control and performance of international joint ventures control is a critical concept for successful management and performance of international joint ventures ijvs this paper reviews and synthesizes prior studies addressing the conceptualization and operationalization of control within ijvs as well as the ijv control performance relationship the paper also presents a new conceptualization of ijv control as well as a conceptual frame work for studying control of ijvs

no arbitrage bounds for financial scenarios abstract we derive no arbitrage bounds for expected excess returns to generate scenarios used in financial applications the bounds allow to distinguish three regions one where arbitrage opportunities will never exist a second where arbitrage may be present and a third where arbitrage opportunities will always exist no arbitrage bounds are derived in closed form for a given covariance matrix using the least possible number of scenarios empirical examples illustrate the practical potential of knowing these bounds

competition and coalition formation of renewable power producers we investigate group formations and strategic behaviors of renewable power producers in electricity markets these producers currently bid into the day ahead market in a conservative fashion because of the real time risk associated with not meeting their bid amount it has been suggested in the literature that producers would bid less conservatively if they can form large groups to take advantages of spatial diversity to reduce the uncertainty in their aggregate output we show that large groups of renewable producers would act strategically to lower the aggregate output because of market power to maximize renewable power production we characterize the trade off between market power and generation uncertainty as a function of the size of the groups we show there is a sweet spot in the sense that there exists groups that are large enough to achieve the uncertainty reduction of the grand coalition but are small enough such that they have no significant market power we consider both independent and correlated forecast errors under a fixed real time penalty we also consider a real time market where both selling and buying of energy are allowed we validate our claims using pjm and nrel data

lp modeling for asset liability management a survey of choices and simplifications dynamic linear programming lp models for asset liability management alm are quite powerful and flexible but face two challenges 1 many modeling choices not all consistent with one another or with finance theory and 2 solution difficulties due to the large number of scenarios obtained from standard interest rate models we first survey these modeling choices with a view to help researchers make self consistent choices next we review how the dynamic lp model for alm and the representation of uncertainty therein have been simplified in the past to motivate new or hybrid models emphasizing tractability to this end we review existing static lp models as extreme modeling simplifications and aggregation as a simplification of uncertainty

simulation and optimization approaches to scenario tree generation in this paper three approaches are presented for generating scenario trees for 3nancial portfolio problems these are based on simulation optimization and hybrid simulation optimization in the simulation approach the price scenarios at each time period are generated as the centroids of random scenario simulations generated sequentially or in parallel the optimization method generates a number of discrete outcomes which satisfy speci3ed statistical properties by solving either a sequence of non linear optimization models one at each node of the scenario tree or onelargeoptimization proble m in thehybrid approach theoptimization proble m is re duce d in size by 3xing price variables to values obtained by simulation these procedures are backtested using historical data and computational results are presented 2003 elsevier b v all rights reserved

ownership based entry mode strategies and international performance this study examines the relationship between ownership entry modes and performance the ownership entry modes examined are the wholly owned modes of acquisition and new venture entry and the non wholly owned mode of joint venture entry a theoretical relationship is developed for international entry modes that is based on the contingency characteristics of resource requirements and organizational control factors this model suggests that different entry modes have different performance outcomes based upon their resource and organizational control demands the theoretical model although developed using the eclectic theoretical approach is based largely on concepts and relationships previously delineated in contingency theory our hypotheses suggest that new ventures should outperform joint ventures and joint ventures should outperform acquisitions an empirical test using a sample of 321 japanese firms entering the north american market provides supporting evidence

performance of transnational corporations in less developed countries this study analyzes the determinants of the performance of a sample of 153 tncs in 6 light manufacturing industries in the 5 asean countries firm profitability increased as the firm s market share advertising and r d intensity increased and as the market shares of the 2 largest firms in the industry and tariffs increased profitability decreased as the market share of the third largest firm in the industry increased as import penetration increased as the growth in the firm s sales increased and as the number of home countries of the tncs in the industry increased

coalitional aggregation of wind power this paper explores scenarios in which independent wind power producers form willing coalitions to exploit the reduction in aggregate power output variability obtainable through geographic diversity in the setting of a two settlement electricity market we examine the advantage gained through optimal coalitional contract offering strategies for quantity risk reduction we show that a group of independent wind power producers can always improve their expected profit by cooperatively offering their aggregated power using coalitional game theory we identify sharing mechanisms to fairly allocate the profits to coalition members we show that the resulting coalitional game is balanced guaranteeing that the core of the game is necessarily nonempty in addition we propose a profit sharing mechanism that minimizes the worst case dissatisfaction to recover an imputation in the core finally we illustrate our theoretical results with empirical studies using data from five representative wind farms in upstate new york

partner contributions as predictors of equity share in international joint ventures the type of expertise that a company contributes to a joint venture may affect the amount of equity that it owns this research observes the ownership patterns associated with four common combinations of partner expertise in international joint ventures the results rank company assets with respect to the contributor s ability to negotiate majority ownership in the original joint venture contract and that company s tendency to buy up equity from the partner later on

retirement saving with contribution payments and labor income as a benchmark for investments abstract in this paper we study the retirement saving problem from the point of view of a plan sponsor who makes contribution payments for the future retirement of an employee the plan sponsor considers the employee s labor income as investment benchmark in order to ensure the continuation of consumption habits after retirement we demonstrate that the demand for risky assets increases at low wealth levels due to the contribution payments we quantify the demand for hedging against changes in wage growth and find that it is relatively small we show that downside risk measures increase risk taking at both low and high levels of wealth

financial asset pricing theory and stochastic programming models for asset liability management a synthesis practical portfolio investment problems under uncertainty can be modeled well as multiperiod stochastic programs however the numerical optimization methods that need to be used to solve such models seriously limit the level of detail in the uncertainty about future asset rices and returns that can be incorporated somewhat surprisingly the question how this necessarily approximate description of the uncertainty should be constructed has received relatively little attention in the stochastic programming literature moreover many of the descriptions that have been used are not arbitrage free and therefore inconsistent with modern financial asset pricing theory in this paper we will present aggregation methods that can be used in combination with financial asset pricing models to obtain a description of the uncertainty that is arbitrage free consistent with observed market prices as well as concise enough for a stochastic programming model furthermore we will discuss how these aggregation methods can form the basis of an iterative solution approach

post tax optimization with stochastic programming abstract in this paper we consider a stochastic programming approach to multistage post tax portfolio optimization asset performance information is specified as a scenario tree generated by two alternative methods based on simulation and optimization we assume three tax wrappers involving the same instruments for an efficient investment strategy and determine optimal allocations to different instruments and wrappers the tax rules are integrated with the linear and mixed integer stochastic models to yield an overall tax and return efficient multistage portfolio the computational performance of these models is tested using a case study with different scenario trees our experiments show that optimal portfolios obtained by both linear programming and mixed integer stochastic models diversify over wrappers and the original capital is distributed among assets within each wrapper

the characteristics and performance of korean joint ventures in ldcs little has been reported on joint ventures between firms from newly industrialized countries and developing countries this paper examines twelve characteristics of a sample of korean firms with partners in developing countries ldcs and contrasts them with existing research where a developed country firms have linked with firms in other developed countries and b developed country firms have linked with local firms in developing countries as part of the analysis ten hypotheses were formulated and tested

high performance computing for asset liability management financial institutions require sophisticated tools for risk management for companywide risk management both sides of the balance sheet should be considered resulting in an integrated asset liability management approach stochastic programming models suit these needs well and have already been applied in the field of asset liability management to improve financial operations and risk management the dynamic aspect of the financial planning problems inevitably leads to multiple decision stages trading dates in the stochastic program and results in an explosion of dimensionality in this paper we show that dedicated model generation specialized solution techniques based on decomposition and high performance computing are the essential elements to tackle these large scale financial planning problems it turns out that memory management is a major bottleneck when solving very large problems given an efficient solution approach and a parallel computing facility we report on the solution of an asset liability management model for an actual dutch pension fund with 4 826 809 scenarios 12 469 250 constraints and 24 938 502 variables which is the largest stochastic linear program ever solved a closer look at the optimal decisions reveals that the initial asset mix is more stable for larger models demonstrating the potential benefits of the high performance computing approach for alm

foreword for the special section on wind and solar energy uncovering and accommodating their impacts on electricity markets the articles in this special section focus on wind and solar energy and the impact these energy technologies and services will have the utility markets the aim is to give particular focus on some of the areas of investigation that may allow to 1 uncover the impact of renewables on electricity market e g on market clearing outcomes need for ancillary services and investment and to 2 propose methodological innovations being theoretically sound and of practical relevance in order to accommodate substantial shares of renewables in power systems electricity network and markets were designed based on a long history of dealing with various forms of dispatchable generation as well as a fairly predictable inelastic electricity consumption pattern in a centralized top down manner little uncertainty was involved on both generation and demand sides hence allowing for a design of electricity markets accounting for the necessity of a forward optimal allocation with a real time mechanism supporting actual power system operation

joint ventures in yugoslavia opportunities and constraints yugoslavia s post 1965 economic policies have been directed towards opening the economy to foreign trade and encouraging inward investment in joint ventures this research examines the opportunities and constraints facing western multinational companies which invest in joint ventures in yugoslav industry the empirical evidence drawn from a sample of 42 west european and north american companies addresses itself to the formation and success of joint ventures the route to foreign direct investment in yugoslavia and motives and preferences for joint ventures to other forms of industrial cooperation

dynamic asset allocation for varied financial markets under regime switching framework asset allocation among diverse financial markets is essential for investors especially under situations such as the financial crisis of 2008 portfolio optimization is the most developed method to examine the optimal decision for asset allocation we employ the hidden markov model to identify regimes in varied financial markets a regime switching model gives multiple distributions and this information can convert the static mean variance model into an optimization problem under uncertainty which is the case for unobservable market regimes we construct a stochastic program to optimize portfolios under the regime switching framework and use scenario generation to mathematically formulate the optimization problem in addition we build a simple example for a pension fund and examine the behavior of the optimal solution over time by using a rolling horizon simulation we conclude that the regime information helps portfolios avoid risk during left tail events

trading wind generation from short term probabilistic forecasts of wind power due to the fluctuating nature of the wind resource a wind power producer participating in a liberalized electricity market is subject to penalties related to regulation costs accurate forecasts of wind generation are therefore paramount for reducing such penalties and thus maximizing revenue despite the fact that increasing accuracy in spot forecasts may reduce penalties this paper shows that if such forecasts are accompanied with information on their uncertainty i e in the form of predictive distributions then this can be the basis for defining advanced strategies for market participation such strategies permit to further increase revenues and thus enhance competitiveness of wind generation compared to other forms of dispatchable generation this paper formulates a general methodology for deriving optimal bidding strategies based on probabilistic forecasts of wind generation as well as on modeling of the sensitivity a wind power producer may have to regulation costs the benefits resulting from the application of these strategies are clearly demonstrated on the test case of the participation of a multi mw wind farm in the dutch electricity market over a year

a multistage linear stochastic programming model for optimal corporate debt management abstract large corporations fund their capital and operational expenses by issuing bonds with a variety of indexations denominations maturities and amortization schedules we propose a multistage linear stochastic programming model that optimizes bond issuance by minimizing the mean funding cost while keeping leverage under control and insolvency risk at an acceptable level the funding requirements are determined by a fixed investment schedule with uncertain cash flows candidate bonds are described in a detailed and realistic manner a specific scenario tree structure guarantees computational tractability even for long horizon problems based on a simplified example we present a sensitivity analysis of the first stage solution and the stochastic efficient frontier of the mean risk trade off a realistic exercise stresses the importance of controlling leverage based on the proposed model a financial planning tool has been implemented and deployed for brazilian oil company petrobras

a mixed integer programming model for multistage mean variance post tax optimization abstract in this paper we introduce a mixed integer stochastic programming approach to mean variance post tax portfolio management this approach takes into account of risk in a multistage setting and allows general withdrawals from original capital the uncertainty on asset returns is specified as a scenario tree the risk across scenarios is addressed using the probabilistic approach of classical stochastic programming the tax rules are used with stochastic linear and mixed integer quadratic programming models to compute an overall tax and return risk efficient multistage portfolio the incorporation of the risk term in the model provides robustness and leads to diversification over wrappers and assets within each wrapper general withdrawals and risk aversion have an impact on the distribution of assets among wrappers computational results are presented using a study with different scenario trees in order to show the performance of these models

a bank asset and liability management model in managing its assets and liabilities in light of uncertainties in cash flows cost of funds and return on investments a bank must determine its optimal trade off between risk return and liquidity in this paper we develop a multiperiod stochastic linear programming model alm that includes the essential institutional legal financial and bank related policy considerations and their uncertainties yet is computationally tractable for realistically sized problems a version of the model was developed for the vancouver city savings credit union for a 5 year planning period the results indicate that alm is theoretically and operationally superior to a corresponding deterministic linear programming model and that the effort required for the implementation of alm and its computational requirements are comparable to those of the deterministic model moreover the qualitative and quantitative characteristics of the solutions are sensitive to the model s stochastic elements such as the asymmetry of cash flow distributions we also compare alm with the stochastic decision tree sdt model developed by s p bradley and d b crane alm is computationally more tractable on realistically sized problems than sdt and simulation results indicate that alm generates superior policies

optimization of electricity retailer s contract portfolio subject to risk preferences when an electricity retailer faces volume risk in meeting load and spot price risk in purchasing from the wholesale market conventional risk management optimization methods can be quite inefficient for the management of an electricity contract portfolio in this context we develop a multistage stochastic optimization approach which accounts for the uncertainties of both electricity prices and loads and which permits the specification of conditional value at risk requirements to optimize hedging across intermediate stages in the planning horizons our experimental results based on real data from nordpool suggest that the modeling of price and load correlations is particularly important the sensitivity analysis is extended to characterize the behavior of retailers with different risk attitudes thus we observe that a risk neutral retailer is more susceptible to price related than load related uncertainties in terms of the expected cost of satisfying the load and that a risk averse retailer is especially sensitive to the drivers of the forward risk premium

interfirm diversity organizational learning and longevity in global strategic alliances organizational theorists have correctly argued that the emergence and maintenance of robust cooperation between global strategic alliance partners is related to the diversity in the partners characteristics yet previous research has failed to systematically delineate the important dimensions of interfirm diversity and integrate the dimensions into a unified framework of analysis this paper develops a multilevel typology of interfirm diversity and focuses on organizational learning and adaptation as critical processes that dynamically moderate diversity s impact on alliance longevity and effectiveness

stochastic network programming for financial planning problems several financial planning problems are posed as dynamic generalized network models with stochastic parameters examples include asset allocation for portfolio selection international cash management and programmed trading arbitrage despite the large size of the resulting stochastic programs the network structure can be exploited within the solution strategy giving rise to efficient implementations empirical results are presented indicating the benefits of the stochastic network approach for the asset allocation case

pros and cons of exposing renewables to electricity market risks a comparison of the market integration approaches in germany spain and the uk abstract the article examines how renewable electricity res e producers are integrated into the electricity market under the support legislations and regulatory frameworks of germany spain and the uk focus is on wind power which faces the highest market integration challenge of all res e the analysis shows that the three countries follow contrasting approaches of exposing res e producers to the market risks of forward electricity markets balancing markets and system planning requirements risk exposure is highest in the uk and lowest in germany from a policy maker s perspective there is a trade off between a high risk and a low risk approach when res e face high market risks a higher level of financial support is required to stimulate res e development than in a low risk environment but the exposure to market risks may also give an incentive to make efficient use of the respective market thus limiting the indirect costs to society the special characteristics of wind energy however put natural limits to the response of wind power plants to market prices and locational price signals and will increasingly influence electricity markets and grid infrastructure these interdependencies should be recognised in the design of res e policies and market regulations

a hybrid simulation optimisation scenario model for asset liability management abstract in this paper we desciibe a decision support model to sustain management of pension funds in the strategic planning of the available asset and liability policy instruments a main characteristic of the approach is that the relevant risk drivers are modelled by scenarios rather than by probability distributions we will describe the scenario generation methodology and how the scenarios are used by pension fund managers to simulate and improve asset liability strategies until a strategy is identified which is agreed upon by all who carry responsibility for the pension fund and her sponsors and trustees next we will describe how this process of managerial learning can be improved by a hybrid simulation optimisation method which applies concepts from the field of non linear global optimisation to determine the asset allocations which determine efficient frontiers of contribution rates and downside insolvency risks we will conclude by showing that the application of the developed models to a particular pension fund leads to the annulment of the infeasibility of the current asset liability policy on the one hand and to a reduction of the expected yearly contributions of us 100 million on the other

scenario generation and stochastic programming models for asset liability management in this paper we develop and test scenario generation methods for asset liability management models we propose a multi stage stochastic programming model for a dutch pension fund both randomly sampled event trees and event trees fitting the mean and the covariance of the return distribution are used for generating the coefficients of the stochastic program in order to investigate the performance of the model and the scenario generation procedures we conduct rolling horizon simulations the average cost and the risk of the stochastic programming policy are compared to the results of a simple fixed mix model we compare the average switching behavior of the optimal investment policies our results show that the performance of the multi stage stochastic program could be improved drastically by choosing an appropriate scenario generation method

equity joint ventures and the theory of the multinational enterprise this paper extends the internalization approach to the theory of the multinational enterprise mne to include an expanded role for equity joint ventures using the transaction cost paradigm of williamson this paper explains why joint ventures may sometimes be preferred over wholly owned subsidiaries also presented is empirical work on joint venture performance in developing countries which demonstrates that under certain conditions joint ventures can be the optimal mode of foreign direct investment

modeling financial reinsurance in the casualty insurance business via stochastic programming abstract in this paper we examine the rationale for financial reinsurance in the casualty insurance business as opposed to regular reinsurance financial reinsurance refers to an investment strategy that uses the financial markets to hedge insurance risk the casualty insurer takes positions in derivatives on underlying assets whose prices are highly positively or negatively correlated with specific insurance risks we formulate the asset liability management problem for a mutually owned casualty insurer in the context of a dynamic stochastic portfolio selection model using numerical studies of the resulting large scale non linear program we compare properties of optimal portfolios with and without the possibility of financial reinsurance we let an alleged representative policyholder endowed with a linear plus negative exponential utility function evaluate the various optimal portfolios when policyholders utility functions exhibit reasonable levels of risk aversion we find that portfolios reflecting financial reinsurance dominate portfolios that are not financially reinsured

a stochastic programming model for money management abstract portfolio managers in the new fixed income securities have to cope with various forms of uncertainty in addition to the usual interest rate changes uncertainy in the timing and amount of cashflows changes in the default and other risk premia and so on complicate the portfolio manager s problem we develop here a multi period dynamic portfolio optimization model to address this problem the model specifies a sequence of investment decisions over time that maximize the expected utility of return at the end of the planning horizon the model is a two stage stochastic program with recourse the dynamics of interest rates cashflow uncertainty and liquidity default and other risk premia are explicitly modeled through postulated scenarios simulation procedures are developed to generate these scenarios the optimization models are then integrated with the simulation procedures extensive validation experiments are carried out to establish the effectiveness of the model in dealing with uncertainty in particular the model is compared against the popular portfolio immunization strategy and against a portfolio based on mean absolute deviation optimization

wind power and electricity prices at the pjm market increased deployment of wind power generation is changing the landscape of power supply around the world when integrated with electricity markets wind power is also widely known to influence the prices cleared at the market this paper examines the effect of wind power generation on the day ahead market prices in the pjm electricity market using robust econometric models and statistical inference results show that the quantified expected benefits to wholesale market participants may be substantial despite the relatively low wind power penetration levels still observed within the pjm jurisdiction relative to other markets the quantified unitary benefits outweigh by a great margin the renewable energy credits given to qualifying wind farms across the market when benefits outweigh the costs incurred to generate them welfare is accrued to this end benefit allocation mechanisms are proposed which may contribute to the continued development of wind power on the roadmap to a cleaner power industry of the future

strategic bidding and rebidding in electricity markets abstract successful deregulation in electricity markets depends crucially on the ability of market regulation to promote and maintain free competition there are however important physical characteristics in electricity markets such as the constraints imposed by the physical transmission infrastructure that have the potential to undermine competition and provide opportunities for market participants to exploit temporary positions of market power in this paper the regional market of queensland australia is analysed it is found that strategic behaviour by generators exists and is closely related to the occurrence of the kind of extreme price events that characterise many deregulated electricity markets in addition rebidding behaviour by base load generators immediately after extreme price events is shown to have negative impacts on the operation of the market the key message is that promotion of competition in electricity markets can have undesirable consequences unless the regulatory policy is carefully designed to counter strategic behaviour by market participants

modeling the impact of a wind power producer as a price maker wind energy is present in many countries throughout the world the main types of wind sales in electricity markets are via regulated tariffs or pool based markets production companies choose cost effective options for selling wind energy and some markets like the irish electricity market use regulated tariffs to remunerate wind production this paper aims to provide some answers to explain what effect wind offers may have in an electricity market if wind power producers participated in the day ahead market without receiving any premium or aid a price maker optimization model is used to detect its effect on prices the model encompasses energy offers by other technologies using residual demand curves and detailed modeling of wind imbalances it is observed that wind acting as price maker reduces electricity prices and the imbalance penalties help the system operator to reduce imbalances a realistic case study using data from the irish electricity market illustrates the methodology used comparing the effect of imbalance penalties in the models in terms of profit and total imbalance of the system

environmental risks and joint venture sharing arrangements multinational enterprises mnes have responded to the open door policies of socialist countries in recent years by investing in their economies through joint ventures mnes must formulate their investment strategies to control and manage the environmental risks peculiar to a traditional centrally planned economy cpe in which contextual and transactional environments are blurred joint venture sharing arrangements may be structured to control exposures to uncertainties and to align the interests of transactional parties mostly state owned enterprises to those of the venture this study tests the hypothesis that a foreign investor s share in a joint venture in a cpe is inversely correlated with 1 the amount of uncertainties and risks and 2 the external dependency of the venture on the contextual and transactional relationships of the host country the hypothesis is supported by empirical evidence from data on american joint ventures in china

applying cvar for decentralized risk management of financial companies abstract over the past decade financial companies have merged diverse areas including investment banking insurance retail banking and trading operations despite this diversity many global financial firms suffered severe losses during the recent recession to reduce enterprise risks and increase profits we apply a decentralized risk management strategy based on a stochastic optimization model we extend the decentralized approach with the cvar risk metric showing the advantages of cvar over traditional risk measures such as value at risk an example taken from the earthquake insurance area illustrates the concepts

electricity market participation of wind farms the success story of the spanish pragmatism abstract in the last 10 years more than 15 gw of wind power asociacion empresarial eolica spanish wind energy association nota de prensa press release 17 de enero de 2008 http www aeeolica org doc np 080117 espana supera los 15000 mw eolicos pdf have been installed in spain of which more than 3 5 gw in 2007 furthermore plans are to reach 20 gw by 2010 and there are expectations of an installed capacity exceeding 40 gw by 2020 this article will present the innovative solutions for technical and economical integration that allow to reach such high level wind penetration objectives the system peaks at around 44 gw and is almost isolated it will be described how the regulation has evolved from a pure feed in tariff to a market premium option where technical and economic integration has been a priority today approximately 97 of installed wind capacity accesses the spanish wholesale electricity market market integration has been crucial sending the correct signals to participants to look for the optimum technical solutions technical improvements have come from both wind power producers fault ride through capabilities visibility and controllability of wind power power production forecasting reactive power control and the system operator specific control centre dedicated to renewable energy sources res new security analysis tools gaining technical confidence of wind capabilities

the performance of stochastic dynamic and fixed mix portfolio models the purpose of this paper is to demonstrate how to evaluate stochastic programming models and more specifically to compare two different approaches to asset liability management the first uses multistage stochastic programming while the other is a static approach based on the so called constant rebalancing or fixed mix particular attention is paid to the methodology used for the comparison the two alternatives are tested over a large number of realistic scenarios created by means of simulation we find that due to the ability of the stochastic programming model to adapt to the information in the scenario tree it dominates the fixed mix approach