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Option-like properties in the distribution of hedge fund returns

Katharina DENK, Ben DJERROUD, Luis SECO, Mohammad SHAKOURIFAR, Rudi ZAGST

《工程管理前沿（英文）》 2020年 第7卷 第2期   页码 275-286 doi: 10.1007/s42524-020-0095-3

摘要： Hedge funds have recently become popular because of their low correlation with traditional investments and their ability to generate positive returns with a relatively low volatility. However, a close look at those high-performing hedge funds raises the questions on whether their performance is truly superior and whether the high management fees are justified. Incurring no alpha costs, passive hedge fund replication strategies raise the question on whether they can similarly perform by improving efficiency at reduced costs. Therefore, this study investigates two different model approaches for the equity long/short strategy, where weighted segmented linear regression models are employed and combined with two-state Markov switching models. The main finding proves a short put option structure, i.e., short equity market volatility, with the put structure present in all market states. We obtain an evidence that the hedge fund managers decrease their short-volatility profile during turbulent markets.

关键词： hedge funds     hedge fund index     segmented linear regression models     regime-switching models     mimicking portfolios     single factor-based hedge fund replication     equity long–short strategy    

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SPT based determination of undrained shear strength: Regression models and machine learning

Walid Khalid MBARAK, Esma Nur CINICIOGLU, Ozer CINICIOGLU

《结构与土木工程前沿（英文）》 2020年 第14卷 第1期   页码 185-198 doi: 10.1007/s11709-019-0591-x

摘要： The purpose of this study is the accurate prediction of undrained shear strength using Standard Penetration Test results and soil consistency indices, such as water content and Atterberg limits. With this study, along with the conventional methods of simple and multiple linear regression models, three machine learning algorithms, random forest, gradient boosting and stacked models, are developed for prediction of undrained shear strength. These models are employed on a relatively large data set from different projects around Turkey covering 230 observations. As an improvement over the available studies in literature, this study utilizes correct statistical analyses techniques on a relatively large database, such as using a train/test split on the data set to avoid overfitting of the developed models. Furthermore, the validity and consistency of the prediction results are ensured with the correct use of statistical measures like -value and cross-validation which were missing in previous studies. To compare the performances of the models developed in this study with the prior ones existing in literature, all models were applied on the test data set and their performances are evaluated in terms of the resulting root mean squared error ( ) values and coefficient of determination ( ). Accordingly, the models developed in this study demonstrate superior prediction capabilities compared to all of the prior studies. Moreover, to facilitate the use of machine learning algorithms for prediction purposes, entire source code prepared for this study and the collected data set are provided as supplements of this study.

关键词： undrained shear strength     linear regression     random forest     gradient boosting     machine learning     standard penetration test    

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Multiple regression models for energy consumption of office buildings in different climates in China

Siyu ZHOU, Neng ZHU

《能源前沿（英文）》 2013年 第7卷 第1期   页码 103-110 doi: 10.1007/s11708-012-0220-z

摘要： The energy consumption of office buildings in China has been growing significantly in recent years. Obviously, there are significant relationships between building envelope and the energy consumption of office buildings. The 8 key building envelope influencing factors were found in this paper to evaluate their effects on the energy consumption of the air-conditioning system. The typical combinations of the key influencing factors were performed in Trnsy simulation. Then on the basis of the simulated results, the multiple regression models were developed respectively for the four climates of China—hot summer and warm winter, hot summer and cold winter, cold, and severely cold. According to the analysis of regression coefficients, the appropriate building envelope design schemes were discussed in different climates. At last, the regression model evaluations consisting of the simulation evaluations and the actual case evaluations were performed to verify the feasibility and accuracy of the regression models. The error rates are within±5% in the simulation evaluations and within±15% in the actual case evaluations. It is believed that the regression models developed in this paper can be used to estimate the energy consumption of office buildings in different climates when various building envelope designs are considered.

关键词： regression model     energy consumption     building envelope     office building     different climates    

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Multiple linear regression, artificial neural network, and fuzzy logic prediction of 28 days compressive

Faezehossadat KHADEMI,Mahmoud AKBARI,Sayed Mohammadmehdi JAMAL,Mehdi NIKOO

《结构与土木工程前沿（英文）》 2017年 第11卷 第1期   页码 90-99 doi: 10.1007/s11709-016-0363-9

摘要： Evaluating the in situ concrete compressive strength by means of cores cut from hardened concrete is acknowledged as the most ordinary method, however, it is very difficult to predict the compressive strength of concrete since it is affected by many factors such as different mix designs, methods of mixing, curing conditions, compaction, etc. In this paper, considering the experimental results, three different models of multiple linear regression model (MLR), artificial neural network (ANN), and adaptive neuro-fuzzy inference system (ANFIS) are established, trained, and tested within the Matlab programming environment for predicting the 28 days compressive strength of concrete with 173 different mix designs. Finally, these three models are compared with each other and resulted in the fact that ANN and ANFIS models enables us to reliably evaluate the compressive strength of concrete with different mix designs, however, multiple linear regression model is not feasible enough in this area because of nonlinear relationship between the concrete mix parameters. Finally, the sensitivity analysis (SA) for two different sets of parameters on the concrete compressive strength prediction are carried out.

关键词： concrete     28 days compressive strength     multiple linear regression     artificial neural network     ANFIS     sensitivity analysis (SA)    

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Integrated uncertain models for runoff forecasting and crop planting structure optimization of the Shiyang

Fan ZHANG, Mo LI, Shanshan GUO, Chenglong ZHANG, Ping GUO

《农业科学与工程前沿（英文）》 2018年 第5卷 第2期   页码 177-187 doi: 10.15302/J-FASE-2017177

摘要： To improve the accuracy of runoff forecasting, an uncertain multiple linear regression (UMLR) model is presented in this study. The proposed model avoids the transfer of random error generated in the independent variable to the dependent variable, as this affects prediction accuracy. On this basis, an inexact two-stage stochastic programming (ITSP) model is used for crop planting structure optimization (CPSO) with the inputs that are interval flow values under different probabilities obtained from the UMLR model. The developed system, in which the UMLR model for runoff forecasting and the ITSP model for crop planting structure optimization are integrated, is applied to a real case study. The aim of the developed system is to optimize crops planting area with limited available water resources base on the downstream runoff forecasting in order to obtain the maximum system benefit in the future. The solution obtained can demonstrate the feasibility and suitability of the developed system, and help decision makers to identify reasonable crop planting structure under multiple uncertainties.

关键词： crop planting structure optimization     inexact two-stage stochastic programming     runoff forecasting     Shiyang River Basin     uncertain multiple linear regression    

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Comparison between linear and non-linear forms of pseudo-first-order and pseudo-second-order adsorptionkinetic models for the removal of methylene blue by activated carbon

Junxiong LIN , Lan WANG ,

《环境科学与工程前沿（英文）》 2009年 第3卷 第3期   页码 320-324 doi: 10.1007/s11783-009-0030-7

摘要： The best-fit equations of linear and non-linear forms of the two widely used kinetic models, namely pseudo-first-order and pseudo-second-order equations, were compared in this study. The experimental kinetics of methylene blue adsorption on activated carbon was used for this research. Both the correlation coefficient () and the normalized standard deviation Δ(%) were employed as error analysis methods to determine the best-fitting equations. The results show that the non-linear forms of pseudo-first-order and pseudo-second-order models were more suitable than the linear forms for fitting the experimental data. The experimental kinetics may have been distorted by linearization of the linear kinetic equations, and thus, the non-linear forms of kinetic equations should be primarily used to obtain the adsorption parameters. In addition, the Δ(%) method for error analysis may be better to determine the best-fitting model in this case.

关键词： adsorption     pseudo-first order     pseudo-second order     kinetic model     linear method     non-linear method    

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Presentation of regression analysis, GP and GMDH models to predict the pedestrian density in various

Iraj BARGEGOL; Seyed Mohsen HOSSEINIAN; Vahid NAJAFI MOGHADDAM GILANI; Mohammad NIKOOKAR; Alireza OROUEI

《结构与土木工程前沿（英文）》 2022年 第16卷 第2期   页码 250-265 doi: 10.1007/s11709-021-0785-x

摘要： In this study, the relationship between space mean speed (SMS), flow rate and density of pedestrians was investigated in different pedestrian facilities, including 1 walkway, 2 sidewalks, 2 signalized crosswalks and 2 mid-block crosswalks. First, statistical analysis was performed to investigate the normality of data and correlation of variables. Regression analysis was then applied to determine the relationship between SMS, flow rate, and density of pedestrians. Finally, two prediction models of density were obtained using genetic programming (GP) and group method of data handling (GMDH) models, and k-fold and holdout cross-validation methods were used to evaluate the models. By the use of regression analysis, the mathematical relationships between variables in all facilities were calculated and plotted, and the best relationships were observed in flow rate-density diagrams. Results also indicated that GP had a higher R2 than GMDH in the prediction of pedestrian density in terms of flow rate and SMS, suggesting that GP was better able to model SMS and pedestrian density. Moreover, the application of k-fold cross-validation method in the models led to better performances compared to the holdout cross-validation method, which shows that the prediction models using k-fold were more reliable. Finally, density relationships in all facilities were obtained in terms of SMS and flow rate.

关键词： pedestrian density     regression analysis     GP model     GMDH model    

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使用数据驱动模型优化抗体纯化策略 Article

刘松崧, Lazaros G. Papageorgiou

《工程（英文）》 2019年 第5卷 第6期   页码 1077-1092 doi: 10.1016/j.eng.2019.10.011

摘要：

本工作致力于抗体片段纯化过程的多尺度优化。优化了生产过程中的色谱决策，包括色谱柱的数量及其大小，每批的循环数以及操作流速。使用基于微型实验数据的制造规模模拟数据集，建立了以负载质量、流速和柱床高度为输入的色谱通量数据驱动模型。与其他方法相比，分段线性回归建模方法具有简单、预测精度高的优点。提出了两种混合整数非线性规划（MINLP）模型，结合数据驱动模型，以最小化每克抗体纯化过程的总成本。然后，使用线性化技术和多参数分解将这些MINLP模型重新构造为混合整数线性规划（MILP）模型。研究了两个具有不同色谱柱尺寸替代品的工业相关案例，以证明所提出模型的适用性。

关键词： 抗体纯化     多尺度优化     抗原结合片段     混合整数规划     数据驱动模型     分段线性回归    

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Dielectric barrier micro-plasma reactor with segmented outer electrode for decomposition of pure CO

Baowei Wang, Xiaoxi Wang, Bo Zhang

《化学科学与工程前沿（英文）》 2021年 第15卷 第3期   页码 687-697 doi: 10.1007/s11705-020-1974-1

摘要： Four coaxial cylinder dielectric barrier discharge micro-plasma reactors were designed for the non-catalytic decomposition of pure CO into CO and O at low temperature and ambient pressure. The influence of segmented outer electrodes on the electrical characteristics and the reaction performance was investigated. Experimental results indicated that the introduction of segmented outer electrodes can significantly promote the decomposition of CO . Encouragingly, the highest conversion of 13.1% was obtained at an applied voltage of 18 kV, which was a substantial increase of 39.4% compared to the traditional device. Compared with other types of dielectric barrier discharge plasma reactors, the proposed segmented outer electrode micro-plasma reactor can give a higher CO conversion and acceptable energy efficiency. The increase in conversion can be attributed mainly to the enhanced corona discharge caused by the fringe effect at electrode edges, the increase in energy density and the increase in the number of micro-discharges. In addition, detailed electrical characterization was performed to reveal some trends in the electrical behavior of proposed reactors.

关键词： CO2 decomposition     dielectric barrier discharge     segmented outer electrodes     electrical analysis     reactor design    

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Using hybrid models to predict blood pressure reactivity to unsupported back based on anthropometric

Gurmanik KAUR,Ajat Shatru ARORA,Vijender Kumar JAIN

《信息与电子工程前沿（英文）》 2015年 第16卷 第6期   页码 474-485 doi: 10.1631/FITEE.1400295

摘要： Accurate blood pressure (BP) measurement is essential in epidemiological studies, screening programmes, and research studies as well as in clinical practice for the early detection and prevention of high BP-related risks such as coronary heart disease, stroke, and kidney failure. Posture of the participant plays a vital role in accurate measurement of BP. Guidelines on measurement of BP contain recommendations on the position of the back of the participants by advising that they should sit with supported back to avoid spuriously high readings. In this work, principal component analysis (PCA) is fused with forward stepwise regression (SWR), artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), and the least squares support vector machine (LS-SVM) model for the prediction of BP reactivity to an unsupported back in normotensive and hypertensive participants. PCA is used to remove multi-collinearity among anthropometric predictor variables and to select a subset of components, termed ‘principal components’ (PCs), from the original dataset. The selected PCs are fed into the proposed models for modeling and testing. The evaluation of the performance of the constructed models, using appropriate statistical indices, shows clearly that a PCA-based LS-SVM (PCA-LS-SVM) model is a promising approach for the prediction of BP reactivity in comparison to others. This assessment demonstrates the importance and advantages posed by hybrid models for the prediction of variables in biomedical research studies.

关键词： Blood pressure (BP)     Principal component analysis (PCA)     Forward stepwise regression     Artificial neural network (ANN)     Adaptive neuro-fuzzy inference system (ANFIS)     Least squares support vector machine (LS-SVM)    

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Unified methodology for site-characterization and sampling of highway runoff

Jy S. WU, Craig J. ALLAN,

《环境科学与工程前沿（英文）》 2010年 第4卷 第1期   页码 47-58 doi: 10.1007/s11783-010-0003-x

摘要： Hydrology, roadway traffic conditions, and atmospheric deposition are three essential data categories for the planning and implementation of highway-runoff monitoring and characterization programs. Causal variables pertaining to each data category could be site specific but have been shown to correlate with runoff pollutant loads. These data categories were combined to derive statistical relationships for characterization and prioritization of the respective pollutant loads at highway runoff sites. Storm runoff data of total suspended solids (TSS), total dissolved solid (TDS), chemical oxygen demand (COD), total Kjeldahl nitrogen (TKN) and total phosphorus (TP) collected from three highway sites in Charlotte, North Carolina, USA, were used to illustrate the development of site-specific highway-runoff pollutant loading models. This unified methodology provides a basis for initial assessment of the pollutant-constituent loads from highway runoff using hydrologic component variables. Improved reliability is achievable when additional traffic and/or atmospheric component variables are incorporated into the basic hydrologic regression model. In addition, operational guidance is suggested for implementing highway-runoff monitoring programs that are subject to sampling and resources constraints.

关键词： highway runoff     pollutant loads     regression models     non-point source pollution     storm water permit    

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A method to predict cooling load of large commercial buildings based on weather forecast and internal occupancy

Junbao JIA,Jincheng XING,Jihong LING,Ren PENG

《能源前沿（英文）》 2016年 第10卷 第4期   页码 459-465 doi: 10.1007/s11708-016-0424-8

摘要： Considering the fact that customers of large commercial buildings have the characteristics of the higher density and randomness, this paper presented an air-conditioning cooling load prediction method based on weather forecast and internal occupancy density. The multiple linear feedback regression model was applied to predict, with precision, the air conditioning cooling load. Case analysis showed that the largest mean relative error of hourly and the daily predicting cooling load maximum were 18.1% and 5.14%, respectively.

关键词： commercial building     load prediction     multiple linear regression    

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Estimating the effects of meteorology on PM

Liu YANG, Ye WU, Jerry M. DAVIS, Jiming HAO

《环境科学与工程前沿（英文）》 2011年 第5卷 第3期   页码 331-341 doi: 10.1007/s11783-011-0307-5

摘要： Particulate pollution was a critical challenge to the promise of good air quality during the 2008 Beijing Olympic Games, which took place from August 8th to 24th. To ensure good air quality for the Games, several temporary emission control measures were implemented in Beijing and surrounding areas. Ambient particulate matter concentration decreased significantly during the Olympic period; however, it is difficult to distinguish the effectiveness of those control measures since meteorology also affects ambient PM concentration. In this work, a multiple linear regression model based on continuous field monitoring at a roadside site was conducted to evaluate the effects of meteorology and emission control measures on the reduction of PM during the 2008 Olympic Games. The hourly data set was divided into two time periods, the no control period, June 22nd to July 4th, and the control period, July 28th to August 21st. The response variable was PM and the meteorology covariates used in the model were hourly temperature, dew point temperature, wind speed and precipitation. Wind direction was not a significant predictor of PM levels in either the control or the no control period. Using the meteorologically-based regression coefficients from the two time periods, meteorology was found to contribute to at least a 16% reduction in PM levels in the roadside microenvironment; while the pollution control measures contributed to at least a 43% reduction in PM levels.

关键词： meteorology     emission control measures     Beijing Olympic Games     PM2.5     linear statistical models    

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Models of thermodynamic and transport properties of POE VG68 and R410A/POE VG68 mixture

WEI Wenjian, DING Guoliang, HU Haitao, WANG Kaijian

《能源前沿（英文）》 2008年 第2卷 第2期   页码 227-234 doi: 10.1007/s11708-008-0020-7

摘要： The thermodynamic properties of a refrigerant-oil mixture are the foundation to predict the performance of air-conditioning and refrigeration systems and to evaluate the influence of oil on heat transfer and pressure drop. Models of the thermodynamic and transport properties of POE VG68 and R410A/POE VG68 mixture were provided based on the analysis of state-of-the-art correlations. New models were developed by modifying the coefficients in existing correlations with multiple regression method according to experimental data. The maximum deviation of the predicted values of these models to the experimental data is within 5%. These models can be used for R410A/POE VG68 to obtain accurate and reliable thermodynamic and transport parameters to evaluate the influence of POE VG68 on the performance of an R410A air-conditioning and refrigeration system.

关键词： multiple regression     foundation     thermodynamic     influence     air-conditioning    

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Relationships of nitrous oxide fluxes with water quality parameters in free water surface constructed wetlands

Juan WU, Jian ZHANG, Wenlin JIA, Huijun XIE, Bo ZHANG

《环境科学与工程前沿（英文）》 2009年 第3卷 第2期   页码 241-247 doi: 10.1007/s11783-009-0023-6

摘要： The effects of chemical oxygen demand (COD) concentration in the influent on nitrous oxide (N O) emissions, together with the relationships between N O and water quality parameters in free water surface constructed wetlands, were investigated with laboratory-scale systems. N O emission and purification performance of wastewater were very strongly dependent on COD concentration in the influent, and the total N O emission in the system with middle COD influent concentration was the least. The relationships between N O and the chemical and physical water quality variables were studied by using principal component scores in multiple linear regression analysis to predict N O flux. The multiple linear regression model against principal components indicated that different water parameters affected N O flux with different COD concentrations in the influent, but nitrate nitrogen affected N O flux in all systems.

关键词： free water surface constructed wetland     nitrous oxide emission     water quality parameter     principal component analysis     multiple linear regression    

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标题 作者 时间 类型 操作

Option-like properties in the distribution of hedge fund returns

Katharina DENK, Ben DJERROUD, Luis SECO, Mohammad SHAKOURIFAR, Rudi ZAGST

期刊论文

SPT based determination of undrained shear strength: Regression models and machine learning

Walid Khalid MBARAK, Esma Nur CINICIOGLU, Ozer CINICIOGLU

期刊论文

Multiple regression models for energy consumption of office buildings in different climates in China

Siyu ZHOU, Neng ZHU

期刊论文

Multiple linear regression, artificial neural network, and fuzzy logic prediction of 28 days compressive

Faezehossadat KHADEMI,Mahmoud AKBARI,Sayed Mohammadmehdi JAMAL,Mehdi NIKOO

期刊论文

Integrated uncertain models for runoff forecasting and crop planting structure optimization of the Shiyang

Fan ZHANG, Mo LI, Shanshan GUO, Chenglong ZHANG, Ping GUO

期刊论文

Comparison between linear and non-linear forms of pseudo-first-order and pseudo-second-order adsorptionkinetic models for the removal of methylene blue by activated carbon

Junxiong LIN , Lan WANG ,

期刊论文

Presentation of regression analysis, GP and GMDH models to predict the pedestrian density in various

Iraj BARGEGOL; Seyed Mohsen HOSSEINIAN; Vahid NAJAFI MOGHADDAM GILANI; Mohammad NIKOOKAR; Alireza OROUEI

期刊论文

使用数据驱动模型优化抗体纯化策略

刘松崧, Lazaros G. Papageorgiou

期刊论文

Dielectric barrier micro-plasma reactor with segmented outer electrode for decomposition of pure CO

Baowei Wang, Xiaoxi Wang, Bo Zhang

期刊论文

Using hybrid models to predict blood pressure reactivity to unsupported back based on anthropometric

Gurmanik KAUR,Ajat Shatru ARORA,Vijender Kumar JAIN

期刊论文

Unified methodology for site-characterization and sampling of highway runoff

Jy S. WU, Craig J. ALLAN,

期刊论文

A method to predict cooling load of large commercial buildings based on weather forecast and internal occupancy

Junbao JIA,Jincheng XING,Jihong LING,Ren PENG

期刊论文

Estimating the effects of meteorology on PM

Liu YANG, Ye WU, Jerry M. DAVIS, Jiming HAO

期刊论文

Models of thermodynamic and transport properties of POE VG68 and R410A/POE VG68 mixture

WEI Wenjian, DING Guoliang, HU Haitao, WANG Kaijian

期刊论文

Relationships of nitrous oxide fluxes with water quality parameters in free water surface constructed wetlands

Juan WU, Jian ZHANG, Wenlin JIA, Huijun XIE, Bo ZHANG

期刊论文