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Do high-frequency data improve high-dimensional portfolio allocations?

Hautsch, Nikolaus; Kyj, Lada. M.; Malec, Peter - 2013 - First version: September 2011, This version: February 2013

This paper addresses the open debate about the usefulness of high-frequency (HF) data in large-scale portfolio allocation. We consider the problem of constructing global minimum variance portfolios based on the constituents of the S&P 500 over a four-year period covering the 2008 financial...

Persistent link: https://www.econbiz.de/10009714536

Evaluating Covariance Forecasts Via Mean-Variance Portfolio Decisions

Franke, Markus - 2012

This paper presents an empirical comparative study of di fferent covariance estimators. The Engle-Colacito test is used for an indirect evaluation of alternative out-of-sample covariance forecasts in a portfolio setting for varying sample sizes, short selling constraints and market conditions....

Persistent link: https://www.econbiz.de/10013112266

DCC-HEAVY : a multivariate GARCH model with realized measures of variance and correlation

Xu, Yongdeng - 2019

This paper proposes a new class of multivariate volatility model that utilising high-frequency data. We call this model the DCC-HEAVY model as key ingredients are the Engle (2002) DCC model and Shephard and Sheppard (2012) HEAVY model. We discuss the models' dynamics and highlight their...

Persistent link: https://www.econbiz.de/10012009351

Package CovRegpy : Regularised Covariance Regression and Forecasting in Python

van Jaarsveldt, Cole; Peters, Gareth; Ames, Matthew; … - 2023

. These seven scripts contain the Dynamic Conditional Correlation (DCC) framework, Instantaneous Frequency Forecasting (IFF … RCR framework to forecast covariance and correlation structures and finally apply portfolio weighting strategies based on …

Persistent link: https://www.econbiz.de/10014253907

Covariance prediction in large portfolio allocation

Trucíos, Carlos; Zevallos, Mauricio; Hotta, Luiz K.; … - In: Econometrics : open access journal 7 (2019) 2/19, pp. 1-24

Many financial decisions, such as portfolio allocation, risk management, option pricing and hedge strategies, are based on forecasts of the conditional variances, covariances and correlations of financial returns. The paper shows an empirical comparison of several methods to predict...

Persistent link: https://www.econbiz.de/10012025822

Testing directional forecast value in the presence of serial correlation

Blaskowitz, Oliver; Herwartz, Helmut - 2008

asymptotically valid for serially independent observations. Yet, in the presence of serial correlation they are markedly oversized as … confirmed in a simulation study. We summarize serial correlation robust test procedures and propose a bootstrap approach. By … relevance to account for serial correlation in economic time series when testing for the value of directional forecasts …

Persistent link: https://www.econbiz.de/10003796145

Default probabilities and default correlations

Erlenmaier, Ulrich; Gersbach, Hans - 2001

Persistent link: https://www.econbiz.de/10001637575

Default probabilities and default correlations

Erlenmaier, Ulrich; Gersbach, Hans - 2001 - First Version: April 2000, This Version: October 2001

Starting from the Merton framework for firm defaults, we provide the analytics and robustness of the relationship between default correlations. We show that loans with higher default probabilities will not only have higher variances but also higher correlations between loans. As a consequence,...

Persistent link: https://www.econbiz.de/10010503718

The Variance Implied Conditional Correlation

Algaba, Andres - 2020

correlation matrix of asset returns. The proposed Variance Implied Conditional Correlation (VICC) exploits the polarization result … that links the correlation between two standardized variables with the variances of linear combinations thereof. In a Monte … Carlo study, we show that the VICC yields accurate correlation estimates for common choices of the correlation dynamics. We …

Persistent link: https://www.econbiz.de/10012852852

Disentangling the Role of Variance and Covariance Information in Portfolio Selection Problems

A. P. Santos, Andre - 2018

The covariation among financial asset returns is often a key ingredient used in the construction of optimal portfolios. Estimating covariances from data, however, is challenging due to the potential influence of estimation error involved specially in high dimensional problems, which can impact...

Persistent link: https://www.econbiz.de/10012933902