Time‐Varying Risk Premium in Large Cross‐Sectional Equity Data Sets

We develop an econometric methodology to infer the path of risk premia from a large unbalanced panel of individual stock returns. We estimate the time‐varying risk premia implied by conditional linear asset pricing models where the conditioning includes both instruments common to all assets and asset‐specific instruments. The estimator uses simple weighted two‐pass cross‐sectional regressions, and we show its consistency and asymptotic normality under increasing cross‐sectional and time series dimensions. We address consistent estimation of the asymptotic variance by hard thresholding, and testing for asset pricing restrictions induced by the no‐arbitrage assumption. We derive the restrictions given by a continuum of assets in a multi‐period economy under an approximate factor structure robust to asset repackaging. The empirical analysis on returns for about ten thousand U.S. stocks from July 1964 to December 2009 shows that risk premia are large and volatile in crisis periods. They exhibit large positive and negative strays from time‐invariant estimates, follow the macroeconomic cycles, and do not match risk premia estimates on standard sets of portfolios. The asset pricing restrictions are rejected for a conditional four‐factor model capturing market, size, value, and momentum effects.     

Evaluating the Benefits of Adaptation of Critical Infrastructures to Hydrometeorological Risks

Infrastructure adaptation measures provide a practical way to reduce the risk from extreme hydrometeorological hazards, such as floods and windstorms. The benefit of adapting infrastructure assets is evaluated as the reduction in risk relative to the “do nothing” case. However, evaluating the full benefits of risk reduction is challenging because of the complexity of the systems, the scarcity of data, and the uncertainty of future climatic changes. We address this challenge by integrating methods from the study of climate adaptation, infrastructure systems, and complex networks. In doing so, we outline an infrastructure risk assessment that incorporates interdependence, user demands, and potential failure‐related economic losses. Individual infrastructure assets are intersected with probabilistic hazard maps to calculate expected annual damages. Protection measure costs are integrated to calculate risk reduction and associated discounted benefits, which are used to explore the business case for investment in adaptation. A demonstration of the methodology is provided for flood protection of major electricity substations in England and Wales. We conclude that the ongoing adaptation program for major electricity assets is highly cost beneficial.     

Illiquide Assets in der Portfoliooptimierung

When optimizing a portfolio, which comprises liquid as well as illiquid assets, under the constraint of a liquidity requirement, one has to take into account the particular characteristics of illiquid assets. Illiquid assets in this context have the constituting property that they can only be sold as a whole and – if sold on a short term basis – selling leads to losses. Performing the analysis of a single period model in a mean downside risk framework with one liquid and one illiquid asset, significant differences are proven in comparison to the results of an optimization concerning solely liquid assets. For example, although the return on assets is safe in the first scenario, the portfolio value is already risky due to the uncertain liquidity requirement and situations arise where the allocation to both the liquid and the illiquid asset is optimal. Furthermore, when asset returns are uncertain, the expected portfolio value depends on the assets’ variances and can even be increased by positive correlations.     

Frontiers of Stochastically Nondominated Portfolios

We consider the problem of constructing a portfolio of finitely many assets whose returns are described by a discrete joint distribution.We propose mean‐risk models that are solvable by linear programming and generate portfolios whose returns are nondominated in the sense of second‐order stochastic dominance. Next, we develop a specialized parametric method for recovering the entire mean‐risk efficient frontiers of these models and we illustrate its operation on a large data set involving thousands of assets and realizations.     

风险资产市场组合的替代品问题的理论探讨

探讨CAPM中风险资产市场组合的替代品选择问题。指出只有算术平均指数(拉斯贝尔指数)表示的市场指数组合才适宜用来代替真正的市场组合。通过选取s个代表风险资产,得出从中选取有效资产组合作为真正的市场组合的替代品的条件。     

Risk‐Based Sampling: I Don't Want to Weight in Vain

Recently, there has been considerable interest in developing risk‐based sampling for food safety and animal and plant health for efficient allocation of inspection and surveillance resources. The problem of risk‐based sampling allocation presents a challenge similar to financial portfolio analysis. Markowitz (1952) laid the foundation for modern portfolio theory based on mean‐variance optimization. However, a persistent challenge in implementing portfolio optimization is the problem of estimation error, leading to false “optimal” portfolios and unstable asset weights. In some cases, portfolio diversification based on simple heuristics (e.g., equal allocation) has better out‐of‐sample performance than complex portfolio optimization methods due to estimation uncertainty. Even for portfolios with a modest number of assets, the estimation window required for true optimization may imply an implausibly long stationary period. The implications for risk‐based sampling are illustrated by a simple simulation model of lot inspection for a small, heterogeneous group of producers.     

The Lucas Orchard

This paper investigates the behavior of asset prices in an endowment economy in which a representative agent with power utility consumes the dividends of multiple assets. The assets are Lucas trees; a collection of Lucas trees is a Lucas orchard. The model generates return correlations that vary endogenously, spiking at times of disaster. Since disasters spread across assets, the model generates large risk premia even for assets with stable cashflows. Very small assets may comove endogenously and hence earn positive risk premia even if their cashflows are independent of the rest of the economy. I provide conditions under which the variation in a small asset's price‐dividend ratio can be attributed almost entirely to variation in its risk premium.     

Disaster Risk Management Policies and the Measurement of Resilience for Philippine Regions

How can a government prioritize disaster risk management policies across regions and types of interventions? Using an economic model to assess welfare risk and resilience to disasters, this article systematically tackles the questions: (1) How much asset and welfare risks does each region in the Philippines face from riverine flood disasters? (2) How resilient is each region to riverine flood disasters? (3) What are, per region, the possible interventions to strengthen resilience to riverine flood disasters and what will be their measured benefit? We study the regions of the Philippines to demonstrate the channels through which macroeconomic asset and output losses from disasters translate to consumption and welfare losses at the micro-economic level. Apart from the regional prioritizations, we identify a menu of policy options ranked according to their level of effectiveness in increasing resilience and reducing welfare risk from riverine floods. The ranking of priorities varies for different regions when their level of expected value at risk is different. This suggests that there are region-specific conditions and drivers that need to be integrated into considerations and policy decisions, so that these are effectively addressed.     

基于银行-资产双边网络模型的系统性风险及投资策略研究

受近几年的国际金融危机及金融全球化的影响,对金融系统的系统性风险的研究已成为国内外学者的关注热点。考虑到当前基于"银行-资产-银行"间接传播渠道的相关研究相对匮乏,本文基于银行-资产双边网络模型来分析银行系统性风险。首先,使用中国47家上市银行2018年的资产负债表数据构建了中国银行系统的双边网络模型,研究分析各类资产遭受冲击时外部冲击、降价出售效应及银行所持有的各类资产占银行总资产的比例对银行系统性风险的影响。然后,引入系统性冲击方式,通过设置具有不同属性的两大类资产并生成四种冲击事件来构建银行的投资策略模型,从资产视角探讨银行最优的投资策略。研究发现,外部冲击与降价出售效应这两个产生系统性风险的影响因素在一定区间值时会产生叠加效应,使银行系统性风险急剧增加;五种资产类中,贷款类资产对外部冲击最敏感;分析发现在各类资产冲击下都未倒闭的所有银行的资产组合具有一定的相似性;进一步研究发现银行系统中存在着最优的资产组合,使得银行在稳定的同时能获取最大收益,并且资产负债比越大的银行其风险承受能力越强,从而可以选择更激进的投资策略来追求高收益。     

投资机会变动与风险收益关系实证研究

应用跨期资本资产定价模型研究股市投资机会变动时的风险收益关系和跨期风险对冲策略。以25个规模-账面市值比组合以及扩展组合作为检验资产,以经济、情绪和市场指标作为状态变量反映投资机会,以DCC-MVGARCH方法估计的资产超额收益与市场超额收益的条件协方差衡量市场风险,以DCC-MVGARCH方法估计的资产超额收益与状态变量新息的条件协方差衡量跨期风险,应用面板回归方法检验资产超额收益与风险的关系。研究结果表明,在单状态变量中,货币供应增长率、房地产投资增长率、宏观经济景气指数、规模溢价等新息降低,投资机会出现不利变动,与这些新息负相关的资产能对冲投资机会的不利变动;存贷差增长率、利率、股市波动等新息增加时,投资机会出现不利变动,与这些新息正相关的资产能对冲投资机会的不利变动;各模型具有良好的解释能力,其中规模溢价、股市波动和货币供应的解释能力较高。还对多状态变量进行检验、比较,并提供了相应投资策略。     

COUNTRY PORTFOLIOS IN OPEN ECONOMY MACRO‐MODELS

This paper develops a simple approximation method for computing equilibrium portfolios in dynamic general equilibrium open economy macro‐models. The method is widely applicable, simple to implement, and gives analytical solutions for equilibrium portfolio positions in any combination or types of asset. It can be used in models with any number of assets, whether markets are complete or incomplete, and can be applied to stochastic dynamic general equilibrium models of any dimension, so long as the model is amenable to a solution using standard approximation methods. We first illustrate the approach using a simple two‐asset endowment economy model, and then show how the results extend to the case of any number of assets and general economic structure.     

基于EVT-POT-SV-MT模型的极值风险度量

针对金融资产收益的异常变化,采用SV-MT模型对风险资产的预期收益做风险补偿并捕捉收益序列的厚尾性、波动的异方差性等特征,将收益序列转化为标准残差序列,通过SV-MT模型与极值理论相结合拟合标准残差的尾部分布,建立了一种新的金融风险度量模型——基于EVT-POT-SV-MT的动态VaR模型.通过该模型对上证综指做实证分析,结果表明该模型能够合理有效地度量上证综指收益的风险.     

Socioeconomic Vulnerability and Adaptation to Environmental Risk: A Case Study of Climate Change and Flooding in Bangladesh

In this article we investigate the complex relationship between environmental risk, poverty, and vulnerability in a case study carried out in one of the poorest and most flood-prone countries in the world, focusing on household and community vulnerability and adaptive coping mechanisms. Based upon the steadily growing amount of literature in this field we develop and test our own analytical model. In a large-scale household survey carried out in southeast Bangladesh, we ask almost 700 floodplain residents living without any flood protection along the River Meghna about their flood risk exposure, flood problems, flood damage, and coping mechanisms. Novel in our study is the explicit testing of the effectiveness of adaptive coping strategies to reduce flood damage costs. We show that, households with lower income and less access to productive natural assets face higher exposure to risk of flooding. Disparity in income and asset distribution at community level furthermore tends to be higher at higher risk exposure levels, implying that individually vulnerable households are also collectively more vulnerable. Regarding the identification of coping mechanisms to deal with flood events, we look at both the ex ante household level preparedness for flood events and the ex post availability of community-level support and disaster relief. We find somewhat paradoxically that the people that face the highest risk of flooding are the least well prepared, both in terms of household-level ex ante preparedness and community-level ex post flood relief.     

Internationalization of Developing Country Firms into Developed Countries: The Role of Host Country Knowledge-Based Assets and IPR Protection in FDI Location Choice

Foreign direct investment (FDI) from developing to developed countries is a widespread phenomenon in the global economy. The literature suggests that such investments frequently follow a motive to seek knowledge-based assets, with the goal of augmenting the firm's resource base through internationalization. We argue that the prevalence of this motive may direct developing country firms' FDI toward developed countries with relatively stronger knowledge-based assets and weaker intellectual property rights (IPR) protection and that this effect is amplified when both conditions coincide. Furthermore, we suggest that the respective importance of knowledge-based assets and IPR protection diminishes as developing countries augment their own knowledge-based assets and that the importance of asset seeking as an internationalization motive for the country's firms declines compared with other motives such as institutional escapism. We investigate our model with FDI data including investment flows from 85 developing countries to 35 developed countries during 2009–2014. We find that developing country firms prefer investing in developed countries with stronger knowledge-based assets and weaker IPR protection. These criteria attract even more FDI when both co-occur. Furthermore, the influence of weaker host country IPR protection on the location decision diminishes for firms originating from home countries with higher stocks of knowledge-based assets.     

受限制投资组合机会成本的实证研究

通过对只能投资于股票和只能投资于债券2种情况下的投资组合的机会成本的计算,研究了受限制情况下所产生效用损失和风险厌恶程度对机会成本的影响。计算中选用上证综合指数、深圳成分指数、中信国债指数、中信企债指数和银行间7日债券回购利率的5年期月度数据,运用向量自回归的方法估计下期组合的期望收益和收益的联合概率分布,并运用Quasi-Newton最优化方法来求得最优投资组合,从而求出机会成本。     

风险预算分析与投资结构优化模型

机构投资者在设计他们的全部投资组合、管理其资产时,面对大量的困难决策。其中,最令人困惑的决策涉及到经理人结构,既使资产配置研究给投资者指出了最合适资产种类结构,但几乎没有人去指导投资者确定经理人结构,使他们的资金最有效的发挥作用。本文把传统构造证券组合的风险收益优化方法,应用到经理组合方面,从雇佣组合经理或其他资产管理者角度,讨论主动式风险控制和经理结构优化框架。     

Risk of Extreme Events Under Nonstationary Conditions

The concept of the return period is widely used in the analysis of the risk of extreme events and in engineering design. For example, a levee can be designed to protect against the 100-year flood, the flood which on average occurs once in 100 years. Use of the return period typically assumes that the probability of occurrence of an extreme event in the current or any future year is the same. However, there is evidence that potential climate change may affect the probabilities of some extreme events such as floods and droughts. In turn, this would affect the level of protection provided by the current infrastructure. For an engineering project, the risk of an extreme event in a future year could greatly exceed the average annual risk over the design life of the project. An equivalent definition of the return period under stationary conditions is the expected waiting time before failure. This paper examines how this definition can be adapted to nonstationary conditions. Designers of flood control projects should be aware that alternative definitions of the return period imply different risk under nonstationary conditions. The statistics of extremes and extreme value distributions are useful to examine extreme event risk. This paper uses a Gumbel Type I distribution to model the probability of failure under nonstationary conditions. The probability of an extreme event under nonstationary conditions depends on the rate of change of the parameters of the underlying distribution.     

Risk-Based Decision Making for Terrorism Applications

This article describes the anti-terrorism risk-based decision aid (ARDA), a risk-based decision-making approach for prioritizing anti-terrorism measures. The ARDA model was developed as part of a larger effort to assess investments for protecting U.S. Navy assets at risk and determine whether the most effective anti-terrorism alternatives are being used to reduce the risk to the facilities and war-fighting assets. With ARDA and some support from subject matter experts, we examine thousands of scenarios composed of 15 attack modes against 160 facility types on two installations and hundreds of portfolios of 22 mitigation alternatives. ARDA uses multiattribute utility theory to solve some of the commonly identified challenges in security risk analysis. This article describes the process and documents lessons learned from applying the ARDA model for this application.     

Flood Catastrophe Model for Designing Optimal Flood Insurance Program: Estimating Location‐Specific Premiums in the Netherlands

As flood risks grow worldwide, a well‐designed insurance program engaging various stakeholders becomes a vital instrument in flood risk management. The main challenge concerns the applicability of standard approaches for calculating insurance premiums of rare catastrophic losses. This article focuses on the design of a flood‐loss‐sharing program involving private insurance based on location‐specific exposures. The analysis is guided by a developed integrated catastrophe risk management (ICRM) model consisting of a GIS‐based flood model and a stochastic optimization procedure with respect to location‐specific risk exposures. To achieve the stability and robustness of the program towards floods with various recurrences, the ICRM uses stochastic optimization procedure, which relies on quantile‐related risk functions of a systemic insolvency involving overpayments and underpayments of the stakeholders. Two alternative ways of calculating insurance premiums are compared: the robust derived with the ICRM and the traditional average annual loss approach. The applicability of the proposed model is illustrated in a case study of a Rotterdam area outside the main flood protection system in the Netherlands. Our numerical experiments demonstrate essential advantages of the robust premiums, namely, that they: (1) guarantee the program's solvency under all relevant flood scenarios rather than one average event; (2) establish a tradeoff between the security of the program and the welfare of locations; and (3) decrease the need for other risk transfer and risk reduction measures.     

基于共同持有资产的银行间接关联网络研究

金融市场是一个复杂系统,银行之间不仅有直接的拆借关系,还能够通过投资市场建立间接关联。本文分析了资产内生相关性、资产降价出售以及银行投资行为等因素对银行间接关联程度的影响,基于这些因素通过持有共同资产构建银行系统的间接关联,并以此为基础通过平面极大过滤图方法生成银行间接关联网络,论证了该网络中的系统重要性银行,并通过对该网络结构特征的分析,发现间接关联网络具有小世界和无标度等特征,这些特征与银行通过直接拆借形成的网络相似。本文对于银行间接关联网络的研究不仅能够更加清晰地了解银行之间的关系,也为银行系统性风险的监管提供了新的视角。