107 research outputs found
Why common factors in international bond returns are not so common
No full textThis paper analyzes the common factor structure of US, German, and Japanese Government bond returns. Unlike previous studies, we formally take into account the presence of country-specific factors when estimating common factors. We show that the classical approach of running a principal component analysis on a multi-country dataset of bond returns captures both local and common influences and therefore tends to pick too many factors. We conclude that US bond returns share only one common factor with German and Japanese bond returns. This single common factor is associated most notably with changes in the level of domestic term structures. We show that accounting for country-specific factors improves the performance of domestic and international hedging strategies
Opening October DataFest “Love your data, share your data”
No full textThe DataFest opening ceremony will start with welcoming remarks by Prof. dr. Pursey Heugens (ERIM Scientific Director) followed by the keynote speaker Prof. dr. Christophe Pérignon (HEC, Paris) who will talk to us about Cascad, the first certification agency for scientific code & data
The level and quality of Value-at-Risk disclosure by commercial banks
No full textInternational audienceIn this paper we study both the level of Value-at-Risk (VaR) disclosure and the accuracy of the disclosed VaR figures for a sample of US and international commercial banks. To measure the level of VaR disclosures, we develop a VaR Disclosure Index that captures many different facets of market risk disclosure. Using panel data over the period 1996-2005, we find an overall upward trend in the quantity of information released to the public. We also find that Historical Simulation is by far the most popular VaR method. We assess the accuracy of VaR figures by studying the number of VaR exceedances and whether actual daily VaRs contain information about the volatility of subsequent trading revenues. Unlike the level of VaR disclosure, the quality of VaR disclosure shows no sign of improvement over time. We find that VaR computed using Historical Simulation contains very little information about future volatility
Diversification and Value-at-Risk
No full textInternational audienceA pervasive and puzzling feature of banks' Value-at-Risk (VaR) is its abnormally high level, which leads to excessive regulatory capital. A possible explanation for the tendency of commercial banks to overstate their VaR is that they incompletely account for the diversification effect among broad risk categories (e.g., equity, interest rate, commodity, credit spread, and foreign exchange). By underestimating the diversification effect, bank's proprietary VaR models produce overly prudent market risk assessments. In this paper, we examine empirically the validity of this hypothesis using actual VaR data from major US commercial banks. In contrast to the VaR diversification hypothesis, we find that US banks show no sign of systematic underestimation of the diversification effect. In particular, diversification effects used by banks is very close to (and quite often larger than) our empirical diversification estimates. A direct implication of this finding is that individual VaRs for each broad risk category, just like aggregate VaRs, are biased risk assessments
Opening October DataFest “Love your data, share your data”
No full textThe DataFest opening ceremony will start with welcoming remarks by Prof. dr. Pursey Heugens (ERIM Scientific Director) followed by the keynote speaker Prof. dr. Christophe Pérignon (HEC, Paris) who will talk to us about Cascad, the first certification agency for scientific code & data
Clearing house, margin requirements, and systemic risk
No full textMargins are the major safeguards against default risk on a derivatives exchange. When the
clearing house sets the margin requirement for a particular clearing firm, it does so by only
focusing on that particular clearing firm’s positions (e.g. the SPAN system). We depart
from this traditional approach and show how to account for interdepencies across clearing
members when setting margins. Our method generalizes the SPAN system by allowing
individual margins to increase when clearing firms are more likely to be in financial
distress simultaneously
Evolution of Market Uncertainty Around Earnings Announcements
No full textThis paper investigates, theoretically and empirically, the dynamic of the implied volatility (ISD) around earnings announcements dates. The volatility implied in option prices can be interpreted as the market's expected level of volatility over the remaining life of the option. In this framework the paper proposes a theoretical model of the evolution of the ISD that takes into accound two well-known features of the instantaneous volatility: volatility clustering and the leverage effect. The model indicates that the ISD should decrease after an earnings announcement except after a bad news where it should be stable or even increase. An empirical investigation is conducted on the Swiss market over the period 1989-1998.The results confirm the main implications of the theoretical model
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