We propose new methods for estimating the bid-ask spread from observed transaction prices alone. Our methods are based on the empirical characteristic function instead of the sample autocovariance function like the method of Roll (1984). As in Roll (1984), we have a closed form expression for...

In structural vector autoregressive analysis identifying the shocks of interest via heteroskedasticity has become a standard tool. Unfortunately, the approaches currently used for modelling heteroskedasticity all have drawbacks. For instance, assuming known dates for variance changes is often...

In structural vector autoregressive analysis identifying the shocks of interest via heteroskedasticity has become a standard tool. Unfortunately, the approaches currently used for modelling heteroskedasticity all have drawbacks. For instance, assuming known dates for variance changes is often...

We give a set of identifying conditions for simultaneous equation systems (SES) with heteroskedasticity in the framework of the Gaussian quasi maximum likelihood (QML) approach. Our conditions rely on the presence of heteroskedasticity rather than exclusion restrictions. The QML estimators are...

We give a set of identifying conditions for simultaneous equation systems (SES) with heteroskedasticity in the framework of the Gaussian quasi maximum likelihood (QML) approach. Our conditions rely on the presence of heteroskedasticity rather than exclusion restrictions. The QML estimators are...

We discuss the finding that cross-sectional characteristic based models have yielded portfolios with higher excess monthly returns but lower risk than their arbitrage pricing theory counterparts in an analysis of equity returns of stocks listed on the JSE. Under the assumption of general...