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Exploring the Relation Between NAV and Price of ETFs in Financial Markets

Description

Exchange traded funds (ETFs) in many ways are similar to more traditional closed-end mutual funds, although thee differ in a crucial way. ETFs rely on a creation and redemption feature to achieve their functionality and this mechanism is designed to

Exchange traded funds (ETFs) in many ways are similar to more traditional closed-end mutual funds, although thee differ in a crucial way. ETFs rely on a creation and redemption feature to achieve their functionality and this mechanism is designed to minimize the deviations that occur between the ETF’s listed price and the net asset value of the ETF’s underlying assets. However while this does cause ETF deviations to be generally lower than their mutual fund counterparts, as our paper explores this process does not eliminate these deviations completely. This article builds off an earlier paper by Engle and Sarkar (2006) that investigates these properties of premiums (discounts) of ETFs from their fair market value. And looks to see if these premia have changed in the last 10 years. Our paper then diverges from the original and takes a deeper look into the standard deviations of these premia specifically.

Our findings show that over 70% of an ETFs standard deviation of premia can be explained through a linear combination consisting of two variables: a categorical (Domestic[US], Developed, Emerging) and a discrete variable (time-difference from US). This paper also finds that more traditional metrics such as market cap, ETF price volatility, and even 3rd party market indicators such as the economic freedom index and investment freedom index are insignificant predictors of an ETFs standard deviation of premia when combined with the categorical variable. These findings differ somewhat from existing literature which indicate that these factors should have a significant impact on the predictive ability of an ETFs standard deviation of premia.

Contributors

Agent

Created

Date Created
2019-05

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Exploring the Relation Between NAV and Price of ETFs in Financial Markets

Description

Exchange traded funds (ETFs) in many ways are similar to more traditional closed-end mutual
funds, although thee differ in a crucial way. ETFs rely on a creation and redemption feature to
achieve their functionality and this mechanism is designed to

Exchange traded funds (ETFs) in many ways are similar to more traditional closed-end mutual
funds, although thee differ in a crucial way. ETFs rely on a creation and redemption feature to
achieve their functionality and this mechanism is designed to minimize the deviations that occur
between the ETF’s listed price and the net asset value of the ETF’s underlying assets. However
while this does cause ETF deviations to be generally lower than their mutual fund counterparts,
as our paper explores this process does not eliminate these deviations completely. This article
builds off an earlier paper by Engle and Sarkar (2006) that investigates these properties of
premiums (discounts) of ETFs from their fair market value. And looks to see if these premia
have changed in the last 10 years. Our paper then diverges from the original and takes a deeper
look into the standard deviations of these premia specifically.
Our findings show that over 70% of an ETFs standard deviation of premia can be
explained through a linear combination consisting of two variables: a categorical (Domestic[US],
Developed, Emerging) and a discrete variable (time-difference from US). This paper also finds
that more traditional metrics such as market cap, ETF price volatility, and even 3rd party market
indicators such as the economic freedom index and investment freedom index are insignificant
predictors of an ETFs standard deviation of premia. These findings differ somewhat from
existing literature which indicate that these factors should have a significant impact on the
predictive ability of an ETFs standard deviation of premia.

Contributors

Agent

Created

Date Created
2019-05

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Extending Profitability to 1927-1953

Description

In this paper we conduct an out-of-sample test on gross profitability and investment in the same manner as Davis, Fama, and French (2000) for the pre-Compustat period (1926-1955). We hand-collect financial statement data from Moodys Industrial Manuals using the company

In this paper we conduct an out-of-sample test on gross profitability and investment in the same manner as Davis, Fama, and French (2000) for the pre-Compustat period (1926-1955). We hand-collect financial statement data from Moodys Industrial Manuals using the company PERMNO list first created by DFF. In total, we collect data from 1,291 firms, largely industrial firms but with some utilities. We then run Fama-Macbeth (1973) regressions using gross profit, scaled operating profit, scaled net income, and investment along with existing variables like book-to-market, market equity, one-month reversal, and one-year momentum. We find that the premiums on gross profitability and investment are not significant for any part of our sample period. For the overall sample period as well as the first half (before the 1933 Securities Act), our accounting data is often missing or cross-sectionally inconsistent. Despite the better-quality data in the period after 1935, however, neither gross profitability not investment have significant Fama-Macbeth slopes. We believe this is caused by inconsistent and incomplete accounting data, chiefly the number of firms that combine SG&A and COGS data into one "cost" number and the inclusion of investment-like costs, like R&D, in COGS or SG&A. This causes gross profitability to not reflect direct economic profitability as closely as in prior research. However, net income has significantly positive coefficients during this period and is not subsumed by gross profitability; this contradicts prior research for the post-1962 period. More data cleaning and analysis is needed in order to form firm conclusions on the gross profitability, net income, and investment premiums during this period.

Contributors

Agent

Created

Date Created
2016-05

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Investnet: Investing Education Made Easy

Description

Millennial involvement levels in the stock market are startlingly low. But what has caused this disconnect between America's younger generation and the financial sector? Stress from past financial crises, distrust of Wall Street, corporate greed, or a dislike of capitalism

Millennial involvement levels in the stock market are startlingly low. But what has caused this disconnect between America's younger generation and the financial sector? Stress from past financial crises, distrust of Wall Street, corporate greed, or a dislike of capitalism could surely all be viable culprits. Through our mutual experiences and research, however, we have found that most millennials aren't cynical anarchists avoiding the stock market in an attempt to fight against the system. Rather, they are individuals who have the desire to learn about investing but are clueless as to where/how to start. We both began investing in the stock market early in our college careers by opening online brokerage accounts and developing investment portfolios based on knowledge we learned within our Finance degrees and through independent research. Word of our involvement in the stock market began to spread in our social circles and people would consistently approach either of us and ask a variety of questions regarding investing. Questions such as: Can you sit down and help me open up an account and pick some stocks? What type of things do you invest in? How do I get started? How much money have you made? (always a favorite). Pre-med students, engineers, business, science, and technology majors alike all showed interest in the stock market. The more and more we talked to people, the more we realized that the problem was not a lack of desire or a lack of intellect. The problem was a lack of logically presented information, and barriers to entry that were far too high. We want to fix that. Investnet will be an online educational platform that will teach anyone the basics of investing, in plain, easy to understand terms. Whether the individual has absolutely zero knowledge of finances, or has some familiarity with investing, Investnet will provide them with the knowledge and confidence necessary to start investing in the stock market (or choose not to, but at least they'll know how).

Contributors

Agent

Created

Date Created
2016-05

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Aggregated Insider Trading Signals and Their Implications

Description

This paper provides evidence through an event study, portfolio simulation, and regression analysis that insider trading, when appropriately aggregated, has predictive power for abnormal risk-adjusted returns on some country and sector exchange traded funds (ETFs). I examine ETFs because of

This paper provides evidence through an event study, portfolio simulation, and regression analysis that insider trading, when appropriately aggregated, has predictive power for abnormal risk-adjusted returns on some country and sector exchange traded funds (ETFs). I examine ETFs because of their broad scope and liquidity. ETF markets are relatively efficient and, thus, the effects I document are unlikely to appear in ETF markets. My evidence that aggregated insider trading predicts abnormal returns in some ETFs suggests that aggregated insider trading is likely to have predictive power for financial assets traded in less efficient markets. My analysis depends on specialized insider trading data covering 88 countries is generously provided by 2iQ.

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Agent

Created

Date Created
2014-05

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A Guide to Financial Mathematics

Description

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

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.

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Created

Date Created
2015-05

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Prioritizing Projects on Time and Cost Savings for a more Efficient Manufacturing Process of a Semiconductor Company

Description

Over the course of six months, we have worked in partnership with Arizona State University and a leading producer of semiconductor chips in the United States market (referred to as the "Company"), lending our skills in finance, statistics, model building,

Over the course of six months, we have worked in partnership with Arizona State University and a leading producer of semiconductor chips in the United States market (referred to as the "Company"), lending our skills in finance, statistics, model building, and external insight. We attempt to design models that help predict how much time it takes to implement a cost-saving project. These projects had previously been considered only on the merit of cost savings, but with an added dimension of time, we hope to forecast time according to a number of variables. With such a forecast, we can then apply it to an expense project prioritization model which relates time and cost savings together, compares many different projects simultaneously, and returns a series of present value calculations over different ranges of time. The goal is twofold: assist with an accurate prediction of a project's time to implementation, and provide a basis to compare different projects based on their present values, ultimately helping to reduce the Company's manufacturing costs and improve gross margins. We believe this approach, and the research found toward this goal, is most valuable for the Company. Two coaches from the Company have provided assistance and clarified our questions when necessary throughout our research. In this paper, we begin by defining the problem, setting an objective, and establishing a checklist to monitor our progress. Next, our attention shifts to the data: making observations, trimming the dataset, framing and scoping the variables to be used for the analysis portion of the paper. Before creating a hypothesis, we perform a preliminary statistical analysis of certain individual variables to enrich our variable selection process. After the hypothesis, we run multiple linear regressions with project duration as the dependent variable. After regression analysis and a test for robustness, we shift our focus to an intuitive model based on rules of thumb. We relate these models to an expense project prioritization tool developed using Microsoft Excel software. Our deliverables to the Company come in the form of (1) a rules of thumb intuitive model and (2) an expense project prioritization tool.

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Created

Date Created
2015-05

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Company A Data Center Group (DCG) Server Segment Analysis

Description

The purpose of our research was to develop recommendations and/or strategies for Company A's data center group in the context of the server CPU chip industry. We used data collected from the International Data Corporation (IDC) that was provided by

The purpose of our research was to develop recommendations and/or strategies for Company A's data center group in the context of the server CPU chip industry. We used data collected from the International Data Corporation (IDC) that was provided by our team coaches, and data that is accessible on the internet. As the server CPU industry expands and transitions to cloud computing, Company A's Data Center Group will need to expand their server CPU chip product mix to meet new demands of the cloud industry and to maintain high market share. Company A boasts leading performance with their x86 server chips and 95% market segment share. The cloud industry is dominated by seven companies Company A calls "The Super 7." These seven companies include: Amazon, Google, Microsoft, Facebook, Alibaba, Tencent, and Baidu. In the long run, the growing market share of the Super 7 could give them substantial buying power over Company A, which could lead to discounts and margin compression for Company A's main growth engine. Additionally, in the long-run, the substantial growth of the Super 7 could fuel the development of their own design teams and work towards making their own server chips internally, which would be detrimental to Company A's data center revenue. We first researched the server industry and key terminology relevant to our project. We narrowed our scope by focusing most on the cloud computing aspect of the server industry. We then researched what Company A has already been doing in the context of cloud computing and what they are currently doing to address the problem. Next, using our market analysis, we identified key areas we think Company A's data center group should focus on. Using the information available to us, we developed our strategies and recommendations that we think will help Company A's Data Center Group position themselves well in an extremely fast growing cloud computing industry.

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Agent

Created

Date Created
2016-05

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Using Natural Diversity of Quorum Sensing to Expand the Synthetic Biology Toolbox

Description

Currently in synthetic biology only the Las, Lux, and Rhl quorum sensing pathways have been adapted for broad engineering use. Quorum sensing allows a means of cell to cell communication in which a designated sender cell produces quorum sensing molecules

Currently in synthetic biology only the Las, Lux, and Rhl quorum sensing pathways have been adapted for broad engineering use. Quorum sensing allows a means of cell to cell communication in which a designated sender cell produces quorum sensing molecules that modify gene expression of a designated receiver cell. While useful, these three quorum sensing pathways exhibit a nontrivial level of crosstalk, hindering robust engineering and leading to unexpected effects in a given design. To address the lack of orthogonality among these three quorum sensing pathways, previous scientists have attempted to perform directed evolution on components of the quorum sensing pathway. While a powerful tool, directed evolution is limited by the subspace that is defined by the protein. For this reason, we take an evolutionary biology approach to identify new orthogonal quorum sensing networks and test these networks for cross-talk with currently-used networks. By charting characteristics of acyl homoserine lactone (AHL) molecules used across quorum sensing pathways in nature, we have identified favorable candidate pathways likely to display orthogonality. These include Aub, Bja, Bra, Cer, Esa, Las, Lux, Rhl, Rpa, and Sin, which we have begun constructing and testing. Our synthetic circuits express GFP in response to a quorum sensing molecule, allowing quantitative measurement of orthogonality between pairs. By determining orthogonal quorum sensing pairs, we hope to identify and adapt novel quorum sensing pathways for robust use in higher-order genetic circuits.

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Created

Date Created
2015-05

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An Analysis of Sovereign Debt Restructurings: The Paths to Economic Sustainability

Description

This paper explores the history of sovereign debt default in developing economies and attempts to highlight the mistakes and accomplishments toward achieving debt sustainability. In the past century, developing economies have received considerable investment due to higher returns and a

This paper explores the history of sovereign debt default in developing economies and attempts to highlight the mistakes and accomplishments toward achieving debt sustainability. In the past century, developing economies have received considerable investment due to higher returns and a degree of disregard for the risks accompanying these investments. As the former Citibank chairman, Walter Wriston articulated, "Countries don't go bust" (This Time is Different, 51). Still, unexpected negative externalities have shattered this idea as the majority of developing economies follow a cyclical pattern of default. As coined by Reinhart and Rogoff, sovereign governments that fall into this continuous cycle have become known as serial defaulters. Most developed markets have not defaulted since World War II, thus escaping this persistent trap. Still, there have been developing economies that have been able to transition out of serial defaulting. These economies are able to leverage debt to compound growth without incurring the protracted consequences of a default. Although the cases are few, we argue that developing markets such as Chile, Mexico, Russia, and Uruguay have been able to escape this vicious cycle. Thus, our research indicates that collaborative debt restructurings coupled with long term economic policies are imperative to transitioning out of debt intolerance and into a sustainable debt position. Successful economies are able to leverage debt to create strong foundational growth rather than gambling with debt in the hopes of achieving rapid catch- up growth.

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Created

Date Created
2015-12