Constructing common-factor portfolios

In this paper we construct common-factor portfolios using a novel linear transformation of standard factor models extracted from large data sets of asset returns. The simple transformation proposed here keeps the basic properties of the usual factor transformations, although some new interesting properties are further attached to them. Some theoretical advantages are shown to be present. Also, their practical importance is confirmed in two applications: the performance of common-factor portfolios are shown to be superior to that of asset returns and factors commonly employed in the finance literature.

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.

Luxury fashion: The role of innovation as a key contributing factor in the development of luxury fashion goods and sustainable fashion design

Luxury is a quality that is difficult to define as the historical concept of luxury appears to be both dynamic and culturally specific. The everyday definition explains a ‘luxury’ in relation to a necessity: a luxury (product or service) is defined as something that consumers want rather than need. However, the growth of global markets has seen a boom in what are now referred to as ‘luxury brands’. This branding of products as luxury has resulted in a change in the way consumers understand luxury goods and services. In their attempts to characterize a luxury brand, Fionda & Moore in their article “The anatomy of a Luxury Brand” summarize a range of critical conditions that are in addition to product branding “... including product and design attributes of quality, craftsmanship and innovative, creative and unique products” (Fionda & Moore, 2009). For the purposes of discussing fashion design however, quality and craftsmanship are inseparable while creativity and innovation exist under different conditions. The terms ‘creative’ and ‘innovative’ are often used inter-changeably and are connected with most descriptions of the design process, defining ‘design’ and ‘fashion’ in many cases. Christian Marxt and Fredrik Hacklin identify this condition in their paper “Design, product development, innovation: all the same in the end?”(Marxt & Hacklin, 2005) and suggest that design communities should be aware that the distinction between these terms, whilst once quite definitive, is becoming narrow to a point where they will mean the same thing. In relation to theory building in the discipline this could pose significant problems. Brett Richards (2003) identifies innovation as different from creativity in that innovation aims to transform and implement rather than simply explore and invent. Considering this distinction, in particular relation to luxury branding, may affect the way in which design can contribute to a change in the way luxury fashion goods might be perceived in a polarised fashion market, namely suggesting that ‘luxury’ is what consumers need rather than the ‘pile it high, sell it cheap’ fashion that the current market dynamic would indicate they want. This paper attempts to explore the role of innovation as a key contributing factor in luxury concepts, in particular the relationship between innovation and creativity, the conditions which enable innovation, the role of craftsmanship in innovation and design innovation in relation to luxury fashion products. An argument is presented that technological innovation can be demonstrated as a common factor in the development of luxury fashion product and that the connection between designer and maker will play an important role in the development of luxury fashion goods for a sustainable fashion industry.

Factor models, VARMA processes and parameter instability with applications in macroeconomics

Avec les avancements de la technologie de l'information, les données temporelles économiques et financières sont de plus en plus disponibles. Par contre, si les techniques standard de l'analyse des séries temporelles sont utilisées, une grande quantité d'information est accompagnée du problème de dimensionnalité. Puisque la majorité des séries d'intérêt sont hautement corrélées, leur dimension peut être réduite en utilisant l'analyse factorielle. Cette technique est de plus en plus populaire en sciences économiques depuis les années 90. Étant donnée la disponibilité des données et des avancements computationnels, plusieurs nouvelles questions se posent. Quels sont les effets et la transmission des chocs structurels dans un environnement riche en données? Est-ce que l'information contenue dans un grand ensemble d'indicateurs économiques peut aider à mieux identifier les chocs de politique monétaire, à l'égard des problèmes rencontrés dans les applications utilisant des modèles standards? Peut-on identifier les chocs financiers et mesurer leurs effets sur l'économie réelle? Peut-on améliorer la méthode factorielle existante et y incorporer une autre technique de réduction de dimension comme l'analyse VARMA? Est-ce que cela produit de meilleures prévisions des grands agrégats macroéconomiques et aide au niveau de l'analyse par fonctions de réponse impulsionnelles? Finalement, est-ce qu'on peut appliquer l'analyse factorielle au niveau des paramètres aléatoires? Par exemple, est-ce qu'il existe seulement un petit nombre de sources de l'instabilité temporelle des coefficients dans les modèles macroéconomiques empiriques? Ma thèse, en utilisant l'analyse factorielle structurelle et la modélisation VARMA, répond à ces questions à travers cinq articles. Les deux premiers chapitres étudient les effets des chocs monétaire et financier dans un environnement riche en données. Le troisième article propose une nouvelle méthode en combinant les modèles à facteurs et VARMA. Cette approche est appliquée dans le quatrième article pour mesurer les effets des chocs de crédit au Canada. La contribution du dernier chapitre est d'imposer la structure à facteurs sur les paramètres variant dans le temps et de montrer qu'il existe un petit nombre de sources de cette instabilité. Le premier article analyse la transmission de la politique monétaire au Canada en utilisant le modèle vectoriel autorégressif augmenté par facteurs (FAVAR). Les études antérieures basées sur les modèles VAR ont trouvé plusieurs anomalies empiriques suite à un choc de la politique monétaire. Nous estimons le modèle FAVAR en utilisant un grand nombre de séries macroéconomiques mensuelles et trimestrielles. Nous trouvons que l'information contenue dans les facteurs est importante pour bien identifier la transmission de la politique monétaire et elle aide à corriger les anomalies empiriques standards. Finalement, le cadre d'analyse FAVAR permet d'obtenir les fonctions de réponse impulsionnelles pour tous les indicateurs dans l'ensemble de données, produisant ainsi l'analyse la plus complète à ce jour des effets de la politique monétaire au Canada. Motivée par la dernière crise économique, la recherche sur le rôle du secteur financier a repris de l'importance. Dans le deuxième article nous examinons les effets et la propagation des chocs de crédit sur l'économie réelle en utilisant un grand ensemble d'indicateurs économiques et financiers dans le cadre d'un modèle à facteurs structurel. Nous trouvons qu'un choc de crédit augmente immédiatement les diffusions de crédit (credit spreads), diminue la valeur des bons de Trésor et cause une récession. Ces chocs ont un effet important sur des mesures d'activité réelle, indices de prix, indicateurs avancés et financiers. Contrairement aux autres études, notre procédure d'identification du choc structurel ne requiert pas de restrictions temporelles entre facteurs financiers et macroéconomiques. De plus, elle donne une interprétation des facteurs sans restreindre l'estimation de ceux-ci. Dans le troisième article nous étudions la relation entre les représentations VARMA et factorielle des processus vectoriels stochastiques, et proposons une nouvelle classe de modèles VARMA augmentés par facteurs (FAVARMA). Notre point de départ est de constater qu'en général les séries multivariées et facteurs associés ne peuvent simultanément suivre un processus VAR d'ordre fini. Nous montrons que le processus dynamique des facteurs, extraits comme combinaison linéaire des variables observées, est en général un VARMA et non pas un VAR comme c'est supposé ailleurs dans la littérature. Deuxièmement, nous montrons que même si les facteurs suivent un VAR d'ordre fini, cela implique une représentation VARMA pour les séries observées. Alors, nous proposons le cadre d'analyse FAVARMA combinant ces deux méthodes de réduction du nombre de paramètres. Le modèle est appliqué dans deux exercices de prévision en utilisant des données américaines et canadiennes de Boivin, Giannoni et Stevanovic (2010, 2009) respectivement. Les résultats montrent que la partie VARMA aide à mieux prévoir les importants agrégats macroéconomiques relativement aux modèles standards. Finalement, nous estimons les effets de choc monétaire en utilisant les données et le schéma d'identification de Bernanke, Boivin et Eliasz (2005). Notre modèle FAVARMA(2,1) avec six facteurs donne les résultats cohérents et précis des effets et de la transmission monétaire aux États-Unis. Contrairement au modèle FAVAR employé dans l'étude ultérieure où 510 coefficients VAR devaient être estimés, nous produisons les résultats semblables avec seulement 84 paramètres du processus dynamique des facteurs. L'objectif du quatrième article est d'identifier et mesurer les effets des chocs de crédit au Canada dans un environnement riche en données et en utilisant le modèle FAVARMA structurel. Dans le cadre théorique de l'accélérateur financier développé par Bernanke, Gertler et Gilchrist (1999), nous approximons la prime de financement extérieur par les credit spreads. D'un côté, nous trouvons qu'une augmentation non-anticipée de la prime de financement extérieur aux États-Unis génère une récession significative et persistante au Canada, accompagnée d'une hausse immédiate des credit spreads et taux d'intérêt canadiens. La composante commune semble capturer les dimensions importantes des fluctuations cycliques de l'économie canadienne. L'analyse par décomposition de la variance révèle que ce choc de crédit a un effet important sur différents secteurs d'activité réelle, indices de prix, indicateurs avancés et credit spreads. De l'autre côté, une hausse inattendue de la prime canadienne de financement extérieur ne cause pas d'effet significatif au Canada. Nous montrons que les effets des chocs de crédit au Canada sont essentiellement causés par les conditions globales, approximées ici par le marché américain. Finalement, étant donnée la procédure d'identification des chocs structurels, nous trouvons des facteurs interprétables économiquement. Le comportement des agents et de l'environnement économiques peut varier à travers le temps (ex. changements de stratégies de la politique monétaire, volatilité de chocs) induisant de l'instabilité des paramètres dans les modèles en forme réduite. Les modèles à paramètres variant dans le temps (TVP) standards supposent traditionnellement les processus stochastiques indépendants pour tous les TVPs. Dans cet article nous montrons que le nombre de sources de variabilité temporelle des coefficients est probablement très petit, et nous produisons la première évidence empirique connue dans les modèles macroéconomiques empiriques. L'approche Factor-TVP, proposée dans Stevanovic (2010), est appliquée dans le cadre d'un modèle VAR standard avec coefficients aléatoires (TVP-VAR). Nous trouvons qu'un seul facteur explique la majorité de la variabilité des coefficients VAR, tandis que les paramètres de la volatilité des chocs varient d'une façon indépendante. Le facteur commun est positivement corrélé avec le taux de chômage. La même analyse est faite avec les données incluant la récente crise financière. La procédure suggère maintenant deux facteurs et le comportement des coefficients présente un changement important depuis 2007. Finalement, la méthode est appliquée à un modèle TVP-FAVAR. Nous trouvons que seulement 5 facteurs dynamiques gouvernent l'instabilité temporelle dans presque 700 coefficients.

Common factors in Latin America's business cycles

This paper constructs new business cycle indices for Argentina, Brazil, Chile, and Mexico based on common dynamic factors extracted from a comprehensive set of sectoral output, external trade, fiscal and financial variables. The analysis spans the 135 years since the insertion of these economies into the global economy in the 1870s. The constructed indices are used to derive a business cyc1e chronology for these countries and characterize a set of new stylized facts. In particular, we show that ali four countries have historically displayed a striking combination of high business cyc1e volatility and persistence relative to advanced country benchmarks. Volatility changed considerably over time, however, being very high during early formative decades through the Great Depression, and again during the 1970s and ear1y 1980s, before declining sharply in three of the four countries. We also identify a sizeable common factor across the four economies which variance decompositions ascribe mostly to foreign interest rates and shocks to commodity terms of trade.

Common factors method to predict the carcass composition tissue in kid goats

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Towards a taxonomy of common factors in psychotherapy-results of an expert survey

BACKGROUND: How change comes about is hotly debated in psychotherapy research. One camp considers 'non-specific' or 'common factors', shared by different therapy approaches, as essential, whereas researchers of the other camp consider specific techniques as the essential ingredients of change. This controversy, however, suffers from unclear terminology and logical inconsistencies. The Taxonomy Project therefore aims at contributing to the definition and conceptualization of common factors of psychotherapy by analyzing their differential associations to standard techniques. METHODS: A review identified 22 common factors discussed in psychotherapy research literature. We conducted a survey, in which 68 psychotherapy experts assessed how common factors are implemented by specific techniques. Using hierarchical linear models, we predicted each common factor by techniques and by experts' age, gender and allegiance to a therapy orientation. RESULTS: Common factors differed largely in their relevance for technique implementation. Patient engagement, Affective experiencing and Therapeutic alliance were judged most relevant. Common factors also differed with respect to how well they could be explained by the set of techniques. We present detailed profiles of all common factors by the (positively or negatively) associated techniques. There were indications of a biased taxonomy not covering the embodiment of psychotherapy (expressed by body-centred techniques such as progressive muscle relaxation, biofeedback training and hypnosis). Likewise, common factors did not adequately represent effective psychodynamic and systemic techniques. CONCLUSION: This taxonomic endeavour is a step towards a clarification of important core constructs of psychotherapy. KEY PRACTITIONER MESSAGE: This article relates standard techniques of psychotherapy (well known to practising therapists) to the change factors/change mechanisms discussed in psychotherapy theory. It gives a short review of the current debate on the mechanisms by which psychotherapy works. We provide detailed profiles of change mechanisms and how they may be generated by practice techniques.

Multivariate methods to identify cancer-related symptom clusters

Multivariate methods are required to assess the interrelationships among multiple, concurrent symptoms. We examined the conceptual and contextual appropriateness of commonly used multivariate methods for cancer symptom cluster identification. From 178 publications identified in an online database search of Medline, CINAHL, and PsycINFO, limited to articles published in English, 10 years prior to March 2007, 13 cross-sectional studies met the inclusion criteria. Conceptually, common factor analysis (FA) and hierarchical cluster analysis (HCA) are appropriate for symptom cluster identification, not principal component analysis. As a basis for new directions in symptom management, FA methods are more appropriate than HCA. Principal axis factoring or maximum likelihood factoring, the scree plot, oblique rotation, and clinical interpretation are recommended approaches to symptom cluster identification.

Alternative analytical methods for the identification of cancer-related symptom clusters

Advances in symptom management strategies through a better understanding of cancer symptom clusters depend on the identification of symptom clusters that are valid and reliable. The purpose of this exploratory research was to investigate alternative analytical approaches to identify symptom clusters for patients with cancer, using readily accessible statistical methods, and to justify which methods of identification may be appropriate for this context. Three studies were undertaken: (1) a systematic review of the literature, to identify analytical methods commonly used for symptom cluster identification for cancer patients; (2) a secondary data analysis to identify symptom clusters and compare alternative methods, as a guide to best practice approaches in cross-sectional studies; and (3) a secondary data analysis to investigate the stability of symptom clusters over time. The systematic literature review identified, in 10 years prior to March 2007, 13 cross-sectional studies implementing multivariate methods to identify cancer related symptom clusters. The methods commonly used to group symptoms were exploratory factor analysis, hierarchical cluster analysis and principal components analysis. Common factor analysis methods were recommended as the best practice cross-sectional methods for cancer symptom cluster identification. A comparison of alternative common factor analysis methods was conducted, in a secondary analysis of a sample of 219 ambulatory cancer patients with mixed diagnoses, assessed within one month of commencing chemotherapy treatment. Principal axis factoring, unweighted least squares and image factor analysis identified five consistent symptom clusters, based on patient self-reported distress ratings of 42 physical symptoms. Extraction of an additional cluster was necessary when using alpha factor analysis to determine clinically relevant symptom clusters. The recommended approaches for symptom cluster identification using nonmultivariate normal data were: principal axis factoring or unweighted least squares for factor extraction, followed by oblique rotation; and use of the scree plot and Minimum Average Partial procedure to determine the number of factors. In contrast to other studies which typically interpret pattern coefficients alone, in these studies symptom clusters were determined on the basis of structure coefficients. This approach was adopted for the stability of the results as structure coefficients are correlations between factors and symptoms unaffected by the correlations between factors. Symptoms could be associated with multiple clusters as a foundation for investigating potential interventions. The stability of these five symptom clusters was investigated in separate common factor analyses, 6 and 12 months after chemotherapy commenced. Five qualitatively consistent symptom clusters were identified over time (Musculoskeletal-discomforts/lethargy, Oral-discomforts, Gastrointestinaldiscomforts, Vasomotor-symptoms, Gastrointestinal-toxicities), but at 12 months two additional clusters were determined (Lethargy and Gastrointestinal/digestive symptoms). Future studies should include physical, psychological, and cognitive symptoms. Further investigation of the identified symptom clusters is required for validation, to examine causality, and potentially to suggest interventions for symptom management. Future studies should use longitudinal analyses to investigate change in symptom clusters, the influence of patient related factors, and the impact on outcomes (e.g., daily functioning) over time.

The effect of screen size on mission commander's situation awareness

Situation awareness lost is a common factor leading to human error in the aviation industry. However, few studies have investigated the effect on situation awareness where the control interface is a touch-screen device that supports simultaneous multi-touch input and information output. This research aims to conduct an experiment to evaluate the difference in situation awareness on a large screen device, DiamondTouch (DT107), and a small screen device, iPad, both with multi-touch interactive functions. The Interface Operation and Situation Awareness Testing Simulator (IOSATS), is a simulator to test the three basis interface operations (Search Target, Information Reading, and Change Detection) by implementing a simplified search and rescue scenario. The result of this experiment will provide reliable data for future research for improving operator's situation awareness in the avionic domain.

Managing creativity on the margins : a comparative study of Beijing’s Songzhuang Art District and Hangzhou’s White Horse Lake Creative Eco-City

In the past decade the ‘creative cluster’ has become a driver of urban renewal in China. Many cluster developments attract human capital and investment to post-industrial spaces. This paper looks at two developments which are more post-agricultural than post-industrial: the first is Songzhuang, a large scale contemporary art community situated on the eastern fringe of Beijing, the second is Hangzhou’s White Horse Lake Creative Eco-City, a ‘mixed variety’ cluster model which integrates elements of art, fashion, design and animation. The common factor in both cases is how they came into existence. In both districts urban creative workers moved into a rural environment. Drawing on interviews with planners, officials, and residents we investigate the challenges of sustaining such fringe clusters.

Proteases and proteomics : cutting to the core of human skin pathologies

Preserving the integrity of the skin's outermost layer (the epidermis) is vital for humans to thrive in hostile surroundings. Covering the entire body, the epidermis forms a thin but impenetrable cellular cordon that repels external assaults and blocks escape of water and electrolytes from within. This structure exists in a perpetual state of regeneration where the production of new cellular subunits at the base of the epidermis is offset by the release of terminally differentiated corneocytes from the surface. It is becoming increasingly clear that proteases hold vital roles in assembling and maintaining the epidermal barrier. More than 30 proteases are expressed by keratinocytes or infiltrating immune cells and the activity of each must be maintained within narrow limits and confined to the correct time and place. Accordingly, over- or under-exertion of proteolytic activity is a common factor in a multitude of skin disorders that range in severity from relatively mild to life-threatening. This review explores the current state of knowledge on the involvement of proteases in skin diseases and the latest findings from proteomic and transcriptomic studies focused on uncovering novel (patho)physiological roles for these enzymes.