Evaluating Specification Tests for Markov-Switching Time-Series Models

We evaluate the performance of several specification tests for Markov regime-switching time-series models. We consider the Lagrange multiplier (LM) and dynamic specification tests of Hamilton (1996) and Ljung–Box tests based on both the generalized residual and a standard-normal residual constructed using the Rosenblatt transformation. The size and power of the tests are studied using Monte Carlo experiments. We find that the LM tests have the best size and power properties. The Ljung–Box tests exhibit slight size distortions, though tests based on the Rosenblatt transformation perform better than the generalized residual-based tests. The tests exhibit impressive power to detect both autocorrelation and autoregressive conditional heteroscedasticity (ARCH). The tests are illustrated with a Markov-switching generalized ARCH (GARCH) model fitted to the US dollar–British pound exchange rate, with the finding that both autocorrelation and GARCH effects are needed to adequately fit the data.

The distribution of the sample minimum-variance frontier

In this paper, we present a finite sample analysis of the sample minimum-variance frontier under the assumption that the returns are independent and multivariate normally distributed. We show that the sample minimum-variance frontier is a highly biased estimator of the population frontier, and we propose an improved estimator of the population frontier. In addition, we provide the exact distribution of the out-of-sample mean and variance of sample minimum-variance portfolios. This allows us to understand the impact of estimation error on the performance of in-sample optimal portfolios. Key Words: minimum-variance frontier; efficiency set constants; finite sample distribution

Yield-factor volatility models

The term structure of interest rates is often summarized using a handful of yield factors that capture shifts in the shape of the yield curve. In this paper, we develop a comprehensive model for volatility dynamics in the level, slope, and curvature of the yield curve that simultaneously includes level and GARCH effects along with regime shifts. We show that the level of the short rate is useful in modeling the volatility of the three yield factors and that there are significant GARCH effects present even after including a level effect. Further, we find that allowing for regime shifts in the factor volatilities dramatically improves the model’s fit and strengthens the level effect. We also show that a regime-switching model with level and GARCH effects provides the best out-of-sample forecasting performance of yield volatility. We argue that the auxiliary models often used to estimate term structure models with simulation-based estimation techniques should be consistent with the main features of the yield curve that are identified by our model.

Why common factors in international bond returns are not so common

This paper analyzes the common factor structure of US, German, and Japanese Government bond returns. Unlike previous studies, we formally take into account the presence of country-specific factors when estimating common factors. We show that the classical approach of running a principal component analysis on a multi-country dataset of bond returns captures both local and common influences and therefore tends to pick too many factors. We conclude that US bond returns share only one common factor with German and Japanese bond returns. This single common factor is associated most notably with changes in the level of domestic term structures. We show that accounting for country-specific factors improves the performance of domestic and international hedging strategies.

Conditional coskewness and asset pricing

We explore the empirical usefulness of conditional coskewness to explain the cross-section of equity returns. We find that coskewness is an important determinant of the returns to equity, and that the pricing relationship varies through time. In particular we find that when the conditional market skewness is positive investors are willing to sacrifice 7.87% annually per unit of gamma (a standardized measure of coskewness risk) while they only demand a premium of 1.80% when the market is negatively skewed. A similar picture emerges from the coskewness factor of Harvey and Siddique (Harvey, C., Siddique, A., 2000a. Conditional skewness in asset pricing models tests. Journal of Finance 65, 1263–1295.) (a portfolio that is long stocks with small coskewness with the market and short high coskewness stocks) which earns 5.00% annually when the market is positively skewed but only 2.81% when the market is negatively skewed. The conditional two-moment CAPM and a conditional Fama and French (Fama, E., French, K., 1992. The cross-section of expected returns. Journal of Finance 47,427465.) three-factor model are rejected, but a model which includes coskewness is not rejected by the data. The model also passes a structural break test which many existing asset pricing models fail.

Australian Library and Information Studies (LIS) researchers' ranking of LIS journals

The paper describes the processes and the outcomes of the ranking of LIS journal titles by Australia’s LIS researchers during 2007-8, firstly through the Australian federal government’s Research Quality Framework (RQF) process and then its replacement, the Excellence in Research for Australia (ERA) initiative. The requirement to rank the journals titles used came from discussions held at the RQF panel meeting held in February 2007 in Canberra, Australia. While it was recognised that the Web of Science (formerly ISI) journal impact approach of journal acceptance for measures of research quality and impact might not work for LIS, it was apparent that this model would be the default if no other ranking of journal titles became apparent. Although an increasing number of LIS and related discipline journals were appearing in the Web of Science listed rankings, the number was few and it was thus decided by the Australian LIS research community to undertake the ranking exercise.

Electro-cortical implicit race bias does not vary with participants' race or sex

Earlier research found evidence for electro-cortical race bias towards black target faces in white American participants irrespective of the task relevance of race. The present study investigated whether an implicit race bias generalizes across cultural contexts and racial in- and out-groups. An Australian sample of 56 Chinese and Caucasian males and females completed four oddball tasks that required sex judgements for pictures of male and female Chinese and Caucasian posers. The nature of the background (across task) and of the deviant stimuli (within task) was fully counterbalanced. Event-related potentials (ERPs) to deviant stimuli recorded from three midline sites were quantified in terms of mean amplitude for four components: N1, P2, N2 and a late positive complex (LPC; 350–700 ms). Deviants that differed from the backgrounds in sex or race elicited enhanced LPC activity. These differences were not modulated by participant race or sex. The current results replicate earlier reports of effects of poser race relative to background race on the LPC component of the ERP waveform. In addition, they indicate that an implicit race bias occurs regardless of participant's or poser's race and is not confined to a particular cultural context.

Evaluation of coronary angiographic projections to balance the clinical yield with the radiation risk

Objective: Radiation safety principles dictate that imaging procedures should minimise the radiation risks involved, without compromising diagnostic performance. This study aims to define a core set of views that maximises clinical information yield for minimum radiation risk. Angiographers would supplement these views as clinically indicated. Methods: An algorithm was developed to combine published data detailing the quality of information derived for the major coronary artery segments through the use of a common set of views in angiography with data relating to the dose–area product and scatter radiation associated with these views. Results: The optimum view set for the left coronary system comprised four views: left anterior oblique (LAO) with cranial (Cr) tilt, shallow right anterior oblique (AP-RAO) with caudal (Ca) tilt, RAO with Ca tilt and AP-RAO with Cr tilt. For the right coronary system three views were identified: LAO with Cr tilt, RAO and AP-RAO with Cr tilt. An alternative left coronary view set including a left lateral achieved minimally superior efficiency (,5%), but with an ,8% higher radiation dose to the patient and 40% higher cardiologist dose. Conclusion: This algorithm identifies a core set of angiographic views that optimises the information yield and minimises radiation risk. This basic data set would be supplemented by additional clinically determined views selected by the angiographer for each case. The decision to use additional views for diagnostic angiography and interventions would be assisted by referencing a table of relative radiation doses for the views being considered.

Risk modelling in quality clinical registries : Monitoring lesion treatment failure rate in percutaneous coronary interventions

Aims: This paper describes the development of a risk adjustment (RA) model predictive of individual lesion treatment failure in percutaneous coronary interventions (PCI) for use in a quality monitoring and improvement program. Methods and results: Prospectively collected data for 3972 consecutive revascularisation procedures (5601 lesions) performed between January 2003 and September 2011 were studied. Data on procedures to September 2009 (n = 3100) were used to identify factors predictive of lesion treatment failure. Factors identified included lesion risk class (p < 0.001), occlusion type (p < 0.001), patient age (p = 0.001), vessel system (p < 0.04), vessel diameter (p < 0.001), unstable angina (p = 0.003) and presence of major cardiac risk factors (p = 0.01). A Bayesian RA model was built using these factors with predictive performance of the model tested on the remaining procedures (area under the receiver operating curve: 0.765, Hosmer–Lemeshow p value: 0.11). Cumulative sum, exponentially weighted moving average and funnel plots were constructed using the RA model and subjectively evaluated. Conclusion: A RA model was developed and applied to SPC monitoring for lesion failure in a PCI database. If linked to appropriate quality improvement governance response protocols, SPC using this RA tool might improve quality control and risk management by identifying variation in performance based on a comparison of observed and expected outcomes.

Delisted stocks and momentum: Evidence from a new Australian dataset

We explore the impact of delisting on the performance of the momentum trading strategy in Australia. We employ a new dataset of hand-collected delisting returns for all Australian stocks and provide the first study outside the U.S. to jointly examine the effects of delisting and missing returns on the magnitude of momentum profits. In the sample of all stocks, we find that the profitability of momentum strategies depends crucially on the returns of delisted stocks, especiallyon bankrupt firms. In the sample of large stocks, however, the momentum effect remains strong after controlling for the effect of delisted stocks, in contrast to the U.S. evidence in which delisting returns can explain 40% of momentum profits. As these large stocks are less exposed to liquidity risks, the momentum effect in Australia is even more puzzling than in the U.S.