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Combination of multivariate volatility forecasts

Amendola, Alessandra; Storti, Giuseppe - 2009

the Generalized Method of Moments (GMM). It is shown how the procedure can be generalized to deal with large dimensional … systems by means of a two-step strategy. The finite sample properties of the GMM estimator of the combination weights are … combination ; GMM ; portfolio optimization …

Persistent link: https://www.econbiz.de/10003796201

A non-elliptical orthogonal GARCH model for portfolio selection under transaction costs

Paolella, Marc S.; Polak, Pawel; Walker, Patrick S. - 2019

Covariance matrix forecasts for portfolio optimization have to balance sensitivity to new data points with stability in order to avoid excessive rebalancing. To achieve this, a new robust orthogonal GARCH model for a multivariate set of non-Gaussian asset returns is proposed. The conditional...

Persistent link: https://www.econbiz.de/10012134234

Combining Multivariate Volatility Forecasts : An Economic-Based Approach

Caldeira, João F. - 2016

We devise a novel approach to combine predictions of high dimensional conditional covariance matrices using economic criteria based on portfolio selection. The combination scheme takes into account not only the portfolio objective function but also the portfolio characteristics in order to...

Persistent link: https://www.econbiz.de/10013003499

Forecasting Stock Market Volatility and Application to Volatility Timing Portfolios

Chun, Dohyun; Cho, Hoon; Ryu, Doojin - 2022

This study predicts stock market volatility and applies them to the standard problem in finance, namely, asset allocation. Based on machine learning and model averaging approaches, we integrate the drivers’ predictive information to forecast market volatilities. Using various evaluation...

Persistent link: https://www.econbiz.de/10013404229

Testing directional forecast value in the presence of serial correlation

Blaskowitz, Oliver J.; Herwartz, Helmut - 2008

Common approaches to test for the economic value of directional forecasts are based on the classical Chi-square test for independence, Fisher’s exact test or the Pesaran and Timmerman (1992) test for market timing. These tests are asymptotically valid for serially independent observations....

Persistent link: https://www.econbiz.de/10010271838

Testing directional forecast value in the presence of serial correlation

Blaskowitz, Oliver; Herwartz, Helmut - 2008

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

Forecasting Expected Shortfall : Should We Use a Multivariate Model for Stock Market Factors?

Fortin, Alain-Philippe - 2019

Is univariate or multivariate modelling more effective when forecasting the market risk of stock portfolios? We examine this question in the context of forecasting the one-week-ahead Expected Shortfall of a portfolio invested in the Fama-French and momentum factors. Apply ingextensive tests and...

Persistent link: https://www.econbiz.de/10012898954

Forecasting value-at-risk under temporal and portfolio aggregation

Kole, Erik; Markwat, Thijs; Opschoor, Anne; Dijk, Dick van - 2015

We examine the impact of temporal and portfolio aggregation on the quality of Value-at-Risk (VaR) forecasts over a horizon of ten trading days for a well-diversified portfolio of stocks, bonds and alternative investments. The VaR forecasts are constructed based on daily, weekly or biweekly...

Persistent link: https://www.econbiz.de/10011431503

Sparse Multivariate Modeling for Stock Returns Predictability

Bernardi, Mauro; Bianchi, Daniele; Bianco, Nicolas - 2021

We develop a new variational Bayes estimation method for large-dimensional sparse vector autoregressive models with exogenous predictors. Unlike existing Markov chain Monte Carlo (MCMC) and variational Bayes (VB) algorithms, our approach is not based on a structural form representation of the...

Persistent link: https://www.econbiz.de/10013239660

Exponential high-frequency-based-volatility (EHEAVY) models

Xu, Yongdeng - 2022

This paper proposes an Exponential HEAVY (EHEAVY) model. The model specifies the dynamics of returns and realized measures of volatility in an exponential form, which guarantees the positivity of volatility without restrictions on parameters and naturally allows the asymmetric effects. It...

Persistent link: https://www.econbiz.de/10013177995