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A multivariate Kernel approach to forecasting the variance covariance of stock market returns

Becker, Ralf; Clements, Adam; O'Neill, Robert - In: Econometrics : open access journal 6 (2018) 1, pp. 1-27

This paper introduces a multivariate kernel based forecasting tool for the prediction of variance-covariance matrices of stock returns. The method introduced allows for the incorporation of macroeconomic variables into the forecasting process of the matrix without resorting to a decomposition of...

Persistent link: https://www.econbiz.de/10011823257

Evaluation of forecasting methods from selected stock market returns

Mallikarjuna, M.; Rao, R. Prabhakara - In: Financial innovation : FIN 5 (2019) 40, pp. 1-16

Forecasting stock market returns is one of the most effective tools for risk management and portfolio diversification. There are several forecasting techniques in the literature for obtaining accurate forecasts for investment decision making. Numerous empirical studies have employed such methods...

Persistent link: https://www.econbiz.de/10012268500

Reexamining Financial and Economic Predictability with New Estimators of Realized Variance and Variance Risk Premium

Casas, Isabel - 2018

This study explores the predictive power of new estimators of the equity variance risk premium and conditional variance for future excess stock market returns, economic activity, and financial instability, both during and after the last global financial crisis. These estimators are obtained from...

Persistent link: https://www.econbiz.de/10012925879

The Properties of Realized Correlation : Evidence from the French, German and Greek Equity Markets

Vortelinos, Dimitrios I. - 2015

In this paper I examine the properties of four realized correlation estimators and model their jumps. The correlations …-of-the-art realized correlation estimators which I then use to testing for normality, long-memory, asymmetries and jumps and also to … modeling for jumps. Jumps are detected when the realized correlation is higher than 0.99 and lower than 0.01 in absolute values …

Persistent link: https://www.econbiz.de/10013029288

Beta-Adjusted Covariance Estimation

Boudt, Kris; Dragun, Kirill; Sauri, Orimar; Vanduffel, … - 2021

The increase in trading frequency of Exchanged Traded Funds (ETFs) presents a positive externality for financial risk management when the price of the ETF is available at a higher frequency than the price of the component stocks. The positive spillover consists in improving the accuracy of...

Persistent link: https://www.econbiz.de/10013235022

A penalized two-pass regression to predict stock returns with time-varying risk premia

Bakalli, Gaetan; Guerrier, Stéphane; Scaillet, Olivier - 2021

We develop a penalized two-pass regression with time-varying factor loadings. The penalization in the first pass enforces sparsity for the time-variation drivers while also maintaining compatibility with the no arbitrage restrictions by regularizing appropriate groups of coefficients. The second...

Persistent link: https://www.econbiz.de/10012487589

Estimation and forecasting of large realized covariance matrices and portfolio choice

Callot, Laurent; Kock, Anders Bredahl; Medeiros, Marcelo C. - 2014

In this paper we consider modeling and forecasting of large realized covariance matrices by penalized vector autoregressive models. We propose using Lasso-type estimators to reduce the dimensionality to a manageable one and provide strong theoretical performance guarantees on the forecast...

Persistent link: https://www.econbiz.de/10010433899

Forecasting crude oil and refined products volatilities and correlations : new evidence from fractionally integrated multivariate GARCH models

Marchese, Malvina; Kyriakou, Ioannis; Tamvakis, Michael; … - In: Energy economics 88 (2020), pp. 1-13

Persistent link: https://www.econbiz.de/10012516745

Determinism and non-linear behaviour of log-return and conditional volatility : empirical analysis for 26 stock markets

Dhifaoui, Zouhaier - In: South Asian journal of macroeconomics and public finance 11 (2022) 1, pp. 69-94

Persistent link: https://www.econbiz.de/10013256597

Predicting the Global Minimum Variance Portfolio

Reh, Laura - 2020

We propose a novel dynamic approach to forecast the weights of the global minimum variance portfolio (GMVP). The GMVP weights are the population coefficients of a linear regression of a benchmark return on a vector of return differences. This representation enables us to derive a consistent loss...

Persistent link: https://www.econbiz.de/10012847269