Strategic financial management in a multinational financial conglomerate: A multiple goal stochastic programming approach

The paper discusses a multi-stage stochastic programming approach to the strategic financial management of a multi-company financial conglomerate. The planning system creates a comprehensive strategy which simultaneously covers a number of future scenarios within a multi-period planning horizon. Multiple conflicting goals may be specified for the group level, company level or individual business area level, and the decision maker’s preferences are allowed to change over time to reflect changing operating conditions and trade-off relationships between the goals. Special features include, among other things, full market valuation throughout the model, integrated treatment of different types of risks, explicit modelling of various types of intra-group transactions and relationships, extensive structures to deal with distressed assets and the covering of losses within the group, as well as consideration of potential portfolio effects of a diversified group structure on the cost of funding.     

Foreign versus domestic banks’ performance in the UK: a multicriteria approach

Although the banking sector in the UK is one of the most open and it is characterized by an increasing foreign bank presence, it remains relatively under-researched compared to studies for other countries. The objective of this paper is to investigate the performance of the UK banking sector focusing on the performance of the domestic banks as opposed to the performance of the foreign banks in order to test the hypothesis of higher performance of the domestic banks in a developed market. For this purpose, the UTADIS multicriteria methodology is employed to compare domestic and foreign banks performance over multiple criteria, such as profitability, liquidity, risk and efficiency, using a data sample covering 26 domestic and 32 foreign banks operating in the UK over the period 1998 to 2001. The results of the study, support the home advantage hypothesis, suggesting that the higher performance of domestic banks compared to foreign banks is also the case in the UK. The most important distinguishing performance factors between the two groups of banks are interest revenue to total earning assets, and profit before taxes to loans plus securities, which are higher for the domestic banks.AMS classification: 91B28     

Management Planning and Control in Multi-Branch Banking

This paper describes a model developed for a British bank to assist management in establishing branch goals, evaluating performance and planning new locations. Econometric methods are used to produce a set of equations which effectively predicts the main dimensions of branch performance.     

A goal programming model for bank assets and liabilities management

Assets and liabilities management is one of the most important issues in bank strategic planning. In the past, this problem has often been addressed through conventional mathematical programming, i.e. linear programming.However, bank management typically involves several conflicting goals, such as the maximisation of returns, minimisation of risk, expansion of deposits and loans, etc. The complexity of this problem can be captured more adequately by multiobjective mathematical programming. This paper discusses the construction and application at the Commercial Bank of Greece of a goal programming model that takes into account the essential institutional, financial, legal and bank policy considerations.     

Evolution of bank efficiency in Brazil: A DEA approach

This paper investigates cost, technical and allocative efficiencies for Brazilian banks in the recent period (2000–2007). We use Data Envelopment Analysis (DEA) to compute efficiency scores. Brazilian banks were found to have low levels of economic (cost) efficiency compared to banks in Europe and in the US. For the period with high macroeconomic volatility (2000–2002) the economic inefficiency in Brazilian banks can be attributed mainly to technical inefficiency rather than allocative inefficiency. State-owned banks are significantly more cost efficient than foreign, private domestic and private with foreign participation. There is no evidence of differences in economic efficiency due to type of activity and bank size. These results may provide some useful guidance for financial regulators and bank managers.     

棉花双关税后进口价格、期货价格与现货价格的感知及传导研究——基于VAR模型

随着我国棉花市场开放程度逐渐提高,探索国内外棉花价格感知和传导机制也愈显重要.国内外棉花价格传递必然受进出口贸易政策的影响,研究征收双关税后的棉花进口价格与国内期、现货价格之间的传递效应,对完善和优化我国棉花价格传导和形成机制更具现实意义.通过VAR模型、格兰杰因果检验、脉冲响应和方差分解等方法检验和探讨三者间的价格感知及传导机制.研究结果表明:征收双关税后的棉花进口价格、国内棉花期货和现货价格三者存在长期协整关系;双关税能够在一定程度上削弱国际棉价对国内棉价的传递能力,双关税后棉花进口价格不是国内棉价的Granger原因;三者在不同时期受到的冲击方向、力度和时间均有差异,据此提出优化国内棉花市场价格感知与传递机制的对策和建议.     

Strategies simulation in an aggregate bank model

A simple balance sheet simulation model was built up to help the top management to evaluate policies which directly affect the whole bank profit.We focused on three main alternative strategies, i.e.: (1) a growth in deposits as a measure of total activity expansion; (2) a change in the interest rates margin; (3) different provision policies for bad debts.According to the chosen strategy, the model allows for a quantitative response in the P and L account and in self-financing, showing the consequent flow of funds.The model was thought to be adaptable and responsive in a rapidly-changing environment. A first scheme refers to the whole bank activity; the same scheme with some adjustments refers to the foreign branches activity. Residually, it is possible to examine the bank's domestic activity.     

A multi-period bank portfolio management program

We describe a bank portfolio management program based on the complete Markowitz model, which explicitly treats risk due to unanticipated fluctuations in interest rate. Our program takes into account both inter-temporal and intra-temporal covariance. The major result of this approach is that, for the same expected return, our model yields a portfolio with significantly smaller risk than that determined by an index model. For the same risk level, our method yields a portfolio with higher expected yield. The model employs a rolling planning horizon, with time periods in the planning horizon of arbitrary length. A novelty in the model is that it permits inter-temporal transactions in the portfolio's securities by generating dummy securities to represent every possible transaction over the planning horizon. The output from the model consists of a list of portfolio strategies showing the expected after-tax return and the 1% worst case yield for each strategy. We also present an illustrative example, using real data from a large Pennsylvania bank, and compare the results from our model to the simpler variance-only and index models. The principles upon which the model is based are sufficiently general to allow the program to be expanded into a general asset-liability balance sheet management program.     

汇改与外汇市场波动性:大玩家理论的视角

央行在外汇市场的行动对市场波动性有重要影响。本文从主观预期概念出发,基于“大玩家”理论解释了2005年和2015年中国外汇管理体制两次改革前后人民币外汇市场的波动性差异。汇改前,央行积极地承担着“大玩家”的角色,人民币对美元汇率波动性较强;汇改后,央行的“大玩家”角色减弱,汇率波动性程度显著下降,市场效率增强。利用汇率数据进行的R/S分析支持了前述解释。     

不确定箱量下内河集装箱班轮航线动态配载决策

内河集装箱班轮运输中海关抽检可导致外贸箱箱量不断发生变化,班轮航线配载需要动态决策。基于滚动调度策略,将当前港口的配载决策按随机事件划分为多个阶段,以最小化班轮堆栈占用数量和相邻阶段间配载计划偏差为目标,构建单港口单阶段的配载决策模型,进而滚动实现班轮航线动态配载决策。基于大邻域搜索思想设计一种包含整数规划、破坏器与修复器的精确启发式算法,实现港口多阶段滚动配载。基于真实场景的算例研究表明,在优化堆栈占用数量方面,模型与算法之间差异不大,但在考虑相邻阶段间配载计划偏差时,算法的求解结果要优于模型。因此,模型与算法可用来辅助实现不确定箱量下内河集装箱班轮航线动态配载决策,且算法表现更优,可实现配载计划对不确定箱量的鲁棒吸收。     

Expanded model of the project portfolio selection problem with divisibility,time profile factors and cardinality constraints

This paper develops a new model for project portfolio selection over a planning horizon with multiple time periods. The model considers the divisibility of projects and combines reinvestment, set-up cost, cardinality constraints and precedence relationship in the scheduling, simultaneously. For efficient computation, an equivalent mixed integer linear programming representation is provided. One numerical example with three scenarios is given to highlight the capability and characteristics of the proposed model.     

Goal Programming and Agricultural Planning

Goal Programming is similar in structure to linear programming, but offers a more flexible approach to planning problems by allowing a number of goals which are not necessarily compatible to be taken into account, simultaneously. The use of linear programming in farm planning is reviewed briefly. Consideration is given to published evidence of the goals of farmers, and ways in which these goals can be represented. A goal programming model of a 600 acre mixed farm is described and evaluated. Advantages and shortcomings of goal programming in relation to linear programming are considered. It is found that goal programming can be used as a means of generating a range of possible solutions to the planning problem.     

Loss aversion with multiple investment goals

This paper presents a time-continuous portfolio selection model with loss averse investors, who possess multiple investment goals at different time horizons. The model assumes partial narrow framing. Investors follow a two-step approach. First, they optimally allocate wealth among investment goals. Second, they determine an optimal investment strategy for each investment goal separately. We show that when loss aversion is according to the experimental findings, investors mainly invest their wealth to reach long-term goals and adopt investment strategies with high leverage to reach short-term goals. The overall strategy also display high leverage. The same patterns is observed when loss aversion is extreme and goals are very ambitious. By contrast, when loss aversion is extreme but goals are not too ambitious, investors mainly invest to reach short-term goals and adopt safe investment strategies for this purpose.     

IMRT treatment planning for prostate cancer using prioritized prescription optimization and mean-tail-dose functions

Treatment planning for intensity modulated radiation therapy (IMRT) is challenging due to both the size of the computational problems (thousands of variables and constraints) and the multi-objective, imprecise nature of the goals. We apply hierarchical programming to IMRT treatment planning. In this formulation, treatment planning goals/objectives are ordered in an absolute hierarchy, and the problem is solved from the top-down such that more important goals are optimized in turn. After each objective is optimized, that objective function is converted into a constraint when optimizing lower-priority objectives. We also demonstrate the usefulness of a linear/quadratic formulation, including the use of mean-tail-dose (mean dose to the hottest fraction of a given structure), to facilitate computational efficiency. In contrast to the conventional use of dose-volume constraints (no more than x% volume of a structure should receive more than y dose), the mean-tail-dose formulation ensures convex feasibility spaces and convex objective functions. To widen the search space without seriously degrading higher priority goals, we allowed higher priority constraints to relax or 'slip' a clinically negligible amount during lower priority iterations. This method was developed and tuned for external beam prostate planning and subsequently tested using a suite of 10 patient datasets. In all cases, good dose distributions were generated without individual plan parameter adjustments. It was found that allowance for a small amount of 'slip,' especially in target dose homogeneity, often resulted in improved normal tissue dose burdens. Compared to the conventional IMRT treatment planning objective function formulation using a weighted linear sum of terms representing very different dosimetric goals, this method: (1) is completely automatic, requiring no user intervention, (2) ensures high-priority planning goals are not seriously degraded by lower-priority goals, and (3) ensures that lower priority, yet still important, normal tissue goals are separately pushed as far as possible without seriously impacting higher priority goals.     

夜盘交易对我国贵金属期货市场的影响研究

对比了我国贵金属期货市场推出夜盘交易制度前后流动性、波动性与联动性的变化,并研究了该交易制度带来的长期与短期不同的影响。首先,采用经过修正的流动性比率衡量市场流动性,并引入虚拟变量纳入回归模型,进一步研究夜盘交易对市场流动性的贡献;接下来,将每日收益率分解为隔夜收益率和日内收益率,通过建立EGARCH模型,分别考察夜盘交易对隔夜波动率和日内波动率长期与短期的影响;最后,通过建立VAR-BEKK-GARCH模型,从均值和方差两个层面研究了国内外贵金属期货市场间的联动性。研究发现:我国推出的夜盘交易制度显著提高了贵金属期货市场的流动性,降低了贵金属期货市场的波动性,尤其是降低了隔夜收益率的波动性,日内收益率的波动性并没有显著减弱;夜盘交易的推出同时增强了国内外期货市场之间的联动性,提升了我国贵金属期货市场对信息的吸收与传递效率。     

Schumann,a modeling framework for supply chain management under uncertainty

We present a modeling framework for the optimization of a manufacturing, assembly and distribution (MAD) supply chain planning problem under uncertainty in product demand and component supplying cost and delivery time, mainly. The automotive sector has been chosen as the pilot area for this type of multiperiod multiproduct multilevel problem, but the approach has a far more reaching application. A deterministic treatment of the problem provides unsatisfactory results. We use a 2-stage scenario analysis based on a partial recourse approach, where MAD supply chain policy can be implemented for a given set of initial time periods, such that the solution for the other periods does not need to be anticipated and, then, it depends on the scenario to occur. In any case, it takes into consideration all the given scenarios. Very useful schemes are used for modeling balance equations and multiperiod linking constraints. A dual approach splitting variable scheme is been used for dealing with the implementable time periods related variables, via a redundant circular linking representation.     

Quality risk prediction at a non-sampling station machine in a multi-product, multi-stage, parallel processing manufacturing system subjected to sequence disorder and multiple stream effects

Most technology companies are experiencing highly volatile markets with increasingly short product life cycles due to rapid technological innovation and market competition. Current supply-demand planning systems remain ineffective in capturing short life-cycle nature of the products and high volatility in the markets. In this study, we propose an alternative demand-characterization approach that models life-cycle demand projections and incorporates advanced demand signals from leading-indicator products through a Bayesian update. The proposed approach describes life-cycle demand in scenarios and provides a means to reducing the variability in demand scenarios via leading-indicator products. Computational testing on real-world data sets from three semiconductor manufacturing companies suggests that the proposed approach is effective in capturing the life-cycle patterns of the products and the early demand signals and is capable of reducing the uncertainty in the demand forecasts by more than 20%.     

Fuzzy goal programming for inventory management: A bacterial foraging approach

An efficient inventory planning approach in today’s global trading regime is necessary not only for increasing the profit margin, but also to maintain system flexibility for achieving higher customer satisfaction. Such an approach should hence be comprised of a prudent inventory policy and clear satisfaction of stakeholder’s goals. Relative significance given to various objectives in a supply chain network varies with product as well as time. In this paper, a model is proposed to fill this void for a single product inventory control of a supply chain consisting of three echelons. A generic modification proposed to the membership functions of the fuzzy goal-programming approach is used to mathematically map the aspiration levels of the decision maker. The bacterial foraging algorithm has been modified with enhancement of the algorithms’ capability to map integer solution spaces and utilised to solve resulting fuzzy multi-objective function. An illustrative example comprehensively covers various decision scenarios and highlights the underlying managerial insights.     

Production planning with uncertainty in the quality of raw materials: a case in sawmills

Motivated by sawmill production planning, this paper investigates multi-period, multi-product (MPMP) production planning in a manufacturing environment with non-homogeneous raw materials, and consequently random process yields. A two-stage stochastic program with recourse is proposed to address the problem. The random yields are modelled as scenarios with stationary probability distributions during the planning horizon. The solution methodology is based on the sample average approximation (SAA) scheme. The stochastic sawmill production planning model is validated through the Monte Carlo simulation. The computational results for a real medium capacity sawmill highlight the significance of using the stochastic model as a viable tool for production planning instead of the mean-value deterministic model, which is a traditional production planning tool in many sawmills.     

上下游企业静动态博弈的反倾销税率模型

反倾销是世界贸易组织(WTO)框架下为国内进口竞争性产业提供保护的一种合法措施,如何制定最优的反倾销税率越来越受到国内企业和政府的重视.文章根据我国某些垄断行业的真实情况,基于上下游均为垄断企业的市场结构,假定国内外上下游企业都追求利润最大化,并假定最终产品市场的国内外下游企业处于斯塔克伯格竞争,而中间产品市场的国内外上游企业处于古诺竞争,运用博弈论的逆向归纳法建立了国内政府基于国内社会福利最大化的对国外进口中间产品和最终产品同时征税的反倾销税率模型,并分析了反倾销税率的影响因素.文章结论对于我国相关企业及政府应对倾销与反倾销问题具有较大的参考价值.