It is well-known in empirical finance that virtually all asset returns, whether monthly, daily, or intraday, are heavy-tailed and, particularly for stock returns, are mildly but often significantly negatively skewed. However, the tail indices, or maximally existing moments of the returns, can differ markedly across assets. To accommodate these stylized facts when modeling the joint distribution of asset returns, an asymmetric extension of the meta-elliptical t distribution is proposed. While the likelihood is tractable, for high dimensions it will be impractical to use for estimation. To address this, a fast, two-step estimation procedure is developed, based on a saddlepoint approximation to the noncentral Student's t distribution. The model is extended to support a CCC-(I)GARCH structure and demonstrated by modeling and forecasting the return series comprising the DJIA. The techniques of shrinkage, time-varying tail dependence, and weighted likelihood are employed to further enhance the forecasting performance of the model with no added computational burden.
We present an overview of corporate-finance models where firms are subject to exogenous market frictions. These models, albeit quite simple, yield reasonable predictions regarding financing, pay-outs and default, as well as asset-pricing implications. The price to pay for the said simplicity is the need to use non-standard mathematical techniques, namely Singular and Impulse Stochastic Control. We explore the cases where a firm with fixed expected profitability has access to costly equity issuance as a refinancing possibility, and that where issuance is infinitely costly. We also present a model of bank leverage.
We study capital requirements when the bank's econometric model only approximately describes the dynamics of portfolio returns—which is virtually always the case in practice. We derive a simple formula for capital requirements based on a first-order Taylor expansion of the Value at Risk around a ‘model confidence’ parameter. This formula allows to reflect the bank's confidence in the econometric model into capital requirements in a theoretically consistent manner. Numerical and empirical applications show that our formula provides valuable information for quantifying capital requirements under model risk.
We present a software system to create and implement internal markets in organizations that want to limit the CO2 emissions or the use of scarce resources by their employees. This system can be applied to domains such as business travel by distributing a limited number of permits for business travel-related CO2 emissions at the beginning of a period and then allowing the permits to be traded inside the organization. The system calculates the CO2 emissions caused by planned trips and provides the market mechanisms to trade the permits. The approach can be generalized from emission permits to any scarce good that is assigned by the management to units or individual members of the organization, such as parking spaces. Both cases are described by way of detailed examples.
