Academic research has shown throughout the years the ability of technical indicators to convey predictive value, informational content, and practical use. The popularity of such studies goes in and out over the years and today is being recognized widely by behavioral economists. Automated technical analysis is said to detect geometric and nonlinear shapes in prices which ordinary time series methods would be unable to detect. Previous papers use smoothing estimators to detect such patterns. Our paper uses local polynomial regressions, digital image processing, and state of the art machine learning tools to detect the patterns. Our results show that they are nonrandom, convey informational value, and have some predictive ability. We validate our results with prior works using stocks from the Dow Jones Industrial Average for a sample period from 1925-2019 using daily price observations.

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Thèse numérisée par la Division de la gestion de documents et des archives de l'Université de Montréal.

Thèse numérisée par la Division de la gestion de documents et des archives de l'Université de Montréal

Farmers around the world rely on IPM practices in order to increase their yields and reduce their losses due to pests. Assessing the impacts of previous IPM CRSP studies is crucial for successful continuance of the program and to provide meaningful recommendations to farmers. This thesis summarizes previous IPM CRSP impact studies, and provides additional impact assessments of IPM practices developed on the program. Scientist-questionnaires were sent to scientists in each IPM CRSP site around the world. Using the data from the questionnaire responses in combination with additional secondary information on elasticities, prices and quantities, economic surplus analyses were conducted. The tomato IPM program in Albania, the plantain IPM program in Ecuador, and the tomato IPM program in Uganda resulted in net present values of approximately $8 million, $7 million and $1 million, respectively. Sensitivity analyses for each case were also conducted, and net benefits ranged from $5 to 23 million in Albania, from $4 to 7 million in Ecuador, and from $0.03 to 3 million in Uganda. Additionally, an ordered probit analysis was conducted to determine the factors affecting adoption of IPM technologies in Bangladesh. The level of education, being a female, IPM training and awareness of pesticide alternatives were found to have positive and statistically significant impact on the adoption of IPM technologies in Bangladesh. / Master of Science

Information technology (IT) investments have increased over the last half-century without clear justification in academic or practice-based literatures. One area that has not been adequately addressed in the past literature is the role of IT investments in mitigating firm financial vulnerability. This dissertation specifically attempts to understand the marginal effects of IT investments on financial vulnerability as defined by firm risk and R&D depreciation. Two research questions are pursued to help explain the role IT investments play in firm financial vulnerability: 1) What is the relationship between IT investments and R&D depreciation? and 2) What is the relationship between IT investments and firm risk? For this, I draw testable from the Real Options Theory. In addition, I develop measures of firm risk and the Depreciation of Business R&D capital. I source the data from three archival sources: Compustat, The Center for Research in Security Prices (CRSP), and the Ci Technology Database (CiTDB). This dissertation uses panel regression models using fixed effects to control the unobservable time invariant firm heterogeneity. To alleviate potential endogeneity and sampling biases, I use generalized method of moments models. The results suggest the relationships between IT investments and both firm risk and depreciation, namely that IT investments increase firm risk and decrease R&D depreciation.