A new approach to the evaluation and selection of leading indicators

This note examines how the DEM/USD rate and US short-term and long-term interest rates respond to the release of payroll announcements. In contrast to a recent paper by Edison (1997), who employs a linear econometric model, we test the influence of news by comparing the absolute values of the percentage change between the means of symmetrically sampled values of daily exchange rate and interest rates before and after the announcement day to the distribution of absolute changes in means for all periods excluding non-farm payroll news. We find a highly significant reaction for both the DEM/USD rate and bond yields, depending on the window size. Short-term US interest rates, by contrast are hardly affected. Finally, the reaction of inflation indexed bond yields to news announcements is investigated.. --leading indicator,turning point,prediction

Stability issues in German money multiplier forecasts

This paper investigates the stability of the German money supply focusing on the period 1991 - 1998. It is shown that the standard ARIMA-Transfer model approach in the literature needs to be augmented by a cointegration term to adequately model the dynamics of money supply in Germany. Additional analysis with regard to the influence of financial innovations on the control of money supply yields evidence that the influence of financial innovations on the multiplier has increased steadily during the observation period. --Money Supply,Financial Innovation,Forecasting Money Multiplier

Approximation properties of the neuro-fuzzy minimum function

The integration of fuzzy logic systems and neural networks in data driven nonlinear modeling applications has generally been limited to functions based upon the multiplicative fuzzy implication rule for theoretical and computational reasons. We derive a universal approximation result for the minimum fuzzy implication rule as well as a differentiable substitute function that allows fast optimization and function approximation with neuro-fuzzy networks. --Fuzzy Logic,Neural Networks,Nonlinear Modeling,Optimization

Closed form integration of artificial neural networks with some applications

Many economic and econometric applications require the integration of functions lacking a closed form antiderivative, which is therefore a task that can only be solved by numerical methods. We propose a new family of probability densities that can be used as substitutes and have the property of closed form integrability. This is especially advantageous in cases where either the complexity of a problem makes numerical function evaluations very costly, or fast information extraction is required for time-varying environments. Our approach allows generally for nonparametric maximum likelihood density estimation and may thus find a variety of applications, two of which are illustrated briefly: Estimation of Value at Risk based on approximations to the density of stock returns; Recovering risk neutral densities for the valuation of options from the option price - strike price relation. --Option Pricing,Neural Networks,Nonparametric Density Estimation

Mixtures of t-distributions for Finance and Forecasting

We explore convenient analytic properties of distributions constructed as mixtures of scaled and shifted t-distributions. A feature that makes this family particularly desirable for econometric applications is that it possesses closed-form expressions for its anti-derivatives (e.g., the cumulative density function). We illustrate the usefulness of these distributions in two applications. In the first application, we use a scaled and shifted t-distribution to produce density forecasts of U.S. inflation and show that these forecasts are more accurate, out-of-sample, than density forecasts obtained using normal or standard t-distributions. In the second application, we replicate the option-pricing exercise of Abadir and Rockinger (2003) using a mixture of scaled and shifted t-distributions and obtain comparably good results, while gaining analytical tractability.ARMA-GARCH models, neural networks, nonparametric density estimation, forecast accuracy, option pricing, risk neutral density

A new approach to the evaluation and selection of leading indicators

SIGLEAvailable from Bibliothek des Instituts fuer Weltwirtschaft, ZBW, Duesternbrook Weg 120, D-24105 Kiel W 1185 (98.1) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman

The monetary impulse measure as an explanation for Fed policy

In response to the perceived instability of the relations between traditional monetary aggregates and nominal aggregate demand a number of nonstandard indicator variables have been developed to enable monetary policy to respond to, and counteract, incipient inflationary pressures before much inflation has developed. While the Federal Reserve Board is believed to pay increasing attention to such indicator variables, it is unclear which ones are perceived as particularly important. In this note, we present a variation of the monetary impulse measure (MIM), which was recently developed by McCallum and Hargraves (Staff studies for the World Economic Outlook, 1995). Modifying the original specification of the measure, we show that the new MIM's performance in explaining actual Fed decisions is clearly superior to other indicator variables, which are widely believed to guide US monetary policy.

Closed Form Integration of Artificial Neural Networks with Some Applications to Finance

Many economic and econometric applications require the integration of functions lacking a closed form antiderivative, which is therefore a task that can only be solved by numerical methods. We propose a new family of probability densities that can be used as substitutes and have the property of closed form integrability. This is especially advantageous in cases where either the complexity of a problem makes numerical function evaluations very costly, or fast information extraction is required for timevarying environments. Our approach allows generally for nonparametric maximum likelihood density estimation and may thus nd a variety of applications, two of which are illustrated briey: Estimation of Value at Risk based on approximations to the density of stock returns. Recovering risk neutral densities for the valuation of options from the option price { strike price relation. JEL Classication: C45, G13, C63; Keywords : Option Pricing, Neural Networks, Nonparametric Density Es..

Neuron-Glia Interactions in Neural Plasticity: Contributions of Neural Extracellular Matrix and Perineuronal Nets

Synapses are specialized structures that mediate rapid and efficient signal transmission between neurons and are surrounded by glial cells. Astrocytes develop an intimate association with synapses in the central nervous system (CNS) and contribute to the regulation of ion and neurotransmitter concentrations. Together with neurons, they shape intercellular space to provide a stable milieu for neuronal activity. Extracellular matrix (ECM) components are synthesized by both neurons and astrocytes and play an important role in the formation, maintenance, and function of synapses in the CNS. The components of the ECM have been detected near glial processes, which abut onto the CNS synaptic unit, where they are part of the specialized macromolecular assemblies, termed perineuronal nets (PNNs). PNNs have originally been discovered by Golgi and represent a molecular scaffold deposited in the interface between the astrocyte and subsets of neurons in the vicinity of the synapse. Recent reports strongly suggest that PNNs are tightly involved in the regulation of synaptic plasticity. Moreover, several studies have implicated PNNs and the neural ECM in neuropsychiatric diseases. Here, we highlight current concepts relating to neural ECM and PNNs and describe an in vitro approach that allows for the investigation of ECM functions for synaptogenesis

The reaction of exchange rates and interest rates of news releases

SIGLEAvailable from Bibliothek des Instituts fuer Weltwirtschaft, ZBW, Duesternbrook Weg 120, D-24105 Kiel W 1185 (98.2) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman