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A Guide to Financial Mathematics is a comprehensive and easy-to-use study guide for students studying for the one of the first actuarial exams, Exam FM. While there are many resources available to students to study for these exams, this study is free to the students and offers an approach to

A Guide to Financial Mathematics is a comprehensive and easy-to-use study guide for students studying for the one of the first actuarial exams, Exam FM. While there are many resources available to students to study for these exams, this study is free to the students and offers an approach to the material similar to that of which is presented in class at ASU. The guide is available to students and professors in the new Actuarial Science degree program offered by ASU. There are twelve chapters, including financial calculator tips, detailed notes, examples, and practice exercises. Included at the end of the guide is a list of referenced material.
ContributorsDougher, Caroline Marie (Author) / Milovanovic, Jelena (Thesis director) / Boggess, May (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05
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Description
Catastrophe events occur rather infrequently, but upon their occurrence, can lead to colossal losses for insurance companies. Due to their size and volatility, catastrophe losses are often treated separately from other insurance losses. In fact, many property and casualty insurance companies feature a department or team which focuses solely on

Catastrophe events occur rather infrequently, but upon their occurrence, can lead to colossal losses for insurance companies. Due to their size and volatility, catastrophe losses are often treated separately from other insurance losses. In fact, many property and casualty insurance companies feature a department or team which focuses solely on modeling catastrophes. Setting reserves for catastrophe losses is difficult due to their unpredictable and often long-tailed nature. Determining loss development factors (LDFs) to estimate the ultimate loss amounts for catastrophe events is one method for setting reserves. In an attempt to aid Company XYZ set more accurate reserves, the research conducted focuses on estimating LDFs for catastrophes which have already occurred and have been settled. Furthermore, the research describes the process used to build a linear model in R to estimate LDFs for Company XYZ's closed catastrophe claims from 2001 \u2014 2016. This linear model was used to predict a catastrophe's LDFs based on the age in weeks of the catastrophe during the first year. Back testing was also performed, as was the comparison between the estimated ultimate losses and actual losses. Future research consideration was proposed.
ContributorsSwoverland, Robert Bo (Author) / Milovanovic, Jelena (Thesis director) / Zicarelli, John (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This expository thesis explores the financial health and actuarial analysis of a particular solution for those seeking stability and security in their golden years: the CCRC industry. A continuing care retirement community, or CCRC, is a comprehensive project and campus that offers its residents a full spectrum of care from

This expository thesis explores the financial health and actuarial analysis of a particular solution for those seeking stability and security in their golden years: the CCRC industry. A continuing care retirement community, or CCRC, is a comprehensive project and campus that offers its residents a full spectrum of care from independent living, to assisted living, to skilled nursing. After reading this paper, any person with no prior knowledge of a continuing care retirement community should gain a firm understanding of the background, risks and benefits, and legislative safeguards of this complex industry. Financially, a CCRC operates in some aspects similar to long-term care (LTC) insurance. However, CCRCs provide multiple levels of care operations while maintaining a pleasant, engaging community environment where seniors can have all their lifestyle needs met. The expensive and complex operations of a CCRC are not without risk: the industry has seen marked periods of bankruptcy followed by increasing and changing regulatory oversight. Thus, CCRCs require a periodic actuarial analysis and report, among array of other legislative safeguards against bankruptcy. A CCRC's insolvency or inability to meet its obligations can be catastrophic and inflict suffering and damages not only to its residents but also their friends and families. With seniors historically being one of the most vulnerable demographic groups, it is absolutely essential that an all-encompassing care facility continues to exist and fulfill its contractual promises by maintaining sound actuarial practices and financial health. This thesis, in addition to providing an exposition of the background and functions of the CCRC, describes the existing actuarial and financial studies and audits in practice to ensure sound governance and the quality of life of CCRC residents.
ContributorsTang, Julie (Author) / Milovanovic, Jelena (Thesis director) / Hassett, Matthew J. (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
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Description

The objective of this study is to build a model using R and RStudio that automates ratemaking procedures for Company XYZ’s actuaries in their commercial general liability pricing department. The purpose and importance of this objective is to allow actuaries to work more efficiently and effectively by using this model

The objective of this study is to build a model using R and RStudio that automates ratemaking procedures for Company XYZ’s actuaries in their commercial general liability pricing department. The purpose and importance of this objective is to allow actuaries to work more efficiently and effectively by using this model that outputs the results they otherwise would have had to code and calculate on their own. Instead of spending time working towards these results, the actuaries can analyze the findings, strategize accordingly, and communicate with business partners. The model was built from R code that was later transformed to Shiny, a package within RStudio that allows for the build-up of interactive web applications. The final result is a Shiny app that first takes in multiple datasets from Company XYZ’s data warehouse and displays different views of the data in order for actuaries to make selections on development and trend methods. The app outputs the re-created ratemaking exhibits showing the resulting developed and trended loss and premium as well as the experience-based indicated rate level change based on prior selections. The ratemaking process and Shiny app functionality will be detailed in this report.

ContributorsGilkey, Gina (Author) / Zicarelli, John (Thesis director) / Milovanovic, Jelena (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2022-05