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on Risk Management |
| By: | Mawuli Segnon; Mark Trede |
| Abstract: | This paper proposes a new methodology for modeling and forecasting market risks of portfolios. It is based on a combination of copula functions and Markov switching multifractal (MSM) processes. We assess the performance of the copula-MSM model by computing the value at risk of a portfolio composed of the NASDAQ composite index and the S&P 500. Using the likelihood ratio (LR) test by Christofferrsen (1998), the GMM duration-based test by Candelon et al. (2011) and the superior predictive ability (SPA) test by Hansen (2005) we evaluate the predictive ability of the copula-MSM model and compare it to other common approaches such as historical simulation, variance-covariance, Risk-Metrics, copula-GARCH and constant conditional correlation GARCH (CCCGARCH) models. We find that the copula-MSM model is more robust, provides the best fit and outperforms the other models in terms of forecasting accuracy and VaR prediction. |
| Keywords: | Copula, Multifractal processes, GARCH, VaR, Backtesting, SPA |
| JEL: | G17 C02 |
| Date: | 2017–09 |
| URL: | http://d.repec.org/n?u=RePEc:cqe:wpaper:6617&r=rmg |
| By: | Javier G. Gómez-Pineda (Banco de la República de Colombia) |
| Abstract: | The paper presents some evidence on the overwhelming relevance of systemic risk and the lesser importance of US interest rates in the global transmission of shocks. This evidence suggests that the literature could benefit from incorporating global confidence variables into global frameworks in the study of the global transmission of shocks. As framework, we used a global semi-structural model (GSSM) augmented with common factors for country risk and country credit. We approximated country risk with historical stock volatility, a measure that is uniform and available across countries; in addition, we measured spillovers as the share of forecast error variance explained by different volatility factors. We found that systemic risk is the main volatility factor in all systemic economies, and also accounts for the bulk of spillovers into non systemic economies. Other volatility factors such as global credit, foreign interest rates and trade-related factors rarely accounted for shares of forecast error variance above one percent. Classification JEL: E58; E37; E43; Q43 |
| Keywords: | Spillovers; Systemic risk; Systemic Economies; Global semi structural model |
| Date: | 2017–09 |
| URL: | http://d.repec.org/n?u=RePEc:bdr:borrec:1011&r=rmg |
| By: | Michael Grill (European Central Bank); Karl Schmedders (University of Zurich); Felix Kubler (University of Zurich); Johannes Brumm (University of Zurich) |
| Abstract: | We assess the quantitative implications of the re-use of collateral on financial market leverage, volatility, and welfare within an infinite-horizon asset-pricing model with heterogeneous agents. In our model, the ability of agents to re-use frees up collateral that can be used to back more transactions. Re-use thus contributes to the build-up of leverage and significantly increases volatility in financial markets. When introducing limits on re-use, we find that volatility is strictly decreasing as these limits become tighter, yet the impact on welfare is non-monotone. In the model, allowing for some re-use can improve welfare as it enables agents to share risk more effectively. Allowing re-use beyond intermediate levels, however, can lead to excessive leverage and lower welfare. So the analysis in this paper provides a rationale for limiting, yet not banning, re-use in financial markets. |
| Date: | 2017 |
| URL: | http://d.repec.org/n?u=RePEc:red:sed017:697&r=rmg |