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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

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

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

Predicting the global minimum variance portfolio

Reh, Laura; Krüger, Fabian; Liesenfeld, Roman - 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/10012243462

Momentum Without Crashes

Chitsiripanich, Soros; Paolella, Marc S.; Polak, Pawel; … - 2022

We construct a momentum factor that identifies cross-sectional winners and losers based on a weighting scheme that incorporates all the price data, over the entire lookback period, as opposed to only the first and last price points of the window. The weighting scheme is derived from the...

Persistent link: https://www.econbiz.de/10014236192

Optimality and diversifiability of mean variance and arbitrage pricing portfolios

Pesaran, M. Hashem; Zaffaroni, Paolo - 2009

This paper investigates the limit properties of mean-variance (mv) and arbitrage pricing (ap) trading strategies using a general dynamic factor model, as the number of assets diverge to infinity. It extends the results obtained in the literature for the exact pricing case to two other cases of...

Persistent link: https://www.econbiz.de/10003910456

Testing directional forecast value in the presence of serial correlation

Blaskowitz, Oliver; 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/10003796145

Predictability of bull and bear markets : a new look at forecasting stock market regimes (and returns) in the US

Haase, Felix; Neuenkirch, Matthias - 2021

The empirical literature of stock market predictability mainly suffers from model uncertainty and parameter instability. To meet this challenge, we propose a novel approach that combines the documented merits of diffusion indices, regime-switching models, and forecast combination to predict the...

Persistent link: https://www.econbiz.de/10012416151

Forecasting GDP at the regional level with many predictors

Lehmann, Robert; Wohlrabe, Klaus - 2013

In this paper, we assess the accuracy of macroeconomic forecasts at the regional level using a large data set at quarterly frequency. We forecast gross domestic product (GDP) for two German states (Free State of Saxony and Baden- Württemberg) and Eastern Germany. We overcome the problem of a...

Persistent link: https://www.econbiz.de/10010350218

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