Information Matrices for Non Full Rank Subsystems

Consider the standard linear model Y=X θ + ε. If the parameter of interest is a full rank subsystem K′θ of mean parameters, the associated information matrix can be defined via an extremal representation. For rank deficient subsystems, Pukelsheim (1993) introduced the notion of generalized information matrices that inherit many properties of the information matrices. However, this notion is not a direct extension of the full rank case in the sense that the definition of the generalized information matrix applied to full rank subsystems does not lead to the usual information matrix. In this paper, we propose a definition of the information matrix via an extremal representation that encompasses the full rank and the non-full rank cases. We also study its properties and show its links with the generalized information matrices.     

Optimal designs for a mixed interference model

This paper generalizes Kunert and Martin’s (Ann Stat 28:1728–1742, 2000) method for finding optimal designs under a fixed interference model, to find optimal designs under a mixed interference model. The results are based on the properties of information matrices in fixed and mixed models given in Markiewicz (J Stat Plan Inference 59:127–137, 1997). The method is applied to find a design which is optimal for any given variances of random neighbor effects. Research partially supported by the KBN Grant Number 5 P03A 041 21.     

Technical Analysis as a Rational Tool of Decision Making for Professional Traders

The psychological background of technical analysis usage is investigated to further explain the popularity and common usage of technical analysis as an investment decision tool. Attitudes toward technical analysis of professional futures market traders and neophyte investors, represented by finance students, were examined. Technical analysis is one of the most popular methods supporting investment decisions and it is much more popular among future market traders than among neophyte investors. The concept of processing information was used to explain this phenomenon. Neophyte investors are more experiential and intuition-driven while using technical analysis models, while futures market traders are more rationally driven. Technical analysis methods help professional traders on futures markets, which are less transparent than regulated stock markets, to process information; those methods are perceived by them as rational, cognitive tools supporting their decision making.     

Cross-sex relationships at work and the impact of gender stereotypes

Organizations pride themselves on their creation of rational structures based primarily on a male perspective of interaction. Workers are expected to set aside interpersonal behaviours that do not directly contribute to task performance. As more women enter management, norms concerning appropriate interpersonal relationships at work are undergoing strain. In addition, the phenomenon of mutual sexual attractions between co-workers is demanding attention. This study systematically describes attitudes, attributions and anticipated consequences of mutual sexual attractions at work. Findings suggest that gender stereotypes are significant factors in people's judgments of persons involved in sexual attractions at work.Irene Devine is currently professor and Director, School of Administration and Information Management, Ryerson Polytechnical Institute, Toronto. She was formerly Associate Dean, Faculty of Commerce and Administration, Concordia University, Montreal. Her research interests include organizational crisis, and women in organizations. She has recently co-authored a management textbook.Dorothy Markiewicz is currently Associate Professor, departments of Psychology and Applied Social Science, and Program Director, Centre for Human Relations and Community Studies, Concordia University, Montreal. She was formerly Chairperson. Applied Social Science. Her research interests include sex differences and stereotypes, adult development, and friendship.     

MODEL UNCERTAINTY AND EXCHANGE RATE VOLATILITY*

This article proposes an explanation for shifts in the volatility of exchange‐rate returns. Agents are uncertain about the true data generating model and deal with this uncertainty by making inference on the models and their parameters' approach, I call model learning. Model learning may lead agents to focus excessively on a subset of fundamental variables. Consequently, exchange‐rate volatility is determined by the dynamics of these fundamentals and changes as agents alter models. I investigate the empirical relevance of model learning and find that the change in volatility of GBP/USD in 1993 was triggered by a shift between models.     

Optimality and efficiency of circular neighbor balanced designs for correlated observations

The purpose of this paper is to apply the Kunert and Martins (2000b) method for finding optimal designs into the case of dependence. Using this method we study optimality of circular neighbor balanced designs at distances 1 and 2 under the one-dimensional interference model with errors correlated according to a circular autoregressive process. We determine the efficiency of binary designs for specified values of correlation coefficient, for which these designs are not optimal.Research partially supported by the KBN Grant Number 5 P03A 041 21.     

Universally optimal designs under mixed interference models with and without block effects

The literature on neighbor designs as introduced by Rees (Biometrics 23:779–791, 1967) is mainly devoted to construction methods, providing few results on their statistical properties, such as efficiency and optimality. A review of the available literature, with special emphasis on the optimality of neighbor designs under various fixed effects interference models, is given in Filipiak and Markiewicz (Commun Stat Theory Methods 46:1127–1143, 2017). The aim of this paper is to verify whether the designs presented by Filipiak and Markiewicz (2017) as universally optimal under fixed interference models are still universally optimal under models with random interference effects. Moreover, it is shown that for a specified covariance matrix of random interference effects, a universally optimal design under mixed interference models with block effects is universally optimal over a wider class of designs. In this paper the method presented by Filipiak and Markiewicz (Metrika 65:369–386, 2007) is extended and then applied to mixed interference models without or with block effects.     

An explanatory analysis of perceived risk decision weights (perceived-risk attitudes) and perceived benefit decision weights (perceived-benefit attitudes) in risk-value models

Abstract

All decision making requires a trade-off between risks and values. While Markowitz defined risk as the variance of returns (thus reasoning that investors should consider it as undesirable), the more general risk–value framework allows risk to be defined as a person’s subjective judgments. Psychological risk–return models go further, decomposing observed behavior (risk taking) into two processes: (1) a judgment of benefits and risks and (2) a trade-off between perceived benefits and perceived risks, with a person-specific willingness to trade-off units of returns (benefits) for units of risk, conceptualized as attitude toward perceived risk (PRA) and attitude toward perceived benefits (PBA). PRA and PBA describe the degree to which people find perceived risks and benefits attractive, all other things being equal, and are assumed to be relatively stable across situations and domains. We test this assumption in an empirical study, checking the temporal stability of PRA and PBA (using the a Domain-Specific Risk-Taking [DOSPERT] scale ) and the cross-task stability of PBA (performing comparisons between the DOSPERT and the Columbia Card Task[CCT]). Finally, we explain both PRA and PBA using the Big Five personality dimensions and Stimulating–Instrumental Risk Inventory (SIRI), showing that PBA weights increase with openness to experience, while the negative effect of perceived risk on risk taking (PRA) increases with conscientiousness and decreases with stimulating risk taking. The results show that PBA and PRA can be treated as traits which, in some instances at least, are stable across time and tasks, and which can be partially explained by personality, providing a link to the idea of a personality dependent ‘ideal point’ for risk preference.