No abstract

Companies need to decide on the optimal amounts of cash to hold. Although this problem has long been acknowledged as a major issue for corporations, new advances in the finance literature have not been fully implemented in this area. We propose here what we believe is the first modelization of a real options approach to determine the financial benefits of holding cash. We measure the benefits of holding cash if raising new capital takes time, is costly and if the firm faces the risk of having to issue underpriced securities to obtain that capital. We show that the methodology proposed leads to non‐intuitive results that warrant further research in the field and should attract academics’ as well practitioners’ attention.

No abstract

Although many credit risk pricing models exist in the academic literature, very little attention has been paid to the impact of risky collateral on credit risk. It is nonetheless well known that practitioners often mitigate credit risk with collateral, using so-called haircuts for collateral level determination. The presence of collateral has a complex effect that can not be analysed simply with existing models. We analyse the value of credit risk when there is collateral in a range of different situations, including dual-default in a simple setting, stochastic collateral, stochastic bond collateral with stochastic interest rates, continuous and discrete marking-to-market and margin calls. The models confirm many practical intuitions, such as the impact on the haircut level required of the risks of the collateral asset and of the underlying asset to the forward as well as the impact of their correlation. Moreover, the model supports the intuition that the frequency of marking-to-market and collateral are substitutes. The models also stress the possibly unexpected magnitude of these factors. More importantly, they give actual solutions to determining the value of the credit risk depending on the haircut chosen and the frequency of marking-to-markets, results not presented before in the literature. The models are also a good basis to understand the portfolio effect of collateral management. Finally, they illustrate how differences in prices may arise from pure differences of credit risk management, as illustrated here in the case of futures and forwards.(J.E.L.: G13).