This paper analyzes recursive and rolling neural network models to forecast one-step-ahead sign variations in gold price. Different combinations of techniques and sample sizes are studied for feed forward and ward neural networks. The results shows the rolling ward networks exceed the recursive...

This study explores the convergence between the prices of American Depositary Receipts (ADRs) listed by Asia-Pacific firms and their original shares listed on home exchanges. Instead of relying on conventional parametric approaches that carry embedded model-specification errors, we contribute to...

This study examines the long-term price performance of share-only versus unit IPOs issued on the Hong Kong Stock Exchange during 1990-2002. Our main objective is to test the extent to which the agency cost and signaling models explain the reasons for unit IPOs issuance using the long-term price...

Previous research concerned with the investigation of intraday data has typically sought to model that data using techniques to control for intraday periodicity, has applied models of short-horizon and long-horizon dependencies, or has utilised intraday data in the construction of realised...

A long-short beta neutral portfolio strategy is constructed based on earnings yields forecasts and a shrunk covariance matrix. Positions are modified with an innovative technique of time-varying risk budgeting based on an integration measure. We consider a set of 14 developed equity markets...

We analyze the effect of cross-country differences in accounting standards on the empirical performance of financial pricing models. We show how the lack of uniform accounting standards across countries generates inconsistent estimates of the model parameters, and leads to rejection of the...