Similar Search Results

Empirical Risk Minimization for Time Series : Nonparametric Performance Bounds for Prediction

Brownlees, Christian T.; Llorens-Terrazas, Jordi - 2021

Empirical risk minimization is a standard principle for choosing algorithms in learning theory. In this paper we study the properties of empirical risk minimization for time series. The analysis is carried out in a general framework that covers different types of forecasting applications...

Persistent link: https://www.econbiz.de/10013216191

Performance of Empirical Risk Minimization for Linear Regression with Dependent Data

Brownlees, Christian; Gudmundsson, Gudmundur - 2021

This paper establishes bounds on the performance of empirical risk minimization for large-dimensional linear regression. We generalize existing results by allowing the data to be dependent and heavy-tailed. The analysis covers both the cases of identically and heterogeneously distributed...

Persistent link: https://www.econbiz.de/10013231026

The Information Content of High-Frequency Data for Estimating Equity Return Models and Forecasting Risk

Dobrev, Dobrislav - 2011

frequency can be obtained almost as precisely as if volatility is observable by simply incorporating the strong information … content of realized volatility measures extracted from high-frequency data. For this purpose, we introduce asymptotically … exact volatility measurement equations in state space form and propose a Bayesian estimation approach. Our highly efficient …

Persistent link: https://www.econbiz.de/10013128339

Sparse spanning portfolios and under-diversification with second-order stochastic dominance

Arvanitis, Stelios - 2025

We develop and implement methods for determining whether relaxing sparsity constraints on portfolios improves the investment opportunity set for risk-averse investors. We formulate a new estimation procedure for sparse second-order stochastic spanning based on a greedy algorithm and Linear...

Persistent link: https://www.econbiz.de/10015194210

Fund-of-Funds Construction by Statistical Multiple Testing Methods

Wolf, Michael; Wunderli, Dan - 2009

Fund-of-funds (FoF) managers face the task of selecting a (relatively) small number of hedge funds from a large universe of candidate funds. We analyse whether such a selection can be successfully achieved by looking at the track records of the available funds alone, using advanced statistical...

Persistent link: https://www.econbiz.de/10014203754

A nonparametric eigenvalue-regularized integrated covariance matrix estimator for asset return data

Lam, Clifford; Feng, Phoenix - In: Journal of econometrics 206 (2018) 1, pp. 226-257

Persistent link: https://www.econbiz.de/10012110378

Improving Portfolio Allocation Through Covariance Matrix Filtering

Golden, Daron - 2017

The sample covariance matrix is known to contain substantial statistical noise, making it inappropriate for use in financial decision making. Leading researchers have proposed various filtering methods that attempt to reduce the level of noise in the covariance matrix estimator. In most cases,...

Persistent link: https://www.econbiz.de/10012965654

Improving Portfolios Global Performance with Robust Covariance Matrix Estimation : Application to the Maximum Variety Portfolio

Emmanuelle, Jay - 2018

This paper presents how the most recent improvements made on covariance matrix estimation and model order selection can be applied to the portfolio optimisation problem. The particular case of the Maximum Variety Portfolio is treated but the same improvements apply also in the other optimisation...

Persistent link: https://www.econbiz.de/10012918912

Robust Inference of Risks of Large Portfolios

Fan, Jianqing - 2015

We propose a bootstrap-based robust high-confidence level upper bound (Robust H-CLUB) for assessing the risks of large portfolios. The proposed approach exploits rank-based and quantile-based estimators, and can be viewed as a robust extension of the H-CLUB method (Fan et al., 2015). Such an...

Persistent link: https://www.econbiz.de/10013030688

Errors, robustness, and the fourth quadrant

Taleb, Nassim Nicholas - In: International journal of forecasting 25 (2009) 4, pp. 744-759

Persistent link: https://www.econbiz.de/10003921416