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A Post Financial Crisis Analysis of the Investment Banking Industry

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This paper examines the qualitative and quantitative effects of the 2008 financial crisis on the current landscape of the investment banking industry. We begin by reviewing what occurred during the financial crisis, including which banks took TARP money, which banks

This paper examines the qualitative and quantitative effects of the 2008 financial crisis on the current landscape of the investment banking industry. We begin by reviewing what occurred during the financial crisis, including which banks took TARP money, which banks became bank holding companies, and significant mergers and acquisitions. We then examine the new regulations that were created in reaction to the crisis, including the Dodd-Frank Act. In particular, we focus on the Volcker Rule, which is a section of the act that prohibits proprietary trading and other risky activities at banks. Then we shift into a quantitative analysis of the changes that banks made from the years 2005-2016. To do this, we chose four banks to be representative of the industry: Goldman Sachs, Morgan Stanley, J.P. Morgan, and Bank of America. We then analyze four metrics for each bank: revenue mix, value at risk, tangible common equity ratio, and debt to equity ratio. These provide methods for analyzing how banks have shifted their revenue centers to accommodate new regulations, as well as how these shifts have affected banks' risk levels and leverage. Our data show that all four banks that we observed shifted their revenue centers to flatter revenue areas, such as investment management, wealth management, and consumer banking operations. This was paired with fairly flat investment banking revenues across the board when controlling for overall market changes in the investment banking sector. Additionally, trading-focused banks significantly shifted their operations away from proprietary trading and higher risk activities. These changes resulted in lower value at risk measures for Goldman Sachs and Morgan Stanley with very minor increases for J.P. Morgan and Bank of America, although these two banks had low levels of absolute value at risk when compared to Goldman Sachs and Morgan Stanley. All banks' tangible common equity ratios increased and debt to equity ratios decreased, indicating a safer investment for shareholders and lower leverage. We conclude by offering a forecast of our expectations for the future, particularly in light of a Trump presidency. We expect less regulation going forward and the potential reversal of the Volcker Rule. We believe that these changes would result in more revenue coming from trading and riskier strategies, increasing value at risk, decreasing tangible common equity ratios, and increasing debt to equity ratios. While we do expect less regulation and higher risk, we do not expect these banks to reach pre-crisis levels due to the significant amount of regulations that would be particularly difficult for the Trump administration to reverse.

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2017-05

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

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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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2018-05

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Preferences for Group Risk and Inequality

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Economists, political philosophers, and others have often characterized social preferences regarding inequality by imagining a hypothetical choice of distributions behind "a veil of ignorance". Recent behavioral economics work has shown that subjects care about equality of outcomes, and are willing

Economists, political philosophers, and others have often characterized social preferences regarding inequality by imagining a hypothetical choice of distributions behind "a veil of ignorance". Recent behavioral economics work has shown that subjects care about equality of outcomes, and are willing to sacrifice, in experimental contexts, some amount of personal gain in order to achieve greater equality. We review some of this literature and then conduct an experiment of our own, comparing subjects' choices in two risky situations, one being a choice for a purely individualized lottery for themselves, and the other a choice among possible distributions to members of a randomly selected group. We find that choosing in the group situation makes subjects significantly more risk averse than when choosing an individual lottery. This supports the hypothesis that an additional preference for equality exists alongside ordinary risk aversion, and that in a hypothetical "veil of ignorance" scenario, such preferences may make subjects significantly more averse to unequal distributions of rewards than can be explained by risk aversion alone.

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2014-05

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Risk-reducing Infrastructure: How Much is too Much?

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This paper examines infrastructure spending in a model economy. Infrastructure is subdivided into two types: one that makes future production more efficient, and another that decreases the risk of devastation to the future economy. We call the first type base

This paper examines infrastructure spending in a model economy. Infrastructure is subdivided into two types: one that makes future production more efficient, and another that decreases the risk of devastation to the future economy. We call the first type base infrastructure, and the second type risk-reducing infrastructure. Our model assumes that a single representative individual makes all the decisions within a society and optimizes their own total utility over the present and future. We then calibrate an aggregate economic, two-period model to identify the optimal allocation of today’s output into consumption, base infrastructure, and risk-reducing infrastructure. This model finds that many governments can make substantive improvements to the happiness of their citizens by investing significantly more into risk-reducing infrastructure.

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2021-05

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Homeward Bound: An Overview of Continuing Care at Home

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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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2019-05