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1.
The behavior and spatial distribution of crime events can be explained through the characterization of an area in terms of its demography, socioeconomy, and built environment. In particular, recent studies on the incidence of crime in a city have focused on the identification of features of the built environment (specific places or facilities) that may increase crime risk within a certain radius. However, it is hard to identify environmental characteristics that consistently explain crime occurrence across cities and crime types. This article focuses on the assessment of the effect that certain types of places have on the incidence of property crime, robbery, and vandalism in three cities of the Valencian region (Spain): Alicante, Castellon, and Valencia. A nonlinear effects model is used to identify such places and to construct a risk map over the three cities considering the three crime types under research. The results obtained suggest that there are remarkable differences across cities and crime types in terms of the types of places associated with crime outcomes. The identification of high-risk areas allows verifying that crime is highly concentrated, and also that there is a high level of spatial overlap between the high-risk areas corresponding to different crime types.  相似文献   
2.
We analyze the institutional determinants of U.S. financial market regulation with a general model of the policy-making process in which legislators delegate authority to regulate financial risk at both the firm and systemic levels. The model explains changes in U.S. financial regulation leading up to the financial crisis. We test the predictions of the general model with a novel, comprehensive data set of financial regulatory laws enacted specifically between 1950 and 2009. The theoretical and empirical analysis finds that economic and political factors impact Congress’ decision to delegate regulatory authority to executive agencies, which in turn impacts the stringency of financial market regulation, and our estimation results indicate that political factors may have been stronger and resulted in inefficiencies.  相似文献   
3.
We suggest that the distortion of the positive risk–return relation in the ICAPM is a consequence of trading by informed investors to exploit mispricing. We hypothesize and demonstrate that a non-positive (strongly positive) risk–return relation following positive (negative) market returns is attributed to short-selling (purchasing) of overpriced (underpriced) stocks along with optimistic (pessimistic) expectations conditional on good (bad) market news. We verify this asymmetry in the risk–return relation through the indirect risk–return relation conditional on good (bad) market news. We also find that the attenuation (reinforcement) of the positive risk–return relation is more profound in high- (low-) sentiment periods.  相似文献   
4.
This study investigates whether gold, USD, and Bitcoin are hedge and safe haven assets against stock and if they are useful in diversifying downside risk for international stock markets. We propose a combined GO-GARCH-EVT-copula approach to examine the hedge and safe haven properties of gold, USD, and Bitcoin. We then examine the attractiveness of these assets in reducing stock portfolio risk by using downside risk measures estimated by the proposed approach and other competing models. We also evaluate the relative performance of the proposed model in reducing downside risk with the competing models. The findings of the study indicate that the USD is the most valuable hedge and safe haven asset closely followed by gold, while Bitcoin is the least valuable. It is also observed that the proposed combined approach performs best in reducing the portfolio downside risk. The findings of this study are of significance for portfolio managers and individual investors who wish to protect the portfolio value during market turmoil.  相似文献   
5.
This study evaluates a wide range of machine learning techniques such as deep learning, boosting, and support vector regression to predict the collection rate of more than 65,000 defaulted consumer credits from the telecommunications sector that were bought by a German third-party company. Weighted performance measures were defined based on the value of exposure at default for comparing collection rate models. The approach proposed in this paper is useful for a third-party company in managing the risk of a portfolio of defaulted credit that it purchases. The main finding is that one of the machine learning models we investigate, the deep learning model, performs significantly better out-of-sample than all other methods that can be used by an acquirer of defaulted credits based on weighted-performance measures. By using unweighted performance measures, deep learning and boosting perform similarly. Moreover, we find that using a training set with a larger proportion of the dataset does not improve prediction accuracy significantly when deep learning is used. The general conclusion is that deep learning is a potentially performance-enhancing tool for credit risk management.  相似文献   
6.
Exploiting a unique conditional disclosure mandate on management earnings forecasts (MEFs) in China, we examine the differential effects of voluntary and mandatory MEFs on the cost of debt. We find that firms providing voluntary MEFs have lower cost of debt than do mandatory forecasters and nonforecasters. The results of the channel analyses reveal that voluntary forecasters have greater commitment to voluntary MEFs in future periods than do mandatory forecasters and nonforecasters, and the precision, accuracy, and timeliness of MEFs are higher for voluntary forecasters than for mandatory forecasters. Additional analyses show that the differential effects of voluntary and mandatory MEFs on cost of debt are stronger for voluntary forecasters operating in opaque information environments, issuing high-quality and confirming forecasts, controlled by private shareholders, and operating in highly competitive product markets. Overall, our results indicate that, compared with mandatory MEFs, voluntary MEFs are more informative for credit investors, particularly for firms facing greater information risk and operating uncertainty.  相似文献   
7.
Using data on Brazil, Colombia, Mexico, the Philippines, Russia and Turkey, our empirical results show that the exchange rates of their currencies have adequate explanatory power in explaining their US dollar-denominated sovereign bonds, particularly in the post-global financial crisis period. We develop a two-factor pricing model with closed-form solutions for the sovereign bonds in which the correlated factors are foreign exchange rates and US risk-free interest rates that follow a double square-root process relevant in the low interest rate environment. The numerical results and associated error analysis show that the model credit spreads can broadly track the market credit spreads.  相似文献   
8.
道德风险总是困扰着职业经理人群体,对企业发展产生不利影响。在实践中,作为建立健全社会信用体系的重要环节,职业经理人信用评价是防范职业经理人群体道德风险的基本思路和必要举措。本文基于马克思主义的理论启示,探索职业经理人三个维度的道德关系和道德风险,并围绕三个维度指向的个人信用、职业信用与职务信用等具体信用构成,阐述职业经理人信用评价内涵。进而,结合职业经理人信用评价内涵,构建系统应对道德风险的职业经理人信用评价体系,并以重庆为例进行实证测度。在此基础上,提出促进职业经理人道德意识与信用水平提升、实现新时代职业经理人群体高素质发展的对策建议。  相似文献   
9.
Using a novel data set for the U.S. states, this paper examines whether household debt and the protracted debt deleveraging help explain the dismal performance of U.S. consumption since 2007 in the aftermath of the housing bubble. By separating the concepts of deleveraging and debt overhang—a flow and a stock effect—we find that excessive indebtedness exerted a meaningful drag on consumption over and beyond wealth and income effects. The overall effect, however, is modest—‐around one sixth of the slowdown in consumption between 2000–06 and 2007–12—and mostly driven by states with particularly large imbalances in their household sector. This might be indicative of non‐linearities, whereby indebtedness begins to bite only when misalignments from sustainable debt dynamics become excessive.  相似文献   
10.
经济资本(EC)是在既定期间和置信水平下,公司根据实际承担的风险计算的用以吸收非预期损失的资本额度,目前市场风险是整体经济资本测算体系中最为突出的风险.根据当前保险运营与资产投资的比例特征,同时对资产端与负债端建立市场风险投资模型,采用嵌套随机模拟方法进行两阶段情景生成,度量未来一年内不同风险测度下的市场风险经济资本需求,并对比不同情景数量下的测算稳定性.结果证明:随着内部或外部情景模拟次数的增加,市场风险经济资本测算结果对于极端风险的预测趋于稳定,在内外部情景数量乘积相同时运算时间基本一致.当内外部两阶段情景生成参数差异较大的情形下,应适当增加情景生成数量,以确保对于极端风险预测的准确性.  相似文献   
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