Macroeconomic forecasting with mixed-frequency data: forecasting output growth in the United States

Many macroeconomic series, such as U.S. real output growth, are sampled quarterly, although potentially useful predictors are often observed at a higher frequency. We look at whether a mixed data-frequency sampling (MIDAS) approach can improve forecasts of output growth. The MIDAS specification used in the comparison uses a novel way of including an autoregressive term. We find that the use of monthly data on the current quarter leads to significant improvement in forecasting current and next quarter output growth, and that MIDAS is an effective way to exploit monthly data compared with alternative methods.

Wireless power and data transfer via a common inductive link using frequency division multiplexing

For wireless power transfer (WPT) systems, communication between the primary side and the pickup side is a challenge because of the large air gap and magnetic interferences. A novel method, which integrates bidirectional data communication into a high-power WPT system, is proposed in this paper. The power and data transfer share the same inductive link between coreless coils. Power/data frequency division multiplexing technique is applied, and the power and data are transmitted by employing different frequency carriers and controlled independently. The circuit model of the multiband system is provided to analyze the transmission gain of the communication channel, as well as the power delivery performance. The crosstalk interference between two carriers is discussed. In addition, the signal-to-noise ratios of the channels are also estimated, which gives a guideline for the design of mod/demod circuits. Finally, a 500-W WPT prototype has been built to demonstrate the effectiveness of the proposed WPT system.

Using data mining with time series data in short-term stocks prediction

Data Mining (DM) methods are being increasingly used in prediction with time series data, in addition to traditional statistical approaches. This paper presents a literature review of the use of DM with time series data, focusing on short- time stocks prediction. This is an area that has been attracting a great deal of attention from researchers in the field. The main contribution of this paper is to provide an outline of the use of DM with time series data, using mainly examples related with short-term stocks prediction. This is important to a better understanding of the field. Some of the main trends and open issues will also be introduced.

Valuuttasuojaus kansainvälisissä osakeportfolioissa - eurosijoittajan näkökulma

Tämän tutkimuksen tarkoituksena on selvittää eurosijoittajan näkökulmasta tehokkain strategia kansainvälisen osakeportfolion valuuttariskin suojaamiseen. Tutkimuksessa tarkastellaan akateemisissa tutkimuksissa eniten käsiteltyjä valuuttasuojausstrategioita ja pyritään tunnistamaan niistä tieteellisesti valideimmat metodit tutkimuksen empiiriseen osioon. Valuuttasuojauksen tehokkuutta tullaan mittaamaan niin riskin kuin tuoton näkökulmista. Empiirisessä osiossa käytetään aineistona kahdeksan eri valtion osakemarkkinaindeksien ja valuuttojen spot- ja termiinikurssien kuukausittaisia tuottoja niin, että tarkastelu tapahtuu euroalueen sijoittajan näkökulmasta. Tutkimuksen aikaväli on 31.12.2004 - 31.12.2010. Tutkimuksessa päädyttiin suosittamaan 50 % valuuttariskin suojausastetta eurosijoittajan näkökulmasta. Kyseinen strategia alensi parhaiten kansainvälisen sijoittajan portfolion riskiä tutkitulla aikavälillä, eikä strategia myöskään heikentänyt merkittävästi portfolion tuottoa. Absoluuttisella kumulatiivisella tuotolla mitattuna suojaamaton osakeportfolio oli tutkimuksen aikavälillä paras, johtuen pääosin vuoden 2010 eurokriisistä, jonka vuoksi euro heikentyi voimakkaasti muita valuuttoja vastaan. Ennen kriisiä ”selektiivinen” valuuttasuojausstrategia oli tuotoilla (sekä kumulatiivinen että riskikorjattu) mitattuna paras.

Modeling Energy Futures Returns With Markov Regime Switching Model

Financial time series have a tendency of abruptly changing their behavior and maintain this behavior for several consecutive periods, and commodity futures returns are not an exception. This quality proposes that nonlinear models, as opposed to linear models, can more accurately describe returns and volatility. Markov regime switching models are able to match this behavior and have become a popular way to model financial time series. This study uses Markov regime switching model to describe the behavior of energy futures returns on a commodity level, because studies show that commodity futures are a heterogeneous asset class. The purpose of this thesis is twofold. First, determine how many regimes characterize individual energy commodities’ returns in different return frequencies. Second, study the characteristics of these regimes. We extent the previous studies on the subject in two ways: We allow for the possibility that the number of regimes may exceed two, as well as conduct the research on individual commodities rather than on commodity indices or subgroups of these indices. We use daily, weekly and monthly time series of Brent crude oil, WTI crude oil, natural gas, heating oil and gasoil futures returns over 1994–2014, where available, to carry out the study. We apply the likelihood ratio test to determine the sufficient number of regimes for each commodity and data frequency. Then the time series are modeled with Markov regime switching model to obtain the return distribution characteristics of each regime, as well as the transition probabilities of moving between regimes. The results for the number of regimes suggest that daily energy futures return series consist of three to six regimes, whereas weekly and monthly returns for all energy commodities display only two regimes. When the number of regimes exceeds two, there is a tendency for the time series of energy commodities to form groups of regimes. These groups are usually quite persistent as a whole because probability of a regime switch inside the group is high. However, individual regimes in these groups are not persistent and the process oscillates between these regimes frequently. Regimes that are not part of any group are generally persistent, but show low ergodic probability, i.e. rarely prevail in the market. This study also suggests that energy futures return series characterized with two regimes do not necessarily display persistent bull and bear regimes. In fact, for the majority of time series, bearish regime is considerably less persistent. Rahoituksen aikasarjoilla on taipumus arvaamattomasti muuttaa käyttäytymistään ja jatkaa tätä uutta käyttäytymistä useiden periodien ajan, eivätkä hyödykefutuurien tuotot tee tähän poikkeusta. Tämän ominaisuuden johdosta lineaaristen mallien sijasta epälineaariset mallit pystyvät tarkemmin kuvailemaan esimerkiksi tuottojen jakauman parametreja. Markov regiiminvaihtomallit pystyvät vangitsemaan tämän ominaisuuden ja siksi niistä on tullut suosittuja rahoituksen aikasarjojen mallintamisessa. Tämä tutkimus käyttää Markov regiiminvaihtomallia kuvaamaan yksittäisten energiafutuurien tuottojen käyttäytymistä, sillä tutkimukset osoittavat hyödykefutuurien olevan hyvin heterogeeninen omaisuusluokka. Tutkimuksen tarkoitus on selvittää, kuinka monta regiimiä tarvitaan kuvaamaan energiafutuurien tuottoja eri tuottofrekvensseillä ja mitkä ovat näiden regiimien ominaisuudet. Aiempaa tutkimusta aiheesta laajennetaan määrittämällä regiimien lukumäärä tilastotieteellisen testauksen menetelmin sekä tutkimalla energiafutuureja yksittäin; ei indeksi- tai alaindeksitasolla. Tutkimuksessa käytetään päivä-, viikko- ja kuukausiaikasarjoja Brent-raakaöljyn, WTI-raakaöljyn, maakaasun, lämmitysöljyn ja polttoöljyn tuotoista aikaväliltä 1994–2014, siltä osin kuin aineistoa on saatavilla. Likelihood ratio -testin avulla estimoidaan kaikille aikasarjoille regiimien määrä,jonka jälkeen Markov regiiminvaihtomallia hyödyntäen määritetään yksittäisten regiimientuottojakaumien ominaisuudet sekä regiimien välinen transitiomatriisi. Tulokset regiimien lukumäärän osalta osoittavat, että energiafutuurien päiväkohtaisten tuottojen aikasarjoissa regiimien lukumäärä vaihtelee kolmen ja kuuden välillä. Viikko- ja kuukausituottojen kohdalla kaikkien energiafutuurien prosesseissa regiimien lukumäärä on kaksi. Kun regiimejä on enemmän kuin kaksi, on prosessilla taipumus muodostaa regiimeistä koostuvia ryhmiä. Prosessi pysyy ryhmän sisällä yleensä pitkään, koska todennäköisyys siirtyä ryhmään kuuluvien regiimien välillä on suuri. Yksittäiset regiimit ryhmän sisällä eivät kuitenkaan ole kovin pysyviä. Näin ollen prosessi vaihtelee ryhmän sisäisten regiimien välillä tiuhaan. Regiimit, jotka eivät kuulu ryhmään, ovat yleensä pysyviä, mutta prosessi ajautuu niihin vain harvoin, sillä todennäköisyys siirtyä muista regiimeistä niihin on pieni. Tutkimuksen tulokset osoittavat myös, että prosesseissa, joita ohjaa kaksi regiimiä, nämä regiimit eivät välttämättä ole pysyvät bull- ja bear-markkinatilanteet. Tulokset osoittavat sen sijaan, että bear-markkinatilanne on energiafutuureissa selvästi vähemmän pysyvä.

Exchange rate pass-through to prices in macrodata: a comparative sensitivity analysis

This paper compares exchange rate pass-through to aggregate prices in the US, Germany and Japan across a number of dimensions. Building on the empirical approaches in the recent literature, our contribution is to perform a thorough sensitivity analysis of pass-through estimates. We find that the econometric method, data frequency and variable proxy employed matter for the precision of details, yet they often agree on some general trends. Thus, pass-through to import prices has declined in the 1990s relative to the 1980s, pass-through to export prices remains country-specific and pass-through to consumer prices is nowadays negligible in all three economies we considered.

Taylor rule with hidden states

This work evaluates empirically the Taylor rule for the US and Brazil using Kalman Filter and Markov-Switching Regimes. We show that the parameters of the rule change significantly with variations in both output and output gap proxies, considering hidden variables and states. Such conclusions call naturally for robust optimal monetary rules. We also show that Brazil and US have very contrasting parameters, first because Brazil presents time-varying intercept, second because of the rigidity in the parameters of the Brazilian Taylor rule, regardless the output gap proxy, data frequency or sample data. Finally, we show that the long-run inflation parameter of the US Taylor rule is less than one in many periods, contrasting strongly with Orphanides (forthcoming) and Clarida, Gal´i and Gertler (2000), and the same happens with Brazilian monthly data.

Mapas de zonas de risco de epidemias e zoneamento agroclimático para o Cancro Cítrico no Estado de São Paulo

O cancro cítrico, causado pela bactéria Xanthomonas axonopodis pv. citri Valterin et alii 1995, é uma doença conhecida mundialmente e sempre constituiu séria ameaça para a citricultura brasileira. O objetivo do presente trabalho foi analisar as condições climáticas do Estado de São Paulo e desenvolver mapas de zonas de maior risco de epidemias de cancro cítrico. Foram utilizados dados meteorológicos referentes aos anos de 2002 a 2005, os quais foram baseados no modelo de previsão desenvolvido por Campbell & Madden (4) e Hau & Kranz (10). A freqüência dos dados foi horária e quando alguma estação apresentava falha, esses eram extrapolados da estação mais próxima. Foram contabilizados os índices de favorabilidade e posteriormente calculadas as porcentagens de dias favoráveis à ocorrência da doença no período de um ano. A partir destas informações, foram gerados os mapas temáticos do Estado de São Paulo, com a distribuição espacial da porcentagem de dias favoráveis à ocorrência de cancro cítrico. A região Noroeste do Estado foi a que apresentou a maior porcentagem de dias favoráveis à ocorrência de cancro cítrico.

Dependência de exercício físico em academias de ginástica e sua interface com suplementação e imagem corporal

O Brasil é o segundo país no mundo em número de academias de ginástica, contando atualmente com cerca de 30 mil unidades. Apesar da transição no modelo de gestão e filosofia das academias do fitness para o wellness, muitas ainda propagam em seus ambientes o culto ao corpo magro e atlético, dietas sem fundamentação nutricional e consumo descontrolado de suplementos. Crescem as evidências de que uma parcela significativa dos frequentadores de academias desenvolve um comprometimento exacerbado à prática de exercícios físicos, gerando até uma dependência patológica. O objetivo foi determinar a associação entre dependência de exercício físico (DEF), consumo de suplementos e insatisfação da imagem corporal em frequentadores de academias. Para tanto foi empregada a Escala de Comprometimento com Exercício Físico (CEF) em uma amostra de 227 frequentadores, maiores de 19 anos, de ambos os sexo em três academias. Foi realizada entrevista individual com emprego de anamnese nutricional para determinar o perfil de consumo suplementar, avaliação antropométrica, da imagem corporal, do compromisso ao exercício físico assim como de participação na academia. A frequência de DEF nas academias foi de 66% e sendo que as chances estimadas deste ser consumidor de suplementos de 4,53. Os indivíduos dependentes de exercício físico são jovens, com maior chance de pertencer ao sexo masculino, frequentar a academia > 5 vezes por semana, consumir mais de um tipo de suplemento e praticar musculação. A frequência de insatisfação com a imagem corporal foi alta tanto entre homens (50,9%) como mulheres (78,4%).

'Taking a sickie':Job satisfaction and job involvement as interactive predictors of absenteeism in a public organization

Correlations between absenteeism and work attitudes such as job satisfaction have often been found to be disappointingly weak. As prior work reveals, this might be due to ignoring interactive effects of attitudes with different attitude targets (e.g. job involvement and organizational commitment). Drawing on basic principles in personality research and insights about the situational variability of job satisfaction judgments, we proposed that similar interactions should be present also for attitudes with the same target. More specifically, it was predicted that job involvement affects absenteeism more if job satisfaction is low as this indicates a situation with weak constraints. Both attitudes were assessed in a sample of 436 employees working in a large civil service organization, and two indexes of absence data (frequency and time lost) were drawn from personnel records covering a 12-month period following the survey. Whereas simple correlations were not significant, a moderated regression documented that the hypothesized interaction was significant for both indicators of absence behaviour. As a range of controls (e.g. age, gender, job level) were accounted for, these findings lend strong support to the importance of this new, specific form of attitude interaction. Thus, we encourage researchers not only to consider interactions of attitudes with a different focus (e.g. job vs. organization) but also interactions between job involvement and job satisfaction as this will yield new insights into the complex function of attitudes in influencing absenteeism. © 2007 The British Psychological Society.

Forecasting exchange rates in the presence of instabilities

Many exchange rate papers articulate the view that instabilities constitute a major impediment to exchange rate predictability. In this thesis we implement Bayesian and other techniques to account for such instabilities, and examine some of the main obstacles to exchange rate models' predictive ability. We first consider in Chapter 2 a time-varying parameter model in which fluctuations in exchange rates are related to short-term nominal interest rates ensuing from monetary policy rules, such as Taylor rules. Unlike the existing exchange rate studies, the parameters of our Taylor rules are allowed to change over time, in light of the widespread evidence of shifts in fundamentals - for example in the aftermath of the Global Financial Crisis. Focusing on quarterly data frequency from the crisis, we detect forecast improvements upon a random walk (RW) benchmark for at least half, and for as many as seven out of 10, of the currencies considered. Results are stronger when we allow the time-varying parameters of the Taylor rules to differ between countries. In Chapter 3 we look closely at the role of time-variation in parameters and other sources of uncertainty in hindering exchange rate models' predictive power. We apply a Bayesian setup that incorporates the notion that the relevant set of exchange rate determinants and their corresponding coefficients, change over time. Using statistical and economic measures of performance, we first find that predictive models which allow for sudden, rather than smooth, changes in the coefficients yield significant forecast improvements and economic gains at horizons beyond 1-month. At shorter horizons, however, our methods fail to forecast better than the RW. And we identify uncertainty in coefficients' estimation and uncertainty about the precise degree of coefficients variability to incorporate in the models, as the main factors obstructing predictive ability. Chapter 4 focus on the problem of the time-varying predictive ability of economic fundamentals for exchange rates. It uses bootstrap-based methods to uncover the time-specific conditioning information for predicting fluctuations in exchange rates. Employing several metrics for statistical and economic evaluation of forecasting performance, we find that our approach based on pre-selecting and validating fundamentals across bootstrap replications generates more accurate forecasts than the RW. The approach, known as bumping, robustly reveals parsimonious models with out-of-sample predictive power at 1-month horizon; and outperforms alternative methods, including Bayesian, bagging, and standard forecast combinations. Chapter 5 exploits the predictive content of daily commodity prices for monthly commodity-currency exchange rates. It builds on the idea that the effect of daily commodity price fluctuations on commodity currencies is short-lived, and therefore harder to pin down at low frequencies. Using MIxed DAta Sampling (MIDAS) models, and Bayesian estimation methods to account for time-variation in predictive ability, the chapter demonstrates the usefulness of suitably exploiting such short-lived effects in improving exchange rate forecasts. It further shows that the usual low-frequency predictors, such as money supplies and interest rates differentials, typically receive little support from the data at monthly frequency, whereas MIDAS models featuring daily commodity prices are highly likely. The chapter also introduces the random walk Metropolis-Hastings technique as a new tool to estimate MIDAS regressions.

Evaluación de las causas de los eventos adversos o incidentes que afectan la seguridad del paciente, en el hospital central de la policía de enero 2012 a diciembre 2013

TITULO DEL TRABAJO: Evaluación de las causas de los eventos adversos o incidentes que afectan la seguridad del paciente, en el hospital central de la policía de enero 2012 a diciembre 2013. OBJETIVO: Determinar y analizar la causa raíz de los principales factores de riesgo que afectan la seguridad del paciente que puedan ocasionar eventos adversos en la atención de los pacientes, con el uso de la teoría de restricciones TOC en el Hospital Central de la Policía HOCEN. MATERIALES Y METODO: Se realizó una investigación descriptiva de naturaleza mixta – cuantitativa de tipo correlacional, la población es la totalidad de pacientes atendidos en el hospital de la policía entre enero de 2012 a diciembre de 2013, en el cual se presentaron un total de 189 eventos adversos los cuales sirvieron de objeto a esta investigación, la recolección de datos se realizó por medio de tablas de Excel 2010, posterior a esto se exporto la información al software de IBM SPSS Statistics 19 donde se analiza la información arrojando datos descriptivos y tablas de frecuencia. Finalmente haciendo uso de la Teoría de restricciones TOC se identificó la causa raíz para la ocurrencia de eventos adversos y plantear una intervención estratégica que promueva un sistema efectivo de seguridad del paciente en pro de la búsqueda de la mejora continua. RESULTADOS: Se analizaron 189 eventos adversos, de los cuales 89 fueron reportados en el turno de la noche, seguido por el turno de la mañana con 57, el turno tarde con 27, 28 eventos que no registraron horario, el servicio con mayor ocurrencia es el de medicina interna con 25 eventos, y finalmente la caída de pacientes, lo relacionado con medicamentos, nutriciones y accesos vasculares son los eventos con mayor incidencia. CONCLUSIONES: Se pudo concluir que es necesario que los procesos de seguridad del paciente deben tener un lineamiento directo desde la dirección de la organización permitiendo que las mejoras sean de inmediata aplicación, también es importante generar en el personal una actitud de compromiso frente al proceso de mejora, hay que redefinir las políticas institucionales ya que se concluyó por medio de la teoría de restricciones TOC que el principal factor para la ocurrencia de eventos adversos son las multitareas que el personal tiene que realizar en el proceso de atención.

Prediction of the chemical composition of lamb carcasses from multi-frequency impedance data

Multi-frequency bioimpedance analysis (MFBIA) was used to determine the impedance, reactance and resistance of 103 lamb carcasses (17.1-34.2 kg) immediately after slaughter and evisceration. Carcasses were halved, frozen and one half subsequently homogenized and analysed for water, crude protein and fat content. Three measures of carcass length were obtained. Diagonal length between the electrodes (right side biceps femoris to left side of neck) explained a greater proportion of the variance in water mass than did estimates of spinal length and was selected for use in the index L-2/Z to predict the mass of chemical components in the carcass. Use of impedance (Z) measured at the characteristic frequency (Z(c)) instead of 50 kHz (Z(50)) did not improve the power of the model to predict the mass of water, protein or fat in the carcass. While L-2/Z(50) explained a significant proportion of variation in the masses of body water (r(2) 0.64), protein (r(2) 0.34) and fat (r(2) 0.35), its inclusion in multi-variate indices offered small or no increases in predictive capacity when hot carcass weight (HCW) and a measure of rib fat-depth (GR) were present in the model. Optimized equations were able to account for 65-90 % of the variance observed in the weight of chemical components in the carcass. It is concluded that single frequency impedance data do not provide better prediction of carcass composition than can be obtained from measures of HCW and GR. Indices of intracellular water mass derived from impedance at zero frequency and the characteristic frequency explained a similar proportion of the variance in carcass protein mass as did the index L-2/Z(50).

Data analysis in multiple-frequency bioelectrical impedance analysis

The performance of three analytical methods for multiple-frequency bioelectrical impedance analysis (MFBIA) data was assessed. The methods were the established method of Cole and Cole, the newly proposed method of Siconolfi and co-workers and a modification of this procedure. Method performance was assessed from the adequacy of the curve fitting techniques, as judged by the correlation coefficient and standard error of the estimate, and the accuracy of the different methods in determining the theoretical values of impedance parameters describing a set of model electrical circuits. The experimental data were well fitted by all curve-fitting procedures (r = 0.9 with SEE 0.3 to 3.5% or better for most circuit-procedure combinations). Cole-Cole modelling provided the most accurate estimates of circuit impedance values, generally within 1-2% of the theoretical values, followed by the Siconolfi procedure using a sixth-order polynomial regression (1-6% variation). None of the methods, however, accurately estimated circuit parameters when the measured impedances were low (<20 Omega) reflecting the electronic limits of the impedance meter used. These data suggest that Cole-Cole modelling remains the preferred method for the analysis of MFBIA data.

Data-based approach for developing a physical activity frequency questionnaire.

Measurement of total energy expenditure may be crucial to an understanding of the relation between physical activity and disease and in order to frame public health intervention. To devise a self-administered physical activity frequency questionnaire (PAFQ), the following data-based approach was used. A 24-hour recall was administered to a random sample of 919 adult residents of Geneva, Switzerland. The data obtained were used to establish the list of activities (and their median duration) that contributed to 95% of the energy expended, separately for men and women. Activities that were trivial for the whole sample but that contributed to > or = 10% of an individual's energy expenditure were also selected. The final PAFQ lists 70 activities or group of activities with their typical duration. About 20 minutes are required for respondents to indicate the number of days and the number of hours per day that they performed each activity. The PAFQ method was validated against a heart rate monitor, a more objective method. The total energy estimated by the PAFQ in 41 volunteers correlated well (r = 0.76) with estimates using a heart rate monitor. The authors conclude that the design of their self-administered physical activity frequency questionnaire based on data from 24-hour recall appeared to accurately estimate energy expenditure.