Deepwater oil and gas projects embody high risks from geology and engineering aspects, which exert substantial influence on project valuation. But the uncer- tainties may be converted to additional value to the projec...Deepwater oil and gas projects embody high risks from geology and engineering aspects, which exert substantial influence on project valuation. But the uncer- tainties may be converted to additional value to the projects in the case of flexible management. Given the flexibility of project management, this paper extends the classical real options model to a multi-factor model which contains oil price, geology, and engineering uncertainties. It then gives an application example of the new model to evaluate deepwater oil and gas projects with a numerical analytical method. Compared with other methods and models, this multi-factor real options model contains more project information. It reflects the potential value deriving not only from oil price variation but also from geology and engi- neering uncertainties, which provides more accurate and reliable valuation information for decision makers.展开更多
In this paper, a new branch-and-bound algorithm based on the Lagrangian dual relaxation and continuous relaxation is proposed for discrete multi-factor portfolio selection model with roundlot restriction in financial ...In this paper, a new branch-and-bound algorithm based on the Lagrangian dual relaxation and continuous relaxation is proposed for discrete multi-factor portfolio selection model with roundlot restriction in financial optimization. This discrete portfolio model is of integer quadratic programming problems. The separable structure of the model is investigated by using Lagrangian relaxation and dual search. Computational results show that the algorithm is capable of solving real-world portfolio problems with data from US stock market and randomly generated test problems with up to 120 securities.展开更多
Fuzzy sets theory cannot describe the neutrality degreeof data, which has largely limited the objectivity of fuzzy time seriesin uncertain data forecasting. With this regard, a multi-factor highorderintuitionistic fuz...Fuzzy sets theory cannot describe the neutrality degreeof data, which has largely limited the objectivity of fuzzy time seriesin uncertain data forecasting. With this regard, a multi-factor highorderintuitionistic fuzzy time series forecasting model is built. Inthe new model, a fuzzy clustering algorithm is used to get unequalintervals, and a more objective technique for ascertaining membershipand non-membership functions of the intuitionistic fuzzy setis proposed. On these bases, forecast rules based on multidimensionalintuitionistic fuzzy modus ponens inference are established.Finally, contrast experiments on the daily mean temperature ofBeijing are carried out, which show that the novel model has aclear advantage of improving the forecast accuracy.展开更多
Weighting values for different habitat variables used in multi-factor habitat suitability index (HSI) modeling reflect the relative influences of different variables on distribution of fish species. Using the winter-s...Weighting values for different habitat variables used in multi-factor habitat suitability index (HSI) modeling reflect the relative influences of different variables on distribution of fish species. Using the winter-spring cohort of neon flying squid (Ommastrephes bartramii) in the Northwestern Pacific Ocean as an example, we evaluated the impact of different weighting schemes on the HSI models based on sea surface temperature, gradient of sea surface temperature and sea surface height. We compared differences in predicted fishing effort and HSI values resulting from different weighting. The weighting for different habitat variables could greatly influence HSI modeling and should be carefully done based on their relative importance in influencing the resource spatial distribution. Weighting in a multi-factor HSI model should be further studied and optimization methods should be developed to improve forecasting squid spatial distributions.展开更多
In this paper, we empirically test a new model with the data of US services sector, which is an extension of the 5-factor model in Fama and French (2015) [1]. 3 types of 5 factors (Global, North American and US) are c...In this paper, we empirically test a new model with the data of US services sector, which is an extension of the 5-factor model in Fama and French (2015) [1]. 3 types of 5 factors (Global, North American and US) are compared. Empirical results show the Fama-French 5 factors are still alive! The new model has better in-sample fit than the 5-factor model in Fama and French (2015).展开更多
In this paper, we analyze US stock market with a new 5-factor model in Zhou and Li (2016) [1]. Data we use are 48 industry portfolios (Jul. 1963-Jan. 2017). Parameters are estimated by MLE. LR and KS are used for mode...In this paper, we analyze US stock market with a new 5-factor model in Zhou and Li (2016) [1]. Data we use are 48 industry portfolios (Jul. 1963-Jan. 2017). Parameters are estimated by MLE. LR and KS are used for model diagnostics. Model comparison is done with AIC. The results show Fama-French 5 factors are still alive. This new model in Zhou and Li (2016) [1] fits the data better than the one in Fama and French (2015) [2].展开更多
This article attempted to construct a multi-factor quantitative stock selection model,analyze the financial indicators and transaction data of listed companies in detail via the big data statistical test method,and to...This article attempted to construct a multi-factor quantitative stock selection model,analyze the financial indicators and transaction data of listed companies in detail via the big data statistical test method,and to find out the alpha excess return relative to the market in the case of short stock index futures as a hedge in the Chinese market.展开更多
国外动态财务分析(DFA)的投资产生器中以往都是采用CAPM对权益型资产进行定价。鉴于CAPM在中国资本市场的适用性尚存较大疑问,本文用较为精确的F am a和F rench的三因子模型对动态财务分析中的CAPM进行替代。并且利用历史数据对FF三因...国外动态财务分析(DFA)的投资产生器中以往都是采用CAPM对权益型资产进行定价。鉴于CAPM在中国资本市场的适用性尚存较大疑问,本文用较为精确的F am a和F rench的三因子模型对动态财务分析中的CAPM进行替代。并且利用历史数据对FF三因子模型的参数进行了估算,并对其解释能力进行了评估,保证了FF三因子模型可行。最后比较了FF三因子模型和CAPM在动态财务分析D ynaM o 3.0平台下的预测能力。得出在DFA下FF三因子模型的解释能力和预测准确性都强于CAPM的结论,建立了适合中国市场状况的投资产生器。展开更多
基金supported from the National Science and Technology Major Project under Grant No.2011ZX05030
文摘Deepwater oil and gas projects embody high risks from geology and engineering aspects, which exert substantial influence on project valuation. But the uncer- tainties may be converted to additional value to the projects in the case of flexible management. Given the flexibility of project management, this paper extends the classical real options model to a multi-factor model which contains oil price, geology, and engineering uncertainties. It then gives an application example of the new model to evaluate deepwater oil and gas projects with a numerical analytical method. Compared with other methods and models, this multi-factor real options model contains more project information. It reflects the potential value deriving not only from oil price variation but also from geology and engi- neering uncertainties, which provides more accurate and reliable valuation information for decision makers.
基金Project supported by the National Natural Science Foundation of China （Grant Nos.70518001. 70671064）
文摘In this paper, a new branch-and-bound algorithm based on the Lagrangian dual relaxation and continuous relaxation is proposed for discrete multi-factor portfolio selection model with roundlot restriction in financial optimization. This discrete portfolio model is of integer quadratic programming problems. The separable structure of the model is investigated by using Lagrangian relaxation and dual search. Computational results show that the algorithm is capable of solving real-world portfolio problems with data from US stock market and randomly generated test problems with up to 120 securities.
基金supported by the National Natural Science Foundation of China(61309022)
文摘Fuzzy sets theory cannot describe the neutrality degreeof data, which has largely limited the objectivity of fuzzy time seriesin uncertain data forecasting. With this regard, a multi-factor highorderintuitionistic fuzzy time series forecasting model is built. Inthe new model, a fuzzy clustering algorithm is used to get unequalintervals, and a more objective technique for ascertaining membershipand non-membership functions of the intuitionistic fuzzy setis proposed. On these bases, forecast rules based on multidimensionalintuitionistic fuzzy modus ponens inference are established.Finally, contrast experiments on the daily mean temperature ofBeijing are carried out, which show that the novel model has aclear advantage of improving the forecast accuracy.
基金supported by the National 863 project (2007AA092201 2007AA092202)+4 种基金National Development and Reform Commission Project (2060403)"Shu Guang" Project (08GG14) from Shanghai Municipal Education CommissionShanghai Leading Academic Discipline Project (Project S30702)supported by the National Distantwater Fisheries Engineering Research Center, and Scientific Observing and Experimental Station of Oceanic Fishery Resources, Ministry of Agriculture, ChinaYong Chen’s involvement in the project was supported by the Shanghai Dongfang Scholar Program
文摘Weighting values for different habitat variables used in multi-factor habitat suitability index (HSI) modeling reflect the relative influences of different variables on distribution of fish species. Using the winter-spring cohort of neon flying squid (Ommastrephes bartramii) in the Northwestern Pacific Ocean as an example, we evaluated the impact of different weighting schemes on the HSI models based on sea surface temperature, gradient of sea surface temperature and sea surface height. We compared differences in predicted fishing effort and HSI values resulting from different weighting. The weighting for different habitat variables could greatly influence HSI modeling and should be carefully done based on their relative importance in influencing the resource spatial distribution. Weighting in a multi-factor HSI model should be further studied and optimization methods should be developed to improve forecasting squid spatial distributions.
文摘In this paper, we empirically test a new model with the data of US services sector, which is an extension of the 5-factor model in Fama and French (2015) [1]. 3 types of 5 factors (Global, North American and US) are compared. Empirical results show the Fama-French 5 factors are still alive! The new model has better in-sample fit than the 5-factor model in Fama and French (2015).
文摘In this paper, we analyze US stock market with a new 5-factor model in Zhou and Li (2016) [1]. Data we use are 48 industry portfolios (Jul. 1963-Jan. 2017). Parameters are estimated by MLE. LR and KS are used for model diagnostics. Model comparison is done with AIC. The results show Fama-French 5 factors are still alive. This new model in Zhou and Li (2016) [1] fits the data better than the one in Fama and French (2015) [2].
基金Supported by National Natural Science Foundation of China(11961005)Guangdong Province General University Characteristic Innovation Project(2018KTSCX253).
文摘This article attempted to construct a multi-factor quantitative stock selection model,analyze the financial indicators and transaction data of listed companies in detail via the big data statistical test method,and to find out the alpha excess return relative to the market in the case of short stock index futures as a hedge in the Chinese market.
文摘国外动态财务分析(DFA)的投资产生器中以往都是采用CAPM对权益型资产进行定价。鉴于CAPM在中国资本市场的适用性尚存较大疑问,本文用较为精确的F am a和F rench的三因子模型对动态财务分析中的CAPM进行替代。并且利用历史数据对FF三因子模型的参数进行了估算,并对其解释能力进行了评估,保证了FF三因子模型可行。最后比较了FF三因子模型和CAPM在动态财务分析D ynaM o 3.0平台下的预测能力。得出在DFA下FF三因子模型的解释能力和预测准确性都强于CAPM的结论,建立了适合中国市场状况的投资产生器。
