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Olivier Ledoit

Bio: Olivier Ledoit is an academic researcher from University of Zurich. The author has contributed to research in topics: Covariance matrix & Covariance. The author has an hindex of 33, co-authored 80 publications receiving 9301 citations. Previous affiliations of Olivier Ledoit include Credit Suisse & Saint Petersburg State University.


Papers
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Journal ArticleDOI
TL;DR: This paper introduces an estimator that is both well-conditioned and more accurate than the sample covariance matrix asymptotically, that is distribution-free and has a simple explicit formula that is easy to compute and interpret.

2,497 citations

Journal ArticleDOI
TL;DR: In this paper, the covariance matrix of stock returns is estimated by an optimally weighted average of two existing estimators: the sample covariance and single-index covariance matrices.

1,609 citations

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TL;DR: Shrinkage as mentioned in this paper is a matrix obtained from the sample covariance matrix through a transformation called shrinkage, which pulls the most extreme coefficients toward more central values, systematically reducing estimation error when it matters most.
Abstract: The central message of this article is that no one should use the sample covariance matrix for portfolio optimization. It is subject to estimation error of the kind most likely to perturb a mean-variance optimizer. Instead, a matrix can be obtained from the sample covariance matrix through a transformation called shrinkage. This tends to pull the most extreme coefficients toward more central values, systematically reducing estimation error when it matters most. Statistically, the challenge is to know the optimal shrinkage intensity. Shrinkage reduces portfolio tracking error relative to a benchmark index, and substantially raises the manager9s realized information ratio.

769 citations

Journal ArticleDOI
TL;DR: In this article, the authors propose to construct a studentized time series bootstrap confidence interval for the difference of the Sharpe ratios and declare the two ratios different if zero is not contained in the obtained interval.

584 citations

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TL;DR: In this article, the authors develop an approach to asset pricing in incomplete markets that bridges the gap between the two fundamental approaches in finance: model-based pricing and pricing by no arbitrage.
Abstract: We develop an approach to asset pricing in incomplete markets that bridges the gap between the two fundamental approaches in finance: model‐based pricing and pricing by no arbitrage. We strengthen the absence of arbtrage assumption by precluding investment opportunities whose attractiveness to a benchmark investor exceeds a specified threshold. In our framework, the attractiveness of an investment opportunity is measured by the gain‐loss ratio. We show that a restriction on the maximum gain‐loss ratio is equivalent to a restriction on the ratio of the maximum to minimum values of the pricing kernel. By limiting the maximum gainloss ratio, we can restrict the admissible set of pricing kernels, which in turn allows us to restrict the set of prices that can be assigned to assets. We illustrate our methodology by computing price bounds for call options in a Black‐Scholes economy without intermediate trading. When we vary the maximum permitted gainloss ratio, these bounds can range from the exact prices implie...

461 citations


Cited by
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Journal ArticleDOI
01 Apr 1988-Nature
TL;DR: In this paper, a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) is presented.
Abstract: Deposits of clastic carbonate-dominated (calciclastic) sedimentary slope systems in the rock record have been identified mostly as linearly-consistent carbonate apron deposits, even though most ancient clastic carbonate slope deposits fit the submarine fan systems better. Calciclastic submarine fans are consequently rarely described and are poorly understood. Subsequently, very little is known especially in mud-dominated calciclastic submarine fan systems. Presented in this study are a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) that reveals a >250 m thick calciturbidite complex deposited in a calciclastic submarine fan setting. Seven facies are recognised from core and thin section characterisation and are grouped into three carbonate turbidite sequences. They include: 1) Calciturbidites, comprising mostly of highto low-density, wavy-laminated bioclast-rich facies; 2) low-density densite mudstones which are characterised by planar laminated and unlaminated muddominated facies; and 3) Calcidebrites which are muddy or hyper-concentrated debrisflow deposits occurring as poorly-sorted, chaotic, mud-supported floatstones. These

9,929 citations

Journal ArticleDOI
TL;DR: In this article, the authors evaluate the out-of-sample performance of the sample-based mean-variance model, and its extensions designed to reduce estimation error, relative to the naive 1-N portfolio.
Abstract: We evaluate the out-of-sample performance of the sample-based mean-variance model, and its extensions designed to reduce estimation error, relative to the naive 1-N portfolio. Of the 14 models we evaluate across seven empirical datasets, none is consistently better than the 1-N rule in terms of Sharpe ratio, certainty-equivalent return, or turnover, which indicates that, out of sample, the gain from optimal diversification is more than offset by estimation error. Based on parameters calibrated to the US equity market, our analytical results and simulations show that the estimation window needed for the sample-based mean-variance strategy and its extensions to outperform the 1-N benchmark is around 3000 months for a portfolio with 25 assets and about 6000 months for a portfolio with 50 assets. This suggests that there are still many "miles to go" before the gains promised by optimal portfolio choice can actually be realized out of sample. The Author 2007. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org, Oxford University Press.

2,809 citations

Journal ArticleDOI
TL;DR: This paper introduces an estimator that is both well-conditioned and more accurate than the sample covariance matrix asymptotically, that is distribution-free and has a simple explicit formula that is easy to compute and interpret.

2,497 citations

Journal ArticleDOI
TL;DR: In this article, the authors examined daily equity return volatilities and correlations obtained from high-frequency intraday transaction prices on individual stocks in the Dow Jones Industrial Average and found that the unconditional distributions of realized variances and covariances are highly right-skewed.

2,269 citations

Journal ArticleDOI
TL;DR: The development of high-resolution neuroimaging and multielectrode electrophysiological recording provides neuroscientists with huge amounts of multivariate data, but the local averaging standardly applied to this end may obscure the effects of greatest neuroscientific interest.
Abstract: The development of high-resolution neuroimaging and multielectrode electrophysiological recording provides neuroscientists with huge amounts of multivariate data. The complexity of the data creates a need for statistical summary, but the local averaging standardly applied to this end may obscure the effects of greatest neuroscientific interest. In neuroimaging, for example, brain mapping analysis has focused on the discovery of activation, i.e., of extended brain regions whose average activity changes across experimental conditions. Here we propose to ask a more general question of the data: Where in the brain does the activity pattern contain information about the experimental condition? To address this question, we propose scanning the imaged volume with a "searchlight," whose contents are analyzed multivariately at each location in the brain.

2,082 citations