Is there timing ability in currency markets? Evidence from ADR issuances

Is there timing ability in the exchange rate markets? We address this question by examining foreign firms' decisions to issue American Depositary Receipts (ADRs). Specifically, we test whether foreign firms consider currency market conditions in their ADR issuance decisions and, in doing so, display some ability to time their local exchange rate market. We study ADR issuances in the U.S. stock market between 1976 and 2003. We find that foreign firms tend to issue ADRs after their local currency has been abnormally strong against the U.S. dollar and before their local currency becomes abnormally weak. This evidence is statistically significant even after controlling for local and U.S. past and future stock market performance and predicable exchange rate movements. Currency market timing is especially significant i) for value companies, relatively small (yet absolutely large) companies issuing relatively large amounts of ADRs, companies with higher currency exposure, manufacturing companies, and emerging market companies, ii) during currency crises (when mispricings are rife) and after the integration of the issuer's local financial market with the world capital markets, iii) when the ADR issue raises capital for the issuing firm (Level III ADR), and iv) regardless of the identity of the underwriting investment bank. Currency market timing is also economically significant since it translates into total savings for the issuing firms of about $646 million (or 1.86% of the total capital-raising ADR issue volume). In contrast, we find no evidence of currency timing ability in a control sample made of non-capital raising ADRs (Level II ADRs). These findings suggest that some companies may have, at least occasionally, private information about foreign exchange.

Temporal-based support vector machines for facial expression recognition

When classifying a signal, ideally we want our classifier to trigger a large response when it encounters a positive example and have little to no response for all other examples. Unfortunately in practice this does not occur with responses fluctuating, often causing false alarms. There exists a myriad of reasons why this is the case, most notably not incorporating the dynamics of the signal into the classification. In facial expression recognition, this has been highlighted as one major research question. In this paper we present a novel technique which incorporates the dynamics of the signal which can produce a strong response when the peak expression is found and essentially suppresses all other responses as much as possible. We conducted preliminary experiments on the extended Cohn-Kanade (CK+) database which shows its benefits. The ability to automatically and accurately recognize facial expressions of drivers is highly relevant to the automobile. For example, the early recognition of “surprise” could indicate that an accident is about to occur; and various safeguards could immediately be deployed to avoid or minimize injury and damage. In this paper, we conducted initial experiments on the extended Cohn-Kanade (CK+) database which shows its benefits.

Improved functional ability and independence in activities of daily living for older adults at high risk of hospital readmission : a randomised controlled trial

Objective: During hospitalisation older people often experience functional decline which impacts on their future independence. The objective of this study was to evaluate a multifaceted transitional care intervention including home-based exercise strategies for at-risk older people on functional status, independence in activities of daily living, and walking ability. Methods: A randomised controlled trial was undertaken in a metropolitan hospital in Australia with 128 patients (64 intervention, 64 control) aged over 65 years with an acute medical admission and at least one risk factor for hospital readmission. The intervention group received an individually tailored program for exercise and follow-up care which was commenced in hospital and included regular visits in hospital by a physiotherapist and a Registered Nurse, a home visit following discharge, and regular telephone follow-up for 24 weeks following discharge. The program was designed to improve health promoting behaviours, strength, stability, endurance and mobility. Data were collected at baseline, then 4, 12 and 24 weeks following discharge using the Index of Activities of Daily Living (ADL), Instrumental Index of Activities of Daily Living (IADL), and the Walking Impairment Questionnaire (Modified). Results: Significant improvements were found in the intervention group in IADL scores (p<.001), ADL scores (p<.001), and WIQ scale scores (p<.001) in comparison to the control group. The greatest improvements were found in the first four weeks following discharge. Conclusions: Early introduction of a transitional model of care incorporating a tailored exercise program and regular telephone follow-up for hospitalised at-risk older adults can improve independence and functional ability.

Analysis of cardiac and epileptic signals using higher order spectra

The theory of nonlinear dyamic systems provides some new methods to handle complex systems. Chaos theory offers new concepts, algorithms and methods for processing, enhancing and analyzing the measured signals. In recent years, researchers are applying the concepts from this theory to bio-signal analysis. In this work, the complex dynamics of the bio-signals such as electrocardiogram (ECG) and electroencephalogram (EEG) are analyzed using the tools of nonlinear systems theory. In the modern industrialized countries every year several hundred thousands of people die due to sudden cardiac death. The Electrocardiogram (ECG) is an important biosignal representing the sum total of millions of cardiac cell depolarization potentials. It contains important insight into the state of health and nature of the disease afflicting the heart. Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. Heart rate variability analysis is an important tool to observe the heart's ability to respond to normal regulatory impulses that affect its rhythm. A computerbased intelligent system for analysis of cardiac states is very useful in diagnostics and disease management. Like many bio-signals, HRV signals are non-linear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of non-linear systems and provides good noise immunity. In this work, we studied the HOS of the HRV signals of normal heartbeat and four classes of arrhythmia. This thesis presents some general characteristics for each of these classes of HRV signals in the bispectrum and bicoherence plots. Several features were extracted from the HOS and subjected an Analysis of Variance (ANOVA) test. The results are very promising for cardiac arrhythmia classification with a number of features yielding a p-value < 0.02 in the ANOVA test. An automated intelligent system for the identification of cardiac health is very useful in healthcare technology. In this work, seven features were extracted from the heart rate signals using HOS and fed to a support vector machine (SVM) for classification. The performance evaluation protocol in this thesis uses 330 subjects consisting of five different kinds of cardiac disease conditions. The classifier achieved a sensitivity of 90% and a specificity of 89%. This system is ready to run on larger data sets. In EEG analysis, the search for hidden information for identification of seizures has a long history. Epilepsy is a pathological condition characterized by spontaneous and unforeseeable occurrence of seizures, during which the perception or behavior of patients is disturbed. An automatic early detection of the seizure onsets would help the patients and observers to take appropriate precautions. Various methods have been proposed to predict the onset of seizures based on EEG recordings. The use of nonlinear features motivated by the higher order spectra (HOS) has been reported to be a promising approach to differentiate between normal, background (pre-ictal) and epileptic EEG signals. In this work, these features are used to train both a Gaussian mixture model (GMM) classifier and a Support Vector Machine (SVM) classifier. Results show that the classifiers were able to achieve 93.11% and 92.67% classification accuracy, respectively, with selected HOS based features. About 2 hours of EEG recordings from 10 patients were used in this study. This thesis introduces unique bispectrum and bicoherence plots for various cardiac conditions and for normal, background and epileptic EEG signals. These plots reveal distinct patterns. The patterns are useful for visual interpretation by those without a deep understanding of spectral analysis such as medical practitioners. It includes original contributions in extracting features from HRV and EEG signals using HOS and entropy, in analyzing the statistical properties of such features on real data and in automated classification using these features with GMM and SVM classifiers.

The development and validation of two complementary measures of drivers' hazard perception ability

Hazard perception in driving involves a number of different processes. This paper reports the development of two measures designed to separate these processes. A Hazard Perception Test was developed to measure how quickly drivers could anticipate hazards overall, incorporating detection, trajectory prediction, and hazard classification judgements. A Hazard Change Detection Task was developed to measure how quickly drivers can detect a hazard in a static image regardless of whether they consider it hazardous or not. For the Hazard Perception Test, young novices were slower than mid-age experienced drivers, consistent with differences in crash risk, and test performance correlated with scores in pre-existing Hazard Perception Tests. For drivers aged 65 and over, scores on the Hazard Perception Test declined with age and correlated with both contrast sensitivity and a Useful Field of View measure. For the Hazard Change Detection Task, novices responded quicker than the experienced drivers, contrary to crash risk trends, and test performance did not correlate with measures of overall hazard perception. However for drivers aged 65 and over, test performance declined with age and correlated with both hazard perception and Useful Field of View. Overall we concluded that there was support for the validity of the Hazard Perception Test for all ages but the Hazard Change Detection Task might only be appropriate for use with older drivers.

Years 2 to 6 students' ability to generalise : models, representations and theory for teaching and learning

Over the last three years, in our Early Algebra Thinking Project, we have been studying Years 3 to 5 students’ ability to generalise in a variety of situations, namely, compensation principles in computation, the balance principle in equivalence and equations, change and inverse change rules with function machines, and pattern rules with growing patterns. In these studies, we have attempted to involve a variety of models and representations and to build students’ abilities to switch between them (in line with the theories of Dreyfus, 1991, and Duval, 1999). The results have shown the negative effect of closure on generalisation in symbolic representations, the predominance of single variance generalisation over covariant generalisation in tabular representations, and the reduced ability to readily identify commonalities and relationships in enactive and iconic representations. This chapter uses the results to explore the interrelation between generalisation and verbal and visual comprehension of context. The studies evidence the importance of understanding and communicating aspects of representational forms which allowed commonalities to be seen across or between representations. Finally the chapter explores the implications of the studies for a theory that describes a growth in integration of models and representations that leads to generalisation.

Hearing impairment affects older people’s ability to drive in the presence of distracters

OBJECTIVES: To investigate the effects of hearing impairment and distractibility on older people's driving ability, assessed under real-world conditions. DESIGN: Experimental cross-sectional study. SETTING: University laboratory setting and an on-road driving test. PARTICIPANTS: One hundred seven community-living adults aged 62 to 88. Fifty-five percent had normal hearing, 26% had a mild hearing impairment, and 19% had a moderate or greater impairment. ---------- MEASUREMENTS: Hearing was assessed using objective impairment measures (pure-tone audiometry, speech perception testing) and a self-report measure (Hearing Handicap Inventory for the Elderly). Driving was assessed on a closed road circuit under three conditions: no distracters, auditory distracters, and visual distracters. RESULTS: There was a significant interaction between hearing impairment and distracters, such that people with moderate to severe hearing impairment had significantly poorer driving performance in the presence of distracters than those with normal or mild hearing impairment. CONCLUSION: Older adults with poor hearing have greater difficulty with driving in the presence of distracters than older adults with good hearing.

Uncertainties that matter : risk, response-ability, ethics and the moment of exchange in Live Art

This article examines the moment of exchange between artist, audience and culture in Live Art. Drawing on historical and contemporary examples, including examples from the Exist in 08 Live Art Event in Brisbane, Australia, in October 2008, it argues that Live Art - be it body art, activist art, site-specific performance, or other sorts of performative intervention in the public sphere - is characterised by a common set of claims about activating audiences, asking them to reflect on cultural norms challenged in the work. Live Art presents risky actions, in a context that blurs the boundaries between art and reality, to position audients as ‘witnesses’ who are personally implicated in, and responsible for, the actions unfolding before them. This article problematises assumptions about the way the uncertainties embedded in the Live Art encounter contribute to its deconstructive agenda. It uses the ethical theory of Emmanuel Levinas, Hans-Thies Lehmann and Dwight Conquergood to examine the mechanics of reductive, culturally-recuperative readings that can limit the efficacy of the Live Art encounter. It argues that, though ‘witnessing’ in Live Art depends on a relation to the real - real people, taking real risks, in real places - if it fails to foreground theatrical frame it is difficult for audients to develop the dual consciousness of the content, and their complicity in that content, that is the starting point for reflexivity, and response-ability, in the ethical encounter.