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Federal Reserve Interest Rate Management: Combatting Speculation of Market Volatility and Recessionary Sentiment

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Abstract: Handling the multiple functions of monetary policy that protect the U.S. economy not only on a short term, but also long-term scale is a complicated responsibility assigned to Federal Reserve, in which their actions present a profound impact on

Abstract: Handling the multiple functions of monetary policy that protect the U.S. economy not only on a short term, but also long-term scale is a complicated responsibility assigned to Federal Reserve, in which their actions present a profound impact on consumer confidence towards financial markets and global economies. Specifically, one of the most important goals of the Federal Reserve is to mitigate the risk of the United States to enter a recession, while maintaining a balanced approach when making those policy decisions. In this thesis, we focus on the monetary policy of the Federal Reserve, particularly, their role in controlling interest rates to prevent recessionary sentiment in the current state of the economy. Since 2008, markets have been stronger and previous policies like Dodd-Frank have ensured that market collapses during the Great Recession do not repeat itself. Yet, fluctuations in the yield curve, polarizing investment views, and unsettled consumer confidence has pointed to another recession in the near future. In this case, we will look at the way the Fed has implemented short term policies to lower this risk in order to fight volatile markets, however, fluctuating interest rates has its consequences. The goal of this thesis is to analyze the various ways the Fed has managed interest rates in the past and present, and further, to offer a framework to serve as the most effective policy to combat volatility and recessionary sentiment in the U.S. economy.

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Agent

Created

Date Created
2020-05

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Brexit and Beyond: The Future Implications on London's Commercial Real Estate Market

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This thesis takes the form of a market research report with the goal of analyzing the implications of the United Kingdom (UK) leaving the European Union (EU) (known as “Brexit”) on London’s office commercial real estate market. The ultimate goal

This thesis takes the form of a market research report with the goal of analyzing the implications of the United Kingdom (UK) leaving the European Union (EU) (known as “Brexit”) on London’s office commercial real estate market. The ultimate goal of this report is to make a prediction, firmly grounded in quantitative and qualitative research conducted over the past several months, as to the direction of London’s commercial real estate market going forward (post-Brexit). Within the commercial real estate sector, this paper narrows its focus to the office segment of the London market.

Understanding the political landscape is crucial to formulating a reasonable prediction as to the future of the London market. Aside from research reports and articles, our main insights into the political direction of Brexit come from our recordings from meetings in March of 2017 with two high-ranking members of Parliament and one member of the House of Lords—all of whom are members of the Tory Party (the meetings being held under the condition of anonymity). The below analysis will be followed by a discussion of the economics of Brexit, primarily focusing on the economic risks and uncertainties which have emerged after the vote, and which currently exist today. Such risks include the UK losing its financial passporting rights, weakening GDP and currency value, the potential for a reduction in foreign direct investment (FDI), and the potential loss of the service sector in the city of London due to not being able to access the European Single Market.

The report will shift focus to analyzing three competing viewpoints of the direction of the London market based on recordings from interviews of stakeholders in the London real estate market. One being an executive of one of the largest REITs in the UK, another being the Global Head of Real Estate at a top asset management firm, and another being a director at a large property consulting firm. The report includes these differing “sub-theses” in order to try to make sense of the vast market uncertainties post-Brexit as well as to contrast their viewpoints with where the market is currently and with the report’s investment recommendation.

The remainder of the report will consist of the methods used for analyzing market trends including how the data was modeled in order to make the investment recommendation. The report will analyze real estate and market metrics pre-Brexit, immediately after the vote, post-Brexit, and will conclude with future projections encapsulating the investment recommendation.

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Date Created
2017-12

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Linear Modeling for Insurance Ratemaking/Reserving: Modeling Loss Development Factors for Catastrophe Claims

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

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.

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Agent

Created

Date Created
2018-05

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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).

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Agent

Created

Date Created
2016-05

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Local Freight Optimization

Description

In order to discover if Company X's current system of local trucking is the most efficient and cost-effective way to move freight between sites in the Western U.S., we will compare the current system to varying alternatives to see if

In order to discover if Company X's current system of local trucking is the most efficient and cost-effective way to move freight between sites in the Western U.S., we will compare the current system to varying alternatives to see if there are potential avenues for Company X to create or implement an improved cost saving freight movement system.

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Agent

Created

Date Created
2015-05

Stock Price Performance in the Covid-19 Era: A Five-Phase Analysis

Description

The Covid-19 pandemic has made a significant impact on both the stock market and the<br/>global economy. The resulting volatility in stock prices has provided an opportunity to examine<br/>the Efficient Market Hypothesis. This study aims to gain insights into the efficiency

The Covid-19 pandemic has made a significant impact on both the stock market and the<br/>global economy. The resulting volatility in stock prices has provided an opportunity to examine<br/>the Efficient Market Hypothesis. This study aims to gain insights into the efficiency of markets<br/>based on stock price performance in the Covid era. Specifically, it investigates the market’s<br/>ability to anticipate significant events during the Covid-19 timeline beginning November 1, 2019<br/><br/>and ending March 31, 2021. To examine the efficiency of markets, our team created a Stay-at-<br/>Home Portfolio, experiencing economic tailwinds from the Covid lockdowns, and a Pandemic<br/><br/>Loser Portfolio, experiencing economic headwinds from the Covid lockdowns. Cumulative<br/>returns of each portfolio are benchmarked to the cumulative returns of the S&P 500. The results<br/>showed that the Efficient Market Hypothesis is likely to be valid, although a definitive<br/>conclusion cannot be made based on the scope of the analysis. There are recommendations for<br/>further research surrounding key events that may be able to draw a more direct conclusion.

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Agent

Created

Date Created
2021-05

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Homeward Bound: An Overview of Continuing Care at Home

Description

AARP estimates that 90% of seniors wish to remain in their homes during retirement. Seniors need assistance as they age, historically they have received assistance from either family members, nursing homes, or Continuing Care Retirement Communities. For seniors not wanting

AARP estimates that 90% of seniors wish to remain in their homes during retirement. Seniors need assistance as they age, historically they have received assistance from either family members, nursing homes, or Continuing Care Retirement Communities. For seniors not wanting any of these options, there has been very few alternatives. Now, the emergence of the continuing care at home program is providing hope for a different method of elder care moving forward. CCaH programs offer services such as: skilled nursing care, care coordination, emergency response systems, aid with personal and health care, and transportation. Such services allow seniors to continue to live in their own home with assistance as their health deteriorates over time. Currently, only 30 CCaH programs exist. With the growth of the elderly population in the coming years, this model seems poised for growth.

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Agent

Created

Date Created
2019-05

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The Effect of Poison Pills on Long Term Value in Cancelled Transactions

Description

The purpose of this paper is to study the impact that poison pills have on the value of share prices after the cancellation of a transaction. While various studies have focused on the generic share price impact of poison pills,

The purpose of this paper is to study the impact that poison pills have on the value of share prices after the cancellation of a transaction. While various studies have focused on the generic share price impact of poison pills, very few have focused on the impact of poison pills in cancelled transactions. Based on our research and analysis, in cancelled transactions, target firms that have poison pills prior to the transaction and target firms without poison pills generate returns above the announcement date premium and subsequent investment in the S&P 500 when held to the cancellation of the transaction and when held from cancellation to 6 months after the transaction. This analysis can contribute to the argument that holding shares of firms regardless of cancellation risk is preferable to taking profit at announcement date. Additionally, it can contribute to the study of undiscovered pricing impact of poison pills.

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Agent

Created

Date Created
2016-12

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Looking at COVID-19 as a Factor in Insurance Loss Reserving Models

Description

A factor accounting for the COVID-19 pandemic was added to a generalized linear model to more accurately predict unpaid claims. COVID-19 has affected not just healthcare, but all sectors of the economy. Because of this, whether or not an automobile

A factor accounting for the COVID-19 pandemic was added to a generalized linear model to more accurately predict unpaid claims. COVID-19 has affected not just healthcare, but all sectors of the economy. Because of this, whether or not an automobile insurance claim is filed during the pandemic needs to be taken into account while estimating unpaid claims. Reserve-estimating functions such as glmReserve from the “ChainLadder” package in the statistical software R were experimented with to produce their own results. Because of their insufficiency, a manual approach to building the model turned out to be the most proficient method. Utilizing the GLM function, a model was built that emulated linear regression with a factor for COVID-19. The effects of such a model are analyzed based on effectiveness and interpretablility. A model such as this would prove useful for future calculations, especially as society is now returning to a “normal” state.

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Agent

Created

Date Created
2022-05