Forecasting VaR models under Different Volatility Processes and Distributions of Return Innovations

This paper provides clear‐cut evidence that the out‐of‐sample VaR (value‐at‐risk) forecasting performance of alternative parametric volatility models, like EGARCH (exponential general autoregressive conditional heteroskedasticity) or GARCH, and Markov regime‐switching models, can be considerably improved if they are combined with skewed distributions of asset return innovations. The performance of these models is found to be similar to that of the EVT (extreme value theory) approach. The performance of the latter approach can also be improved if asset return innovations are assumed to be skewed distributed. The performance of the Markov regime‐switching model is considerably improved if this model allows for EGARCH effects, for all different volatility regimes considered. Copyright © 2014 John Wiley & Sons, Ltd.     

Forecasting Death Rates Using Exogenous Determinants

Mortality models used for forecasting are predominantly based on the statistical properties of time series and do not generally incorporate an understanding of the forces driving secular trends. This paper addresses three research questions: Can the factors found in stochastic mortality‐forecasting models be associated with real‐world trends in health‐related variables? Does inclusion of health‐related factors in models improve forecasts? Do resulting models give better forecasts than existing stochastic mortality models? We consider whether the space spanned by the latent factor structure in mortality data can be adequately described by developments in gross domestic product, health expenditure and lifestyle‐related risk factors using statistical techniques developed in macroeconomics and finance. These covariates are then shown to improve forecasts when incorporated into a Bayesian hierarchical model. Results are comparable or better than benchmark stochastic mortality models. Copyright © 2014 John Wiley & Sons, Ltd.     

Exploring Survey‐Based Inflation Forecasts

This paper first shows that survey‐based expectations (SBE) outperform standard time series models in US quarterly inflation out‐of‐sample prediction and that the term structure of survey‐based inflation forecasts has predictive power over the path of future inflation changes. It then proposes some empirical explanations for the forecasting success of survey‐based inflation expectations. We show that SBE pool a large amount of heterogeneous information on inflation expectations and react more flexibly and accurately to macro conditions both contemporaneously and dynamically. We illustrate the flexibility of SBE forecasts in the context of the 2008 financial crisis. Copyright © 2011 John Wiley & Sons, Ltd.     

Forecasting regional house price inflation: a comparison between dynamic factor models and vector autoregressive models

This paper uses the dynamic factor model framework, which accommodates a large cross‐section of macroeconomic time series, for forecasting regional house price inflation. In this study, we forecast house price inflation for five metropolitan areas of South Africa using principal components obtained from 282 quarterly macroeconomic time series in the period 1980:1 to 2006:4. The results, based on the root mean square errors of one to four quarters ahead out‐of‐sample forecasts over the period 2001:1 to 2006:4 indicate that, in the majority of the cases, the Dynamic Factor Model statistically outperforms the vector autoregressive models, using both the classical and the Bayesian treatments. We also consider spatial and non‐spatial specifications. Our results indicate that macroeconomic fundamentals in forecasting house price inflation are important. Copyright © 2010 John Wiley & Sons, Ltd.     

What do numerical (climate) models really represent?

The translation of a mathematical model into a numerical one employs various modifications in order to make the model accessible for computation. Such modifications include discretizations, approximations, heuristic assumptions, and other methods. The paper investigates the divergent styles of mathematical and numerical models in the case of a specific piece of code in a current atmospheric model. Cognizance of these modifications means that the question of the role and function of scientific models has to be reworked. Neither are numerical models pure intermediaries between theory and data, nor are they autonomous tools of inquiry. Instead, theory and data are transformed into a new symbolic form of research due to the fact that computation has become an essential requirement for every scientific practice. Therefore the question is posed: What do numerical (climate) models really represent?     

水平评估对高职院校图书馆的影响

阐述了水平评估的概况及图书馆在评估中的重要地位,分析了评估给高职院校图书馆带来的发展机遇和负面影响,并提出促进图书馆良性发展的机制。     

破除“西部意识”:西部高等教育全面振兴的思路与策略

全面振兴西部高等教育是推进新时代西部大开发的重要方面,是《中国教育现代化2035》重点部署的十大战略任务的重要内容。西部高等教育振兴已取得很大成绩,但全面振兴仍在路上,其面临的真正约束是“西部意识”的思想约束。因此,西部高等教育的全面振兴,需要破除“西部意识”,突破思想约束。要坚持追求卓越,切实提高西部高等教育定位站位,确立西部高等教育志存高远、对标一流的发展意识,激发不懈奋斗、追求卓越的精神动力。要坚持问题导向,深化改革,通过建构信息化时代西部高等教育发展新生态、加快推进西部高等教育思想观念更新、强化西部高等教育振兴的制度供给、增强西部高等教育自主发展能力等举措,全面增强自我“造血”功能,推动西部高等教育全面振兴,加快实现教育现代化。     

退化秩为0的二阶混合型方程斜微商问题解的唯一性(英文)

讨论带抛物退化线的二阶混合型方程的斜微商边值问题,这个问题包括空气动力学中Chaplygin方程的Tricomi问题作为特殊情况.先给出这个问题的提法和解的表示式,然后使用复分析方法,证明了上述二阶混合型方程斜微商问题解的唯一性.     

高职高专英语教育专业高级英语教学对策探讨

高级英语是英语教育专业高级阶段的专业必修课,教学大纲对这门课的教学提出了较高的要求。从问卷和访谈中发现了当前高级英语教学中存在的一些问题,本文分析了这些问题产生的原因,并结合高职高专学生特点和师范专业特点,对如何解决这些问题提出了一些见解。     

战后初期美国联邦政府高等教育助学贷款政策探析

经历了30年代大萧条和第二次世界大战,美国开始和平时期的建设。为了在冷战中处于优势地位,联邦政府十分关注高等教育的发展。其助学贷款政策正式确立于1958年,1965年又设立了"担保学生贷款"。作为战后初期的两项主要的助学贷款政策,它们为国家培养各类专业人才,实现高等教育机会平等做出了重大的贡献。