Bond portfolio immunization is a classical issue in finance. Since Macaulaygave the concept of duration in 1938, many scholars proposed different kinds of duration immunization models. In the literature of bond portfo...Bond portfolio immunization is a classical issue in finance. Since Macaulaygave the concept of duration in 1938, many scholars proposed different kinds of duration immunization models. In the literature of bond portfolio immunization usingmultifactor model, to the best of our knowledge, researchers only use the first-orderimmunization, which is usually called as duration immunization, and no one hasconsidered second-order effects in immunization, which is well known as “convexity” in the case of single-factor model. In this paper, we introduce the second-orderinformation associated with multifactor model into bond portfolio immunization andreformulate the corresponding problems as tractable semidefinite programs. Bothsimulation analysis and empirical study show that the second-order immunization strategies exhibit more accurate approximation to the value change of bonds and thusresult in better immunization performance.展开更多
The soybean aphid, Aphis glycines Matsumura(Hemiptera: Aphididae), is one of the greatest threats to soybean production, and both trend analysis and periodic analysis of its population dynamics are important for integ...The soybean aphid, Aphis glycines Matsumura(Hemiptera: Aphididae), is one of the greatest threats to soybean production, and both trend analysis and periodic analysis of its population dynamics are important for integrated pest management(IPM). Based on systematically investigating soybean aphid populations in the field from 2018 to 2020, this study adopted the inverse logistic model for the first time, and combined it with the classical logistic model to describe the changes in seasonal population abundance from colonization to extinction in the field. Then, the increasing and decreasing phases of the population fluctuation were divided by calculating the inflection points of the models, which exhibited distinct seasonal trends of the soybean aphid populations in each year. In addition, multifactor logistic models were then established for the first time, in which the abundance of soybean aphids in the field changed with time and relevant environmental conditions. This model enabled the prediction of instantaneous aphid abundance at a given time based on relevant meteorological data. Taken as a whole, the successful approaches implemented in this study could be used to build a theoretical framework for practical IPM strategies for controlling soybean aphids.展开更多
Process integration method is used to establish a composite model to perform computations of hybrid models for water quality assessment of Haihe River, and a resolution is presented to clear the long-term obscurity ab...Process integration method is used to establish a composite model to perform computations of hybrid models for water quality assessment of Haihe River, and a resolution is presented to clear the long-term obscurity about the differences between single-factor assessment(SFA) and multifactor assessment(MFA) of water quality in this paper. Symbolic models were introduced to describe the types and orders of computations involved in SFA and such MFAs as Nemerow comprehensive index(NCI) and fuzzy comprehensive assessment(FCA). Facilitated by paired t-tests, the composite model of absolute distance(AD) was established to test the differences between SFA and MFAs on four water quality indicators(WQI). Matlab(R14) programs for these models were developed to perform integrative computations on 3 217 batches of water data obtained from seven monitoring sites of Haihe River from 2008 to 2017. Paired t-tests show that results of our SFA model(SFA-4) are not significantly different(p=0.926) from that of SFA based on all WQI, however, extremely significantly different from results of NCI(p=0) and FCA(p=0). SFA-4 is proved by AD model to be farther away from FCA(AD-S→F=1.075) than from NCI(AD-S→N=0.634). More than proving the deduction of SFA≥NCI≥FCA in most cases(p=0.885), the results from AD show that MFAs approach SFA when surface water becomes good(SFA=1) or worst(SFA=6), whereas depart to the farthest distance from SFA when surface water becomes worse(SFA=3). To sum up, the integrative computations involved in AD model on the water data are effective and efficient(improved by 44.2%). Furthermore, AD model shows the differences between SFA and MFAs clearly.展开更多
基金This research is partially supported by the National Natural Science Foundation of China(Nos.71471180 and 71571062).
文摘Bond portfolio immunization is a classical issue in finance. Since Macaulaygave the concept of duration in 1938, many scholars proposed different kinds of duration immunization models. In the literature of bond portfolio immunization usingmultifactor model, to the best of our knowledge, researchers only use the first-orderimmunization, which is usually called as duration immunization, and no one hasconsidered second-order effects in immunization, which is well known as “convexity” in the case of single-factor model. In this paper, we introduce the second-orderinformation associated with multifactor model into bond portfolio immunization andreformulate the corresponding problems as tractable semidefinite programs. Bothsimulation analysis and empirical study show that the second-order immunization strategies exhibit more accurate approximation to the value change of bonds and thusresult in better immunization performance.
基金supported by the Chinese National Special Fund for Agro-scientific Research in the Public Interest (201003025 and 201103022)the National Key Research and Development Program of China (2018YFD0201004)the Discipline Construction Project of Liaoning Academy of Agricultural Sciences, China (2019DD082612)。
文摘The soybean aphid, Aphis glycines Matsumura(Hemiptera: Aphididae), is one of the greatest threats to soybean production, and both trend analysis and periodic analysis of its population dynamics are important for integrated pest management(IPM). Based on systematically investigating soybean aphid populations in the field from 2018 to 2020, this study adopted the inverse logistic model for the first time, and combined it with the classical logistic model to describe the changes in seasonal population abundance from colonization to extinction in the field. Then, the increasing and decreasing phases of the population fluctuation were divided by calculating the inflection points of the models, which exhibited distinct seasonal trends of the soybean aphid populations in each year. In addition, multifactor logistic models were then established for the first time, in which the abundance of soybean aphids in the field changed with time and relevant environmental conditions. This model enabled the prediction of instantaneous aphid abundance at a given time based on relevant meteorological data. Taken as a whole, the successful approaches implemented in this study could be used to build a theoretical framework for practical IPM strategies for controlling soybean aphids.
基金Supported by the National Natural Science Foundation of China(61872147,61761023).
文摘Process integration method is used to establish a composite model to perform computations of hybrid models for water quality assessment of Haihe River, and a resolution is presented to clear the long-term obscurity about the differences between single-factor assessment(SFA) and multifactor assessment(MFA) of water quality in this paper. Symbolic models were introduced to describe the types and orders of computations involved in SFA and such MFAs as Nemerow comprehensive index(NCI) and fuzzy comprehensive assessment(FCA). Facilitated by paired t-tests, the composite model of absolute distance(AD) was established to test the differences between SFA and MFAs on four water quality indicators(WQI). Matlab(R14) programs for these models were developed to perform integrative computations on 3 217 batches of water data obtained from seven monitoring sites of Haihe River from 2008 to 2017. Paired t-tests show that results of our SFA model(SFA-4) are not significantly different(p=0.926) from that of SFA based on all WQI, however, extremely significantly different from results of NCI(p=0) and FCA(p=0). SFA-4 is proved by AD model to be farther away from FCA(AD-S→F=1.075) than from NCI(AD-S→N=0.634). More than proving the deduction of SFA≥NCI≥FCA in most cases(p=0.885), the results from AD show that MFAs approach SFA when surface water becomes good(SFA=1) or worst(SFA=6), whereas depart to the farthest distance from SFA when surface water becomes worse(SFA=3). To sum up, the integrative computations involved in AD model on the water data are effective and efficient(improved by 44.2%). Furthermore, AD model shows the differences between SFA and MFAs clearly.
