This paper proposes a novel approach to the combination of conditional covariancematrix forecasts based on the use of the Generalized Method of Moments (GMM). Itis shown how the procedure can be generalized to deal with large dimensional systemsby means of a two-step strategy. The finite sample...

This paper proposes a novel approach to the combination of conditional covariance matrix forecasts based on the use of 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...

Literature and textbooks on capital budgeting endorse net present value (NPV) and generally treat accounting rates of return as not being reliable tools. This paper shows that accounting numbers can be reconciled with NPV and fruitfully employed in real-life applications. Focusing on project...

This paper proposes a latent dynamic factor model for low- as well as high-dimensional realized covariance matrices of stock returns. The approach is based on the matrix logarithm and allows for flexible dynamic dependence patterns by combining common latent factors driven by HAR dynamics and...

Similar to the cross-sectional momentum crashes, the time series momentum experiences deep and persistent drawdowns in the stressed time of slumps in the upward momentum, rebounds in the downward momentum, and long time sideways market. We measure the upside and downside risk using the upper and...

This paper examines momentum and contrarian effects in the Ukrainian stock market after one-day abnormal returns. To do this, UX futures data over the period 2010–2018 are used. The following hypotheses are tested: H1) hourly returns on overreaction days differ from hourly returns on normal...

The paper provides an introductory guide for active managers that illustrates econometric techniques for alpha generation in active asset management. For modelling stock market returns three different model types are discussed: (i) fair value models that identify over- and undervaluations, (ii)...

The objective this work is to calculate the VaR of portfolios via GARCH family models with normal and t-student distribution and via Monte Carlo Simulation. We used three portfolios composite with preferential stocks of five Ibovespa companies. The results show that the t distribution adjusts...

Risk estimation or volatility estimation at financial markets, particularly stock exchange markets, is complex issue of great importance to theorists and practitioners. Models used to estimate volatility forecasts are translated into better pricing of stocks and better risk management. The aim...

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...