dynamic value at risk under optimal and suboptimal portfolio policies abstract at present all value at risk var implementations i e all risk measures of the maximum loss at a given level of confidence type are based on the assumption that the portfolio mix will not change before the var horizon this hypothesis may be unrealistic especially when the var horizon is established by the regulators bis at the opposite we measure var dynamically i e taking into consideration portfolio mix adjustments over time adjustments do not occur continuously since they are costly we allow both optimal rebalancing policies which entail changing the portfolio mix whenever it is too far from the optimal one and suboptimal policies which mean adjusting at pre fixed dates we show that in both cases usual var measures underestimate portfolio losses even if the underlying returns are normal we study the dependence of the misestimate on the var horizon the initial portfolio mix and the risk aversion of the portfolio manager which in turn determines the frequency of interventions the bias can be more relevant over one day than over longer horizons and even if the initial portfolio is nearly optimal we also perform backtesting and estimate a coherent risk measure namely conditional var which confirms the inappropriateness of the usual static var

day of the week effects and asset returns the number of empirical studies using daily stock returns is rapidly increasing researchers generally assume that the distribution of stock returns is identical for all days of the week a convenient statistical assumption but not a necessary condition of market equilibrium nevertheless there are reasons to suspect that the distribution of returns may vary according to the day of the week the most obvious is the impact of weekends on monday s return since monday s return is calculated over three instead of one calender day the mean and variance may well be higher on monday compared with any other daily return perhaps three times as large previous research has examined the daily distribution of stock returns for a monday effect while fama 1965 does not compare daily mean returns he does report that monday s variance is about 20o greater than other daily returns with a traditional distributional assumption regarding the returns on a financial asset specifies that the expected returns are identical for all days of the week contrary to this plausible assumption this paper discovers that the expected returns on common stocks and treasury bills are not constant across days of the week the most notable evidence is for monday s returns where the mean is unusually low or even negative several explanations of the results are investigated but none proves satisfactory aside from documenting significant day of the week effects the implications of the results for tests of market efficiency are examined while market adjusted returns continue to exhibit day of the week effects these effects are no longer concentrated on monday during the last year we have had many conversations with our colleagues throughout the professions we are particularly thankful to the participants at sessions of the western and american finance associations where preliminary versions of this paper were presented special thanks are due to gene fama gailen hite jon ingersoll robert jarrow merton miller clifford smith and rex thompson the expert research assistance of frank rabinovitch and youngsup yun is gratefully acknowledged 1 the list of papers using daily stock returns is too long to name recent examples include charest 1978 dodd 1980 banz 1981 and reinganum 1981

determining the optimal return on investment for an advertising campaign abstract in this this paper we adopt the point of view that advertising is an investment and propose a simple formula for calculating the level of media spending which maximizes the return on investment the information which must be supplied for the calculation is commonly available and we express the optimal expenditure level in terms which are meaningful to media planners we show that when maximizing return on investment not all of the allocated media budget should be spent

substitution in consumption an application to the allocation of time abstract in this article we have constructed a model where the commodity price effect and the good price effect in a becker lancaster model are related and the relevance of factor substitution in consumption technology can be verified a first application is made to the allocation of time for belgian data

the rationale of the mean standard deviation analysis skewness preference and the demand for money publisher summary this chapter discusses the rationale of the mean standard deviation analysis skewness preference and the demand for money in january 1969 issue of the review of economic studies karl borch and martin feldstein separately criticized the widely used mean variance analysis of portfolio selection borch contended that any system of upward sloping mean standard deviation e s indifference curves can be shown to be inconsistent with the basic axiom of choice under uncertainty he pointed out that one can always pick any two points on an upward sloping indifference curve to represent two bernoulli distributions with probability 1 p of gaining the same amount x in both the cases and probability p of gaining y1 in the case of one distribution and y2 in the case of the second distribution with y2 y1 if the second distribution represents the point to the northeast of the other point then by the dominance axiom the second distribution must be preferred to the first which contradicts the basic meaning of indifference curves feldstein by using a log utility function and a lognormal distribution for investment outcome showed that e s indifference curves for a risk averter need not be convex downwards though upward sloping they would change from convex to concave once the standard deviation of the outcome exceeds the mean multiplied by on the face of it this seems to suggest that risk aversion might decrease as risk is increased beyond a certain extent

export diversification through resource based industrialization the case of natural gas for small resource rich developing economies specialization in raw exports is usually considered to be detrimental to growth and resource based industrialization rbi is often advocated to promote export diversification this paper develops a new methodology to assess the performance of these rbi policies we first formulate an adapted mean variance portfolio model that explicitly takes into consideration i a technology based representation of the set of feasible export combinations and ii the cost structure of the resource processing industries second we provide a computationally tractable reformulation of the resulting mixed integer nonlinear optimization problem finally we present an application to the case of natural gas comparing current and efficient export oriented industrialization strategies of nine gas rich developing countries

too risky to hold the effect of downside risk accumulated equity wealth and firm performance on ceo equity reduction although the alignment effect of equity ownership is often studied with emphasis on changes in firm strategy the exposure of ceos firm specific wealth to firm risk is more easily controlled by changing their level of equity holdings than by changing firm strategic risk we rely on prospect theory and the behavioral theory of the firm to examine the antecedents of ceo equity reduction and investigate whether it serves to decouple ceo wealth from firm risk given its central role in loss avoidance we underline the effect of the firm s downside risk and distinguish the total loss potential on equity holdings from the loss potential due to firm specific factors allowing for own performance referents we also consider firm performance and the value of a ceo s equity holdings in the analysis based on a sample of 208 u s ceos for the years 1997 1999 we find empirical support for the role of downside risk and firm performance in ceo equity reductions implications on incentive alignment through equity ownership are presented

conditional heteroscedasticity in time series of stock returns evidence and forecasts this article presents new evidence about the time series behavior of stock prices daily return series exhibit significant levels of second order dependence and they cannot be modeled as linear white noise processes a reasonable return generating process is empirically shown to be a first order autoregressive process with conditionally heteroskedastic innovations in particular generalized autoregressive conditional heteroskedastic garch 1 1 processes fit to data very satisfactorily various out of sample forecasts of monthly return variances are generated and compared statistically forecasts based on the garch model are found to be superior copyright 1989 by the university of chicago

managing r d in vertical relationships we study the optimal strategy for research and development r d in a buyer supplier relationship the buyer chooses whether to 1 insource a cost reducing r d to its own research subunit or to 2 outsource it to its manufacturing supplier the buyer cannot observe the r d effort in either case but can better observe the r d result when the r d is conducted internally according to our analysis the buyer prefers insourcing r d to mitigate information asymmetry when the r d cost is either small or large when the r d cost is intermediate however the buyer prefers outsourcing r d and can achieve the full information outcome first best outcome despite the information asymmetry associated with outsourcing r d moreover the buyer s preference for outsourcing high cost r d increases when the r d is more likely to succeed or to generate significant cost reductions or the r d result is more difficult to predict our analysis provides a theoretical explanation for the increasing trend of outsourcing innovation to manufacturing suppliers jel d82 l22 l23

shortfall as a risk measure properties optimization and applications motivated from second order stochastic dominance we introduce a risk measure that we call shortfall we examine shortfall s properties and discuss its relation to such commonly used risk measures as standard deviation var lower partial moments and coherent risk measures we show that the mean shortfall optimization problem unlike mean var can be solved e7ciently as a convex optimization problem while the sample mean shortfall portfolio optimization problem can be solved very e7ciently as a linear optimization problem we provide empirical evidence a in asset allocation and b in a problem of tracking an index using only a limited number of assets that the mean shortfall approach might have advantages over mean variance 2003 elsevier b v all rights reserved

a simple approximation for semivariance abstract semivariance can differentiate among skewed return distributions but variance is unable to do so thus semivariance has been used as a risk surrogate in portfolio analysis and capital budgeting problems unfortunately semivariance analysis is relatively unknown and poses difficult analytic and computational problems in this paper an expression is derived which very closely approximates semivariance this expression is simple in form and uses only familiar statistics namely mean variance critical value and cumulative probability below the critical value

asset pricing in a generalized mean lower partial moment framework theory and evidence a new asset pricing model that generalizes earlier results in the downside risk literature is developed and empirically tested using a multivariate approach by specifying risk as deviations below any arbitrary target rate of return the generalized mean lower partial moment mlpm model overcomes the limited appeal of earlier formulations and moreover a large class of extant pricing models using alternative risk measures variance semivariance semideviation probability of loss etc becomes special cases of the new framework empirical tests indicate that the new model cannot be rejected against an unspecified alternative for a large set of target rates of return the traditional capm on the other hand is rejected as a well specified alternative the mlpm target rates inferred from market data appear to be related to equity market mean returns rather than to the riskfree rate the target rate that is implicit in the capm and explicit in earlier downside risk formulations the attractiveness of downside risk measures for decision making purposes has been noted in the financial economic literature for over a quarter of a century 1 risk from this perspective is measured in terms of deviations below some exogenously prespecified target rate of return and a formal analysis of these risk measures for various utility functions has been presented by bawa 1975 in terms of the lower partial moment lpm of the asset distributions the appeal of these risk measures has been based in part on their consistency with the way individuals actually perceive risk notwithstanding its intuitive appeal this area of research has been virtually neglected in recent years we believe that this disaffection with downside risk models tends from two sources first earlier models of this genre exogenously specify the target rate to equal the risk free interest rate in the absence of a satisfactory theory for explaining how investors establish their target rates this assumption as argued herein has been motivated more by technical reasons than economic considerations second empirical tests

an analysis of cooperative research and development i analyze the effects of cooperative research whereby member firms agree to share the costs andfruits of a research project before they undertake it in this model industrywide agreements tend to have socially beneficial effects when the degree ofproduct market competition is low when there are r d spillovers in the absence of cooperation when a high degree of sharing is technologically feasible and when the agreement concerns basic research rather than development activities i show that a royalty free cross licensing agreement among any number offirms lowers the equilibrium level of innovation even though it increases the efficiency of r d through sharing

two moment decision models and expected utility maximization two moment decision models are consistent with expected utility maximization only if the choice set or the agent s preferences are restricted this paper identifies a restriction which is sufficient to ensure this consistency and confirms that it holds in many economic models the implications for economic analysis are then derived two different approaches to representing an agent s preferences over strategies yielding random payoffs are in wide use under the mean standard deviation ms approach the agent is assumed to rank the alternatives according to the value of some function defined over the first two moments of the random payoff while the expected utility eu criterion assumes that the expected value of some utility function defined over payoffs is used instead the fact that there are these two competing approaches has generated a considerable literature some authors are concerned with the advantages and disadvantages of each while others deal with conditions under which the potentially different approaches would yield the same results or at least approximately so space does not

seminonparametric estimation of conditionally constrained heterogeneous processes asset pricing applications the overidentifying restrictions of the intertemporal capital asset pricing model are usually rejected when tested using data on consumption growth and asset returns particu larly when additively separable constant relative risk utility is attributed to the representa tive agent this article investigates the extent to which specification error can explain these rejections the empirical strategy is limited information maximum likelihood in conjunc tion with seminonparametric expanding parameter space representations for both the law of motion and utility we find that consumption growth and asset returns display conditional heterogeneity but this fact does not account for rejection of the overidentifying restrictions as might be anticipated from the work of hansen singleton and others using generalized method of moments methods we also find that expansion of the parameter space in the direction of nonseparable utility causes the overidentifying restrictions to be accepted our estimation strategy provides information on the manner in which the restrictions distort the law of motion in particular imposition of additively separable constant relative risk aversion utility causes the conditional variance of consumption growth to be overpredicted the conditional covariance of asset returns with consumption growth to be overpredicted and an equity premium imposition of nonseparable seminon parametric utility causes distortion in these same directions though the distortions are much smaller which is consistent with the outcomes of the tests of the restrictions

fuzzy multi period portfolio selection with different investment horizons abstract this paper considers a fuzzy multi period portfolio selection problem with v shaped transaction cost compared with the traditional studies assuming that assets have the same investment horizon we handle the practical but complicated situation in which assets have different investment horizons within the framework of credibility theory a mean variance model is formulated with the objective of maximizing the terminal return under the total risk constraint over the whole investment alternatively a variation is given by minimizing the total risk under the terminal return constraint a fuzzy simulation based genetic algorithm fsga is designed and three numerical examples are given to illustrate the effectiveness of the proposed approach

information management in incentive problems we extend the standard procurement model to examine how an agent is optimally induced to acquire valuable planning information before he choose an unobservable level of cost reducing effort concer

comparative statics under uncertainty the case of mean variance preferences we analyze the comparative statics of optimal decisions under uncertainty when preferences are represented by twomoment mean variance utility functions we relate our findings to concepts for risk attitudes that are familiar from the expected utility approach in the two parameter approach a number of plausible comparative static effects already emerges under the assumption of decreasing absolute risk aversion to determine comparative static effects of changes in background risks stronger concepts are needed risk vulnerability temperance and standardness imply appropriately transferred to the mean variance framework the plausible effect that risk taking will be reduced if background risks increase 2002 elsevier b v all rights reserved

agency costs and innovation abstract stylized facts indicate that small firms are responsible for a disproportionate share of innovative research there are many possible explanations for this fact the paper seeks to understand this phenomenon as the outcome of an optimal assignment of tasks across individuals and organizations it is shown that incentive costs associated with a given task depend on the total portfolio of tasks that an individual or an organization undertakes mixing hard to measure activities innovation with easy to measure activities routine is particularly costly since it will either lead to misallocation of attention across tasks or to misallocation of risk larger firms are at a comparative disadvantage in conducting highly innovative research because of the costs associated with managing a heterogeneous set of tasks it is further argued that optimal organizational responses to coordination and control of routine tasks will lead to bureaucratization within the firm and to financial constraints imposed by capital markets both of which are hostile to innovation

to innovate or not to innovate incentives and innovation in hierarchies hierarchical organizations often perform poorly in inducing the adoption of innovations the authors examine a principal offering contracts to agents who make unobservable effort and adoption of innovation choices yielding moral hazard who occupy jobs of differing unobserved productivities yielding adverse selection and who engage in a repeated relationship with the principal causing a ratchet effect to arise increasing the rate of adoption of an innovation in such an organization causes the incentive costs of adoption to increase at an increasing rate relatively low rates of adoption may then be a response to the prohibitive incentive costs of higher adoption rates copyright 1990 by american economic association

the benefits of differential variance based constraints in portfolio optimization abstract the main problem of portfolio optimization is parameter estimation error various methods have been suggested to mitigate this problem among which are shrinkage resampling bayesian updating naive diversification and imposing constraints on the portfolio weights this study suggests two substantial extensions of the constrained optimization approach the variance based constraints vbc and the global variance based constraints gvbc methods by the vbc method the constraint imposed on the weight of a given stock is inversely proportional to its standard deviation the higher a stock s sample standard deviation the higher the potential estimation error of its parameters and therefore the tighter the constraint imposed on its weight gvbc employs a similar idea but instead of imposing a sharp boundary constraint on each stock a quadratic cost is assigned to deviations from the naive 1 n weight and a single global constraint is imposed on the total cost of all deviations comparing ten optimization methods we find that the two new suggested methods typically yield the best performance as measured by the sharpe ratio gvbc ranks first these results are obtained for two different datasets and are also robust to the number of assets under consideration

downside loss aversion and portfolio management downside loss averse preferences have seen a resurgence in the portfolio management literature this is due to the increasing use of derivatives in managing equity portfolios and the increased use of quantitative techniques for bond portfolio management we employ the lower partial moment as a risk measure for downside loss aversion and compare mean variance m v and mean lower partial moment m lpm optimal portfolios under nonnormal asset return distributions when asset returns are nearly normally distributed there is little difference between the optimal m v and m lpm portfolios when asset returns are nonnormal with large left tails we document significant differences in m v and m lpm optimal portfolios this observation is consistent with industry usage of m v theory for equity portfolios but not for fixed income portfolios

mean variance analysis of a single supplier and retailer supply chain under a returns policy abstract in the literature most of the supply chain coordinating policies target at improving the supply chain s efficiency in terms of expected cost reduction or expected profit improvement however optimizing the expected performance alone cannot guarantee that the realized performance measure will fall within a small neighborhood of its expected value when the corresponding variance is high moreover it ignores the risk aversion of supply chain members which may affect the achievability of channel coordination as a result we carry out in this paper a mean variance mv analysis of supply chains under a returns policy we first propose an mv formulation for a single supplier single retailer supply chain with a newsvendor type of product the objective of each supply chain decision maker is to maximize the expected profit such that the standard deviation of profit is under the decision maker s control we study both the cases with centralized and decentralized supply chains we illustrate how a returns policy can be applied for managing the supply chains to address the issues such as channel coordination and risk control extensive numerical studies are conducted and managerial findings are proposed

optimal mean variance portfolio selection using cauchy schwarz maximization fund managers highly prioritize selecting portfolios with a high sharpe ratio traditionally this task can be achieved by revising the objective function of the markowitz mean variance portfolio model and then resolving quadratic programming problems to obtain the maximum sharpe ratio portfolio this study presents a closed form solution for the optimal sharpe ratio portfolio by applying cauchy schwarz maximization and the concept of kuhn tucker conditions an empirical example is used to demonstrate the efficiency and effectiveness of the proposed algorithms moreover the proposed algorithms can also be used to obtain the optimal portfolio containing large numbers of securities which is not possible or at least is complicated via traditional quadratic programming approaches

analysis of the conditional stock return distribution under incomplete specification abstract the analysis of the distribution of the stock returns plays an important role in financial theory since a distributional assumption is required for mean variance portfolio theory theoretical models of capital asset prices determining the price of derivative products efficient estimation by maximum likelihood procedure and establishing forecasting confidence intervals up to now most of the studies analyze the unconditional distribution of the stock returns using the likelihood ratio test the schwarz information criterion or by graphical analysis however the analysis of the conditional distribution is very important since most of the empirical financial studies use high frequency data and these data present dynamic structure in this paper we focus on the conditional distribution we design different bootstrap mechanisms for comparing the goodness of fit of several functional forms postulated under the null hypothesis for individual spanish stocks and for the general index of the madrid stock market we use the cramer von mises test statistic based on the standardized residuals and assuming that the null distribution can depend on some unknown parameters

on the unimodality of the price setting newsvendor problem with additive demand under risk considerations abstract we present a mean variance analysis of the single product single period price setting newsvendor problem with additive price dependent demand the main goal of this paper is to use a mean variance framework to solve any risk sensitive instance and find conditions under which the unimodality of the problem is guaranteed we introduce such conditions via the lost sales rate elasticity the elasticity of the optimal price and the elasticity of the expected safety stock surplus to provide managerial insight in terms of the newsvendor s level of service we also simplify the optimization problem in case that those conditions do not hold the main contribution of this paper is that by evaluating the unimodality of the problem for any possible risk attitude it extends previously published results found for the concavity of the solution in risk neutral and moderately risk sensitive cases

forecasting the volatility of crude oil futures using intraday data abstract we use the information in intraday data to forecast the volatility of crude oil at a horizon of 1 66 days using a variety of models relying on the decomposition of realized variance in its positive or negative semivariances part and its continuous or discontinuous part jumps we show the importance of these decompositions in predictive in sample regressions using a number of specifications nevertheless an important empirical finding comes from an out of sample analysis which unambiguously shows the limited interest of considering these components overall our results indicates that a simple autoregressive specification mimicking long memory and using past realized variances as predictors does not perform significantly worse than more sophisticated models which include the various components of realized variance

the simulation of option prices with application to liffe options on futures we build a framework for modelling the deviation of observed option prices from the black scholes prices we use a flexible model for a density a two sided switching weibull to capture the implied volatility the model can be used to generate prices it can take into account no arbitrage bounds for option prices and is capable of generating such stylised facts as the smile effect we apply this methodology to liffe options on german government bond futures

robust tracking error portfolio selection with worst case downside risk measures abstract this paper proposes downside risk measure models in portfolio selection that captures uncertainties both in distribution and in parameters the worst case distribution with given information on the mean value and the covariance matrix is used together with ellipsoidal and polytopic uncertainty sets to build up this type of downside risk model as an application of the models the tracking error portfolio selection problem is considered by lifting the vector variables to positive semidefinite matrix variables we obtain semidefinite programming formulations of the robust tracking portfolio models numerical results are presented in tracking sse50 of the shanghai stock exchange compared with the tracking error variance portfolio model and the equally weighted strategy the proposed models are more stable have better accumulated wealth and have much better sharpe ratio in the investment period for the majority of observed instances

repeated auctions of incentive contracts investment and bidding parity with an application to takeovers this article considers a two period model of natural monopoly and second sourcing the incumbent supplier invests in the first period after observing the incumbent s first period performance the buyer may break out in the second period the investment may or may not be transferable to the second source and it may be monetary or take the form of human capital we determine whether the incumbent should be favored at the reprocurement stage and how the slope of his incentive scheme should evolve over time we find that the gains from second sourcing are not so large as one might hope finally we reinterpret the second source as a raider and the breakout as a takeover we discuss the desirability of defensive tactics and obtain a rich set of testable implications concerning the size of managerial stock options the extent of defensive tactics the firm s performance and the probability of a takeover

estimating a household production function heterogeneity the demand for health inputs and their effects on birth weight the household production literature emphasizes that technical or biological processes condition input selection by households in their production activities along with prices and income exogenous variations in health to the extent that they are perceived by individuals heterogeneity lead to correlations between inputs and health outcomes that cannot be used to derive causal conclusions therefore estimates of health technology must be obtained from a behavioral model in which health inputs are themselves choices consistent estimates are reported of the effect of endogenous inputs such as medical care smoking and fertility on birth weight and fetal growth in the presence of health heterogeneity

non separation in the mean lower partial moment portfolio optimization problem abstract with a number of advantages lower partial moments lpm serve as alternatives to variance as measures of portfolio risk for two specific targets a separation property holds in the context of mean lpm portfolio optimization that allows investors to separate the decision about investment proportions among risky assets from the decision about how much to invest in risky versus risk free assets for other targets however separation is not guaranteed and this case has not received much attention in the literature we show in the case of non separation that investment curves are not common to all optimizing investors but that they are convex in mean lpm space and their lower envelope is the efficient frontier we consider the interesting behavior of investment curves and optimal risky portfolios we also show empirically that an investor who mistakenly assumes separation holds will not experience significant excess portfolio risk in all practical cases

portfolio optimization under loss aversion abstract we present an integrated methodological approach for selecting portfolios the proposed methodology is focused on incorporation of investor s preferences in the mean risk framework we propose a risk measure calculated with the downside part of the portfolio return distribution which we argue captures better the practical behavior of the loss averse investor we establish its properties study the link with stochastic dominance criteria point out the relations with conditional value at risk and lower partial moment of first order and give the explicit formula for the case of scenario based portfolio optimization the proposed methodology involves two stages firstly the investment opportunity set efficient frontier is determined and secondly one single preferred efficient portfolio is selected namely the one having the highest expected utility value three classes of utility functions with loss aversion corresponding to three types of investors are considered the empirical study is targeted on assessing the differences between the efficient frontier of the proposed model and the classical mean variance mean cvar and mean lpm1 frontiers we firstly analyze the loss of welfare incurred by using another model instead of the proposed one and measure the corresponding gain loss of utility secondly we assess how much the portfolios really differ in terms of their compositions using a dissimilarity index based on the 1 norm we describe and interpret the optimal solutions obtained and emphasize the role and influence of loss aversion parameters values and of constraints three types of constraints are studied no short selling allowed a certain degree of diversification imposed and short selling allowed

international portfolio diversification with estimation risk international portfolio diversification has long been advocated as a way of enhancing average returns while reducing portfolio risk for the investor who considers diversifying into foreign securities this proposition however relies on the assumption that the required inputs to the classical mean variance analysis are known with certainty typically expected returns variances and covariances are simply replaced by their ex post sample values and the optimal portfolio is derived without mentioning the uncertainty inherent in these parameter values but the rational investor should take this uncertainty into account when forming expectations and probably will consider estimators that are less subject to estimation error than the classical sample mean this paper investigates alternative estimators of expected returns and their implications for the alleged gains from diversification an important observation is the crucial influence that errors in estimating expected returns have on portfolio analysis a closer examiprevious studies of international portfolio diversification have relied on ex post meanvariance analysis without considering the problem of estimation risk typically past averages are substituted for expected returns and no allowance is made for the uncertainty inherent in these parameter values first i demonstrate the shortcomings of such an approach and second i investigate another method of estimating expected returns initially proposed by stein by shrinking the sample averages toward a common mean i find that the out of sample performance of the optimal portfolio is substantially increased one of the implications of this method is that the classical conclusions vastly overestimate the possible gains in average returns instead benefits from diversification are more likely to accrue from a reduction in risk this paper draws on part of my dissertation at the university of chicago i am grateful to arnold zellner michael mussa george constantinides and especially john bilson for useful discussions and comments numerous improvements were also suggested by the referee this research received the generous financial support of the college interuniversitaire d etudes doctorales dans les sciences du management

portfolio optimization under lower partial moments in emerging electricity markets evidence from turkey abstract optimization of the electricity markets under modern portfolio theory has a crucial role for financial decision makers power suppliers in deregulated electricity markets need to optimize their generation capacities and bidding strategies so as to effectively participate in bilateral contract and spot markets market players have to deal with continuously changing electricity prices in competitive electricity market environment during their daily routine system operations electricity not like the others is a unique product service and cannot be stored economically however it should be generated and consumed simultaneously in addition to all power suppliers face with fuel price water regime delivery and network risks in view of the scene described above prudent decision making methodologies are of critical importance to maximize profit while minimizing managing risks this paper presents a comprehensive comparison of mean variance down side and semi variance methods for optimization in electricity markets and the corresponding methodologies to maximize the return while minimizing risk real turkish day ahead market data set between december 2009 and december 2012 is used in numerical calculations generation cost data of hydraulic plants lignite coal fired thermal power plants and natural gas combined cycle power plants are taken into consideration in the course of optimization evaluations in the present of real data these methods can also be applied to renewable energy generation types these three methods were able to be applied to all case scenarios effectively and produced efficient frontiers optimal minimal portfolios and utility functions successfully the results have revealed that the methods significantly provide decisions for power suppliers with different risk aversion levels and for various instruments to maximize the profit while minimizing the associated market risks and to meet generation obligations consequently financial optimization under lower partial moments constraints would give notable results in analyzing the efficient frontiers for electricity markets in turkey

mean lower partial moment valuation and lognormally distributed returns in this paper we develop a capital asset pricing model in a mean lower partial moment framework specifically we show that when partial moments are computed about the expected risky portfolio return optimal portfolio choice in a mean lower partial framework permits a two fund portfolio separation between a riskless asset and a market portfolio of risky assets in this new framework risk is measured as semideviation for second degree stochastic dominance and semivariance for third degree stochastic dominance further when security returns are lognormally distributed and small risk this new mean lower partial moment valuation specializes to the mean logarithmic variance capital asset pricing model

a risk return model with risk and return measured as deviations from a target return two attribute risk and return models are very popular in the economics and finance literature for analyzing decisions under uncertainty their popularity stems primarily from the intuitive appeal of the dichotomy into risk and return and from the ease with which the concepts can be diagrammed in two dimensions the most commonly used risk return model is the mean variance model in which risk is measured as the variance and return by the mean of the probability distribution over outcomes the mean variance model has a number of shortcomings which are widely known but of particular concern here are the facts that 1 mean variance dominance is neither necessary nor sufficient for second degree stochastic dominance 2 unless the form of the probability distribution is restricted mean variance is consistent with von neumann morgenstern utility theory only if the utility function is quadratic and 3 as peter fishburn has noted

split awards procurement and innovation in many procurement settings it is possible for a buyer to split a production award between suppliers in this article we develop a model of split award procurement auctions in which the split choice is endogenous we characterize the set of equilibrium bids and allocations for optimizing agents in an environment in which suppliers are fully informed about each other s costs split award equilibria simultaneously exhibit strong collusive features and cost efficiency properties despite the former property of the equilibria upstream investment considerations may lead a buyer to prefer a split award auction format to a winner take all auction format

variance vs downside risk is there really that much difference abstract the popularity of downside risk among investors is growing and mean return downside risk portfolio selection models seem to oppress the familiar mean variance approach the reason for the success of the former models is that they separate return fluctuations into downside risk and upside potential this is especially relevant for asymmetrical return distributions for which mean variance models punish the upside potential in the same fashion as the downside risk the paper focuses on the differences and similarities between using variance or a downside risk measure both from a theoretical and an empirical point of view we first discuss the theoretical properties of different downside risk measures and the corresponding mean downside risk models against common beliefs we show that from the large family of downside risk measures only a few possess better theoretical properties within a return risk framework than the variance on the empirical side we analyze the differences between some us asset allocation portfolios based on variances and downside risk measures among other things we find that the downside risk approach tends to produce on average slightly higher bond allocations than the mean variance approach furthermore we take a closer look at estimation risk viz the effect of sampling error in expected returns and risk measures on portfolio composition on the basis of simulation analyses we find that there are marked differences in the degree of estimation accuracy which calls for further research

regulating a monopolist with unknown costs we consider the problem of how to regulate a monopolistic firm whose costs are unknown to the regulator the regulator s objective is to maximize a linear social welfare function of the consumers surplus and the firm s profit in the optimal regulatory policy prices and subsidies are designed as functions of the firm s cost report so that expected social welfare is maximized subject to the constraints that the firm has nonnegative profit and has no incentive to misrepresent its costs we explicitly derive the optimal policy and analyze its properties in their classic papers dupuit 2 and hotelling 5 considered pricing policies for a bridge that had a fixed cost of construction and zero marginal cost they demonstrated that the pricing policy that maximizes consumer well being is to set price equal to marginal cost and to provide a subsidy to the supplier equal to the fixed cost so that a firm would be willing to provide the bridge this first best solution is based on a number of informational assumptions first the demand function is assumed to be known to both the regulator and to the firm while the assumption of complete information may be too strong the assumption that information about demand is as available to the regulator as it is to the firm does not seem unnatural a second informational assumption is that the regulator has complete information about the cost of the firm or at least has the same information about cost as does the firm this assumption is unlikely to be met in reality since the firm would be expected to have better information about costs than would the regulator as weitzman has stated an essential feature of the regulatory environment i am trying to describe is uncertainty about the exact specification of each firm s cost function in most cases even the managers and engineers most closely associated with production will be unable to precisely specify beforehand the cheapest way to generate various hypothetical output levels because they are yet removed from the production process the regulators are likely to be vaguer still about a firm s cost function 12 p 684 as this observation suggests it is natural to expect that a firm would have better information regarding its costs than would a regulator the purpose of this paper is to develop an optimal regulatory policy for the case in which the regulator does not know the costs of the firm one strategy that a regulator could use in the absence of full information about costs is to give the firm the title to the total social surplus and to delegate the pricing decision to the firm in pursuing its own interests which would then be to maximize the total social surplus the firm would adopt the same marginal cost pricing strategy that the regulator would have imposed if the regulator had

the impact of financial leverage on risk of equity measured by loss oriented risk measures an option pricing approach abstract we investigate how financial leverage influences the risk of equity in companies with limited liability in our study the risk is measured by loss oriented risk measures var downside deviation etc also the dependence of the risk premium on risk is under consideration var based and downside risk measures are considered in similar frameworks and risk premium is introduced which is symmetrical to these risk measures the value of equity is modeled by the price of a call option in most cases there is a positive relationship between the level of leverage measured by the debt ratio and the risk measured by the loss oriented risk measures however there exist exceptions the risk premium is not a linear function of the risk still for a reasonable range of leverage the dependence of the risk premium on risk is approximately linear in most cases

optimal algorithms and lower partial moment ex post results portofolio management in the finance literature has typically used optimization algorithms to determine security allocations within a portfolio in order to obtain the best trade off between risk and return these algorithms despite some improvements are restrictive in terms of an investor s risk aversion utility function since individual investors have different levels of risk aversion this paper proposes two portfolio optimization algorithms that can be tailored to the specific level of risk aversion of the individual investor and performs ex postevaluation tests of the algorithm performance