The Interactions between the Credit Default Swap and the Bond Markets in Financial Turmoil

We analyse the links between credit default swap (CDS) and bond spreads in order to determine which one is the leading market in the price discovery process. To do that, we construct a sample of CDS premia and bond spreads on a generic 5‐year bond for 17 financials and 18 sovereigns. First, we run panel vector error correction model estimations, showing that the CDS market has a lead over the bond market for financial institutions. This also holds for high‐yield sovereigns, whereas the reverse is found for low‐yield sovereigns in the core of the euro area. We interpret these results according to the relative liquidity of both markets for different types of entities. Second, we check for nonlinearities in the adjustment process. Results show that the CDS market's lead is amplified when default risk increases, during crisis periods, as well as continuously when CDS premia increase.     

Retirement Incentives in Belgium: Estimations and Simulations Using SHARE Data

The paper studies retirement behavior of wage-earners in Belgium—for the first time using a rich survey dataset to analyze retirement incentives as faced by individuals. Specifically, we use SHARE data to estimate a model à la Stock and Wise (Econom Econ Soc 58(5):1151–1180, 1990). Exploring the data on individual life-histories from SHARELIFE, we construct a measure of financial incentive to retire. Our analysis explicitly takes into account the different take-up rates of the various early retirement exit paths across time and ages. The results show that financial incentives play a strong role. Health and education also matter, as do regional differences. Against the general background of the 2020 strategy, we perform a set of policy simulations and illustrate the scope but also the limits associated with selective parametric reforms.     

A new microstructure noise index

We introduce a new microstructure noise index for financial data. This index, the computation of which is based on the p-variations of the considered asset or rate at different time scales, can be interpreted in terms of Besov smoothness spaces. We study the behavior of our new index using empirical data. It gives rise to phenomena that a classical signature plot is unable to detect. In particular, with our data set, it enables us to separate the sampling frequencies into three zones: no microstructure noise for low frequencies, increasing microstructure noise from low to high frequencies, and some kind of additional regularity on the finest scales. We then investigate the index from a theoretical point of view, under various contexts of microstructure noise, trying to reproduce the facts observed on the data. We show that this can be partially done using models involving additive correlated errors or rounding error. Accurate reproduction seems to require either both kinds of error together or some unusual form of rounding error.     

Cash flow at risk valuation of mining project using Monte Carlo simulations with stochastic processes calibrated on historical data

Mining projects are subject to multiple sources of market uncertainties such as metal price, exchange rates, and their volatilities. Assessing a mining project's exposure to market risk usually requires Monte Carlo simulations to capture a range of probable outcomes. The probability of a major loss is extracted from the probability density function of simulated prices at a given time into the future. This article proposes an approach to calibrate the stochastic process to be used in Monte Carlo simulations. The simulations are then used for measuring the cash flow at risk of a mining project. To assess the performance of the proposed approach, a case study is conducted on a mining project. The results show that the calibration approach is robust and apt at fitting various stochastic processes to historical observations.     

Managing learning in informal innovation networks: overcoming the Daphne-dilemma

In this article we discuss the nature and productivity of informal innovation networks, i.e. informal collaborative arrangements between organizations engaged in product or process innovation. Such networks can be used in any phase of the innovation process, but their informal nature makes them especially suited for its fuzzy front end. We explore their potential in technology exchange and learning on the basis of a combination of organization network theory and knowledge management theory. We discuss issues in network governance and network operational management and discuss the basic dilemma – which we named the Daphne-dilemma – facing attempts to improve the productivity of informal innovation networks: too little management effort may lead to under-exploitation of their potential and poor productivity, but too much management effort may destroy their informal nature and hence their creative and explorative potential.     

Determinants of the Level of Knowledge Application: A Knowledge‐Based and Information‐Processing Perspective*

Knowledge application is of key importance in the development of successful new products. Knowledge application refers to an organization's timely response to technological change by utilizing the knowledge and technology generated into new products and processes. This study uses the knowledge‐based theory of the firm and considers its roots in the information‐processing approach to organization theory to identify and structure potential antecedents of knowledge application. This study develops four hypotheses concerning antecedents of knowledge application. The hypotheses are tested using data collected from 277 high‐technology firms. Empirical results indicate that a long‐term orientation supported by a research and development (R&D) budget, formal rewards, and information technology directly increases the level of knowledge application, while R&D co‐location indirectly increases the level of knowledge application. It is surprising to find that an increase in the level of organizational redundancy reduces the level of knowledge application. The findings also suggest that information technologies, lead‐user, and supplier networks do not appear to significantly influence organizational redundancy.     

The alpha and omega of fund of hedge fund added value

In spite of a somewhat disappointing performance throughout the crisis, investors are showing interest in hedge funds. Still, funds of hedge funds keep on experiencing outflows. Can this phenomenon be explained by the failure of fund of hedge fund managers to deliver on their promise to add value through active management, or is it symptomatic of a move toward greater disintermediation in the hedge fund industry? We introduce a return-based attribution model allowing for a full decomposition of fund of hedge fund performance. The results of our empirical study suggest that funds of hedge funds are funds of funds like others. Strategic allocation turns out to be a crucial step in the investment process, in that it not only adds value over the long-term, but most importantly, it brings resilience precisely when investors need it the most. Fund picking, on the other hand, turns out to be a double-edged sword.