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79
On estimating the expected return on the market  an exploratory investigation
 Journal of Financial Economics
, 1980
"... The expected market return is a number frequently required for the solution of many investment and corporate tinance problems, but by comparison with other tinancial variables, there has been little research on estimating this expected return. Current practice for estimating the expected market retu ..."
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Cited by 245 (1 self)
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The expected market return is a number frequently required for the solution of many investment and corporate tinance problems, but by comparison with other tinancial variables, there has been little research on estimating this expected return. Current practice for estimating the expected market return adds the historical average realized excess market returns to the current observed interest rate. While this model explicitly reflects the dependence of the market return on the interest rate, it fails to account for the effect of changes in the level of market risk. Three models of equilibrium expected market returns which reflect this dependence are analyzed in this paper. Estimation procedures which incorporate the prior restriction that equilibrium expected excess returns on the market must be positive are derived and applied to return data for the period 19261978. The principal conclusions from this exploratory investigation are: (1) in estimating models of the expected market return, the nonnegativity restriction of the expected excess return should be explicitly included as part of the specification; (2) estimators which use realized returns should be adjusted for heteroscedasticity. 1.
Robust Portfolio Selection Problems
 Mathematics of Operations Research
, 2001
"... In this paper we show how to formulate and solve robust portfolio selection problems. The objective of these robust formulations is to systematically combat the sensitivity of the optimal portfolio to statistical and modeling errors in the estimates of the relevant market parameters. We introduce "u ..."
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Cited by 95 (8 self)
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In this paper we show how to formulate and solve robust portfolio selection problems. The objective of these robust formulations is to systematically combat the sensitivity of the optimal portfolio to statistical and modeling errors in the estimates of the relevant market parameters. We introduce "uncertainty structures" for the market parameters and show that the robust portfolio selection problems corresponding to these uncertainty structures can be reformulated as secondorder cone programs and, therefore, the computational effort required to solve them is comparable to that required for solving convex quadratic programs. Moreover, we show that these uncertainty structures correspond to confidence regions associated with the statistical procedures used to estimate the market parameters. We demonstrate a simple recipe for efficiently computing robust portfolios given raw market data and a desired level of confidence.
Offering versus choice in 401(k) plans: Equity exposure and number of funds
 Journal of Finance
, 2006
"... Records of over half a million participants in more than 600 401(k) plans indicate that participants tend to allocate their contributions evenly across the funds they use, with the tendency weakening with the number of funds used. The number of funds used, typically between three and four, is not se ..."
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Cited by 25 (0 self)
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Records of over half a million participants in more than 600 401(k) plans indicate that participants tend to allocate their contributions evenly across the funds they use, with the tendency weakening with the number of funds used. The number of funds used, typically between three and four, is not sensitive to the number of funds offered by the plans, which ranges from 4 to 59. A participant’s propensity to allocate contributions to equity funds is not very sensitive to the fraction of equity funds among offered funds. The paper also comments on limitations on inferences from experiments and aggregatelevel data analysis. HOW MUCH AND HOW TO SAVE FOR RETIREMENT is one of the most important financial decisions made by most people. Defined contribution (DC) pension plans, such as the popular 401(k) plans, are important instruments of such savings. By 2001 yearend, about 45 million American employees held 401(k) plan accounts with a total of $1.75 trillion in assets (Holden and VanDerhei (2001)). An important characteristic of these plans is that the participant has responsibility over his savings among a plan’s various funds. How responsibly do the participants behave? In particular, how sensitive are participants ’ choices to possible framing effects associated with the menu of choices they are offered? To explore these questions, this paper analyzes a data set recently provided by the Vanguard Group consisting of records of more than half a million participants in about 640 DC plans. These plans offer between 4 and 59 funds in which participants can invest. All plans offer at least one stock fund, 635 plans
Markowitz revisited: meanvariance models in financial portfolio analysis
 SIAM Rev
, 2001
"... Abstract. Meanvariance portfolio analysis provided the first quantitative treatment of the tradeoff between profit and risk. We describe in detail the interplay between objective and constraints in a number of singleperiod variants, including semivariance models. Particular emphasis is laid on avo ..."
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Cited by 21 (1 self)
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Abstract. Meanvariance portfolio analysis provided the first quantitative treatment of the tradeoff between profit and risk. We describe in detail the interplay between objective and constraints in a number of singleperiod variants, including semivariance models. Particular emphasis is laid on avoiding the penalization of overperformance. The results are then used as building blocks in the development and theoretical analysis of multiperiod models based on scenario trees. A key property is the possibility of removing surplus money in future decisions, yielding approximate downside risk minimization.
Equilibrium Bandwidth and Buffer Allocations for Elastic Traffics
, 2000
"... Consider a set of users sharing a network node under an allocation scheme that provides each user with a fixed minimum and a random extra amount of bandwidth and buffer. Allocations and prices are adjusted to adapt to resource availability and user demands. Equilibrium is achieved when all users opt ..."
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Cited by 14 (1 self)
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Consider a set of users sharing a network node under an allocation scheme that provides each user with a fixed minimum and a random extra amount of bandwidth and buffer. Allocations and prices are adjusted to adapt to resource availability and user demands. Equilibrium is achieved when all users optimize their utility and demand equals supply for nonfree resources. We analyze two models of user behavior. We show that at equilibrium expected return on purchasing variable resources can be higher than that on fixed resources. Thus users must balance the marginal increase in utility due to higher return on variable resources and the marginal decrease in utility due to their variability. For the first user model we further show that at equilibrium where such tradeoff is optimized all users hold strictly positive amounts of variable bandwidth and buffer. For the second model we show that if both variable bandwidth and buffer are scarce then at equilibrium every user either holds both variab...
An Equilibrium Model of Asset Pricing and Moral Hazard
 Review of Financial Studies
, 2005
"... paper represents a major extension of a section in Chapter 2 of my Ph.D. dissertation submitted to the University of California at Berkeley, where a twoasset equilibrium was developed. I am very grateful to Navneet Arora ..."
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Cited by 9 (1 self)
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paper represents a major extension of a section in Chapter 2 of my Ph.D. dissertation submitted to the University of California at Berkeley, where a twoasset equilibrium was developed. I am very grateful to Navneet Arora
Equilibrium allocation of variable resources for elastic traffics
 In Proceedings of the IEEE INFOCOM
, 1998
"... Abstract — Consider a set of connections sharing a network node under an allocation scheme that provides each connection with a fixed minimum and a random extra amount of bandwidth and buffer. Allocations and prices are adjusted to adapt to resource availability y and user demands. We consider two ..."
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Cited by 6 (2 self)
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Abstract — Consider a set of connections sharing a network node under an allocation scheme that provides each connection with a fixed minimum and a random extra amount of bandwidth and buffer. Allocations and prices are adjusted to adapt to resource availability y and user demands. We consider two scenarios of user behavior. In the first scenario a connection purchases an allocation to maximize its expected utility in such a way that the resource cost of the new allocation, and hence its connection charge, remains the same as that for the old allocation. In the second scenario this budget constraint is relaxed and a connection tries to maximize its benefit, expected utility minus the resource cost. Equilibrium is achieved when all connections ach]eve their optimality and demand equals supply for nonfree resources. We show that at equilibrium expected return on purchasing variable resources can be higher than that on fixed resources. Thus connections must balance the marginal increase in utility due to higher return on variable resources and the marginal decrease in utility due to their variability. We further show that in equilibrium where such tradeoff is optimized all connections hold strictly positive amounts of variable bandwidth and bufer. I.
Equilibrium Allocation and Pricing of Variable Resources among UserSuppliers
 Performance Evaluation
, 1998
"... We propose a novel model of resource sharing schemes that provide each user with a fixed minimum and a random extra amount of bandwidth and buffer. Allocations and prices are adjusted to adapt to resource availability and user demands. At equilibrium, if it exists, all users optimize their utility a ..."
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Cited by 5 (2 self)
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We propose a novel model of resource sharing schemes that provide each user with a fixed minimum and a random extra amount of bandwidth and buffer. Allocations and prices are adjusted to adapt to resource availability and user demands. At equilibrium, if it exists, all users optimize their utility and resource demand equals supply, i.e., the marginal increase in user utility due to higher return on variable resources is balanced by the marginal decrease in utility due to their variability. We show how an equilibrium might be approached using a simple price adjustment rule that does not require any knowledge on the part of the network about user utilities. We further show that at equilibrium every user holds strictly positive amounts of variable bandwidth and variable buffer, and in the same ratio. We characterize the equilibrium prices to lie in a hyperplane that can be computed by the network without having to know user utilities. We illustrate with an example how this characterizatio...
IS MEANVARIANCE ANALYSIS VACUOUS: or Was Beta Still Born?
, 1996
"... We show in any economy trading options, with investors having meanvariance preferences, that there are arbitrage opportunities resulting from negative prices for out of the money call options. The theoretical implication of this inconsistency is that meanvariance analysis is vacuous. The practical ..."
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Cited by 5 (0 self)
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We show in any economy trading options, with investors having meanvariance preferences, that there are arbitrage opportunities resulting from negative prices for out of the money call options. The theoretical implication of this inconsistency is that meanvariance analysis is vacuous. The practical implications of this inconsistency are investigated by developing an option pricing model for a CAPM type economy. It is observed that negative call prices begin to appear at strikes that are two standard deviations out of the money. Such outofthe money options often trade. For near money options, the CAPM option pricing model is shown to permit estimation of the mean return on the underlying asset, its volatility and the length of the planning horizon. The model is estimated on S&P 500 futures options data covering the period January 1992  September 1994. It is found that the mean rate of return though positive, is poorly identified. The estimates for the volatility are stable and avera...