In this paper, the discrete mean-variance model is considered for portfolio selection under concave transaction costs. By using the Cholesky decomposition technique, the convariance matrix to obtain a separable mixed ...In this paper, the discrete mean-variance model is considered for portfolio selection under concave transaction costs. By using the Cholesky decomposition technique, the convariance matrix to obtain a separable mixed integer nonlinear optimization problem is decomposed. A brand-and-bound algorithm based on Lagrangian relaxation is then proposed. Computational results are reported for test problems with the data randomly generated and those from the US stock market.展开更多
This paper proposes a multi-period portfolio investment model with class constraints, transaction cost, and indivisible securities. When an investor joins the securities market for the first time, he should decide on ...This paper proposes a multi-period portfolio investment model with class constraints, transaction cost, and indivisible securities. When an investor joins the securities market for the first time, he should decide on portfolio investment based on the practical conditions of securities market. In addition, investors should adjust the portfolio according to market changes, changing or not changing the category of risky securities. Markowitz meanvariance approach is applied to the multi-period portfolio selection problems. Because the sub-models are optimal mixed integer program, whose objective function is not unimodal and feasible set is with a particular structure, traditional optimization method usually fails to find a globally optimal solution. So this paper employs the hybrid genetic algorithm to solve the problem. Investment policies that accord with finance market and are easy to operate for investors are put forward with an illustration of application.展开更多
This paper concerns with modeling and design of an algorithm for the portfolio selection problems with fixed transaction costs and minimum transaction lots. A mean-variance model for the portfolio selection problem is...This paper concerns with modeling and design of an algorithm for the portfolio selection problems with fixed transaction costs and minimum transaction lots. A mean-variance model for the portfolio selection problem is proposed, and the model is formulated as a non-smooth and nonlinear integer programming problem with multiple objective functions. As it has been proven that finding a feasible solution to the problem only is already NP-hard, based on NSGA-II and genetic algorithm for numerical optimization of constrained problems (Genocop), a multi-objective genetic algorithm (MOGA) is designed to solve the model. Its features comprise integer encoding and corresponding operators, and special treatment of constraints conditions. It is illustrated via a numerical example that the genetic algorithm can efficiently solve portfolio selection models proposed in this paper. This approach offers promise for the portfolio problems in practice.展开更多
We present a parallel algorithm that computes the ask and bid prices of an American option when proportional transaction costs apply to trading in the underlying asset. The algorithm computes the prices on recombining...We present a parallel algorithm that computes the ask and bid prices of an American option when proportional transaction costs apply to trading in the underlying asset. The algorithm computes the prices on recombining binomial trees, and is designed for modern multi-core processors. Although parallel option pricing has been well studied, none of the existing approaches takes transaction costs into consideration. The algorithm that we propose partitions a binomial tree into blocks. In any round of computation a block is further partitioned into regions which are assigned to distinct processors. To minimise load imbalance the assignment of nodes to processors is dynamically adjusted before each new round starts. Synchronisation is required both within a round and between two successive rounds. The parallel speedup of the algorithm is proportional to the number of processors used. The parallel algorithm was implemented in C/C++ via POSIX Threads, and was tested on a machine with 8 processors. In the pricing of an American put option, the parallel speedup against an efficient sequential implementation was 5.26 using 8 processors and 1500 time steps, achieving a parallel efficiency of 65.75%.展开更多
The purpose of the article is to formulate, under the ∞ risk measure, a model of portfolio selection with transaction costs and then investigate the optimal strategy within the proposed. The characterization of a opt...The purpose of the article is to formulate, under the ∞ risk measure, a model of portfolio selection with transaction costs and then investigate the optimal strategy within the proposed. The characterization of a optimal strategy and the efficient algorithm for finding the optimal strategy are given.展开更多
In this paper, a convex programming model for portfolio select with trans- action costs was present, we proved the existence condition of optimal solution, and gave a simple example to the optimal solution.
In this paper, we consider the problem of optimal dividend payout and equity issuance for a company whose liquid asset is modeled by the dual of classical risk model with diffusion. We assume that there exist both pro...In this paper, we consider the problem of optimal dividend payout and equity issuance for a company whose liquid asset is modeled by the dual of classical risk model with diffusion. We assume that there exist both proportional and fixed transaction costs when issuing new equity. Our objective is to maximize the expected cumulative present value of the dividend payout minus the equity issuance until the time of bankruptcy,which is defined as the first time when the company＇s capital reserve falls below zero. The solution to the mixed impulse-singular control problem relies on two auxiliary subproblems： one is the classical dividend problem without equity issuance, and the other one assumes that the company never goes bankrupt by equity issuance.We first provide closed-form expressions of the value functions and the optimal strategies for both auxiliary subproblems. We then identify the solution to the original problem with either of the auxiliary problems. Our results show that the optimal strategy should either allow for bankruptcy or keep the company＇s reserve above zero by issuing new equity, depending on the model＇s parameters. We also present some economic interpretations and sensitivity analysis for our results by theoretical analysis and numerical examples.展开更多
To study the uncertain optimization problems on implementation schedule, time-cost trade-off and quality in enterprise resource planning （ERP） implementation, combined with program evaluation and review technique （...To study the uncertain optimization problems on implementation schedule, time-cost trade-off and quality in enterprise resource planning （ERP） implementation, combined with program evaluation and review technique （PERT）, some optimization models are proposed, which include the implementation schedule model, the timecost trade-off model, the quality model, and the implementation time-cost-quality synthetic optimization model. A PERT-embedded genetic algorithm （GA） based on stochastic simulation technique is introduced to the optimization models solution. Finally, an example is presented to show that the models and algorithm are reasonable and effective, which can offer a reliable quantitative decision method for ERP implementation.展开更多
We seek a discussion about the most suitable feedback control structure for stock trading under the consideration of proportional transaction costs. Suitability refers to robustness and performance capability. Both ar...We seek a discussion about the most suitable feedback control structure for stock trading under the consideration of proportional transaction costs. Suitability refers to robustness and performance capability. Both are tested by considering different one-step ahead prediction qualities, including the ideal case （perfect price-ahead prediction）, correct prediction of the direction of change in daily stock prices and the worst-case （wrong price rate sign-prediction at all sampling intervals）. Feedback control structures are partitioned into two general classes： stochastic model predictive control （SMPC） and genetic. For the former class, three controllers are discussed, whereby it is distinguished between two Markowitz- and one dynamic hedging-inspired SMPC formulation. For the latter class, five trading algorithms are disucssed, whereby it is distinguished between two different moving average （MA） based strategies, two trading range （TR） based strategies, and one strategy based on historical optimal （HistOpt） trajectories. This paper also gives a preliminary discussion about how modified dynamic hedging-inspired SMPC formulations may serve as alternatives to Markowitz portfolio optimization. The combinations of all of the eight controllers with five different one-step ahead prediction methods are backtested for daily trading of the 30 components of the German stock market index DAX for the time period between November 27, 2015 and November 25, 2016.展开更多
In this paper, we study the optimal financing problem in the dual model. We introduce a value function which considers both the expected present value of the dividends payout minus the equity issuance and a penalty at...In this paper, we study the optimal financing problem in the dual model. We introduce a value function which considers both the expected present value of the dividends payout minus the equity issuance and a penalty at ruin. In order to get the optimal strategy,two categories of suboptimal models are constructed and studied. Based on these two suboptimal models, we identify the value function and the optimal strategy in the general optimal problem.展开更多
The layout optimization design of a natural gas gathering pipeline network is a multi-objective optimization problem because the extant theories are unable to meet the different decision preferences in scheme design,w...The layout optimization design of a natural gas gathering pipeline network is a multi-objective optimization problem because the extant theories are unable to meet the different decision preferences in scheme design,which restricts the intelligentization of gas gathering pipeline layout optimization.Currently,there are no generic design studies on the loop-star pipeline network.Therefore,this paper proposes a generic layout optimization model containing a large number of discrete and continuous variables,such as pipe connection relationships,pipe sizes,pipe length,and pipe specifications.In the solution section,drawing inspiration from the hormone regulation mechanism and local foraging rule in bionics,an improved particle swarm optimization algorithm based on hormone regulation(HRPSO)is proposed,and it obtains the favorable parameters range of the HRPSO algorithm.The results illustrate that the HRPSO algorithm exhibits convergence to the global optimum with a probability of 1.In comparison to manual design,the comprehensive costs of the optimized scheme are saved by 22.71%with the HRPSO algorithm.Compared to the four PSO variants in the paper,it can save costs by 5.38%,4.95%,4.09%,and 3.65%,respectively.展开更多
基金supported by the National Natural Science Foundation of China (Grant Nos.70671064,70518001)
文摘In this paper, the discrete mean-variance model is considered for portfolio selection under concave transaction costs. By using the Cholesky decomposition technique, the convariance matrix to obtain a separable mixed integer nonlinear optimization problem is decomposed. A brand-and-bound algorithm based on Lagrangian relaxation is then proposed. Computational results are reported for test problems with the data randomly generated and those from the US stock market.
基金Supported by Natural Science Foundation of Tianjin (No 09JCYBJC01800, No07JCYBJC05200)Application Mathematic Center of Liu Hui, Nankai University and Tianjin University (No2001T08)
文摘This paper proposes a multi-period portfolio investment model with class constraints, transaction cost, and indivisible securities. When an investor joins the securities market for the first time, he should decide on portfolio investment based on the practical conditions of securities market. In addition, investors should adjust the portfolio according to market changes, changing or not changing the category of risky securities. Markowitz meanvariance approach is applied to the multi-period portfolio selection problems. Because the sub-models are optimal mixed integer program, whose objective function is not unimodal and feasible set is with a particular structure, traditional optimization method usually fails to find a globally optimal solution. So this paper employs the hybrid genetic algorithm to solve the problem. Investment policies that accord with finance market and are easy to operate for investors are put forward with an illustration of application.
文摘This paper concerns with modeling and design of an algorithm for the portfolio selection problems with fixed transaction costs and minimum transaction lots. A mean-variance model for the portfolio selection problem is proposed, and the model is formulated as a non-smooth and nonlinear integer programming problem with multiple objective functions. As it has been proven that finding a feasible solution to the problem only is already NP-hard, based on NSGA-II and genetic algorithm for numerical optimization of constrained problems (Genocop), a multi-objective genetic algorithm (MOGA) is designed to solve the model. Its features comprise integer encoding and corresponding operators, and special treatment of constraints conditions. It is illustrated via a numerical example that the genetic algorithm can efficiently solve portfolio selection models proposed in this paper. This approach offers promise for the portfolio problems in practice.
文摘We present a parallel algorithm that computes the ask and bid prices of an American option when proportional transaction costs apply to trading in the underlying asset. The algorithm computes the prices on recombining binomial trees, and is designed for modern multi-core processors. Although parallel option pricing has been well studied, none of the existing approaches takes transaction costs into consideration. The algorithm that we propose partitions a binomial tree into blocks. In any round of computation a block is further partitioned into regions which are assigned to distinct processors. To minimise load imbalance the assignment of nodes to processors is dynamically adjusted before each new round starts. Synchronisation is required both within a round and between two successive rounds. The parallel speedup of the algorithm is proportional to the number of processors used. The parallel algorithm was implemented in C/C++ via POSIX Threads, and was tested on a machine with 8 processors. In the pricing of an American put option, the parallel speedup against an efficient sequential implementation was 5.26 using 8 processors and 1500 time steps, achieving a parallel efficiency of 65.75%.
基金Supported by the National Natural Sciences Foundation of China.
文摘The purpose of the article is to formulate, under the ∞ risk measure, a model of portfolio selection with transaction costs and then investigate the optimal strategy within the proposed. The characterization of a optimal strategy and the efficient algorithm for finding the optimal strategy are given.
文摘In this paper, a convex programming model for portfolio select with trans- action costs was present, we proved the existence condition of optimal solution, and gave a simple example to the optimal solution.
基金partially supported by grants of the National Natural Science Foundation of China(Nos.71231008,71201173,71301031,71471045)Natural Science Foundation of Guangdong Province of China(No.S2013010011959)the Post-Doctoral Foundation of China(Nos.2012M510195,2014T70796)
文摘In this paper, we consider the problem of optimal dividend payout and equity issuance for a company whose liquid asset is modeled by the dual of classical risk model with diffusion. We assume that there exist both proportional and fixed transaction costs when issuing new equity. Our objective is to maximize the expected cumulative present value of the dividend payout minus the equity issuance until the time of bankruptcy,which is defined as the first time when the company＇s capital reserve falls below zero. The solution to the mixed impulse-singular control problem relies on two auxiliary subproblems： one is the classical dividend problem without equity issuance, and the other one assumes that the company never goes bankrupt by equity issuance.We first provide closed-form expressions of the value functions and the optimal strategies for both auxiliary subproblems. We then identify the solution to the original problem with either of the auxiliary problems. Our results show that the optimal strategy should either allow for bankruptcy or keep the company＇s reserve above zero by issuing new equity, depending on the model＇s parameters. We also present some economic interpretations and sensitivity analysis for our results by theoretical analysis and numerical examples.
基金the National High-Tech. R & D Program for CIMS, China (2003AA413210).
文摘To study the uncertain optimization problems on implementation schedule, time-cost trade-off and quality in enterprise resource planning （ERP） implementation, combined with program evaluation and review technique （PERT）, some optimization models are proposed, which include the implementation schedule model, the timecost trade-off model, the quality model, and the implementation time-cost-quality synthetic optimization model. A PERT-embedded genetic algorithm （GA） based on stochastic simulation technique is introduced to the optimization models solution. Finally, an example is presented to show that the models and algorithm are reasonable and effective, which can offer a reliable quantitative decision method for ERP implementation.
文摘We seek a discussion about the most suitable feedback control structure for stock trading under the consideration of proportional transaction costs. Suitability refers to robustness and performance capability. Both are tested by considering different one-step ahead prediction qualities, including the ideal case （perfect price-ahead prediction）, correct prediction of the direction of change in daily stock prices and the worst-case （wrong price rate sign-prediction at all sampling intervals）. Feedback control structures are partitioned into two general classes： stochastic model predictive control （SMPC） and genetic. For the former class, three controllers are discussed, whereby it is distinguished between two Markowitz- and one dynamic hedging-inspired SMPC formulation. For the latter class, five trading algorithms are disucssed, whereby it is distinguished between two different moving average （MA） based strategies, two trading range （TR） based strategies, and one strategy based on historical optimal （HistOpt） trajectories. This paper also gives a preliminary discussion about how modified dynamic hedging-inspired SMPC formulations may serve as alternatives to Markowitz portfolio optimization. The combinations of all of the eight controllers with five different one-step ahead prediction methods are backtested for daily trading of the 30 components of the German stock market index DAX for the time period between November 27, 2015 and November 25, 2016.
基金Supported by the National Natural Science Foundation of China(Grant No.11361007)the Guangxi Natural Science Foundation(Grant No.2014GXNSFCA118001)+3 种基金the Fostering Project of Dominant Discipline and Talent Team of Shandong Provincial Higher Education Institutionsthe Fostering Project of Dominant Discipline and Talent Team of SDUFEProject of Shandong Provincial Higher Educational Science and Technology Program(Grant Nos.J15LI01J17KA163)
文摘In this paper, we study the optimal financing problem in the dual model. We introduce a value function which considers both the expected present value of the dividends payout minus the equity issuance and a penalty at ruin. In order to get the optimal strategy,two categories of suboptimal models are constructed and studied. Based on these two suboptimal models, we identify the value function and the optimal strategy in the general optimal problem.
基金funding provided by the National Natural Science Foundation of China,China(Grant No.52104065,52074090)the Heilongjiang Provincial Natural Science Foundation of China,China(Grant No.LH2021E019)+3 种基金the China Postdoctoral Science Foundation,China(Grant Nos.2022T150089 and 2020M681064)the Heilongjiang Postdoctoral Foundation,China(Grant No.LBH-Z20101)the Scientific Research Personnel Training Foundation of Northeast Petroleum University,China(Grant No.XNYXLY202103)Northeast Petroleum University Scientific Research Foundation,China(Grant No.2019KQ54).
文摘The layout optimization design of a natural gas gathering pipeline network is a multi-objective optimization problem because the extant theories are unable to meet the different decision preferences in scheme design,which restricts the intelligentization of gas gathering pipeline layout optimization.Currently,there are no generic design studies on the loop-star pipeline network.Therefore,this paper proposes a generic layout optimization model containing a large number of discrete and continuous variables,such as pipe connection relationships,pipe sizes,pipe length,and pipe specifications.In the solution section,drawing inspiration from the hormone regulation mechanism and local foraging rule in bionics,an improved particle swarm optimization algorithm based on hormone regulation(HRPSO)is proposed,and it obtains the favorable parameters range of the HRPSO algorithm.The results illustrate that the HRPSO algorithm exhibits convergence to the global optimum with a probability of 1.In comparison to manual design,the comprehensive costs of the optimized scheme are saved by 22.71%with the HRPSO algorithm.Compared to the four PSO variants in the paper,it can save costs by 5.38%,4.95%,4.09%,and 3.65%,respectively.
