Block bootstrap methods and the choice of stocks for the long run

DOI10.1080/14697688.2012.713115zbMath1281.91141OpenAlexW3124833267MaRDI QIDQ5397473

Valeri I. Zakamouline, Philippe Cogneau

Publication date: 20 February 2014

Published in: Quantitative Finance (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/14697688.2012.713115

zbMATH Keywords

bootstrapparameter estimationblock bootstrapserial dependencetime series datalong-run

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Bootstrap, jackknife and other resampling methods (62F40) Economic time series analysis (91B84) Portfolio theory (91G10)

Related Items (6)

A data-driven neural network approach to optimal asset allocation for target based defined contribution pension plans ⋮ Beating a Benchmark: Dynamic Programming May Not Be the Right Numerical Approach ⋮ Optimal Asset Allocation for Retirement Saving: Deterministic Vs. Time Consistent Adaptive Strategies ⋮ ROBUST ASSET ALLOCATION FOR LONG-TERM TARGET-BASED INVESTING ⋮ The surprising robustness of dynamic mean-variance portfolio optimization to model misspecification errors ⋮ Management of Portfolio Depletion Risk through Optimal Life Cycle Asset Allocation

Cites Work

• Unnamed Item
• Resampling a coverage pattern
• The use of subseries values for estimating the variance of a general statistic from a stationary sequence
• Bootstrap methods: another look at the jackknife
• Matched-block bootstrap for dependent data
• The jackknife and the bootstrap for general stationary observations
• On blocking rules for the bootstrap with dependent data
• Are Output Fluctuations Transitory?
• BIAS IN THE ESTIMATION OF AUTOCORRELATIONS

This page was built for publication: Block bootstrap methods and the choice of stocks for the long run