associated with yield curves, (2) (partially) keeps in line with the economic interpretations of Nelson–Siegel summarized by Diebold and Li ( 2006 ), and (3) dominates the competing models in curve‐fitting performance measured by mean fitted‐price errors over the sample period. In addition, the exact specification of a nonparametric interpolation model is pinned down by applying three statistical tools, which enable us to jointly take into account validity, optimality, and parsimoniousness of the proposed model.