The Finance Professor Podcast

Dr. Wilson reads and discusses his new paper:

Wilson, Linus, Estimating the Life Expectancy and Value of Statistical Life (VSL) Losses from COVID-19 Infections in the United States (April 19, 2020). Available at SSRN: https://ssrn.com/abstract=3580414

His the "Download this paper" button to get a free copy.

Estimating the Life Expectancy and Value of Statistical Life (VSL) Losses from COVID-19 Infections in the United States

 By 

Dr. Linus Wilson

Associate Professor of Finance

Department of Economics & Finance

B.I. Moody III College of Business

University of Louisiana at Lafayette

Theses are the views of the author alone.

 "

Abstract

 

Americans aged sixty or older stand to lose 153 to 222 days of life expectancy from contracting COVID-19. Over 90 percent of the U.S. population was under stay at home orders by April 2020. These social distancing measures to slow the spread of the SARS-CoV-2 or novel coronavirus have led to over 20 million new applications for unemployment benefits. Are these economic losses justified? We find the value of statistical lives lost (VSL) from an unconstrained spread of the virus which hypothetically infected 81 percent of the population would amount to $8 to $60 trillion.

 

 

Journal of Economic Literature Codes: G22, I1, I18, J31, J65, K32

 

Keywords: actuarial tables, mortality, death rates, CFR, COVID-19, IFR, life expectancy, SARS-CoV-2, school closures, social distancing, stay at home orders, VSL

1. Introduction

This paper attempts to open the discussion of how to model the benefits of social distancing measures in terms of the value of statistical lives (VSL) saved in the SARS-CoV-2 or COVID-19 pandemic. To do this we compare the infection fatality rates IFR’s of Ferguson et al. (2020) to the VSL from several studies. We find in figure 3 panels A and B that the costs of 50 percent of the U.S. population being infected with COVID-19 in lives lost and VSL are, respectively, between 0.659 million and 2.305 million lives lost and between $5 trillion and $37 trillion in VSL losses. The Gross Domestic Product (GDP) was only $21.7 trillion at the end of 2019 according to Mataloni and Aversa (2020).

We use U.S. Census data to control for the age and gender of the population and show how a COVID-19 infection affects an individual’s life expectancy and compares to a typical year’s mortality. Life expectancy losses of between 153 and 222 days can be expected for Americans over 60 with a novel coronavirus infection, according to figure 2, panel C. Americans younger than forty can expect to lose less than two weeks of life expectancy from contracting the virus. In figure 1, panel C, persons over fifty can expect COVID-19 to be about as deadly or up to 70 percent more deadly than a year’s mortality risks. Persons younger than forty-years-old can expect less than half a year’s mortality risk in a COVID-19 infection.

To argue against the social distancing measures, either the IFR of COVID-19 must be nearer to the low end of Ferguson et al. (2020)’s 95 percent confidence interval or the social distancing measure must be very ineffective in reducing the reproductive number, R0, of the SARS-CoV-2 virus. As to the former, a few studies suggest a much lower mean IFR than the 0.9 percent from Ferguson et al. (2020). Ioannidis (2020) argues that, after adjusting for the age of the infected on the Diamond Princess cruise ship, the IFR for the U.S. population should be 0.3 percent, which is below the lower bound of the 95 percent confidence interval calculated in Ferguson et al. (2020) and used here. Likewise, a population-weighted study, Bendavid et al. (2020), recruited people to be tested in Santa Clara County, California regardless of symptoms for COVID-19. It found infection rates were severely under-reported. They calculated an IFR between 0.12 and 0.2 percent.

On the other hand, social distancing may be effective in reducing the spread of COVID-19. R0 is the number of additional persons that an infected person goes on to infect on average. Anecdotal evidence indicates that social distancing in late March and early April 2020 has been effective. Governor Andrew Cuomo of New York State, which has had the highest number of deaths and confirmed cases of COVID-19 of the U.S. states on April 16, 2020, argued in his daily briefing in CNBC (2020) that his modeling teams believed that R0 fell from a median of 2.5 in Wuhan before social distancing and 2.2 on the Diamond Princess Cruise ship to 0.9 in New York State after the mitigation efforts. Governor Cuomo argued that his advisors’ projected hospitals in the state would be overwhelmed with COVID-19 patients if R0 was persistently above 1.2.[1]  Rocklöv et al. (2020) estimate that uncontrolled R0 for COVID-19 on the Diamond Princess cruise ship was 14.8 before social isolation and 1.8 afterward. Chowell et al. (2011) argued that school closures in Mexico reduced the R0 of the H1N1 outbreak by more than 30 percent.

This paper will not attempt to measure the costs of social distancing which, no doubt, number in the many trillions of dollars in the United States alone. By April 7, 2020, Secon and Woodward (2020) reported that 95 percent of the U.S. population was under a stay at home order that meant all but “essential” businesses were shuddered. Morath and Chaney (2020) report that by April 16, 2020, 13 percent of the U.S. workforce or 22 million workers had filed unemployment insurance claims. The COVID-19 multi-state stay at home orders, and associated non-essential business shutdowns, began with California, on March 19, 2020, according to Mervosh et al. (2020). Before the SARS-CoV-2 disruptions, the U.S. unemployment rate stood at a record low 3.5 percent in February 2020 according to the Bureau of Labor Statistics.

Eichenbaum et al. (2020) estimate containing COVID-19 “optimally” with social distancing will lead to consumption dropping by 22 percent versus 7 percent without containment of the virus. Since consumption is about 68.1 percent of GDP, according to the St. Louis Fed, and 2019 GDP was $21.7 trillion, they are arguing macroeconomic consumption losses are about (0.22 – .07)*$21.7 trillion = $3.26 trillion. The loss of freedom cannot just be measured in just macroeconomic statistics. Aggregate consumption does not measure the loss of consumer and producer surplus. There may also be long-term effects to school-age children or households facing bankruptcy that may not be captured fully in Eichenbaum et al. (2020). People losing their jobs also lose their health insurance and may be more likely to die as a result. Certainly, more empirical work can be done to estimate the actual costs of social distancing measures relative to their R0 benefits.

One press release, Yale News (2020), from the Yale Tobin Center for Economic Policy estimated the daily losses of shutdowns at $19 billion per day or about $7 trillion per year. Nevertheless, $3 to $7 trillion annually is less than this paper’s low-end estimates of the VSL losses for anything resembling the unconstrained spread of the virus infecting 81 percent of the population that Ferguson et. al (2020) project. Our low-end VSL losses are $8 trillion for an 81 percent infection rate. For the high-end estimate, the value of statistical lives lost is about $60 trillion.

Overall, the results of this paper point to sizable personal risks for individuals over sixty becoming infected with COVID-19 in terms of the increased chance of death and reduced life expectancy. We also find that the number of deaths and value of statistical life (VSL) losses are extremely high from high rates of COVID-19 infection. Thus, major economic disruptions from social distancing, stay at home orders, and school closures will be justified if the infection fatality rate estimates are reasonable. Measurement error of IFR, pharmaceutical treatments reducing the fatality rates, or a vaccine could make social distancing economic disruptions not worth the cost.

 

[1] See the discussion around the 24:45 minute mark of CNBC (2020)."

A year from the inauguration, four of the top five Democratic 2020 U.S. Presidential election candidates in the polls are in their seventies. Using actuarial data and the history of Presidential assassinations, the top two contenders, Former Vice President Joe Biden and Vermont Senator Bernie Sanders, have a 24 to 29 percent chance of not surviving to the end of a hypothetical first term. The 77 and 78-year-old men’s chances of dying before the end of a second term as POTUS are between 46 and 56 percent.

The 2020 Presidential Election: A Race Against Mortality

by Dr. Linus Wilson, University of Louisiana at Lafayette

 Dr. Wilson reads his paper on episode 12 of The Finance Professor Podcast

 

 

Download the full paper at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3523251 or go to linuswilson.com or financeprofessor.org 

 

Below is the introduction of the paper:

"

1. Introduction

 

Generations of Americans have never lived to see an American President die in office. Indeed, the last President to die was John F. Kennedy who in 1963 died from an assassin’s bullet at the relatively young age of 46 years. That was over 56 years from the start of the first in the nation nominating contest in 2020, the February 3, Iowa Democratic Caucuses. You would have to go back to Franklin D. Roosevelt’s death in office in 1945 in his record 4^th term to find a U.S. President who died of “natural causes”. To be alive for that event in 2020, someone would have to be 74 years old. To have voted for FDR, someone would have to be at least 96 years old. (The voting age was not lowered from 21 to 18 years old until March 21, 1971, with the ratification of the 26^th Amendment to the U.S. Constitution.)

According to Panetta (2020), on January 20, 2017, Donald Trump became the oldest President to be sworn in to his first term at 70 years 222 days old. Joseph Biden, Bernie Sanders, and Michael Bloomberg, aged 77, 78, and 77 were all at least three years older than Donald Trump, who was 73, on January 15, 2020. Biden, Sanders, and Bloomberg were 1^st, 2^nd, and 5^th in the Real Clear Politics Democratic Primary polling average on that day. The 3^rd place democratic candidate, Elizabeth Warren on that date was 70 and would be older than Donald Trump was at his inauguration in 2017 if she won the election and took office on January 20, 2021.

The likely winner of the 2020 election based on betting markets will be pushing the bounds of life expectancy at birth at some time during his tenure in office. He or she will likely be the oldest person to take the oath of office of President of the United States. This paper seeks to quantify the chances that the leading candidates will die before their first or second term in office using actuarial life expectancy data.

If we project out a year out from the January 20, 2021, inauguration, Former Vice President Joseph Biden, Vermont Senator Bernie Sanders, and Billionaire Michael Bloomberg have 24 to 29 percent chance of dying before the end of their first term as President of the United States. The range depends on the age and gender of the candidate and how we account for the chances of assassination. Those same leading Democratic challengers have a 46 to 56 percent chance of not surviving two terms as President of the United States (POTUS).

Kenski and Jamieson (2010) found that perceptions of the septuagenarian Republican nominee John McCain changed through the course of the 2008 election. Voters increasing perceived him a “too old” as election day neared. Thus, the current preference for older candidates by voters may change as the 2020 election progresses. Senator McCain died in 2018 at the age of 81, according to Pitzl (2018).

If the field of viable candidates survives to inauguration day, January 20, 2021, this paper finds that there is a 16 to 21 percent chance that the man or woman sworn in will die before the end of his or her four-year Presidential term on January 20, 2025.

In section 2, we discuss our data collection and how we determined if a 2020 Presidential candidate was “viable.” In section 3, we discuss the death probability calculations in table 2. In section 4, the paper concludes.

"

www.financeprofessor.org

www.linuswilson.com

Professor Linus Wilson discusses his new paper "Clickbait Works! The secret to getting views with the YouTube algorithm." There is a lot of contradictory advice about what metrics the largest video sharing site in the world and the second largest social network promotes. Using a new data set available to YouTube creators starting in 2018, Dr. Wilson finds that click-through rates are by far the most important predictor of a new video getting views from YouTube's black-box recommendation system.

The link is https://ssrn.com/abstract=3369353 

Click the download button for a free download. Next, if you don’t want to register or login with SSRN, click “Download without registration” under the gray text under the picture of Greg Gordon.

"Clickbait Works! The secret to getting views with the YouTube algorithm”

By Dr. Linus Wilson

Abstract

In 2018, YouTube began releasing click-through rates (CTR) data to its video creators. Since 2012, YouTube has emphasized how it favors watch time over clicks in its recommendations to viewers. This is the first academic study employing that data to test what matters more for views on YouTube. Is watch time or CTR more important to getting views on YouTube? This paper finds no to limited evidence that higher percent audience retention or and total average watch time per view are associated with more views on YouTube. Instead, videos with higher CTR got significantly more views as did videos on trending or newsworthy topics. The marginal benefit in terms of views scaled by subscribers of increased CTR is between 71 and 318 times larger than the marginal benefits of increased watch time per view.

Journal of Economic Literature Codes:  D12, D22, D26, D83, D85, L15, L21, L82, L86, M15

Keywords:  YouTube, algorithm, search, discovery, video, CTR, click-through rates, clickbait, watch time, audience retention, neural networks, recommendation systems

Wilson, Linus, Clickbait Works! The secret to getting views with the YouTube algorithm (April 9, 2019). Available at SSRN: https://ssrn.com/abstract=3369353

 

For all of Linus Wilson’s research go to

www.financeprofessor.org

www.linuswilson.com

Find out about the secret $2.7 trillion bailout of Money Market Mutual Funds MMMFs in 2008. The collapse of Lehman Brothers its commercial paper default caused the Primary Reserve Fund to "break the buck" or sell for less than $1.00 per share. 

Wilson, Linus, Broken Bucks: Money Funds that Took Taxpayer Guarantees in 2008 (August 28, 2015). Available at SSRN: https://ssrn.com/abstract=2195358 or http://dx.doi.org/10.2139/ssrn.2195358

The U.S. Treasury rolled out a bailout guarantee on September 19, 2008 without Congressional approval using the exchange rate stabilization fund led by Hank Paulson, David Nason, and Steve Shafran. Paulson and Shafran were Goldman Sach alums (p. 263) ON THE BRINK by Henry Paulson.

Broken Bucks: Money Funds that Took Taxpayer Guarantees in 2008
42 Pages Posted: 2 Jan 2013 Last revised: 29 Aug 2015
Linus Wilson
University of Louisiana at Lafayette - College of Business Administration

Date Written: August 28, 2015

Abstract
This is the first study to look at the characteristics of funds accepting the $2.7 trillion taxpayer guarantee of money market mutual funds during the 2008 financial crisis. Funds with lower asset maturities were significantly less likely to need federal or sponsor bailouts. Fund shares that benefited from Federal Reserve’s asset-backed commercial paper program were significantly more likely to get bailed out by taxpayers and sponsors. Finally, the paper tests if funds adhering to the SEC’s 2010 liquidity reforms prior to their enactment were less likely to be bailed out in 2008.

Keywords: breaking the buck, bailout, Dodd-Frank, DLA, exchange rate stabilization fund, Financial Stability Oversight Council (FSOC), guarantees, liquidity, money market mutual funds, Primary Reserve Fund, regulation, SEC, Securities and Exchange Commission, U.S. Treasury, WAL, WAM, WLA

JEL Classification: G01, G18, G22, G23, G28, H12, H81, L5

Music by www.BenSound.com
(c) Linus Wilson, 2019
www.linuswilson.com
www.financeprofessor.org

Janna Wilson performs Minuet by Boccherini.

Linus Wilson reads his recently updated working paper entitled "A Dove to Hawk Ranking of the Martin to Yellen Federal Reserves" and talks about the current state of Federal Reserve interest rate policy. He previews his talk with the New York Times Bestselling author Roger Lowenstein which will be released in an upcoming episode.

The paper read is as follows: 

"A Dove to Hawk Ranking of the Martin to Yellen Federal Reserves" 

by

 Dr. Linus Wilson [1]

Associate Professor of Finance
University of Louisiana at Lafayette
B. I. Moody III College of Business
Department of Economics & Finance
Web:  http://www.linuswilson.com

http://www.financeprofessor.org

 

Abstract

This note ranks the Federal Reserves based on the tenure of their chairs from William McChesney Martin, Jr. to Janet L. Yellen, using data from 1958 through 2018.  Inflation “doves” are willing to tolerate more inflation than inflation “hawks.”  Comparing the Taylor (1993) rule and core inflation to the effective fed funds rates, it is found that the Yellen Fed is the most dovish Fed since 1958.

Journal of Economic Literature Codes:  E52, E58

Keywords:  dove, Fed funds rates, Federal Open Market Committee, Federal Reserve, gender hawk, inflation, interest rates, monetary policy, overnight lending, output gap, Janet Yellen, Taylor rule, unemployment

[1]This paper reflects the views of the author alone. The author thanks Zhenbin Liu for providing excellent research assistance.

Wilson, Linus, A Dove to Hawk Ranking of the Martin to Yellen Federal Reserves, 2018, Available at SSRN: https://ssrn.com/abstract=2529195 or http://dx.doi.org/10.2139/ssrn.2529195

In this episode you will hear how nonrecourse loans can lead to option payoffs for the borrower. The securitzation market got a boost from the Federal Reserve during the financial crisis. Dr. Linus Wilson, Associate Professor of Finance at the University of Louisiana at Lafayette reads his working paper 

Toxic Asset Subsidies and the Early Redemption of TALF Loans

https://ssrn.com/abstract=1742640

Abstract

This paper develops a formula to numerically estimate the unsubsidized, fair-market value of the toxic assets purchased with Federal Reserve loans.  It finds that subsidy rates on these loans were on average 33.9 percent at origination.  In contrast, by the 3^rd quarter of the 2010, there was on average no subsidy in TALF loans.  The theoretical model is used to predict the early redemption of Term Asset-Backed Securities Loan Facility (TALF) loans used to purchase commercial mortgage backed securities (CMBS).  The predictions of the model are strongly supported by the data.  In addition, this paper looks at the determinants of early redemption.  CMBS originated inside the peak bubble years of 2005-2007 were much less likely to be redeemed early.  The giant investment managers, Blackrock and PIMCO, were much more likely to redeem their TALF loans early than smaller investment managers.

Journal of Economic Literature Codes:  G12, G13, G18, G21, G28, G38

Keywords:  alternative investments; bailout; banking; Blackrock; call options; commercial mortgage backed securities; CMBS; CDOs; Dodd-Frank Financial Reform Law of 2010; emergency lending; EESA; Emergency Economic Stabilization Act; lending; Legacy Securities Program; mortgages; PIMCO; Public-Private Investment Partnership; PPIP; put options; TALF; Term Asset-Backed Securities Loan; TARP; Troubled Asset Relief Program; toxic assets

Come and see Dr. Wilson present the paper at the 2018 Midwest Economics Association meeting on March 24, 2018, at 1:15PM in session 7E Credit. 

The MEA conference in at the Hilton Orrington in Evanston, Illinois.

http://mea.grinnell.edu/conferences

Like the Finance Professor Podcast's Facebook page to see any Facebook live versions of MEA conference presentations.

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Check out the video presentation of the episode 6 podcast guest:

https://www.youtube.com/watch?v=ZyjqU_vEVHs

on the Linus Wilson YouTube channel:

https://www.youtube.com/channel/UCYY02-A8UQ6307k8PPDj5hQ

Professor Andrew Metrick is the Michael H. Jordan Professor of Finance and Management at the Yale School of Management. He is the director, Yale Program on Financial Stability and the Faculty Director, Masters in Systemic Risk program at Yale. 

Linus Wilson reads his joint work with Wendy Yan Wu of Wilfrid Laurier University and updates the plans for the 2018 for the The Finance Professor Podcast.

 

Does Receiving TARP Funds Make it Easier to Roll Your Commercial Paper Onto the Fed?

 

32 Pages Posted: 17 Aug 2011 Last revised: 24 Aug 2011

Linus Wilson

University of Louisiana at Lafayette - College of Business Administration

Yan Wendy Wu

Wilfrid Laurier University

Date Written: August 22, 2011

Abstract

The Commercial Paper Funding Facility (CPFF) bought commercial paper from highly-rated issuers of U.S. dollar commercial paper during the financial crisis of 2008 to 2009. This is the only study to analyze the characteristics of firms selected for this Federal Reserve program. CPFF participants and non-participants differed little in terms of profitability, solvency, or liquidity ratios. Nevertheless, CPFF participants were significantly more likely to come from the financial sector, to pose greater systemic risks, and to have received funds from the Troubled Asset Relief Program (TARP) bailout. The baseline predicted probability of participation in the CPFF jumps from 37.2 percent to 65.9 percent if the commercial paper issuer participated in the TARP bailout.

 

Keywords: ABCP, Asset Backed Commercial Paper, bailout, banks, Capital Purchase Program (CPP), commercial paper, Commercial Paper Funding Facility (CPFF), emergency lending, Federal Reserve, multinational firms, section 13(3), Troubled Asset Relief Program (TARP), U.S. Treasury, unsecured commercial paper

JEL Classification: G01, G18, G2, G28

Suggested Citation:

Wilson, Linus and Wu, Yan Wendy, Does Receiving TARP Funds Make it Easier to Roll Your Commercial Paper Onto the Fed? (August 22, 2011). Available at SSRN: https://ssrn.com/abstract=1911454 or http://dx.doi.org/10.2139/ssrn.1911454

 

The show blog is at 

https://financeprofessorpodcast.wordpress.com/

Like us on facebook at 

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Professor Andrew Metrick is the Michael H. Jordan Professor of Finance and Management at the Yale School of Management. He is the director, Yale Program on Financial Stability and the Faculty Director, Masters in Systemic Risk program at Yale. Professor Metrick was an assistant professor in economics at Harvard University and was an assistant and associate professor of finance at the Wharton School of Business at the University of Pennsylvania. He also served as a senior economist and the cheif economist on President Obama's Council of Economic Advisers while the administration worked on the Dodd–Frank Wall Street Reform and Consumer Protection Act and tried to manage the hugely unpopular bailout of the financial sector, the Troubled Asset Relief Program (TARP). The latter bailout turned a modest profit and many believe it helped to stabilize the financial system.

Professor Metrick outlines the responses to the 2008 financial crises in the USA and abroad and speaks about the tension between regulation and shadow banking.

The YouTube version of this talk is at

https://www.youtube.com/watch?v=ZyjqU_vEVHs&t=220s

The Finance Professor Podcast's facebook page is 

https://www.facebook.com/FinanceProfessorOrg/

Subscriber to the youtube channel at

https://www.youtube.com/channel/UCYY02-A8UQ6307k8PPDj5hQ?sub_confirmation=1

Check out Dr. Metrick's CV at
http://faculty.som.yale.edu/andrewmetrick/documents/cv.pdf

The Financial Management Association 2017 program from its Boston meeting is at
http://fmaconferences.org/Boston/BostonProgram.htm
This was session 214 at the Marriot Copley Place.
#FMABoston2017
www.facebook.com/FMA.org
The next meeting is in San Diego.

Dr. Linus Wilson is an associate professor of finance at the University of Louisiana at Lafayette. He has published extensively on the TARP bailout and has studied the bailouts orchestrated by the U.S. Federal Reserve and the FDIC during the financial crisis of 2008. You can see his research at
www.linuswilson.com
www.financeprofessor.org

I mentioned the following papers whose working paper versions are at 

Wilson, Linus, Debt Overhang and Bank Bailouts (September 12, 2009). Available at SSRN: https://ssrn.com/abstract=1336288 or http://dx.doi.org/10.2139/ssrn.1336288

Wilson, Linus and Wu, Yan Wendy, Common (Stock) Sense about Risk-Shifting and Bank Bailouts (January 1, 2010). Financial Markets and Portfolio Management, Vol. 24, No. 1, pp. 3-29, 2010. Available at SSRN: https://ssrn.com/abstract=1321666

Wilson, Linus, Broken Bucks: Money Funds that Took Taxpayer Guarantees in 2008 (August 28, 2015). Available at SSRN: https://ssrn.com/abstract=2195358 or http://dx.doi.org/10.2139/ssrn.2195358

Wilson, Linus and Wu, Yan Wendy, 'Escaping TARP' (September 21, 2010). Journal of Financial Stability, Vol. 8, No. 1, 2012. Available at SSRN: https://ssrn.com/abstract=1619689 or http://dx.doi.org/10.2139/ssrn.1619689

Wilson, Linus and Wu, Yan Wendy, Does Receiving TARP Funds Make it Easier to Roll Your Commercial Paper Onto the Fed? (August 22, 2011). Available at SSRN: https://ssrn.com/abstract=1911454 or http://dx.doi.org/10.2139/ssrn.1911454

Wilson, Linus, Toxic Asset Subsidies and the Early Redemption of TALF Loans (August 17, 2011). Available at SSRN: https://ssrn.com/abstract=1742640 or http://dx.doi.org/10.2139/ssrn.1742640

Look to my CV for the full citation of published papers.

Professor Linus Wilson is the host of the Finance Professor Podcast at
https://www.stitcher.com/podcast/linus-wilson/the-finance-professor-podcast
https://itunes.apple.com/us/podcast/the-finance-professor-podcast/id1226939293?mt=2

Dr. Jeffry L Coles a Professor of Finance at the David Eccles School of Business at the University of Utah and served as the Vice President of the 2017 Annual Meeting Program .

Professor Linus Wilson reads his paper "Discrete Portfolio Adjustment with Fixed Transaction Costs"

Suggested Citation:

Wilson, Linus, Discrete Portfolio Adjustment with Fixed Transaction Costs (January 3, 2016). Available at SSRN: https://ssrn.com/abstract=2406021 or http://dx.doi.org/10.2139/ssrn.2406021

Abstract

This paper presents a closed form solution to the portfolio adjustment problem in discrete time when the investor faces fixed transaction costs. This transaction cost model assumes a mean-variance investor who wants to adjust her holdings of a risky and risk-free asset. It is shown how this model can be calibrated to be used with a variety of risk models such as life cycle portfolio weights and value at risk (VaR) models. The decision problem can easily be inputted into and calculated in Excel.

 Keywords: adjustment costs, alpha models, brokerage commissions, fixed costs, lifecycle funds, portfolio selection, portfolio theory, risk management, transaction costs, Value at Risk (VaR)

JEL Classification: G11

Click the orange download button to get the full paper on SSRN.

 

 

Linus Wilson reads his joint work at 

https://ssrn.com/abstract=1977345

"Overpaid CEOs Got FDIC Debt Guarantees"

By Linus Wilson, University of Louisiana at Lafayette and Yan Wendy Wu, Wilfrid Laurier University

abstract

From 2008 to 2009, the FDIC guaranteed hundreds of billions of dollars of newly issued bank debt through the Temporary Liquidity Guarantee Program (TLGP). We find that CEOs making more than their peer groups were significantly more likely to steer their companies to obtain federal guarantees for their banks’ debt. The average bank in our sample with a debt guarantee had a CEO who was paid $1.6 million per year more than the average CEO in his or her peer group. In addition, there is strong evidence that large, systemically important banks were more likely to obtain FDIC debt guarantees.

Keywords: bailout, banks, CDS, Citigroup, CEO Compensation, corporate governance, credit default swaps, debt, debt guarantees, Dodd-Frank Wall Street Reform and Consumer Protection Act of 2010, emergency lending, FDIC, Federal Deposit Insurance Corporation, Federal Reserve, financial crisis, FOIA, Freedom

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