Barrett

Barrett, The Honors College at Arizona State University proudly showcases the work of undergraduate honors students by sharing this collection exclusively with the ASU community.

Barrett accepts high performing, academically engaged undergraduate students and works with them in collaboration with all of the other academic units at Arizona State University. All Barrett students complete a thesis or creative project which is an opportunity to explore an intellectual interest and produce an original piece of scholarly research. The thesis or creative project is supervised and defended in front of a faculty committee. Students are able to engage with professors who are nationally recognized in their fields and committed to working with honors students. Completing a Barrett thesis or creative project is an opportunity for undergraduate honors students to contribute to the ASU academic community in a meaningful way.

Displaying 1 - 5 of 5
Filtering by

Clear all filters

136332-Thumbnail Image.png

Applying the Hedonic Estimation Method to South Mountain Municipal Park

Description
South Mountain is the largest municipal park in the nation. It is a bundled amenity, providing a series of linked services to the surrounding communities. A dataset of 19,209 homes in 155 neighborhoods within three miles of the park was utilized in order to complete a hedonic estimation for two…

South Mountain is the largest municipal park in the nation. It is a bundled amenity, providing a series of linked services to the surrounding communities. A dataset of 19,209 homes in 155 neighborhoods within three miles of the park was utilized in order to complete a hedonic estimation for two nearby urban villages, Ahwatukee Foothills and South Mountain Village. Measures of access include proximity to the park, trailhead access, and adjacency to the park. Two regressions were estimated, the first including lot characteristics and subdivision fixed effects and the second using the coefficients for each subdivision as the dependent variable. These estimates describe how the location of a house in a subdivision contributes to its conditional mean price. As a result they offer a direct basis for capturing amenities measured at the neighborhood scale on home values. Park proximity, trailhead access and adjacency were found to significantly influence the price of homes at the 5% confidence level in Ahwatukee, but not in South Mountain Village. The results of this study can be applied to issues of environmental justice and park access in determining which areas and attributes of the park are associated with a high premium. Though South Mountain was preserved some time ago, development and future preservation in the City of Phoenix can be informed by such studies.
ContributorsRamakrishna, Saritha Kambhampati (Author) / Abbott, Joshua (Thesis director) / Smith, V. Kerry (Committee member) / Schoon, Michael (Committee member) / Barrett, The Honors College (Contributor) / School of Sustainability (Contributor) / Economics Program in CLAS (Contributor) / Department of English (Contributor)
Created2015-05
132368-Thumbnail Image.png

Moving Target Defense: Defending against Adversarial Defense

Description
A defense-by-randomization framework is proposed as an effective defense mechanism against different types of adversarial attacks on neural networks. Experiments were conducted by selecting a combination of differently constructed image classification neural networks to observe which combinations applied to this framework were most effective in maximizing classification accuracy. Furthermore, the…

A defense-by-randomization framework is proposed as an effective defense mechanism against different types of adversarial attacks on neural networks. Experiments were conducted by selecting a combination of differently constructed image classification neural networks to observe which combinations applied to this framework were most effective in maximizing classification accuracy. Furthermore, the reasons why particular combinations were more effective than others is explored.
ContributorsMazboudi, Yassine Ahmad (Author) / Yang, Yezhou (Thesis director) / Ren, Yi (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Economics Program in CLAS (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
132164-Thumbnail Image.png

Design and Analysis of Algorithmic Trading Automation

Description
With the coming advances of computational power, algorithmic trading has become one of the primary strategies to trading on the stock market. To understand why and how these strategies have been effective, this project has taken a look at the complete process of creating tools and applications to analyze and…

With the coming advances of computational power, algorithmic trading has become one of the primary strategies to trading on the stock market. To understand why and how these strategies have been effective, this project has taken a look at the complete process of creating tools and applications to analyze and predict stock prices in order to perform low-frequency trading. The project is composed of three main components. The first component is integrating several public resources to acquire and process financial trading data and store it in order to complete the other components. Alpha Vantage API, a free open source application, provides an accurate and comprehensive dataset of features for each stock ticker requested. The second component is researching, prototyping, and implementing various trading algorithms in code. We began by focusing on the Mean Reversion algorithm as a proof of concept algorithm to develop meaningful trading strategies and identify patterns within our datasets. To augment our market prediction power (“alpha”), we implemented a Long Short-Term Memory recurrent neural network. Neural Networks are an incredibly effective but often complex tool used frequently in data science when traditional methods are found lacking. Following the implementation, the last component is to optimize, analyze, compare, and contrast all of the algorithms and identify key features to conclude the overall effectiveness of each algorithm. We were able to identify conclusively which aspects of each algorithm provided better alpha and create an entire pipeline to automate this process for live trading implementation. An additional reason for automation is to provide an educational framework such that any who may be interested in quantitative finance in the future can leverage this project to gain further insight.
ContributorsYurowkin, Alexander (Co-author) / Kumar, Rohit (Co-author) / Welfert, Bruno (Thesis director) / Li, Baoxin (Committee member) / Economics Program in CLAS (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
135311-Thumbnail Image.png

Temporal and Spatial Aggregation Effects on Environmental Economic Studies

Description
We examine the bias resulting from temporal and spatial aggregation of weather variables in environmental economics. In order to include temporally and/or spatially continuous environmental variables (such as temperature and precipitation), many studies discritize them. The finer the scale of discrization chosen, the more difficult it can be to obtain…

We examine the bias resulting from temporal and spatial aggregation of weather variables in environmental economics. In order to include temporally and/or spatially continuous environmental variables (such as temperature and precipitation), many studies discritize them. The finer the scale of discrization chosen, the more difficult it can be to obtain a complete and reliable data set. Studies performed at very fine scales often find tighter and more dramatic relationships between variables such as temperature and income per capita. We examine this question by repeating the same empirical study at various temporal and spatial scales and comparing the resulting parameter estimates.
ContributorsOber-Reynolds, Daniel Steven (Author) / Hanemann, Michael W. (Thesis director) / Kuminoff, Nicolai V. (Committee member) / School of Historical, Philosophical and Religious Studies (Contributor) / Economics Program in CLAS (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05

Free Trade and the Environmental Impact of Resource Extraction: A Comparative Study of Brazil and Chile Post-Democratization

Description

Mining is a key component of both the Brazilian and Chilean economies and accounts for an outsized share of these countries’ exports. Yet, it is a common target for environmental criticism, especially due to its impacts on local populations and ecosystems. Brazil and Chile have adopted markedly different trade strategies…

Mining is a key component of both the Brazilian and Chilean economies and accounts for an outsized share of these countries’ exports. Yet, it is a common target for environmental criticism, especially due to its impacts on local populations and ecosystems. Brazil and Chile have adopted markedly different trade strategies over the past three decades, most notably with regards to their involvement in international trade agreements. This paper investigates how these differences in trade policy since 1990 have affected the sustainability of each country’s mining sector by identifying and comparing the channels through which free trade agreements influence the environmental impacts of resource extraction.
ContributorsKopek, Justin (Author) / Sheriff, Glenn (Thesis director) / Goodman, Glen (Committee member) / Barrett, The Honors College (Contributor) / Economics Program in CLAS (Contributor) / School of Politics and Global Studies (Contributor) / Historical, Philosophical & Religious Studies, Sch (Contributor) / School of International Letters and Cultures (Contributor)
Created2023-05