Optimal Portfolio Insurance under Nonlinear Transaction Costs

The minimization of the costs related to portfolio insurance is a very important investment strategy. In this article, by adding the transaction costs to the classical minimum cost portfolio insurance (MCPI) problem, we define and study the MCPI under transaction costs (MCPITC) problem as a nonlinear programming (NLP) problem. In this way, the MCPI problem becomes more realistic. Since such NLP problems are commonly solved by heuristics, we use the Beetle Antennae Search (BAS) algorithm to provide a solution to the MCPITC problem. Numerical experiments and computer simulations in real-world data sets confirm that our approach is an excellent alternative to other evolutionary computation algorithms

MARKOV CLUSTERING FOR PORTFOLIO CONSTRUCTION UNDER STOCHASTIC ENVIRONMENT

Until recently there were still many new investors andfinancial consultants whoface dificulties in stocks portfolio construction, both in terms of selection anddeciding how large portion ofeach asset in the portfolio. It takes relatively longertime and hence they constantly strive to achieve faster portfolio constructionbecause timely information can mean the difference between a deal struck ormissed, which translates to substantial profit or loss. This paper aims to analyzethe efficiency ofMarkov clustering processes for portfolio construction in order tospeed up assets selection based on correlation principle. Furthermore, portfoliooptimization for selected assets will be achieved with Markovian modeldriven bya Brownian motion process under stochastic environment. We compare theperformance ofthe constructed portfolio to LQ45, Kompcisioo, and Bisnis2y indicesusing Sharpe Ratio, and the results show that it outperforms these benchmarkindices. Hence, investors might use Markov clustering technique in the stocksselection as an alternative since it is more efficient in terms oftime and in this caseproven to provide better reward to risk taken by the investors

Interpretive structural model of key performance indicators for sustainable manufacturing evaluation in automotive companies

This paper aims to analyze the interrelationships among the key performance indicators of sustainable manufacturing evaluation in automotive companies. The initial key performance indicators have been identified and derived from literature and were then validated by industry survey. Interpretive structural modeling (ISM) methodology is applied to develop a hierarchical structure of the key performance indicators in three levels. Of nine indicators, there are five unstable indicators which have both high driver and dependence power, thus requiring further attention. It is believed that the model can provide a better insight for automotive managers in assessing their sustainable manufacturing performance

Valuing infrastructure investments as portfolios of interdependent real options

The value of infrastructure investments is frequently influenced by enormous uncertainty surrounding both exogenous and endogenous factors. At the same time, however, their value is generally driven by much flexibility - i.e. options - with respect to design, financing, construction and operation. Real options analysis aims to pro-actively manage risks by valuing the flexibilities inherent in uncertain investments. Although real options generally occur within portfolios whose value is affected by both exogenous and endogenous uncertainty, most existing valuation approaches focus on single (i.e. individual) options and consider only exogenous uncertainty. In this thesis, we introduce an approach for modelling and approximating the value of portfolios of interdependent real options under exogenous uncertainty, using both influence diagrams and simulation-and-regression. The key features of this approach are that it translates the interdependencies between real options into linear constraints and then integrates these in a portfolio optimisation problem, formulated as a multi-stage stochastic integer programme. To approximate the value of this optimisation problem we present a transparent valuation algorithm based on simulation and parametric regression that explicitly takes into account the state variable's multidimensional resource component. We operationalise this approach using three numerical examples of increasing complexity: an American put option in a simple single-factor setting; a natural resource investment with a switching option in a one-factor setting; and the same investment in a three-factor setting. Subsequently, we demonstrate the ability of the proposed approach to evaluate a complex natural resource investment that features both a large portfolio of interdependent real options and four underlying uncertainties. We show how our approach can be used to investigate the way in which the value of that portfolio and its individual real options are affected by the underlying operating margin and the degrees of different uncertainties. Lastly, we extend this approach to include endogenous, decision- and state-dependent uncertainties. We present an efficient valuation algorithm that is more transparent than those used in existing approaches; by exploiting the problem structure it explicitly accounts for the path dependencies of the state variables. The applicability of the extended approach to complex investment projects is illustrated by valuing an urban infrastructure investment. We show the way in which the optimal value of the portfolio and its single, well-defined options are affected by the initial operating revenues, and by the degrees of exogenous and endogenous uncertainty.Open Acces

Applying Formal Methods to Networking: Theory, Techniques and Applications

Despite its great importance, modern network infrastructure is remarkable for the lack of rigor in its engineering. The Internet which began as a research experiment was never designed to handle the users and applications it hosts today. The lack of formalization of the Internet architecture meant limited abstractions and modularity, especially for the control and management planes, thus requiring for every new need a new protocol built from scratch. This led to an unwieldy ossified Internet architecture resistant to any attempts at formal verification, and an Internet culture where expediency and pragmatism are favored over formal correctness. Fortunately, recent work in the space of clean slate Internet design---especially, the software defined networking (SDN) paradigm---offers the Internet community another chance to develop the right kind of architecture and abstractions. This has also led to a great resurgence in interest of applying formal methods to specification, verification, and synthesis of networking protocols and applications. In this paper, we present a self-contained tutorial of the formidable amount of work that has been done in formal methods, and present a survey of its applications to networking.Comment: 30 pages, submitted to IEEE Communications Surveys and Tutorial