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University of Minnesota

Applying Supervised Machine Learning Techniques to Municipal Bond Trading

Abstract

dc:description.abstract

In this paper we will examine how artificial intelligence or machine learning can be used to make better municipal bond trading decisions. The paper will examine a variety of classification models trained in a supervised environment. The paper will discuss: i. How to prepare data for machine learning analysis ii. The basic mathematical concepts of each model iii. The results of each model and how to interpret them iv. How to fine‐tune parameters for optimal performance

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Jacobus, Roland

Rights

Language dc:language.iso
en

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/11299/188792
OAI identifier oai:identifier
oai:conservancy.umn.edu:11299/188792

Chain of custody

source
Harvested from
University of Minnesota
Base URL
conservancy.umn.edu/server/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
related terms
citation

Jacobus, Roland. Applying Supervised Machine Learning Techniques to Municipal Bond Trading. 2017. http://hdl.handle.net/11299/188792