This paper examines the forecasting performance of different kinds of GARCH model （GRACH, EGARCH, TARCH and APARCH） under the Normal, Student-t and Generalized error distributional assumption. We compare the effect ...This paper examines the forecasting performance of different kinds of GARCH model （GRACH, EGARCH, TARCH and APARCH） under the Normal, Student-t and Generalized error distributional assumption. We compare the effect of different distributional assumption on the GARCH models. The data we analyze are the daily stocks indexes for Shenzhen Stock Exchange （SSE） in China from April 3^rd, 1991 to April 14^th, 2005. We find that improvements of the overall estimation are achieved when asymmetric GARCH models are used with student-t distribution and generalized error distribution. Moreover, it is found that TARCH and GARCH models give better forecasting performance than EGARCH and APARCH models. In forecasting performance, the model under normal distribution gives more accurate forecasting performance than non-normal densities and generalized error distributions clearly outperform the student-t densities in case of SSE.展开更多
As trust becomes increasingly important in software domain, software trustworthiness--as a complex high- composite concept, has developed into a big challenge people have to face, especially in the current open, dynam...As trust becomes increasingly important in software domain, software trustworthiness--as a complex high- composite concept, has developed into a big challenge people have to face, especially in the current open, dynamic and ever-changing Internet environment. Furthermore, how to recognize and define trust problem from its nature and how to measure software trustworthiness correctly and effectively play a key role in improving users＇ trust in choosing software. Based on trust theory in the field of humanities and sociology, this paper proposes a measurable S2S （Social-to-Software） software trustworthiness framework, introduces a generalized indicator loss to unify three parts of trustworthiness result, and presents a whole metric solution for software trustworthiness, including the advanced J-M model based on power function and time-loss rate for ability trustworthiness measurement, the fuzzy comprehensive evaluation advanced-model considering effect of multiple short boards for basic standard trustworthiness, and the identity trustworthiness measurement method based on the code homology detecting tools. Finally, it provides a case study to verify that the solution is applicable and effective.展开更多
文摘This paper examines the forecasting performance of different kinds of GARCH model （GRACH, EGARCH, TARCH and APARCH） under the Normal, Student-t and Generalized error distributional assumption. We compare the effect of different distributional assumption on the GARCH models. The data we analyze are the daily stocks indexes for Shenzhen Stock Exchange （SSE） in China from April 3^rd, 1991 to April 14^th, 2005. We find that improvements of the overall estimation are achieved when asymmetric GARCH models are used with student-t distribution and generalized error distribution. Moreover, it is found that TARCH and GARCH models give better forecasting performance than EGARCH and APARCH models. In forecasting performance, the model under normal distribution gives more accurate forecasting performance than non-normal densities and generalized error distributions clearly outperform the student-t densities in case of SSE.
基金This work was supported by the National Natural Science Foundation of China under Grant No. 90818021, the HeGaoJi Program of China under Grant No. 2012zx01039-004-46, and the Information Security Program of National Development and Reform Commission of China under Grant No. 2012-1424.
文摘As trust becomes increasingly important in software domain, software trustworthiness--as a complex high- composite concept, has developed into a big challenge people have to face, especially in the current open, dynamic and ever-changing Internet environment. Furthermore, how to recognize and define trust problem from its nature and how to measure software trustworthiness correctly and effectively play a key role in improving users＇ trust in choosing software. Based on trust theory in the field of humanities and sociology, this paper proposes a measurable S2S （Social-to-Software） software trustworthiness framework, introduces a generalized indicator loss to unify three parts of trustworthiness result, and presents a whole metric solution for software trustworthiness, including the advanced J-M model based on power function and time-loss rate for ability trustworthiness measurement, the fuzzy comprehensive evaluation advanced-model considering effect of multiple short boards for basic standard trustworthiness, and the identity trustworthiness measurement method based on the code homology detecting tools. Finally, it provides a case study to verify that the solution is applicable and effective.
