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Articles 1 - 6 of 6
Full-Text Articles in Statistical Models
Retail Trading And Stock Volatility: The Case Of Robinhood, Cooper Jones
Retail Trading And Stock Volatility: The Case Of Robinhood, Cooper Jones
All Graduate Plan B and other Reports, Spring 1920 to Spring 2023
We examine the relation between Robinhood usership and stock market volatility. We show that daily fluctuations in Robinhood usership, which is used to proxy retail trading, significantly influence various measures of volatility. These results might suggest that Robinhood users contribute to noise trading as they are generally individuals trading on name recognition, media coverage, popularity, and familiarity of products, rather than on fundamental values. In our empirical approach, we find that the percentage increase in Robinhood usership Granger causes increases in daily stock volatility.
Predictive Distributions Via Filtered Historical Simulation For Financial Risk Management, Tyson Clark
Predictive Distributions Via Filtered Historical Simulation For Financial Risk Management, Tyson Clark
All Graduate Plan B and other Reports, Spring 1920 to Spring 2023
Filtered historical simulation with an underlying GARCH process can be used as a valuable tool in VaR analysis, as it derives risk estimates that are sensitive to the distributional properties of the historical data of the produced predictive density. I examine the applications to risk analysis that filtered historical simulation can provide, as well as an interpretation of the predictive density as a poor man’s Bayesian posterior distribution. The predictive density allows us to make associated probabilistic statements regarding the results for VaR analysis, giving greater measurement of risk and the ability to maintain the optimal level of risk per …
Rfviz: An Interactive Visualization Package For Random Forests In R, Christopher Beckett
Rfviz: An Interactive Visualization Package For Random Forests In R, Christopher Beckett
All Graduate Plan B and other Reports, Spring 1920 to Spring 2023
Random forests are very popular tools for predictive analysis and data science. They work for both classification (where there is a categorical response variable) and regression (where the response is continuous). Random forests provide proximities, and both local and global measures of variable importance. However, these quantities require special tools to be effectively used to interpret the forest. Rfviz is a sophisticated interactive visualization package and toolkit in R, specially designed for interpreting the results of a random forest in a user-friendly way. Rfviz uses a recently developed R package (loon) from the Comprehensive R Archive Network (CRAN) to create …
Seasonal Resource Selection And Habitat Treatment Use By A Fringe Population Of Greater Sage-Grouse, Rhett Boswell
Seasonal Resource Selection And Habitat Treatment Use By A Fringe Population Of Greater Sage-Grouse, Rhett Boswell
All Graduate Plan B and other Reports, Spring 1920 to Spring 2023
Movement and habitat selection by Greater Sage-grouse (Centrocercus uropasianus) is of great interest to wildlife managers tasked with applying conservation measures for this iconic western species. Current technology has created small and lightweight GPS (Global Positioning Systems) transmitters that can be attached to sage-grouse. Using GIS software and statistical programs such as Program R, land managers can analyze GPS location data to assess how sage-grouse are geospatially interacting with their habitats. Within the Panguitch Sage-Grouse Management Area (SGMA) thousands of acres of land have been restored or manipulated to enhance sage-grouse habitat; this usually involves removal of pinyon pine …
Comparison Of Survival Curves Between Cox Proportional Hazards, Random Forests, And Conditional Inference Forests In Survival Analysis, Brandon Weathers
Comparison Of Survival Curves Between Cox Proportional Hazards, Random Forests, And Conditional Inference Forests In Survival Analysis, Brandon Weathers
All Graduate Plan B and other Reports, Spring 1920 to Spring 2023
Survival analysis methods are a mainstay of the biomedical fields but are finding increasing use in other disciplines including finance and engineering. A widely used tool in survival analysis is the Cox proportional hazards regression model. For this model, all the predicted survivor curves have the same basic shape, which may not be a good approximation to reality. In contrast the Random Survival Forests does not make the proportional hazards assumption and has the flexibility to model survivor curves that are of quite different shapes for different groups of subjects. We applied both techniques to a number of publicly available …
A Comparison Of Statistical Methods Relating Pairwise Distance To A Binary Subject-Level Covariate, Rachael Stone
A Comparison Of Statistical Methods Relating Pairwise Distance To A Binary Subject-Level Covariate, Rachael Stone
All Graduate Plan B and other Reports, Spring 1920 to Spring 2023
A community ecologist provided a motivating data set involving a certain animal species with two behavior groups, along with a pairwise genetic distance matrix among individuals. Many community ecologists have analyzed similar data sets with a method known as the Hopkins method, testing for an association between the subject-level covariate (behavior group) and the pairwise distance. This community ecologist wanted to know if they used the Hopkins method, would their results be meaningful? Their question inspired this thesis work, where a different data set was used for confidentiality reasons. Multiple methods (Hopkins method, ADONIS, ANOSIM, and Distance Regression) were used …