Boundedness of the value function of the worst-case portfolio selection problem with linear constraints
Motivated by applications in manufacturing industry, we consider a supply chain scheduling problem, where each job is characterised by non-identical sizes, different release times and unequal processing times. The objective is to minimise the makespan by making batching and sequencing decisions. The problem is formalised as a mixed integer programming model and proved to be strongly NP-hard. Some structural properties are presented for both the general case and a special case. Based on these properties, a lower bound is derived, and a novel two-phase heuristic (TP-H) is developed to solve the problem, which guarantees to obtain a worst case performance ratio of . Computational experiments with a set of different sizes of random instances are conducted to evaluate the proposed approach TP-H, which is superior to another two heuristics proposed in the literature. Furthermore, the experimental results indicate that TP-H can effectively and efficiently solve large-size problems in a reasonable time.
The problem of optimal portfolio liquidation under transaction costs has been widely researched recently, thus producing several approaches to problem formulation and solving. Obtained results can be used for decision making during portfolio selection or automatic trading at high-frequency electronic markets. This work gives a review of modern studies in this field, comparing models and tracking their evolution. The paper also presents results of applying the most recent findings in this field to real MICEX shares high-frequency data and gives an interpretation of the results.
One of the most important indicators of company's success is the increase of its value. The article investigates traditional methods of company's value assessment and the evidence that the application of these methods is incorrect in the new stage of economy. So it is necessary to create a new method of valuation based on the new main sources of company's success that is its intellectual capital.
This paper proposes a procedure for dynamic optimization of an investment portfolio, consisting of stock market indices. SJC-copulas were used to assets statistical characteristics of assets. Copulas allow to measure interdependence between financial instruments, and to build an efficient investment portfolio. Since statistical characteristics of assets are changing with time, the structure of the portfolio is upgrading accordingly. The portfolio is then compared with two benchmarks in terms of return and risk. As a result the proposed procedure provides better performance. Also, the paper studies building a portfolio with short positions