I compared various MIDAS (mixed data sampling) regression models to predict volatility from one week to one month with different regressors based on the records of Chinese Shanghai composite index. The main regressors are in 2 types, one is the realized power (involving 5-min absolute returns), the other is the quadratic variation, computed by squared returns. And realized power performs best at all the forecast horizons. I also compare the effect of lag numbers in regression, form 1 to 200, and it doesn’t change much after 50. In 3 week and month predict horizons, the fitness result with different lag numbers has a waving type among all the regressors, that implies there exists a seasonal effect which is the same as predict horizons in the lagged variables. At last,the out-of -sample and in-sample result of RV and RAV are quite similar, but in sometimes, out-of sample performs better.

A previsão do PIB é um dos principais balizadores para as decisões produtivas de agentes econômicos. Com o objetivo de realizar previsões para o crescimento do PIB trimestral brasileiro, são utilizadas 16 séries mensais financeiras e econômicas como potenciais preditores, abrangendo o período do segundo trimestre de 1996 ao quarto trimestre de 2012. Para isso, aplicou-se as abordagens MIDAS (Mixed Data Sampling) e UMIDAS (Unrestricted Mixed Data Sampling), confrontando seus resultados de previsão fora da amostra com o benchmark ARMA. Foram encontrados erros de previsão menores nessas abordagens, principalmente quando utilizadas informações dentro do trimestre de previsão. Os resultados foram ainda melhores quando empregados múltiplos regressores. / The GDP forecast is an important indicator for production decisions taken by economic agents. In order to make forecasts for the Brazilian quarterly GDP growth, we used 16 monthly financial and economic series as potential predictors, covering the period from the second quarter of 1996 to the fourth quarter of 2012. For this purpose, we applied MIDAS (Mixed Data Sampling) and UMIDAS (Unrestricted Mixed Data Sampling) approaches and compared the out of sample forecasts with the benchmark ones provided by ARMA. MI- DAS and UMIDAS showed smaller prediction errors, especially when information inside the quarter forecast is used. The results were even better when multiple regressors were employed.

A previsão do PIB é um dos principais balizadores para as decisões produtivas de agentes econômicos. Com o objetivo de realizar previsões para o crescimento do PIB trimestral brasileiro, são utilizadas 16 séries mensais financeiras e econômicas como potenciais preditores, abrangendo o período do segundo trimestre de 1996 ao quarto trimestre de 2012. Para isso, aplicou-se as abordagens MIDAS (Mixed Data Sampling) e UMIDAS (Unrestricted Mixed Data Sampling), confrontando seus resultados de previsão fora da amostra com o benchmark ARMA. Foram encontrados erros de previsão menores nessas abordagens, principalmente quando utilizadas informações dentro do trimestre de previsão. Os resultados foram ainda melhores quando empregados múltiplos regressores. / The GDP forecast is an important indicator for production decisions taken by economic agents. In order to make forecasts for the Brazilian quarterly GDP growth, we used 16 monthly financial and economic series as potential predictors, covering the period from the second quarter of 1996 to the fourth quarter of 2012. For this purpose, we applied MIDAS (Mixed Data Sampling) and UMIDAS (Unrestricted Mixed Data Sampling) approaches and compared the out of sample forecasts with the benchmark ones provided by ARMA. MI- DAS and UMIDAS showed smaller prediction errors, especially when information inside the quarter forecast is used. The results were even better when multiple regressors were employed.

Using high frequency data for forecasting or nowcasting, we have to deal with three major problems: the mixed frequency problem, the high dimensionality (fat re- gression, parameter proliferation) problem, and the unbalanced data problem (miss- ing observations, ragged edge data). We propose a BSTS-U-MIDAS model (Bayesian Structural Time Series-Unlimited-Mixed-Data Sampling model) to handle these prob- lem. This model consists of four parts. First of all, a structural time series with regressors model (STM) is used to capture the dynamics of target variable, and the regressors are chosen to boost the forecast accuracy. Second, a MIDAS model is adopted to handle the mixed frequency of the regressors in the STM. Third, spike- and-slab regression is used to implement variable selection. Fourth, Bayesian model averaging (BMA) is used for nowcasting. We use this model to nowcast quarterly GDP for Canada, and find that this model outperform benchmark models: ARIMA model and Boosting model, in terms of MAE (mean absolute error) and MAPE (mean absolute percentage error). / Graduate / 0501 / 0508 / 0463 / jonduan@uvic.ca

Objective: To assess patient reported efficacy of Botulinum toxin type-A for the prophylaxis of migraine headaches in patients with frequent migraine headaches prior to initiation of treatment with Botulinum toxin type-A compared to post treatment. Questions addressed include is there a difference in frequency of migraine headaches following treatment with Botulinum toxin type-A, is there a difference in cost of conventional treatment versus Botulinum toxin type-A and is there a difference in quality of life. Research Plan: Questions addressed patient status prior to the initiation of treatment as well as post treatment. Patient quality of life change, duration and frequency headache improvement are the primary focus. Other considerations included the cost difference between the previous use of other treatment and the periodic treatment with Botulinum toxin type-A. Methodology: A Cross Sectional study utilizing a questionnaire consisting of a modified Migraine Disability Assessment (MIDAS) questionnaire will be given to patients who had received more than one series of injections. Patients who reported chronic migraine headaches and were refractory to previous treatment methods were screened and placed in programs utilizing intramuscular injection of Botulinum toxin type-A at standard points on the face, Temporalis muscle and paracervical muscles. Clinical Relevance: This assessment is relevant to occupational issues due to the increasing number of patients applying for disability due to uncontrolled migraine headaches as well as lost productivity and reduction in functional capacity for activities of daily living. Impact and Significance: Patients that are debilitated by recurrent chronic migraine headaches suffer loss of productive time at work and home. Treatment with Botulinum toxin type-A may results in significant relief allowing fewer days lost at work and improved quality of life. There may be significant cost saving if treatment results in discontinuation of other medications previously used for treatment of migraine headaches. Findings: According to the patients' responses to this survey, it appears that there was an overall improvement in the patients' ability to do work, for those who were employed, as well as their ability to do activities of daily living post treatment with Botulinum toxin-A. Though there were occasionally conflicting data seen in individual cases regarding responses to some of the answers, there appeared to be an overall statistically significant reduction in the mean of responses to the questions. The general implication is consistent with studies that indicate Botulinum toxin-A may be a useful adjunct in the prophylactic treatment of refractory migraine headaches.

Attention Deficit Hyperactivity Disorder (ADHD) has typically been treated with a deficits-based response while most research has ignored any intelligence differences between the subtypes, despite differing symptomology. This quantitative study explored whether or not a distinct pattern of intelligences existed within each of the subtypes or presentations of ADHD: inattentive (IT), hyperactive (HT), and combined (CT). Using Gardner's multiple intelligences theory, data were collected via an online, self-administered survey from a sample of 132 participants, over 18 years of age, with IT, HT, and CT ADHD. The goal was to identify the most predominant of 8 different strengths or intelligences. Predominant intelligence types were measured through the completion of the online Multiple Intelligences Developmental Assessment Scale (MIDAS). Discriminant function analysis was used to interpret differences and combinations among predictors through identification of interdependency and pattern delineation. Study results failed to identify a distinct pattern of a relationship between the types of intelligence and ADHD subtypes. Further research is needed in the area of identifying the strengths of individuals diagnosed with ADHD in an effort to shift treatment and intervention responses to a more strengths-based perspective, possibly impacting individual, academic, and social success for those with ADHD.

No description available.

In this thesis the Tobii eye-tracker 4L was used to investigate how well eye-tracking solutions such as a confirmation-click and dwell-time algorithm compares to the standard mouse input device when performing selection tasks in a map environment. In order to distinguish the different complexity one could face, two user cases are proposed. Scenario one includes non clustered objects. Scenario two include clustered occluded objects. A user study with nine different participants where conducted in order to compare the execution times and find out how error prone the different methods were. Each test participant performed eight different tests, three in the non-clustered scenario and five in the clustered scenario. In two of the tests in the clustered scenario test participants were aided with zooming through a zoom algorithm. The methods was evaluated by calculating the average execution times and errors along with the corresponding standard deviations. In order to grasp the users experience a subjective cognitive load score was calculated with the help of a questionnaire. The eye-tracker methods was found to be competitive in comparison to mouse interaction in the more simple non-clustered case. However, in a more complex scenario such as the clustered case the mouse interaction had the lowest average completion time and cognitive load score. A different type of selection behaviour was discovered among the test participants in the clustered scenario due to the difference in precision between the eye-tracker and mouse interaction. Finally interesting areas to consider in the future is presented and discussed. / I denna avhandling användes en Tobii eye-tracker 4L för att undersöka hur väl eye-tracking metoder så som en bekräftelseklick och dwell-time algoritm jämför sig med standard mus interaktion vid objekt selektion i en kartmiljö. För att urskilja variationen i komplexitet man kan möta föreslås två olika användarfall. Scenario ett inkluderar objekt som är distinktivt separerade och därav ej grupperade. Scenario två inkluderar grupperade samt ockluderade objekt. En användarstudie med nio olika deltagare genomfördes för att jämföra exekveringstiderna och ta reda på hur felbenägna de olika metoderna var. Varje testdeltagare utförde åtta olika tester, tre i det icke-grupperade scenariot och fem i det grupperade scenariot. I två av testerna i det grupperade scenariot fick deltagarna hjälp med att zooma genom en zoomalgoritm. Metoderna utvärderades genom att beräkna de genomsnittliga exekveringstiderna samt antal fel tillsammans med motsvarande standardavvikelser. För att förstå hur användarna upplevde de olika metoderna togs en subjektiv kognitiv belastningspoäng fram genom ett frågeformulär. Eye-tracker metoderna var konkurrenskraftiga i jämförelse med musinteraktion i det enklare fallet där objekt ej var grupperade. I ett mer komplext scenario, såsom i det grupperade fallet, hade dock musinteraktionen den lägsta genomsnittliga exekveringstiden och kognitiva belastningspoängen. En annan typ av selektions beteende upptäcktes bland testdeltagarna i det grupperade scenariot på grund av skillnaden i precision mellan eye-trackern och musinteraktionen. Slutligen presenteras och diskuteras intressanta områden att överväga vid framtida arbeten.

The decline of employment globally with various countries and economies either in recession, post recession or on the brink of recession is a serious concern to governments, the private sector, civic organizations and the general population. Associated with this decline are dynamics of poverty, food insecurity, maladministration and corruption, civil war, and a new world order. Governments are now looking to implement and support successful solutions that have been tried and tested. It has been identified that franchising is successful solution that is on the increase globally. Franchising is a multibillion dollar revenue creator globally and accounts significantly for employment. The automotive sector is growing at an unprecedented rate with the greater number of motor cycles, cars, taxis, busses and trucks on the road. The Midas franchise is the second fastest growing franchise in South Africa. There are more than two hundred and twenty franchises in South Africa and surrounding countries. The aim of this research study is to investigate if franchising provides entrepreneurs, especially new business owners a more secure business start up, and to assess the success of the Midas franchise. The research methodology adopted in this study adopts a qualitative research method. The instruments used to obtain data are questionnaires, face to face interviews, observation and photography. The study area encompasses franchisees from the eThekwini Municipal area. Six Midas franchisees and the KZN regional Midas franchisor have been interviewed. The findings have proven to be remarkable, supporting the hypothesis which states that franchising is a successful tool to assist entrepreneurs. Most entrepreneurs have citied their contentment with being with a franchisee and their optimism to venture into more franchises. The franchisor boasted their rapid expansion in South Africa. There were also recommendations arising out of the study so as to enhance entrepreneurship and franchising in South Africa. / MBA University of KwaZulu-Natal, Durban 2012.

Potentially valuable information about the underlying data generating process of a dependent variable is often lost when an independent variable is transformed to fit into the same sampling frequency as a dependent variable. With the mixed data sampling (MIDAS) technique and increasingly available data at high frequencies, the issue of choosing an optimal sampling frequency becomes apparent. We use financial data and the MIDAS technique to estimate thousands of regressions and forecasts in the quarterly, monthly, weekly, and daily sampling frequencies. Model fit and forecast performance measurements are calculated from each estimation and used to generate summary statistics for each sampling frequency so that comparisons can be made between frequencies. Our regression models contain an autoregressive component and five additional independent variables and are estimated with varying lag length specifications that incrementally increase up to five years of lags. Each regression is used to forecast a rolling, one and two-step ahead, static forecast of the quarterly Yen and U.S Dollar spot exchange rate. Our results suggest that it may be favourable to include high frequency variables for closer modeling of the underlying data generating process but not necessarily for increased forecasting performance. / Graduate / 0501 / 0508 / 0511 / benjamincann@gmail.com