In this paper, we extend the concept of the news impact curve of volatility developed by Engle and Ng (1993) to the higher moments and co-moments of the multivariate generalized autoregressive conditional heteroskedasticity (GARCH) model with non-normal innovations. For this purpose, we present...

We evaluate how departure from normality may affect the allocation of assets. A Taylor series expansion of the expected utility allows to focus on certain moments and to compute numerically the optimal portfolio allocation. A decisive advantage of this approach is that it remains operational...

We evaluate how departure from normality may affect the conditional allocation of wealth. The expected utility function is approximated by a fourth-order Taylor expansion that allows for non-normal returns. Market returns are characterized by a joint model that captures the time dependency and...

We evaluate how deviations from normality may affect the allocation of assets. A Taylor expansion of expected utility allows us to focus on certain moments and to compute numerically the optimal portfolio allocation. A decisive advantage of our approach is that it remains operational even if a...

We develop a new methodology to measure conditional dependency between time series each driven by complicated marginal distributions. We achieve this by using copula functions that link marginal distributions, and by expressing the parameter of the copula as a function of predetermined...

Designing an investment strategy in transition economies is a difficult task because stock-markets opened through time, time series are short, and there is little guidance how to obtain expected returns and covariance matrices necessary for mean-variance portfolio allocation. Also, structural...

We develop a new methodology that measures conditional dependency. We achieve this by using copula functions that link marginal distributions, here chosen to obey a GARCH-type model with time-varying skewness and kurtosis. We apply this model to daily returns of stock-market indices. We find...

Recent portfolio choice, asset pricing, and option valuation models highlight the importance of skewness and kurtosis. Since skewness and kurtosis are related to extreme variations, they are also important for Value-at-Risk measurements. Our framework builds on a GARCH model with a conditional...

Using a sample of 188 European listed banks covering 2004 to 2016, we conduct textual analysis on banks' Pillar 3 reports and annual reports to showcase how banks formulate their regulatory reports. We first develop dictionaries relying on machine learning tools and its subfield of textual...

It is well known that non-normality plays an important role in asset and risk management. However, handling a large number of assets has long been a challenge due to the curse of dimensionality. We describe a statistical technique, which we call Moment Component Analysis (MCA), that extends...