The Experts below are selected from a list of 20961 Experts worldwide ranked by ideXlab platform
Stavros Panageas - One of the best experts on this subject based on the ideXlab platform.
-
high water marks high risk appetites convex compensation long horizons and Portfolio Choice
Journal of Finance, 2009Co-Authors: Stavros Panageas, Mark M WesterfieldAbstract:We study the Portfolio Choice of hedge fund managers who are compensated by high-water mark contracts. We find that even risk-neutral managers do not place unbounded weights on risky assets, despite option-like contracts. Instead, they place a constant fraction of funds in a mean-variance efficient Portfolio and the rest in the riskless asset, acting as would constant relative risk aversion (CRRA) investors. This result is a direct consequence of the in(de)finite horizon of the contract. We show that the risk-seeking incentives of option-like contracts rely on combining finite horizons and convex compensation schemes rather than on convexity alone.
-
high water marks high risk appetites convex compensation long horizons and Portfolio Choice
Social Science Research Network, 2007Co-Authors: Mark M Westerfield, Stavros PanageasAbstract:We study the optimal Portfolio Choice of hedge fund managers who are compensated by high-water mark contracts. Surprisingly, we find that even risk-neutral managers will not place unboundedly large weights on the risky assets, despite the option-type features of the contract. Instead they will place a constant fraction of assets in a mean-variance efficient Portfolio and the rest in the riskless asset, similar to investors with constant relative risk aversion. This result is a direct consequence of the in(de)finite horizon of the contract. We argue more generally that the risk-seeking incentives of option-type compensation contracts rely on the interaction of convex compensation and finite horizons, rather than on the convexity of the compensation scheme alone.
Mark M Westerfield - One of the best experts on this subject based on the ideXlab platform.
-
Portfolio Choice with illiquid assets
Management Science, 2014Co-Authors: Andrew Ang, Dimitris Papanikolaou, Mark M WesterfieldAbstract:We present a model of optimal allocation to liquid and illiquid assets, where illiquidity risk results from the restriction that an asset cannot be traded for intervals of uncertain duration. Illiquidity risk leads to increased and state-dependent risk aversion and reduces the allocation to both liquid and illiquid risky assets. Uncertainty about the length of the illiquidity interval, as opposed to a deterministic nontrading interval, is a primary determinant of the cost of illiquidity. We allow market liquidity to vary from "normal" periods, when all assets are fully liquid, to "illiquidity crises," when some assets can only be traded infrequently. The possibility of a liquidity crisis leads to limited arbitrage in normal times. Investors are willing to forgo 2% of their wealth to hedge against illiquidity crises occurring once every 10 years. This paper was accepted by Itay Goldstein, finance.
-
Portfolio Choice with illiquid assets
National Bureau of Economic Research, 2013Co-Authors: Andrew Ang, Dimitris Papanikolaou, Mark M WesterfieldAbstract:We present a model of optimal allocation over liquid and illiquid assets, where illiquidity is the restriction that an asset cannot be traded for intervals of uncertain duration. Illiquidity leads to increased and state-dependent risk aversion, and reduces the allocation to both liquid and illiquid risky assets. Uncertainty about the length of the illiquidity interval, as opposed to a deterministic non-trading interval, is a primary determinant of the cost of illiquidity. We allow market liquidity to vary from `normal' periods, when all assets are fully liquid, to 'illiquidity crises,' when some assets can only be traded infrequently. The possibility of a liquidity crisis leads to limited arbitrage in normal times. Investors are willing to forego 2% of their wealth to hedge against illiquidity crises occurring once every ten years.
-
high water marks high risk appetites convex compensation long horizons and Portfolio Choice
Journal of Finance, 2009Co-Authors: Stavros Panageas, Mark M WesterfieldAbstract:We study the Portfolio Choice of hedge fund managers who are compensated by high-water mark contracts. We find that even risk-neutral managers do not place unbounded weights on risky assets, despite option-like contracts. Instead, they place a constant fraction of funds in a mean-variance efficient Portfolio and the rest in the riskless asset, acting as would constant relative risk aversion (CRRA) investors. This result is a direct consequence of the in(de)finite horizon of the contract. We show that the risk-seeking incentives of option-like contracts rely on combining finite horizons and convex compensation schemes rather than on convexity alone.
-
high water marks high risk appetites convex compensation long horizons and Portfolio Choice
Social Science Research Network, 2007Co-Authors: Mark M Westerfield, Stavros PanageasAbstract:We study the optimal Portfolio Choice of hedge fund managers who are compensated by high-water mark contracts. Surprisingly, we find that even risk-neutral managers will not place unboundedly large weights on the risky assets, despite the option-type features of the contract. Instead they will place a constant fraction of assets in a mean-variance efficient Portfolio and the rest in the riskless asset, similar to investors with constant relative risk aversion. This result is a direct consequence of the in(de)finite horizon of the contract. We argue more generally that the risk-seeking incentives of option-type compensation contracts rely on the interaction of convex compensation and finite horizons, rather than on the convexity of the compensation scheme alone.
James Wolter - One of the best experts on this subject based on the ideXlab platform.
-
multiple regression model averaging and the focused information criterion with an application to Portfolio Choice
Journal of Business & Economic Statistics, 2019Co-Authors: Filip Klimenka, James WolterAbstract:We consider multiple regression (MR) model averaging using the focused information criterion (FIC). Our approach is motivated by the problem of implementing a mean-variance Portfolio Choice rule. T...
-
multiple regression model averaging and the focused information criterion with an application to Portfolio Choice
Social Science Research Network, 2017Co-Authors: Filip Klimenka, James WolterAbstract:We consider multiple regression (MR) model averaging using the Focused Information Criterion (FIC). Our approach is motivated by the problem of implementing a mean-variance Portfolio Choice rule. The usual approach is to estimate parameters ignoring the intention to use them in Portfolio Choice. We develop an estimation method that focuses on the trading rule of interest. Asymptotic distributions of submodel estimators in the MR case are derived using a localization framework. The localization is of both regression coefficients and error covariances. Distributions of submodel estimators are used for model selection with the FIC. This allows comparison of submodels using the risk of Portfolio rule estimators. FIC model averaging estimators are then characterized. This extension further improves risk properties. We show in simulations that applying these methods in the Portfolio Choice case results in improved estimates compared with several competitors. An application to futures data shows superior performance as well.
-
focused shrinkage with an application to Portfolio Choice
Social Science Research Network, 2017Co-Authors: Filip Klimenka, James WolterAbstract:We propose a shrinkage estimator for parameters θ which improves the mean squared error of functions x (θ) over standard Choices. When the restricted model estimator is in the class of minimum distance estimators, we project onto the restricted parameter space using a matrix based on the derivatives of x (θ). The proposed matrix is shown to minimize the bias among estimators in this class. This Choice is then incorporated into a shrinkage procedure. We derive a risk bound for shrinkage estimators which allows for arbitrary projection matrices. Using this result, it is shown the proposed projection matrix can lead to substantially lower risk. The improvement is largest when the restricted model has nontrivial bias. This is shown with our motivating example: implementing a mean-variance Portfolio Choice rule. Our method is applied by shrinking toward a model with restricted covariance matrix. Extensive simulations demonstrate improved risk in this case. The estimator is also implemented in a Portfolio Choice application to futures data. Our approach outperforms standard procedures here as well.
Wolfgang Schmid - One of the best experts on this subject based on the ideXlab platform.
-
on the exact solution of the multi period Portfolio Choice problem for an exponential utility under return predictability
European Journal of Operational Research, 2015Co-Authors: Taras Bodnar, Nestor Parolya, Wolfgang SchmidAbstract:In this paper we derive the exact solution of the multi-period Portfolio Choice problem for an exponential utility function under return predictability. It is assumed that the asset returns depend on predictable variables and that the joint random process of the asset returns and the predictable variables follow a vector autoregressive process. We prove that the optimal Portfolio weights depend on the covariance matrices of the next two periods and the conditional mean vector of the next period. The case without predictable variables and the case of independent asset returns are partial cases of our solution. Furthermore, we provide an exhaustive empirical study where the cumulative empirical distribution function of the investor’s wealth is calculated using the exact solution. It is compared with the investment strategy obtained under the additional assumption that the asset returns are independently distributed.
-
a closed form solution of the multi period Portfolio Choice problem for a quadratic utility function
Annals of Operations Research, 2015Co-Authors: Taras Bodnar, Nestor Parolya, Wolfgang SchmidAbstract:In the present paper, we derive a closed-form solution of the multi-period Portfolio Choice problem for a quadratic utility function with and without a riskless asset. All results are derived under weak conditions on the asset returns. No assumption on the correlation structure between different time points is needed and no assumption on the distribution is imposed. All expressions are presented in terms of the conditional mean vectors and the conditional covariance matrices. If the multivariate process of the asset returns is independent, it is shown that in the case without a riskless asset the solution is presented as a sequence of optimal Portfolio weights obtained by solving the single-period Markowitz optimization problem. The process dynamics are included only in the shape parameter of the utility function. If a riskless asset is present, then the multi-period optimal Portfolio weights are proportional to the single-period solutions multiplied by time-varying constants which are dependent on the process dynamics. Remarkably, in the case of a Portfolio selection with the tangency Portfolio the multi-period solution coincides with the sequence of the single-period solutions. Finally, we compare the suggested strategies with existing multi-period Portfolio allocation methods on real data.
-
on the exact solution of the multi period Portfolio Choice problem for an exponential utility under return predictability
arXiv: Portfolio Management, 2012Co-Authors: Taras Bodnar, Nestor Parolya, Wolfgang SchmidAbstract:In this paper we derive the exact solution of the multi-period Portfolio Choice problem for an exponential utility function under return predictability. It is assumed that the asset returns depend on predictable variables and that the joint random process of the asset returns and the predictable variables follow a vector autoregressive process. We prove that the optimal Portfolio weights depend on the covariance matrices of the next two periods and the conditional mean vector of the next period. The case without predictable variables and the case of independent asset returns are partial cases of our solution. Furthermore, we provide an empirical study where the cumulative empirical distribution function of the investor's wealth is calculated using the exact solution. It is compared with the investment strategy obtained under the additional assumption that the asset returns are independently distributed.
-
a closed form solution of the multi period Portfolio Choice problem for a quadratic utility function
2012Co-Authors: Taras Bodnar, Nestor Parolya, Wolfgang SchmidAbstract:In the present paper, we derive a closed-form solution of the multi-period Portfolio Choice problem for a quadratic utility function with and without a riskless asset. All results are derived under weak conditions on the asset returns. No assumption on the correlation structure between different time points is needed and no assumption on the distribution is imposed. All expressions are presented in terms of the conditional mean vectors and the conditional covariance matrices. If the multivariate process of the asset returns is independent it is shown that in the case without a riskless asset the solution is presented as a sequence of optimal Portfolio weights obtained by solving the single-period Markowitz optimization problem. The process dynamics are included only in the shape parameter of the utility function. If a riskless asset is present then the multi-period optimal Portfolio weights are proportional to the single-period solutions multiplied by time-varying constants which are depending on the process dynamics. Remarkably, in the case of a Portfolio selection with the tangency Portfolio the multi-period solution coincides with the sequence of the simple-period solutions. Finally, we compare the suggested strategies with existing multi-period Portfolio allocation methods for real data.
Nicole Maestas - One of the best experts on this subject based on the ideXlab platform.
-
medical expenditure risk and household Portfolio Choice
Journal of Applied Econometrics, 2007Co-Authors: Dana P Goldman, Nicole MaestasAbstract:Medical expenses are an increasingly important contributor to household financial risk. We examine the effect of medical expenditure risk on the willingness of Medicare beneficiaries to hold risky assets. Using a discrete factor maximum likelihood method to address the endogeneity of insurance Choices, we find that having a moderately protective Medigap or employer supplemental policy increases risky asset holding by 7.1 percentage points relative to those without supplemental coverage, while participation in a highly protective Medicare HMO increases risky asset holding by 13.0 percentage points. Our results highlight an important link between the availability of health insurance and financial behavior.
-
medical expenditure risk and household Portfolio Choice
Social Science Research Network, 2007Co-Authors: Dana P Goldman, Nicole MaestasAbstract:As health care costs continue to rise, medical expenses have become an increasingly important contributor to financial risk. Economic theory suggests that when background risk rises, individuals will reduce their exposure to other risks. This paper presents a test of this theory by examining the effect of medical expenditure risk on the willingness of elderly Medicare beneficiaries to hold risky assets. The authors measure exposure to medical expenditure risk by whether an individual is covered by supplemental insurance through Medigap, an employer, or a Medicare HMO. They account for the endogeneity of insurance Choice by using county variation in Medigap prices and non-Medicare HMO market penetration. They find that having Medigap or an employer policy increases risky asset holding by 6 percentage points relative to those enrolled in only Medicare Parts A and B. HMO participation increases risky asset holding by 12 percentage points. Their results point to an important link between the availability and pricing of health insurance and the financial behavior of the elderly.
