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A Machine Learning Approach to Estimating Large Positive Definite Covariance Matrix of High Frequency Data

Cui, Liyuan - 2019

This paper proposes a novel covariance estimator via a machine learning approach when both the sampling frequency and covariance dimension are large. Assuming that a large covariance matrix can be decomposed into low rank and sparse components, our method simultaneously provides a consistent...

Persistent link: https://www.econbiz.de/10012867396

Covariance Prediction in Large Portfolio Allocation : Supplementary Material

Trucíos, Carlos - 2019

In this supplementary material we discuss the results corresponding to the case without short-selling constraints of the empirical application in the paper of Trucíos et al. (2019). These results are given in Tables 9-16

Persistent link: https://www.econbiz.de/10012869690

Fractional Integration and Fat Tails for Realized Covariance Kernels and Returns

Lucas, Andre - 2017

We introduce a new fractionally integrated model for covariance matrix dynamics based on the long-memory behavior of daily realized covariance matrix kernels and daily return observations. We account for fat tails in both types of data by appropriate distributional assumptions. The covariance...

Persistent link: https://www.econbiz.de/10012968271

Large Dynamic Covariance Matrices

Engle, Robert F. - 2017

for conditional heteroskedasticity; a favored model is Dynamic Conditional Correlation (DCC), derived from the ARCH …

Persistent link: https://www.econbiz.de/10012968636

Nonlinear Shrinkage of the Covariance Matrix for Portfolio Selection : Markowitz Meets Goldilocks

Ledoit, Olivier - 2017

Markowitz (1952) portfolio selection requires an estimator of the covariance matrix of returns. To address this problem, we promote a nonlinear shrinkage estimator that is more flexible than previous linear shrinkage estimators and has just the right number of free parameters (that is, the...

Persistent link: https://www.econbiz.de/10012973579

Correlation Dynamics in the G7 Stock Markets

Suurlaht, Anita - 2016

The present study explores the trend of the correlation level within the synchronised returns on the G7 equity market … positive trend toward higher correlation level and significant time-series autocorrelation in the magnitude of cross …-market return correlation. Correlation level is higher when financial markets experience turbulent periods. The sample period is …

Persistent link: https://www.econbiz.de/10012979790

Financialisation of the Commodity Markets. Conclusions from the VARX DCC GARCH

Szafranek, Karol - 2016

's to a much stronger correlation between the financial and commodity markets, sparking a heated debate on the commodity … impact of speculative aspects alters the dynamic conditional correlation path between commodities and the financial markets …

Persistent link: https://www.econbiz.de/10013003293

Correlation and Lead-Lag Relationships in a Hawkes Microstructure Model

Da Fonseca, José - 2016

at high frequency and to study the lead-lag relationship as well as the correlation between the stocks within this …

Persistent link: https://www.econbiz.de/10013005817

Value, Size, Momentum and the Average Correlation of Stock Returns

Becker, Christoph - 2015

average returns of value, size and momentum portfolios. While the influence of market volatility on average correlation is … predictors of average correlation, we obtain a global minimum variance portfolio with a Sharpe ratio that is 1.5% higher relative …

Persistent link: https://www.econbiz.de/10013011599

A DCC-Type Approach for Realized Covariance Modelling With Score-Driven Dynamics

Vassallo, Danilo - 2020

We propose a class of score-driven realized covariance models where volatilities and correlations are separately estimated. We can thus combine univariate realized volatility models with a recently introduced class of score-driven realized covariance models based on Wishart and matrix-F...

Persistent link: https://www.econbiz.de/10012850563