Search Results - subject:"Robust Optimization"

Global Robust Bayesian Analysis in Large Models

Ho, Paul - 2020

This paper develops a tool for global prior sensitivity analysis in large Bayesian models. Without imposing parametric restrictions, the methodology provides bounds for posterior means or quantiles given any prior close to the original in relative entropy, and reveals features of the prior that...

Persistent link: https://www.econbiz.de/10014048810

Robust Estimation of a Location Parameter with the Integrated Hogg Function

Catania, Leopoldo; Luati, Alessandra - 2020

We study the properties of an M-estimator arising from the minimisation of an integrated version of the quantile loss function. The estimator depends on a tuning parameter which controls the degree of robustness. We show that the sample median and the sample mean are obtained as limit cases....

Persistent link: https://www.econbiz.de/10014102661

Robust Multi-Product Newsvendor Model With Substitution Under Cardinality-Constrained Uncertainty Set

Zhang, Jie; Xie, Weijun; Sarin, Subhash - 2020

This work studies a Robust Multi-product Newsvendor Model with Substitution (R-MNMS), where the demand and the substitution rates are stochastic and are subject to cardinality-constrained uncertainty sets. The goal of this work is to determine the optimal order quantities of multiple products to...

Persistent link: https://www.econbiz.de/10014110418

Characterizing Robust Solutions to Monotone Games

Barthel, Anne-Christine; Hoffmann, Eric; Sabarwal, Tarun - 2020

In game theory, p-dominance and p-best response sets serve as important robustness solution concepts by allowing for deviations from the stringent common knowledge requirements of Nash equilibrium. However, solving for such sets remains largely intractable beyond the simplest of settings. The...

Persistent link: https://www.econbiz.de/10014031702

An Extended McKean — Vlasov Dynamic Programming Approach to Robust Equilibrium Controls under Ambiguous Covariance Matrix

Lei, Qian; Pun, Chi Seng - 2020

This paper studies a general class of time-inconsistent stochastic control problems under ambiguous covariance matrix. The time-inconsistency is caused in various ways by a general objective functional and thus the associated control problem does not admit Bellman's principle of optimality....

Persistent link: https://www.econbiz.de/10014032214

Data-Driven Distributionally Robust Chance-Constrained Optimization With Wasserstein Metric

Ji, Ran; Lejeune, Miguel - 2020

-driven Wasserstein ambiguity sets. The proposed algorithmic and reformulation framework applies to distributionally robust optimization …

Persistent link: https://www.econbiz.de/10014033590

Robust and Optimal Estimation for Partially Linear Instrumental Variables Models with Partial Identification

Chen, Qihui - 2020

This paper studies robust and optimal estimation of the slope coefficients in a partially linear instrumental variables model with nonparametric partial identification. We establish the root-n asymptotic normality of a penalized sieve minimum distance estimator of the slope coefficients. We show...

Persistent link: https://www.econbiz.de/10012855597

Price Discounts and Personalized Product Assortment under Multinomial Logit Choice Model : A Robust Approach

Jin, Qingwei - 2020

With increasing availability of consumer data and rapid advancement and applications of technologies, online retailers are gaining better knowledge of shopping behavior and preferences of their customers. Thus more and more retailers are providing customized product assortment to better match...

Persistent link: https://www.econbiz.de/10012842523

A Practical Guide to Robust Portfolio Optimization

Yin, Chenyang - 2020

Robust optimization considers uncertainty in inputs to address the shortcomings of mean-variance optimization. We … investigate the mechanisms by which robust optimization achieves its goal and give practical guidance regarding its … with the proposed parametrization to show that robust optimization efficiently overcomes the weaknesses of mean …

Persistent link: https://www.econbiz.de/10012846631

A Robust Estimator of the Efficient Frontier

Lopez de Prado, Marcos - 2020

Convex optimization solutions tend to be unstable, to the point of entirely offsetting the benefits of optimization. For example, in the context of financial applications, it is known that portfolios optimized in-sample often underperform the naïve (equal weights) allocation out-of-sample. This...

Persistent link: https://www.econbiz.de/10012847307