The Influence of Domestic and International Interest Rates on the ISEQ

We investigate the influence of international and domestic monetary policy shocks on the Irish stock market. Specifically, we analyse the impact of (un)expected changes in domestic, US, UK and German / euro area policy rates on the ISEQ between 1988 to 2002 in an event type study. Our decomposition of (un)expected changes in policy rates are based on futures markets and is akin to Kuttner (2001). In the absence of an Irish interest rate futures market, we use a more indirect method by appealing to the expectations theory of the term structure of interest rates. Overall, our results suggest that, with the exception of the US, unanticipated changes in domestic and international interest rates appear to have little significant influence on the Irish stock market.

Gradual Information Diffusion and Asset Price Momentum

Gradual information diffusion model predicts that as private information travels across the population, pricing accuracy would improve and asset prices would exhibit momentum as a result. In laboratory markets I investigate the market’s aggregation capacity in response to varying proportions of informed traders as a consequence of information diffusion. The results demonstrate that pricing errors are high when private information is dispersed and that, as the information spreads, the market gradually revise the errors and manifest momentum. Analysis suggests that aggregation under dispersed information conditions is hampered by three factors: equilibrium multiplicity, slow arrival of myopic traders, and anonymous trading.

Is the P300 Speller Independent?

The P300 speller is being considered as an independent brain-computer interface. That means it measures the user's intent, and does not require the user to move any muscles. In particular it should not require eye fixation of the desired character. However, it has been shown that posterior electrodes provide significant discriminative information, which is likely related to visual processing. These findings imply the need for studies controlling the effect of eye movements. In experiments with a 3x3 character matrix, attention and eye fixation was directed to different characters. In the event-related potentials, a P300 occurred for the attended character, and N200 was seen for the trials showing the focussed character. It occurred at posterior sites, reaching its peak at 200ms after stimulus onset. The results suggest that gaze direction plays an important role in P300 speller paradigm. By controlling gaze direction it is possible to separate voluntary and involuntary EEG responses to the highlighting of characters.Comment: 7 pages, 5 figure

Assessing the UK experience functional separation in fixed telecommunications markets

This paper focuses on functional separation. After reviewing the literature on separation in its various guises and describing the circumstances that culminated in the creation of Openreach in the UK, the paper focuses on the implementation of the undertakings. It is shown that difficulties have been encountered in the implementation of the undertakings, and that while the relationship between BT and other service providers may have improved, tensions remain

Machine Analysis of Facial Expressions

No abstract

Time Consistency of Monetary Policy in Separating Exchange Markets

Though a dual exchange rate system might be a preferable intermediate step from a fixed to a flexible rate, the efficiency of such a regime depends on the complete separation between two markets. When government reneges on its announcement and changes the commercial rate, the time inconsistency of monetary policy arises. This event might result in incomplete separation, the instability of spread and hence the erosion of this management. This paper attempts to investigate the role of credibility in such a regime. It concludes that, for successfully separating exchange markets, government should fix the commercial exchange rate rather than change it.

Optimal set of EEG features for emotional state classification and trajectory visualization in Parkinson's disease

In addition to classic motor signs and symptoms, individuals with Parkinson's disease (PD) are characterized by emotional deficits. Ongoing brain activity can be recorded by electroencephalograph (EEG) to discover the links between emotional states and brain activity. This study utilized machine-learning algorithms to categorize emotional states in PD patients compared with healthy controls (HC) using EEG. Twenty non-demented PD patients and 20 healthy age-, gender-, and education level-matched controls viewed happiness, sadness, fear, anger, surprise, and disgust emotional stimuli while fourteen-channel EEG was being recorded. Multimodal stimulus (combination of audio and visual) was used to evoke the emotions. To classify the EEG-based emotional states and visualize the changes of emotional states over time, this paper compares four kinds of EEG features for emotional state classification and proposes an approach to track the trajectory of emotion changes with manifold learning. From the experimental results using our EEG data set, we found that (a) bispectrum feature is superior to other three kinds of features, namely power spectrum, wavelet packet and nonlinear dynamical analysis; (b) higher frequency bands (alpha, beta and gamma) play a more important role in emotion activities than lower frequency bands (delta and theta) in both groups and; (c) the trajectory of emotion changes can be visualized by reducing subject-independent features with manifold learning. This provides a promising way of implementing visualization of patient's emotional state in real time and leads to a practical system for noninvasive assessment of the emotional impairments associated with neurological disorders