input output selection in dea under expert information with application to financial markets abstract data envelopment analysis dea as generally used assumes precise knowledge regarding which variables are inputs and outputs however in many applications there exists only partial knowledge this paper presents a new methodology for selecting input output variables endogenously to the dea model in the presence of partial or expert s knowledge by employing a reward variable observed exogenous to the operation of the dmus the reward is an allocation of a limited resource by an external agency e g capital allocation by a market based on the perceived internal managerial efficiencies we present an iterative two stage optimization model which addresses the benefit of possibly violating the expert information to determine an optimal internal performance evaluation of the dmus for maximizing its correlation with the reward metric theoretical properties of the model are analyzed and statistical significance tests are developed for the marginal value of expert violation the methodology is applied in fundamental analysis of publicly traded firms using quarterly financial data to determine an optimized dea based fundamental strength indicator more than 800 firms covering all major sectors of the us stock market are used in the empirical evaluation of the model the firms so screened by the model are used within out of sample mean variance long portfolio allocation to demonstrate the superiority of the methodology as an investment decision tool

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

non parametric frontier estimates of mutual fund performance using c and l moments some specification tests there is a burgeoning literature using non parametric frontier methods to measure mutual fund performance these articles measure the relationship between the various characteristics mainly return information and some costs of ownership of these specialized financial products to establish a ranking using some efficiency measure we argue in favor of the use of the shortage function which is compatible with general investor preferences and question some of the often maintained hypotheses in this line of research the empirical part employs a large database of us and european mutual funds to offer extensive tests of the underlying modeling assumptions using various frontier estimators

macroeconomic forecasting and structural change the aim of this paper is to assess whether explicitly modeling structural change increases the accuracy of macroeconomic forecasts we produce real time out of sample forecasts for inflation the unemployment rate and the interest rate using a time varying coefficients var with stochastic volatility tv var for the us the model generates accurate predictions for the three variables in particular for inflation the tv var outperforms in terms of mean square forecast error all the competing models fixed coefficients vars time varying ars and the na ove random walk model these results are also shown to hold over the period commonly referred to as the great moderation

portfolio performance evaluation in a mean variance skewness framework abstract astronomical amounts of money are being invested in financial markets consequently the evaluation of portfolio performance has created a great deal of interest among practitioners as well as academic researchers the literature suggests that portfolio efficiency based on mean variance skewness is more desirable than the one based on mean variance however there are no well established procedures to measure efficiency in this framework mainly due to the computational difficulties the aim of this paper is to develop a portfolio performance measure based on mean variance skewness framework by utilizing a non parametric efficiency analysis tool namely data envelopment analysis

equilibrium in a dynamic game of capital accumulation with the overtaking criterion abstract a stationary overtaking equilibrium is constructed for a class of discrete time games of capital accumulation a verification of the equilibrium properties is made using some functional characterization of the overtaking optimality in dynamic programming

efficiency of mutual funds and portfolio performance measurement a non parametric approach abstract in finance portfolio performance assessment is an important area of research the two popular indices of performance are the jensen s alpha and the sharpe index however there are a number of shortcomings of the above measures that have been highlighted in the literature we propose a new measure of performance that seeks to address the limitations of the earlier indices the new index is calculated by employing a well known method in operations research called data envelopment analysis we show the benefits of the proposed approach and assess the performance of mutual funds we compare the results with traditional indices of performance an interesting result we obtain is that the mutual funds are all approximately mean variance efficient

forecast comparisons in unstable environments we propose new methods for comparing the out of sample forecasting performance of two competing models in the presence of possible instabilities the main idea is to develop a measure of the relative local forecasting performance for the two models and to investigate its stability over time by means of statistical tests we propose two tests the fluctuation test and the one time reversal test that analyze the evolution of the models relative performance over historical samples in contrast to previous approaches to forecast comparison which are based on measures of global performance we focus on the entire time path of the models relative performance which may contain useful information that is lost when looking for the model that forecasts best on average we apply our tests to the analysis of the time variation in the out of sample forecasting performance of monetary models of exchange rate determination relative to the random walk copyright 2010 john wiley sons ltd

the carry trade and fundamentals nothing to fear but feer itself the carry trade is the investment strategy of going long in high yield target currencies and short in low yield funding currencies recently this nave trade has seen very high returns for long periods followed by large crash losses after large depreciations of the target currencies based on low sharpe ratios and negative skew these trades could appear unattractive even when diversied across many currencies but more sophisticated conditional trading strategies exhibit more favorable payos we apply novel within economics binary outcome classication tests to show that our directional trading forecasts are informa tive and out of sample loss function analysis to examine trading performance the critical conditioning variable we argue is the fundamental equilibrium exchange rate feer expected returns are lower all else equal when the target currency is overvalued like traders researchers should incorporate this information when evaluating trading strategies when we do so some questions are resolved negative skewness is purged and market volatility vix is uncorrelated with returns other puzzles remain the more sophisticated strategy has a very high sharpe ratio suggesting market ineciency

testing long horizon predictive ability with high persistence and the meese rogoff puzzle a well known puzzle in the international finance literature is that a random walk predicts exchange rates better than economic models meese and rogoff 1983a b and 1988 this paper offers a potential explanation for this finding when exchange rates and fundamentals are highly persistent long horizon forecasts of economic models are asymptotically biased by the estimation error in the parameter that measures the persistence when this bias outweighs the benefits from exploiting economic information the random walk model will forecast better this happens even if the economic model is the true data generating process the reason is that a random walk model imposes a unit root rather than estimates it the paper thus proposes a test for equal predictive ability in the presence of highly persistent variables when applied to the meese rogoff exercise this test shows that the poor forecasting ability of economic models does not imply that the models are not a good description of the data

frontier based vs traditional mutual fund ratings a first backtesting analysis we explore the potential benefits of a series of existing and new non parametric convex and non convex frontier based fund rating models to summarize the information contained in the moments of the mutual fund price series limiting ourselves to the traditional mean variance portfolio setting we test in a simple backtesting setup whether these efficiency measures fare any better than more traditional financial performance measures in selecting promising investment opportunities the evidence points to a remarkable superior performance of these frontier models compared to most but not all traditional financial performance measures

assessing the performance of alternative investments using non parametric efficiency measurement approaches is it convincing abstract dea based performance assessment in the alternative investment fund industry is often motivated by the fact that dea is capable of simultaneously handling multiple input risk and multiple output return measures thereby still offering a single real number as a performance index without utilizing subjective weights to aggregate these inputs and outputs this paper aims at investigating whether dea based performance indexes previously used to assess alternative investment fund performance are actually able to satisfy these properties and to contrast the findings using a dea based performance index with those using a traditional financial performance index

a computation of interest equivalences for nonprice characteristics of bank products this paper seeks to price the nonprice features of british retail bank products it outlines a methodology for computing interest equivalences for a selection of characteristics estimates are obtained for a full observation set and a subset of survivor products on an efficiency frontier its main findings are that certain nonprice features are significant and there does not appear to be a strong case for separating out those products that lie on an efficiency frontier copyright 1992 by ohio state university press

exchange rate predictability the main goal of this article is to provide an answer to the question does anything forecast exchange rates and if so which variables it is well known that exchange rate fluctuations are very difficult to predict using economic models and that a random walk forecasts exchange rates better than any economic model the meese and rogoff puzzle however the recent literature has identified a series of fundamentals methodologies that claim to have resolved the puzzle this article provides a critical review of the recent literature on exchange rate forecasting and illustrates the new methodologies and fundamentals that have been recently proposed in an up to date thorough empirical analysis overall our analysis of the literature and the data suggests that the answer to the question are exchange rates predictable is it depends on the choice of predictor forecast horizon sample period model and forecast evaluation method predictability is most apparent when one or more of the following hold the predictors are taylor rule or net foreign assets the model is linear and a small number of parameters are estimated the toughest benchmark is the random walk without drift

a great fish war model with asymmetric players this paper analyzes the coalitional great fish war model under the assumption that players differ in their time preferences and use different discount rates we derive the equilibrium payoffs of this coalitional game and investigate the impact of the asymmetry assumption on the extreme schemes of cooperative and non cooperative equilibria we then proceed to the computation of stable coalitions using time consistent harvest sharing policies for the partial coordination scheme in the case where players are divided into two groups high and low discount rates we find that asymmetry has a significant impact on the way the resource is shared and on the profitability of coalitions we also find that asymmetry is not a sufficient feature to overcome the puzzle of small coalitions

mean variance skewness portfolio performance gauging a general shortage function and dual approach this paper proposes a nonparametric efficiency measurement approach for the static portfolio selection problem in mean variance skewness space a shortage function is defined that looks for possible increases in return and skewness and decreases in variance global optimality is guaranteed for the resulting optimal portfolios we also establish a link to a proper indirect mean variance skewness utility function for computational reasons the optimal portfolios resulting from this dual approach are only locally optimal this framework permits to differentiate between portfolio efficiency and allocative efficiency and a convexity efficiency component related to the difference between the primal nonconvex approach and the dual convex approach furthermore in principle information can be retrieved about the revealed risk aversion and prudence of investors an empirical section on a small sample of assets serves as an illustration

dynamic factor model with infinite dimensional factor space forecasting abstract the paper compares the pseudo real time forecasting performance of threedynamic factor models i the standard principal component model stock and watson 2002a ii the model based on generalized principal components forni et al 2005 iii the model recently proposed in forni et al 2015 and forni et al 2016 we employa large monthly dataset of macroeconomic and financial time series for the us economy which includes the great moderation the great recession and the subsequent recovery using a rolling window for estimation and prediction we find that iii neatly outperforms i and ii in the great moderation period for both industrial production and inflation and for inflation over the full sample however iii is outperfomed by i and ii over thefull sample for industrial production

what do discounted optima converge to a theory of discount rate asymptotics in economic models abstract this paper considers a sequence of stochastic dynamic problems in which the discount rate goes to zero sufficient conditions are given under which the limit of discounted optimal policies and normalized values are a i long run average optimal and ii catching up optimal policy and value these conditions are shown to be satisfied in many economic models a new decision criterion for the undiscounted problem the strong long run average is introduced this criterion refines the long run average is often equivalent to the catching up and is easier to use than the latter since it has a recursive representation a generalization of fatou s lemma which has wider applicability is also proved

labour market forecasting in germany is disaggregation useful this paper examines whether labour market forecasts can be improved by using disaggregated information we construct vector autoregressive models for employment by sector in order to produce out of sample forecasts of aggregate employment forecast accuracy is compared to univariate models by using clark west tests in an application to german data it is evident that disaggregation significantly improves the employment forecast moreover using fluctuation window tests we find that disaggregation yields superior results especially in phases with strong and sustained employment changes

data envelopment analysis models of investment funds abstract this paper develops theory missing in the sizable literature that uses data envelopment analysis to construct return risk ratios for investment funds it explores the production possibility set of the investment funds to identify an appropriate form of returns to scale it discusses what risk and return measures can justifiably be combined and how to deal with negative risks and identifies suitable sets of measures it identifies the problems of failing to deal with diversification and develops an iterative approximation procedure to deal with it it identifies relationships between diversification coherent measures of risk and stochastic dominance it shows how the iterative procedure makes a practical difference using monthly returns of 30 hedge funds over the same time period it discusses possible shortcomings of the procedure and offers directions for future research

portfolio selection in multidimensional general and partial moment space abstract this paper develops a general approach for the single period portfolio optimization problem in a multidimensional general and partial moment space a shortage function is defined that looks for possible increases in odd moments and decreases in even moments a main result is that this shortage function ensures sufficient conditions for global optimality it also forms a natural basis for developing tests on the influence of additional moments furthermore a link is made with an approximation of an arbitrary order of a general indirect utility function this non parametric efficiency measurement framework permits to differentiate mainly between portfolio efficiency and allocative efficiency finally information can in principle be inferred about the revealed risk aversion prudence temperance and other higher order risk characteristics of investors

making inefficient market indices efficient this paper uses the concept of marginal conditional stochastic dominance and a generalization of the 50 portfolio rule to develop a tractable and parsimonious methodology for constructing a second degree stochastic dominance ssd efficient portfolio from a given inefficient index because the ssd approach considers the entire probability distributions of asset returns the resulting portfolios are efficient with respect to all risk averse utility maximizing investors regardless of the form of their utility functions or the distributions of asset returns

macroeconomic forecasting using diffusion indexes this article studies forecasting a macroeconomic time series variable using a large number of predictors the predictors are summarized using a small number of indexes constructed by principal component analysis an approximate dynamic factor model serves as the statistical framework for the estimation of the indexes and construction of the forecasts the method is used to construct 6 12 and 24 monthahead forecasts for eight monthly u s macroeconomic time series using 215 predictors in simulated real time from 1970 through 1998 during this sample period these new forecasts outperformed univariate autoregressions small vector autoregressions and leading indicator models

geometric representation of the mean variance skewness portfolio frontier based upon the shortage function the literature suggests that investors prefer portfolios based on mean variance and skewness rather than portfolios based on mean variance mv criteria solely furthermore a small variety of methods have been proposed to determine meanvariance skewness mvs optimal portfolios recently the shortage function has been introduced as a measure of e ciency allowing to characterize mvs optimal portfolios using non parametric mathematical programming tools while tracing the mv portfolio frontier has become trivial the geometric representation of the mvs frontier is an open challenge a hitherto unnoticed advantage of the shortage function is that it allows to geometrically represent the mvs portfolio frontier the purpose of this contribution is to systematically develop geometric representations of the mvs portfolio frontier using the shortage function and related approaches