LOG-PERIODOGRAM ESTIMATION OF LONG MEMORY VOLATILITY DEPENDENCIES WITH CONDITIONALLY HEAVY TAILED RETURNS

Many recent papers have used semiparametric methods, especially the log-periodogram regression, to detect and estimate long memory in the volatility of asset returns. In these papers, the volatility is proxied by measures such as squared, log-squared, and absolute returns. While the evidence for the existence of long memory is strong using any of these measures, the actual long memory parameter estimates can be sensitive to which measure is used. In Monte-Carlo simulations, I find that if the data is conditionally leptokurtic, the log-periodogram regression estimator using squared returns has a large downward bias, which is avoided by using other volatility measures. In United States stock return data, I find that squared returns give much lower estimates of the long memory parameter than the alternative volatility measures, which is consistent with the simulation results. I conclude that researchers should avoid using the squared returns in the semiparametric estimation of long memory volatility dependencies.     

论工程训练与创新人才培养

工程训练是重要的实践性教学环节 ,必须把工作重点转移到培养学生创新能力上来 ,创造有利于培养创新人才的环境 ,传授给学生丰富的创新知识基础 ,改革教学内容、教学方法、教学手段和考核办法 ,以保证培养创新人才的需要 ,并注意培养学生各种创新素质 ,鼓励学生创新 ,促进其创新能力的发展     

论企业组织创新风险

企业组织创新伴随着巨大风险 ,导致创新行为的失败。风险蛰伏在以人为中心、以组织结构为中心和组织流程为中心的组织创新内容中 ,通过创新动机、战略、整合和速度等创新行为要素表现出来。造成创新风险的原因在于企业组织创新动因机理的复杂性、运行过程的动态不平衡性以及组织创新环境与条件的变动性诸方面。     

Type I error rates from likelihood‐based repeated measures analyses of incomplete longitudinal data

The last observation carried forward (LOCF) approach is commonly utilized to handle missing values in the primary analysis of clinical trials. However, recent evidence suggests that likelihood‐based analyses developed under the missing at random (MAR) framework are sensible alternatives. The objective of this study was to assess the Type I error rates from a likelihood‐based MAR approach – mixed‐model repeated measures (MMRM) – compared with LOCF when estimating treatment contrasts for mean change from baseline to endpoint (Δ). Data emulating neuropsychiatric clinical trials were simulated in a 4 × 4 factorial arrangement of scenarios, using four patterns of mean changes over time and four strategies for deleting data to generate subject dropout via an MAR mechanism. In data with no dropout, estimates of Δ and SE_Δ from MMRM and LOCF were identical. In data with dropout, the Type I error rates (averaged across all scenarios) for MMRM and LOCF were 5.49% and 16.76%, respectively. In 11 of the 16 scenarios, the Type I error rate from MMRM was at least 1.00% closer to the expected rate of 5.00% than the corresponding rate from LOCF. In no scenario did LOCF yield a Type I error rate that was at least 1.00% closer to the expected rate than the corresponding rate from MMRM. The average estimate of SE_Δ from MMRM was greater in data with dropout than in complete data, whereas the average estimate of SE_Δ from LOCF was smaller in data with dropout than in complete data, suggesting that standard errors from MMRM better reflected the uncertainty in the data. The results from this investigation support those from previous studies, which found that MMRM provided reasonable control of Type I error even in the presence of MNAR missingness. No universally best approach to analysis of longitudinal data exists. However, likelihood‐based MAR approaches have been shown to perform well in a variety of situations and are a sensible alternative to the LOCF approach. MNAR methods can be used within a sensitivity analysis framework to test the potential presence and impact of MNAR data, thereby assessing robustness of results from an MAR method. Copyright © 2004 John Wiley & Sons, Ltd.     

图书馆实现知识管理的思考

介绍图书馆知识管理的内容,分析知识管理对图书馆管理核心、业务工作范围、信息技术要求的影响,提出了构建知识团队组织、运用支撑知识管理的信息技术、显性知识的数字化处理、注重智力知识资源开发是图书馆实现知识管理的有效途径。     

Significant Factors of Aviation Insurance and Risk Management Strategy: An Empirical Study of Taiwanese Airline Carriers

Aviation insurance premiums have become a heavy burden for the airline industry since September 11, 2001. Although the industry must constantly balance its operations between profitability and safety, the reality is that airlines are in the business of making money. Therefore, their ability to reduce cost and manage risk is a key factor for success. Unlike past research, which used subjective judgment methods, this study applied quantitative historical data (1999–2000) and gray relation analysis to identify the primary factors influencing ratemaking for aviation insurance premiums. An empirical study of six airlines in Taiwan was conducted to determine these factors and to analyze the management strategies used to deal with them. Results showed that the loss experience and performance of individual airlines were the key elements associated with aviation insurance premiums paid by each airline. By identifying and understanding the primary factors influencing ratemaking for aviation insurance, airlines will better understand their relative operational strengths and weaknesses, and further help top management identify areas for further improvement. Knowledge of these factors combined with effective risk management strategies, may result in lower premiums and operating costs for airline companies.     

Implied Preference for Seismic Design Level and Earthquake Insurance

Seismic risk can be reduced by implementing newly developed seismic provisions in design codes. Furthermore, financial protection or enhanced utility and happiness for stakeholders could be gained through the purchase of earthquake insurance. If this is not so, there would be no market for such insurance. However, perceived benefit associated with insurance is not universally shared by stakeholders partly due to their diverse risk attitudes. This study investigates the implied seismic design preference with insurance options for decisionmakers of bounded rationality whose preferences could be adequately represented by the cumulative prospect theory (CPT). The investigation is focused on assessing the sensitivity of the implied seismic design preference with insurance options to model parameters of the CPT and to fair and unfair insurance arrangements. Numerical results suggest that human cognitive limitation and risk perception can affect the implied seismic design preference by the CPT significantly. The mandatory purchase of fair insurance will lead the implied seismic design preference to the optimum design level that is dictated by the minimum expected lifecycle cost rule. Unfair insurance decreases the expected gain as well as its associated variability, which is preferred by risk-averse decisionmakers. The obtained results of the implied preference for the combination of the seismic design level and insurance option suggest that property owners, financial institutions, and municipalities can take advantage of affordable insurance to establish successful seismic risk management strategies.     

从“知识考古”到“美学解救”——论现代“人”的福柯式解构

笛卡尔以来，主体问题始终是现代哲学最为核心的问题。但是，从哲学的语言论转向开始，主体已经声名狼藉，主体哲学的范式被视为陈腐过时了，传统的主体之争已经没有意义，无论语言是第一位，或者自我意识的个体优先，这两个范式中的任何一个都凸现和遮蔽着什么，将这两者联系起来或者寻找一种介于这两种范式之间的思路倒是可能的，如米歇尔福柯之路。     

Effects of Marriage and Children on Financial Risk Tolerance: A Synthesis of Family Development and Prospect Theory

Family development and prospect theory were used as a framework to predict variability in individuals' subjective financial risk tolerance within distinct family structures. Gender, age, and income were expected to interact with the main effects of family structure (marital status and children). Theory-generated hypotheses were examined in Study 1 (data from university housing respondents, n = 76) and Study 2 (the 1998 Survey of Consumer Finances, n = 4,305). One family structure main effect (child presence) was significant for investment risk tolerance in both studies. Family structure interactions (marital status × age and child × income) were significant for employment risk (Study 1), and child × age was significant for investment risk in Study 2.     

Assessing goodness-of-fit of categorical regression models based on case-control data

Demonstrated equivalence between a categorical regression model based on case‐control data and an I‐sample semiparametric selection bias model leads to a new goodness‐of‐fit test. The proposed test statistic is an extension of an existing Kolmogorov–Smirnov‐type statistic and is the weighted average of the absolute differences between two estimated distribution functions in each response category. The paper establishes an optimal property for the maximum semiparametric likelihood estimator of the parameters in the I‐sample semiparametric selection bias model. It also presents a bootstrap procedure, some simulation results and an analysis of two real datasets.