mixed integer programming approaches for index tracking and enhanced indexation we consider the problem of reproducing the performance of a stock market index but without purchasing all of the stocks that make up the index index tracking we also consider the problem of out performing the index enhanced indexation we present mixed integer linear programming formulations of these problems our formulations include transaction costs a constraint limiting the number of stocks that can be purchased and a limit on the total transaction cost that can be incurred as our formulations of these problems are mixed integer linear programs we can use a standard solver cplex numeric results are presented for eight data sets drawn from major markets the largest of these data sets involves over 2000 stocks

an econometric analysis of u s foreign direct investment this paper constructs a theoretical model of foreign direct investment and examines the extent to which the model can explain the level of outward direct investment by u s companies over the last two decades the authors find that market size and factor costs both labor and capital are important factors in the investment decision instrumental variable estimation is used to demonstrate that the expectation of short run fluctuations in the dollar also influences the timing of investment copyright 1996 by mit press

contagion volatility persistence and volatility spill overs the case of energy markets during the european financial crisis the aim of this paper is to investigate if and to what extent events in financially troubled eu markets greece ireland and portugal affected energy prices during the eu financial crisis more specifically i we test for contagion effects of bond prices on energy commodity prices ii we examine whether the nature of energy price volatility is affected and iii we investigate whether bond volatility from the financially distressed eu markets spills over to energy commodity return volatility our results indicate the existence of significant contagion effects notable changes in the nature of energy commodity volatility during the eu financial crisis and spill over effects the results are robust to the use of short term yields instead of long term bond price changes and to the inclusion of spain and italy in the sample

allocating between active and passive management with the recent difficulty in beating the s p 500 index the debate over active versus passive investing has risen to a new level of importance we provide a framework for analyzing the trade off the typical pension fund faces in deciding how much to index our analysis gets at the root of active performance stock picking skill after analyzing the performance associated with various degrees of skill in various equity styles for the 1985 97 period we found that a modest amount of stock picking skill goes a long way and that the optimal amount of allocation to indexing declines as skill increases for most risk categories however some allocation to indexing is appropriate

portfolio optimization with tracking error constraints this article explores the risk and return relationship of active portfolios subject to a constraint on tracking error volatility tev which can also be interpreted in terms of value at risk such a constrained portfolio is the typical setup for active managers who are given the task of beating a benchmark the problem with this setup is that the portfolio manager pays no attention to total portfolio risk which results in seriously inefficient portfolios unless some additional constraints are imposed the development in this article shows that tev constrained portfolios are described by an ellipse on the traditional mean variance plane this finding yields a number of new insights because of the flat shape of this ellipse adding a constraint on total portfolio volatility can substantially improve the performance of the active portfolio in general plan sponsors should concentrate on controlling total portfolio risk

oil shocks and oil stocks evidence from the 1970s the present paper examines the returns to 29 oil companies listed on the new york stock exchange during the period surrounding the oil shock of 1973 the returns are decomposed into production refining foreign and domestic operations the hypothesis that domestic price controls benefitted refiners is tested finally the hypothesis that oil price risk was priced in the sense of the arbitrage pricing theory is tested

portfolio selection with mental accounts and delegation das et al 2010 develop an elegant framework where an investor selects portfolios within mental accounts but ends up holding an aggregate portfolio on the mean variance frontier this investor directly allocates the wealth in each account among available assets in practice however investors often delegate the task of allocating wealth among assets to portfolio managers who seek to beat certain benchmarks accordingly we extend their framework to the case where the investor allocates the wealth in each account among portfolio managers our contribution is threefold first we provide an analytical characterization of the existence and composition of the optimal portfolios within accounts and the aggregate portfolio second we present conditions under which such portfolios are not on the mean variance frontier and conditions under which they are third we show that the aforementioned analytical characterization is also applicable within the framework of das et al and thus improves upon their numerical approach

multiple benchmark and multiple portfolio optimization numerous real life portfolio optimization problems require consideration of more than one benchmark and or more than one portfolio these problems are formulated in a way that seems to be more complicated than the standard problem of mean tracking error variance optimization in fact however these diverse problems can be reduced to the standard case and solved with the same algorithm this article provides solutions to the dual benchmark problem the portfolio partition problem and the completion portfolio problem such solutions and applications are important to both portfolio managers and plan sponsors

a comparison of var and cvar constraints on portfolio selection with the mean variance model in this paper we analyze the portfolio selection implications arising from imposing a value at risk var constraint on the mean variance model and compare them with those arising from the imposition of a conditional value at risk cvar constraint we show that for a given confidence level a cvar constraint is tighter than a var constraint if the cvar and var bounds coincide consequently a cvar constraint is more effective than a var constraint as a tool to control slightly risk averse agents but in the absence of a risk free security has a perverse effect in that it is more likely to force highly risk averse agents to select portfolios with larger standard deviations however when the cvar bound is appropriately larger than the var bound or when a risk free security is present a cvar constraint dominates a var constraint as a risk management tool

portfolio selection based on return risk and relative performance markowitz introduced the concept of portfolio selection based on return and variance recognition that many investors evaluate performance relative to a benchmark led to the idea of portfolio selection based on return and relative risk for many investors both approaches fail to yield satisfactory results although they acknowledge the importance of benchmarks in the decision process they are not indifferent to the variance of absolute returns in this situation a utility function that measures return variance and tracking error is more appropriate analysis of this utility function shows that its set of efficient portfolios includes the mean variance efficient set the mean tracking error efficient set and all convex combinations of these two sets optimization with this utility function may find solutions that investors will actually use

natural gas trade and sustainable growth empirical evidence from the top gas consumers of the developing world abstractnatural gas is the key non renewable source of energy for a low carbon economy the research applies heterogeneous panel techniques to investigate the impact of natural gas consumption on economic growth across a panel of top 15 natural gas consumers of the developing world we establish long run dynamics with cross sectional dependence and heterogeneity across the sample countries the long run output elasticities suggest that the natural gas consumption and trade variables have significant positive effect on the output in a panel of developing economies further we establish feedback relationship among gas consumption output and trade in the short run given the significance of natural gas as the low emission source of energy we suggest governments and policy advisers of these major natural gas consumers to focus on developing pipeline infrastructure for adequate supply reforming natural gas sector with a competitive price structure to combat excess demand in individual natural gas market w

the causal relationship between information and communication technology and foreign direct investment this paper investigates the simultaneous causal relationship between investments in information and communication technology ict and foreign direct investment fdi with reference to its implications on economic growth for the empirical analysis we use data from 23 major countries with heterogeneous economics development for the period 1976 99 the results of unit roots and johansen co integration tests indicate variations in degrees of integration among the sample countries our causality test results suggest that there is a causal relationship from ict to fdi interpreted as the higher level of ict investment leads to increased inflow of fdi ict contributes to economic growth indirectly by attracting more foreign direct investment in developed countries there already exist a build up ict capacity which causes inflow of fdi while in developing countries ict capacity must be build up to attract fdi the inflow of fdi causes further increases in ict investment and capacity

optimal portfolio selection and dynamic benchmark tracking abstract this paper analyzes different approaches to portfolio selection when the requirement to portfolio performance is formulated relative to a given benchmark for example it may be desirable to track a market index as closely as possible we develop several portfolio selection algorithms based on different perceptions of risk and different risk target measures ranging from the traditional variance to the more modern value at risk in a dynamic setting we address the issue of optimal portfolio rebalancing we develop an algorithm for determining whether or not to rebalance a given portfolio based on transaction costs and new information about market conditions our approaches are tested on a set of stock data from the oslo stock exchange

an evolutionary heuristic for the index tracking problem abstract index tracking is a popular form of passive fund management the index tracking problem is the problem of reproducing the performance of a stock market index but without purchasing all of the stocks that make up the index our formulation of the problem explicitly includes transaction costs associated with buying or selling stocks and a limit on the total transaction cost that can be incurred our formulation also includes a constraint limiting the number of stocks that can be purchased an evolutionary heuristic population heuristic is presented for the solution of the index tracking problem reduction tests are also presented computational results are presented for five data sets drawn from major world markets these data sets are made publicly available for use by other workers

using genetic algorithms to find technical trading rules1 abstract we use a genetic algorithm to learn technical trading rules for the s p 500 index using daily prices from 1928 to 1995 after transaction costs the rules do not earn consistent excess returns over a simple buy and hold strategy in the out of sample test periods the rules are able to identify periods to be in the index when daily returns are positive and volatility is low and out when the reverse is true these latter results can largely be explained by low order serial correlation in stock index returns

modelling energy spot prices empirical evidence from nymex this paper investigates the behaviour of spot prices in eight energy markets that trade futures contracts on nymex we consider two types of models a mean reverting model and a spike model with mean reversion that incorporates two different speeds of mean reversion one for the fast mean reverting behaviour of prices after a jump occurs and another for the slower mean reversion rate of the diffusive part of the model we also extend these models to incorporate time varying volatility in their specification modelled as a garch and an egarch process we compare the relative goodness of fit of the different modelling variations both in sample using monte carlo simulations as well as out of sample in a value at risk var setting our results indicate the presence of a leverage effect for wti heating oil and heating oil wti crack spread whereas for the remaining energy markets we find the presence of an inverse leverage effect also the addition of the egarch specification for the volatility process improves both the in sample fit as well as the out of sample var performance for most energy markets that we examine

financial networks with intermediation risk management with variable weights in this paper we develop a framework for the modeling analysis and computation of solutions to multitiered financial network problems with intermediaries in which both the sources of financial funds as well as the intermediaries are multicriteria decision makers in particular we assume that these decision makers seek not only to maximize their net revenues but also to minimize risk with the risk being penalized by a variable weight we make explicit the behavior of the various decision makers including the consumers at the demand markets for the financial products we derive the optimality conditions and demonstrate that the governing equilibrium conditions of the financial network economy can be formulated as a finite dimensional variational inequality problem qualitative properties of the equilibrium financial flow and price pattern are provided a computational procedure that exploits the network structure of the problem is proposed and then applied to several numerical examples

does environmental degradation shackle economic growth a panel data investigation on 11 asian countries sustainable economic growth needs to be the primary objective of every government including developing asian countries to improve the social welfare of the people therefore to achieve the desirable level of sustainable economic growth environmental degradation must be controlled without lowering real growth and the well being of the society this study empirically investigates the impact of environmental degradation by co2 emissions on the economic growth of 11 asian countries between 1990 and 2011 based on the nature of the data traditional panel estimation techniques encompassing fixed effects and random effects are employed in which the results of hausman s test and other tests show that the use of fixed effects is preferable over the random effect estimator empirical results exhibit that environmental degradation has a significantly negative impact on economic growth empirical findings also suggest that environmental degradation should be regulated therefore environmentally enlightened management policies for the decrease of co2 emissions and fuel consumption by transportation and industries need to be pursued by asian countries the adoption of safe carbon emission cut back policies is a promising path to sustainable economic growth

money as a medium of exchange in an economy with artificially intelligent agents abstract we study the exchange economies of kiyotaki and wright 1989 in which agents must use a commodity or fiat money as a medium of exchange if trade is to occur our agents are artificially intelligent and are modeled as using classifier systems to make decisions in the assignment of credit within the classifier systems we introduce some innovations designed to study sequential decision problems in a multi agent environment for most economies that we have simulated trading and consumption patterns converge to a stationary nash equilibrium even if agents start with random rules in economies with multiple equilibria the only equilibrium that emerges in our simulations is the one in which goods with low storage costs play the role of medium of exchange i e the fundamental equilibrium of kiyotaki and wright

the citizen versus consumer distinction an exploration of individuals preferences in contingent valuation studies abstract contingent valuation has been used extensively in estimating the value of environmental goods one criticism of this approach however is that respondents in referendum style contingent valuation surveys may express citizen assessments that take into account benefits to others rather than benefits that accrue purely to the respondent themselves within this context the aim of this paper is to examine to what extent individuals express different preferences when adopting a personal or a social citizen perspective while this paper provides some support for the hypothesis that individuals express different preferences when adopting collective as opposed to personal choices reported willingness to pay wtp was found to be insensitive to whether or not the respondents were asked the wtp question from a personal or social perspective

fat tails and truncated bids in contingent valuation an application to an endangered shorebird species a yes response function in a contingent valuation study is said to have fat tails if it has a high and slowly declining yes response rate at high bid levels truncated bids refer to the practice of dropping high bid offers before a yes response rate of near zero is reached this is a common practice in contingent valuation we explore the extent and implications of fat tails and truncated bids in a study of an endangered shorebird species we find among other things that mean willingness to pay is quite sensitive to the highest bid offered so much so that the choice of highest bid nearly dictates outcomes

active portfolio management with benchmarking adding a value at risk constraint abstract we examine the impact of adding a value at risk var constraint to the problem of an active manager who seeks to outperform a benchmark while minimizing tracking error variance tev by using the model of roll 1992 a mean variance analysis of tracking error journal of portfolio management 18 13 22 we obtain three main results first portfolios on the constrained mean tev boundary still exhibit three fund separation but the weights of the three funds when the constraint binds differ from those in roll s model second the constraint mitigates the problem that when an active manager seeks to outperform a benchmark using the mean tev model he or she selects an inefficient portfolio finally when short sales are disallowed the extent to which the constraint reduces the optimal portfolio s efficiency loss can still be notable but is smaller than when short sales are allowed

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

asset allocation in a downside risk framework 1991 asset allocation in a downside risk framework financial analysts journal vol 47 no 5 pp 28 40

performance replication of the spot energy index with optimal equity portfolio selection evidence from the uk us and brazilian markets abstract this paper reproduces the performance of a geometric average spot energy index by investing only in a subset of stocks from the dow jones composite average the ftse 100 and bovespa composite indexes and in two pools that include only energy sector stocks from the us and the uk respectively daily data are used and the index tracking problem for passive investment is addressed with two evolutionary algorithms the differential evolution algorithm and the genetic algorithm the performance of the suggested investment strategy is tested under three different scenarios buy and hold quarterly and monthly rebalancing accounting for transaction costs where necessary

index tracking model downside risk and non parametric kernel estimation abstract in this paper we propose an index tracking model with the conditional value at risk cvar constraint based on a non parametric kernel npk estimation framework in theory we demonstrate that the index tracking model with the cvar constraint is a convex optimization problem we then derive npk estimators for tracking errors and cvar and thereby construct the npk index tracking model monte carlo simulations show that the npk method outperforms the linear programming lp method in terms of estimation accuracy in addition the npk method can enhance computational efficiency when the sample size is large empirical tests show that the npk method can effectively control downside risk and obtain higher excess returns in both bearish and bullish market environments

a markov regime switching approach for hedging energy commodities abstract this paper estimates constant and dynamic hedge ratios in the new york mercantile exchange oil futures markets and examines their hedging performance we also introduce a markov regime switching vector error correction model with garch error structure this specification links the concept of disequilibrium with that of uncertainty as measured by the conditional second moments across high and low volatility regimes overall in and out of sample tests indicate that state dependent hedge ratios are able to provide significant reduction in portfolio risk

dynamic portfolio optimization with transaction costs heuristics and dual bounds we consider the problem of dynamic portfolio optimization in a discrete time finite horizon setting our general model considers risk aversion portfolio constraints e g no short positions return predictability and transaction costs this problem is naturally formulated as a stochastic dynamic program unfortunately with nonzero transaction costs the dimension of the state space is at least as large as the number of assets and the problem is very difficult to solve with more than one or two assets in this paper we consider several easy to compute heuristic trading strategies that are based on optimizing simpler models we complement these heuristics with upper bounds on the performance with an optimal trading strategy these bounds are based on the dual approach developed in brown et al brown d b j e smith p sun 2009 information relaxations and duality in stochastic dynamic programs oper res 58 4 785 801 in this context these bounds are given by considering an investor who has access to perfect information about future returns but is penalized for using this advance information these heuristic strategies and bounds can be evaluated using monte carlo simulation we evaluate these heuristics and bounds in numerical experiments with a risk free asset and 3 or 10 risky assets in many cases the performance of the heuristic strategy is very close to the upper bound indicating that the heuristic strategies are very nearly optimal this paper was accepted by dimitris bertsimas optimization

in defense of optimization the fallacy of 1 n previous research has shown that equally weighted portfolios outperform optimized portfolios which suggests that optimization adds no value in the absence of informed inputs this article argues the opposite with naive inputs optimized portfolios usually outperform equally weighted portfolios the ostensible superiority of the 1 n approach arises not from limitations in optimization but rather from reliance on rolling short term samples for estimating expected returns this approach often yields implausible expectations by relying on longer term samples for estimating expected returns or even naively contrived yet plausible assumptions optimized portfolios outperform equally weighted portfolios out of sample

portfolio frontiers with restrictions to tracking error volatility and value at risk abstract asset managers are often given the task of restricting their activity by keeping both the value at risk var and the tracking error volatility tev under control however these constraints may be impossible to satisfy simultaneously because var is independent of the benchmark portfolio the management of these restrictions is likely to affect portfolio performance and produces a wide variety of scenarios in the risk return space the aim of this paper is to analyse various interactions between portfolio frontiers when risk managers impose joint restrictions upon tev and var specifically we provide analytical solutions for all the intersections and we propose simple numerical methods when such solutions are not available finally we introduce a new portfolio frontier

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

optimal portfolios in good times and bad recent experience with emerging market investments and hedge funds has highlighted the fact that risk parameters are unstable to address this problem we introduce a procedure for identifying multivariate outliers and use the outliers to estimate a new covariance matrix we suggest that a covariance matrix estimated from outliers characterizes a portfolio s riskiness during market turbulence better than a full sample covariance matrix we also introduce a procedure for blending an inside sample covariance matrix with one from an outlier sample this procedure enables one to express views about the likelihood of each risk regime and to differentiate one s aversion to them our framework collapses to the markowitz mean variance model if 1 we set the probabilities of the inside and outlying covariance matrixes equal to their empirical frequencies 2 we are equally averse to both risk regimes and 3 we estimate the inside and outlying covariances around the full sample s mean

is technical analysis in the foreign exchange market profitable a genetic programming approach using genetic programming techniques to find technical trading rules we find strong evidence of economically significant out of sample excess returns to those rules for each of six exchange rates over the period 1981 1995 further when the dollar deutsche mark rules are allowed to determine trades in the other markets there is significant improvement in performance in all cases except for the deutsche mark yen betas calculated for the returns according to various benchmark portfolios provide no evidence that the returns to these rules are compensation for bearing systematic risk bootstrapping results on the dollar deutsche mark indicate that the trading rules detect patterns in the data that are not captured by standard statistical models

bayesian asset allocation and u s domestic bias u s investors hold much less international stock than is optimal according to mean variance portfolio theory applied to historical data we investigated whether this home bias can be explained by bayesian approaches to international asset allocation in comparison with mean variance analysis bayesian approaches use different techniques for obtaining the set of expected returns by shrinking the sample means toward a reference point that is inferred from economic theory applying the bayesian approaches to the field of international diversification we found that a substantial home bias can be explained when a u s investor has a strong belief in the global mean variance efficiency of the u s market portfolio and in this article we show how to quantify the strength of this belief we also found that one of the bayesian approaches leads to the same implications for asset allocation as the mean variance tracking error criterion in both cases the optimal portfolio is a combination of the u s market por

is referendum the same as dichotomous choice contingent valuation the noaa panel on contingent valuation arrow et al 1993 recommends that the valuation question be cast under the form of a referendum because of incentive properties and familiarity to the respondent even though the literature has generally accepted the panel recommendation it is not clear whether explicitly mentioning a referendum leads to different values than asking a dichotomous yes no question without mentioning any voting process the results of our specifically designed contingent valuation survey indicate that the estimated willingness to pay is significantly larger when a referendum is explicitly mentioned

a linear model for tracking error minimization abstract this article investigates four models for minimizing the tracking error between the returns of a portfolio and a benchmark due to linear performance fees of fund managers we can argue that linear deviations give a more accurate description of the investors risk attitude than squared deviations all models have in common that absolute deviations are minimized instead of squared deviations as is the case for traditional optimization models linear programs are formulated to derive explicit solutions the models are applied to a portfolio containing six national stock market indexes usa japan uk germany france switzerland and the tracking error with respect to the msci morgan stanley capital international index world stock market index is minimized the results are compared to those of a quadratic tracking error optimization technique the portfolio weights of the optimized portfolio and its risk return properties are different across the models which implies that optimization models should be targeted to the specific investment objective finally it is shown that linear tracking error optimization is equivalent to expected utility maximization and lower partial moment minimization