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GENERALIZED STOCHASTIC DURATION INMARKOVIAN HEATH-JARROW-MORTONFRAMEWORK 被引量:1
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作者 简志宏 李楚霖 《Acta Mathematica Scientia》 SCIE CSCD 2002年第1期99-106,共8页
This paper focuses on how to measure the interest rate risk. The conventional measure methods of interest rate risk are reviewed and the duration concept is generalized to stochastic duration in the Markovian HJM fram... This paper focuses on how to measure the interest rate risk. The conventional measure methods of interest rate risk are reviewed and the duration concept is generalized to stochastic duration in the Markovian HJM framework. The generalized stochastic duration of the coupon bond is defined as the time to maturity of a zero coupon bond having the same instantaneous variance as the coupon bond. According to this definition., the authors first present the framework of Markovian HJM model, then deduce the measures of stochastic duration in some special cases which cover some extant interest term structure. 展开更多
关键词 generalized stochastic duration interest rate term structure HJM model
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Effect of time-of-day and day-of-the-week on congestion duration and breakdown:A case study at a bottleneck in Salem,NH 被引量:1
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作者 Eric M.Laflamme Paul J.Ossenbruggen 《Journal of Traffic and Transportation Engineering(English Edition)》 2017年第1期31-40,共10页
This work uses regression models to analyze two characteristics of recurrent congestion: breakdown, the transition from freely flowing conditions to a congested state, and duration, the time between the onset and cle... This work uses regression models to analyze two characteristics of recurrent congestion: breakdown, the transition from freely flowing conditions to a congested state, and duration, the time between the onset and clearance of recurrent congestion. First, we apply a binary logistic regression model where a continuous measurement for traffic flow and a dichoto- mous categorical variable for time-of-day (AM- or PM-rush hours) is used to predict the probability of breakdown. Second, we apply an ordinary least squares regression model where categorical variables for time-of-day (AM- or PM-rush hours) and day-of-the-week (Monday-Thursday or Friday) are used to predict recurrent congestion duration. Models are fitted to data collected from a bottleneck on 1-93 in Salem, NH, over a period of 9 months. Results from the breakdown model, predict probabilities of recurrent congestion, are consistent with observed traffic and illustrate an upshift in breakdown probabilities between the AM- and PM-rush periods. Results from the regression model for congestion duration reveal the presences of significant interaction between time-of-day and day-of-the-week. Thus, the effect of time-of-day on congestion duration depends on the day-of-the-week. This work provides a simplification of recurrent congestion and recovery, very noisy processes. Simplification, conveying complex relationships with simple statistical summaries-facts, is a practical and powerful tool for traffic administrators to use in the decision-making process. 展开更多
关键词 stochastic models Ordinary least squares regression Binary logistic regression Congestion duration Breakdown
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