Using a modified DCC-MIDAS specification that allows the long-term correlation component to be a function of multiple explanatory variables, we show that the stock-bond correlation in the US, the UK, Germany, France, and Italy is mainly driven by inflation and interest rate expectations as well...

In this paper we investigate exponential smoothing (ES) predictors for the weights of high-dimensional realized global minimum variance portfolios (GMVP) which only depend on the realized covariance matrix of risky financial assets. We compare direct ES predictions of realized GMVP proportions...

In this paper, we build efficient portfolios using different frameworks proposed in the literature with several datasets containing an increasing number of predictors as conditioning information. We carry an extensive empirical study to investigate several approaches to impose sparsity and...

Using a modified DCC-MIDAS specification that allows the long-term correlation component to be a function of multiple explanatory variables, we show that the stock-bond correlation in the US, the UK, Germany, France, and Italy is mainly driven by inflation and interest rate expectations as well...

Employing both the mean-variance framework and the common portfolio risk-optimization, this study adds to the investment research by examining how ideal holdings for emerging and frontier markets (EFM) of the four global regions (Asian, Europe, and Commonwealth of Independent States (Eastern +...

The paper examines the performance of four multivariate volatility models, namely CCC, VARMA-GARCH, DCC and BEKK, for the crude oil spot and futures returns of two major benchmark international crude oil markets, Brent and WTI, to calculate optimal portfolio weights and optimal hedge ratios, and...

We propose direct multiple time series models for predicting high dimensional vectors of observable realized global minimum variance portfolio (GMVP) weights computed based on high-frequency intraday returns. We apply Lasso regression techniques, develop a class of multiple AR(FI)MA models for...

When principal component analysis (PCA) is used on a rolling or conditional setting, ordering and incoherence issues may emerge. We provide empirical evidence supporting this claim and introduce an algorithm that allows dynamic re-ordering of the principal components (PCs). We provide additional...

We use S&P 500 index return data for the time period 1985-2012 to evaluate the performance of portfolio insurance strategies. We shed light on the question if the performance of a constant proportion portfolio insurance (CPPI) strategy can be improved by means of a time-varying multiplier which...

We discuss the problems of strategy selection in the framework of mathematical finance, stochastic control, and risk management in finance and economics. A problem setting that takes in to account a possibility of short term forecasting for market parameters is suggested. In this setting,...