Transport infrastructure equities in mixed-asset portfolios: estimating risk with a Garch-Copula CVaR model

Transport infrastructure is an important subsector within infrastructure, but knowledge of its equities in terms of risk-return characteristics and contribution to portfolio performance is still limited. This study assesses the subsector individually and in a multi-asset, index-based portfolio. In doing so, we apply a t-Copula-based Conditional Value-at-Risk model to simulate risk and returns. Our findings reveal that the subsector has a relatively low dependency on other equities, performs like other alternative asset classes such as general real estate, and does not grant significant risk diversification benefits for mainstream institutional investors such as pension funds. Investors aiming for higher target returns may however assign substantial weights to transport infrastructure, supporting our conjecture that it does not share the same asset class characteristics as general infrastructure. By contrasting Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR) scores for both the mean-variance framework and the t-Copula simulation, we further document the limitations of traditional VaR approaches. Hence, this study’s results support the use of risk assessment tools that incorporate non-normal distributions to represent multivariate dependence structures.     

Basel III capital surcharges for G-SIBs are far less effective in managing systemic risk in comparison to network-based,systemic risk-dependent financial transaction taxes

In addition to constraining bilateral exposures of financial institutions, there exist essentially two options for future financial regulation of systemic risk: First, regulation could attempt to reduce the financial fragility of global or domestic systemically important financial institutions (G-SIBs or D-SIBs), as for instance proposed by Basel III. Second, it could focus on strengthening the financial system as a whole by reducing the probability of large-scale cascading events. This can be achieved by re-shaping the topology of financial networks. We use an agent-based model of a financial system and the real economy to study and compare the consequences of these two options. By conducting three computer experiments with the agent-based model we find that re-shaping financial networks is more effective and efficient than reducing financial fragility. Capital surcharges for G-SIBs could reduce systemic risk, but they would have to be substantially larger than those specified in the current Basel III proposal in order to have a measurable impact. This would cause a loss of efficiency.     

Can (unusual) weather conditions in New York predict South African stock returns?

This paper investigates the explanatory power of certain weather variables, measured as deviations from their monthly averages, in a leading international financial trading centre, i.e., New York, for South African stock returns, over the daily period January 2nd, 1973 to December, 31, 2015. The empirical results highlight that these unusual deviations of weather variables have a statistically significant negative effect on the stock returns in South Africa, indicating that unusual weather conditions in New York can be used to predict South African stock returns, which otherwise seems to be highly unpredictable. In fact, a forecasting exercise recommends that a trading rule that considers those weather variables through a GARCH modelling approach seems to outperform the random walk model and thus beat the market.     

Tornado activity,house prices,and stock returns

In this paper we investigate the effects of tornado activity on house prices and stock returns in the US. First, using geo-referenced and metropolitan statistical area (MSA)-level data, we find tornado activity to be responsible for a significant drop in house prices. Spillover tornado effects between adjacent MSAs are also detected. Furthermore, our granular analysis provides evidence of tornadoes having a negative impact on stock returns. However, only two sectors seem to contribute to such a negative effect (i.e., consumer discretionary and telecommunications). In a macro-analysis, which relies on aggregate data for the South, West, Midwest and Northeast US regions, we then show that tornado activity generates a significant drop in house prices only in the South and Midwest. In these regions, tornadoes are also responsible for a drop in income. Tornado activity is finally found to positively (negatively) affect stock returns in the Midwest (South). If different sectors are examined, a more heterogeneous picture emerges.     

国际黄金价格波动特性与 “上海金”定价机制

本文通过对比伦敦和上海黄金市场交易价格的波动规律,得出伦敦市场黄金交易价格的波动比上海市场黄金交易价格波动性更为强烈的结论。通过数据分析,发现定价机制不够公开透明是造成伦敦市场价格波动性更为强烈的制度性因素,进而指出 “上海金”定价机制的先进性和市场应用相关建议。     

国内外黄金市场价格间的联动关系稳定吗?——基于外部冲击视角的分析

在全球金融市场不断开放和融合的大背景下,黄金市场不但与外部市场频繁互动,其系统内部的联动关系也变得极为多元和复杂,黄金市场间的价格联动反映了信息和风险在不同市场间的传递过程。黄金价格通常会受到外部因素干扰而产生波动,但市场间的联动关系是否会因此而改变是值得重点关注的问题,黄金市场功能的有效性及稳固的市场关系是投资者利用全球黄金市场进行对冲和避险的先决条件,同时也关系到整个金融市场的稳定性。本文将研究重点聚焦于黄金市场内部,在研究中外各主要黄金市场间动态相关性和波动溢出效应的同时引入外部冲击以检验不同因素对黄金期货、现货市场间联动关系的影响从而探讨国内外黄金市场间价格联动的稳定性问题。结果表明:中国与全球主要黄金期货、现货市场间整体上保持了正相关关系,同时与各主要黄金市场间均存在显著的波动溢出效应。在一般市场条件下,外部冲击并没有显著改变中国与全球主要黄金期货、现货市场间的联动关系,表明黄金市场内部的价格联动具有较强的稳定性。     

战略人力资源管理、双重网络嵌入与大数据能力研究

大数据时代的到来已改变组织管理的多重形态,其中战略人力资源管理已经逐渐成为组织人才管理的重要方式.本文依据资源基础理论和动态能力理论,引入双重网络嵌入作为中介变量,大数据能力作为调节变量,以166个技术型企业为研究样本,探索战略人力资源管理的形成机理和作用机制.研究发现,战略柔性、技术动荡性和大数据能力对战略人力资源管理具有正向促进作用;战略人力资源管理显著促进组织创新;双重网络嵌入在战略人力资源管理与组织创新关系中具有部分中介作用;大数据能力在战略人力资源管理与组织创新关系中具有正向调节作用.本文为大数据时代战略人力资源管理提出了有益建议.     

全球外汇衍生品交易的发展特点及启示

该文根据国际清算银行对全球外汇衍生品交易的调查统计情况，对全球外汇衍生品交易及主要交易货币的在岸与离岸外汇衍生品交易的发展特点进行了归纳，以期为国内外汇衍生品市场的发展提供借鉴。文章指出，结合本国汇率和资本项目管理体制改革逐步取消外汇衍生品交易的实需原则，有利于在维护金融稳定的前提下进一步发展本国的外汇衍生品市场。     

我国交易所行业国际化发展指标调查研究

国内交易所在自身规模不断扩大和金融业双向开放力度加大的背景下，纷纷实施“走出去”国际化发展战略，参与全球竞争。鉴于交易所行业的特殊性，行业国际化水平的评价体系与其他行业无法混用。本文通过文献调研和业务分析，梳理出6大类一、二、三级指标，并通过旋转矩阵分析、因子分析等方法进一步优化简化指标，概括成管理能力国际化、业务能力国际化、引领能力国际化、货币支撑能力国际化四个维度，形成新的一二三级指标体系。最后通过问卷评价国内交易所与国外同要素交易所的国际化差距，结合前述指标体系和同行差距调研结果，提出国内交易所治理能力、国际定价影响力、信息披露与国际化接轨、监管方式国际一致、技术能力国际化、国际化先天优势能力等方面的强化路径，并给出针对性的意见建议。     

全球价值链分工对全球失衡的影响研究--基于全球生产分解模型下GVC参与方式的视角

本文基于全球生产分解模型,实证检验了全球价值链分工对全球失衡的影响。研究发现,参与全球价值链分工会对经常账户产生影响,最终导致全球失衡,且采用上游供给的前向参与对全球失衡存在正向作用,而采取下游需求的后向参与对全球失衡具有负向作用,即不同参与方式对全球失衡具有差异化影响。本文还发现,全球价值链分工参与深浅复杂程度差异、产业类型参与差别对全球失衡均具有差别化影响。本研究为缓解中美贸易摩擦等国家间不必要贸易争端提供有益的理论探索。