196,326 research outputs found
Opinion Dynamics and Disagreements on Financial Networks
No full textWe propose a new measure of disagreement based on connectedness, which generalizes the disagreement index introduced in Billio et al. (2018). Building on the lifting approach in Hendrickx (2014), we extend Billio et al. (2018) to signed networks, which allows us to consider more general consensus dynamics and disagreement with antagonistic behaviour. Synthetic and real-world financial networks of serial correlation are considered for illustrating the new measure and for studying opinion dynamics and convergence to consensus on prices for financial assets.We propose a new measure of disagreement based on connectedness, whichgeneralizes the disagreement index introduced in Billio et al. (2018). Building on the lifting approach in Hendrickx (2014), we extend Billio et al. (2018) to signed networks, which allows us to consider more general consensus dynamics and disagreement with antagonistic behaviour. Synthetic and real world financial networks of serial correlation are considered for illustrating the new measure and for studying opinion dynamics and convergence to consensus on prices for financial assets
A generalised Dynamic Conditional Correlation model for portfolio risk evaluation
No full textWe propose a generalization of the Dynamic Conditional Correlation multivariate GARCH model of Engle and of the Asymmetric Dynamic Conditional Correlation model of Cappiello
et al. The model we propose introduces a block structure in parameter matrices that allows for interdependence with a reduced number of parameters. Our model nests the Flexible Dynamic Conditional Correlation model of Billio
et al. and is named Quadratic Flexible Dynamic Conditional Correlation Multivariate GARCH. In the paper, we provide conditions for positive definiteness of the conditional correlations. We also present an empirical application to the Italian stock market comparing alternative correlation models for portfolio risk evaluation
Market Linkages, Variance Spillover and Correlation Stability: Empirical Evidences of Financial Contagion
No full textTo model the contemporaneous relationships among Asian and American stock markets, a simultaneous equation system with GARCH errors is introduced. In the estimated residuals,
the correlation matrix is analyzed over rolling windows and using a correlation matrix distance, which allows a graphical analysis and the development of a statistical test of correlation movements. Furthermore, a methodology that can be used to identify turmoil
periods on a data-driven basis is presented. The previous results are applied in the analysis of the contagion issue between Asian and American stock markets. The results show some evidence of contagion, and the proposed statistics identify, on a data-driven basis, turmoil periods consistent with the ones currently assumed in the literature
Stochastic Optimisation for Allocation Problem with Shortfall Risk Constraints
No full textOne of the crucial aspects in asset allocation problems is the assumption concerning the probability distribution of asset returns. Financial managers generally suppose normal distribution, even if extreme realizations usually have an higher frequency than in the Gaussian case. The aim of this paper is to propose a general Monte Carlo simulation approach able to solve an asset allocation problem with shortfall constraint, and to evaluate the exact portfolio risk-level when managers assume a misspecified return behaviour. We assume that returns are generated by a multivariate skewed Student-t distribution where each marginal
can have different degrees of freedom. The stochastic optimization allows us to value the effective risk for managers. In the empirical application we consider a symmetric and heterogeneous case, and interestingly note that a multivariate Student-t with heterogeneous marginal distributions produces in the optimization problem a shortfall probability and a shortfall return level that can be adequately approximated by assuming a multivariate Student-t with common degrees of freedom. Thus, the proposed simulation-based approach could be an important instrument for investors who require a qualitative assessment of the reliability
and sensitivity of their investment strategies in the case their models could be potentially misspecified
Flexible Dynamic Conditional Correlation Multivariate GARCH models for Asset Allocation
No full textThis paper introduces the Flexible Dynamic Conditional Correlation
(FDCC) multivariate GARCH model which generalizes the Dynamic
Conditional Correlation (DCC) multivariate GARCH model proposed by Engle (2002). The FDCC model relax the assumption of common dynamics among all assets used in the DCC model. In fact, we cannot impose that the correlation dynamics of, say, European sectorial stock indexes are identical to the corresponding US ones. We thus extend the DCC model introducing a block-diagonal structure; in the FDCC the
dynamics are constrained to be equal among groups of variables.
We present an application to a sectorial asset allocation problem
Bayesian Combinations of Stock Price Predictions with an Application to the Amsterdam Exchange Index
No full textThis paper deals with the problem of combining predictive densities for financial series. We summarize the general combination approach based on a Bayesian state space representation of the predictive densities and of the combination scheme which allows for incomplete model space proposed
by Billio et al. [2010]. In the combination model the weights follow logistic autoregressive processes, change over
time and their dynamics are possible driven by the past forecasting performances of the predictive densities. For
illustrative purposes we apply it to combine White Noise and GARCH models to forecast the Amsterdam Exchange index and use the combined predictive forecasts in an investment
asset allocation exercise
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