The principal objective of this paper is to develop a new approach to the construction of composite leading indicators using the signal extraction capabilities of the powerful Kalman filter. The resultant leading indicator properties are found to outperform those already derived using the...

In this paper we compare the performance of three indices in an inflation forecasting experiment. The evidence not only suggests that an evolved neural network is superior to traditionally trained networks in the majority of cases, but also that a risky money index performs at least as well as...

In this paper, the exchange rate forecasting performance of neural network models are evaluated against the random walk, autoregressive moving average and generalised autoregressive conditional heteroskedasticity models. There are no guidelines available that can be used to choose the parameters...

This study is the first of its kind to focus on the effect of interest-rate tiers on aggregate measures of the monetary services flow. We address the role and impact of measurement errors in building monetary index numbers directly. Using a unique data set obtained from Barclays Bank plc, we...

In this paper we compare the performance of three indices in an inflation forecasting experiment. The evidence not only suggests that an evolved neural network is superior to traditionally trained networks in the majority of cases, but also that a risky money index performs at least as well as...

This study is the first of its kind to focus on the effect of interest-rate tiers on aggregate measures of the monetary services flow. We address the role and impact of measurement errors in building monetary index numbers directly. Using a unique data set obtained from Barclays Bank plc, we...

In this paper, a Divisia monetary index measure of money is constructed for the Italian economy and its inflation forecasting potential is compared with that of its traditional simple sum counterpart. The powerful and flexible Artificial Intelligence technique of neural networks is used to allow...

In this paper, the exchange rate forecasting performance of neural network models are evaluated against the random walk, autoregressive moving average and generalised autoregressive conditional heteroskedasticity models. There are no guidelines available that can be used to choose the parameters...