This article explores the use of artificial neural networks in the modeling of foreclosure of commercial mortgages. The study employs a large set of individual loan histories previously used in the literature of proportional hazard models on loan default. Radial basis function networks are...

This paper investigates the short-term dynamics of stock returns in an emerging stock market namely, the Cyprus Stock Exchange (CYSE). Stock returns are modelled as conditionally heteroscedastic processes with time-dependent serial correlation. The conditional variance follows an EGARCH process,...

Despite the growing importance of the commercial paper market there is no empirical work investigating the hedging performance of dynamic hedging strategies versus traditional static hedging strategies. This article proposes a dynamic hedging model for commercial paper that takes advantage of...

EGARCH-M models based on a daily, weekly, and monthly S&P–500 returns over the period October 1934–September 1994 reveal that higher margins have a much stronger negative relation to subsequent volatility in bull markets than in bear markets. Higher margins are also negatively related to...

This article proposes a dynamic hedging model for Government National Association Mortgage-Backed Securities (GNMA MBSs) that is free of the drawbacks associated with the static hedging strategies currently used. The simultaneity bias of the regression approach is dealt with by modeling the...