Leverage Caused the 2007-2009 Crisis
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Intermediary Leverage Cycles and Financial Stability Tobias Adrian and Nina Boyarchenko Federal Reserve Bank of New York Staff Reports, No
Federal Reserve Bank of New York Staff Reports Intermediary Leverage Cycles and Financial Stability Tobias Adrian Nina Boyarchenko Staff Report No. 567 August 2012 Revised February 2015 This paper presents preliminary findings and is being distributed to economists and other interested readers solely to stimulate discussion and elicit comments. The views expressed in this paper are those of the authors and do not necessarily reflect the position of the Federal Reserve Bank of New York or the Federal Reserve System. Any errors or omissions are the responsibility of the author. Intermediary Leverage Cycles and Financial Stability Tobias Adrian and Nina Boyarchenko Federal Reserve Bank of New York Staff Reports, no. 567 August 2012; revised February 2015 JEL classification: E02, E32, G00, G28 Abstract We present a theory of financial intermediary leverage cycles within a dynamic model of the macroeconomy. Intermediaries face risk-based funding constraints that give rise to procyclical leverage and a procyclical share of intermediated credit. The pricing of risk varies as a function of intermediary leverage, and asset return exposures to intermediary leverage shocks earn a positive risk premium. Relative to an economy with constant leverage, financial intermediaries generate higher consumption growth and lower consumption volatility in normal times, at the cost of endogenous systemic financial risk. The severity of systemic crisis depends on two state variables: intermediaries’ leverage and net worth. Regulations that tighten funding constraints affect the systemic risk-return tradeoff by lowering the likelihood of systemic crises at the cost of higher pricing of risk. Key words: financial stability, macro-finance, macroprudential, capital regulation, dynamic equilibrium models, asset pricing _________________ Adrian, Boyarchenko: Federal Reserve Bank of New York (e-mail: [email protected], [email protected]). -
DIVIDEND GROWERS DOMINATE OTHER DIVIDEND CATEGORIES June 7, 2021
DIVIDEND GROWERS DOMINATE OTHER DIVIDEND CATEGORIES June 7, 2021 Dividend growers outperformed all dividend categories for the past 48 1/4 years with less risk. This is our conclusion based on data provided by Ned Davis Research. The research focuses on dividend payers, non-dividend payers, and dividend cutters. Note that the pattern of dividend growers outperformance holds for both the entire period of analysis and each sub-period (First Table). It also holds that growers experienced lower volatility for both the entire period and each sub-period (Second Table). In this note, we address why we think this phenomenon exists and what it could mean to investors. RETURN BY DIVIDEND CATEGORY (ANNUAL) Period Increased Paid No Change Not Paid Cut 1973-79 5.9% 5.3% 4.9% 1.7% -3.9% 1980-89 17.8% 16.3% 12.8% 8.6% 8.4% 1990-99 13.2% 12.0% 9.4% 10.3% 6.3% 2000-09 3.5% 2.4% 0.3% -6.5% -12.2% 2010-19 12.9% 11.6% 7.9% 9.3% -1.1% 1973-April 21 10.6% 9.5% 7.0% 4.8% -0.8% VOLATILITY BY DIVIDEND CATEGORY (ANNUAL) Period Increased Paid No Change Not Paid Cut 1973-79 19.2% 19.5% 20.7% 25.5% 23.7% 1980-89 17.3% 17.6% 18.9% 21.2% 21.5% 1990-99 13.9% 13.9% 14.4% 18.5% 17.1% 2000-09 15.9% 18.1% 20.1% 27.2% 31.8% 2010-19 12.7% 13.4% 15.8% 16.1% 21.9% 1973-April 21 16.1% 16.9% 18.5% 22.2% 25.1% Source: Ned Davis Research; WCA WHY DIVIDEND GROWERS GENERATE SUPERIOR RISK-ADJUSTED RETURNS We believe there are five main reasons why investors should prefer dividend growers based on years of research and study. -
Use of Leverage, Short Sales, and Options by Mutual Funds
Use of Leverage, Short Sales, and Options by Mutual Funds Paul Calluzzo, Fabio Moneta, and Selim Topaloglu* This draft: March 2017 Abstract We study the use of leverage, short sales, and options by equity mutual funds. Consistent with agency-induced motives for the use of these complex instruments, we find that they are often used by poorly monitored funds, and are associated with poor outcomes for investors such as lower performance, higher idiosyncratic risk, more negative skewness, greater kurtosis, and higher fees. Consistent with moral hazard, we also find that mutual funds that use these instruments hold riskier equity positions. Mutual funds attempt to use complex instruments to reduce the risk of their portfolios but in an imperfect and costly way. JEL Classification: G11, G23 Keywords: mutual funds, leverage, short sales, options, complex instruments, fees, performance, risk * Smith School of Business, Queen's University, 143 Union Street, Kingston, Ontario K7L 3N6, Canada. Emails: [email protected], [email protected], and [email protected]. We thank George Aragon, Laurent Barras and seminar participants at the 2nd Smith-Ivey Finance Workshop and the 2016 Telfer Annual Conference on Accounting and Finance for their helpful comments. Electronic copy available at: https://ssrn.com/abstract=2938146 I can resist anything except temptation. -Oscar Wilde 1. Introduction Over the past fifteen years there has been a rise in the complexity of mutual funds as more funds are given the authority to use leverage, short sales, and options. Over this period 42.5% of domestic equity funds have reported using at least one of these instruments. -
Leverage Networks and Market Contagion
Leverage Networks and Market Contagion Jiangze Bian, Zhi Da, Dong Lou, Hao Zhou∗ First Draft: June 2016 This Draft: March 2019 ∗Bian: University of International Business and Economics, e-mail: [email protected]. Da: University of Notre Dame, e-mail: [email protected]. Lou: London School of Economics and CEPR, e-mail: [email protected]. Zhou: PBC School of Finance, Tsinghua University, e-mail: [email protected]. We are grateful to Matthew Baron (discussant), Markus Brunnermeier (discussant), Adrian Buss (discus- sant), Agostino Capponi, Vasco Carvalho, Tuugi Chuluun (discussant), Paul Geertsema (discussant), Denis Gromb (discussant), Harald Hau, Zhiguo He (discussant), Harrison Hong, Jennifer Huang (discussant), Wenxi Jiang (discussant), Bige Kahraman (discussant), Ralph Koijen, Guangchuan Li, Fang Liang (discus- sant), Shu Lin (discussant), Xiaomeng Lu (discussant), Ian Martin, Per Mykland, Stijn Van Nieuwerburgh, Carlos Ramirez, L´aszl´oS´andor(discussant), Andriy Shkilko (discussant), Elvira Sojli, and seminar partic- ipants at Georgetown University, Georgia Institute of Technology, London School of Economics, Michigan State University, Rice University, Southern Methodist University, Stockholm School of Economics, Texas Christian University, Tsinghua University, UIBE, University of Hawaii, University of Houston, University of Miami, University of South Florida, University of Zurich, Vienna Graduate School of Finance, Washington University in St. Louis, 2016 China Financial Research Conference, 2016 Conference on the Econometrics -
Deleveraging and the Aftermath of Overexpansion
May 28th, 2009 Jeffrey Owen Herzog Deleveraging and the aftermath of overexpansion [email protected] O The deleveraging process for commercial banks is likely to last years and overshoot compared to fundamentals Banking System Asset and Leverage Growth O A strong procyclical correlation exists between asset growth and Nominal Values, 1934-2008 leverage growth over the past 75 years 25% O At the level of the firm, boom times generate decreasing 20% 1942 collateralization rates and increasing average loan sizes 15% O Given two-year loan losses of $1.1tr and leverage declines of -5% 10% 2008 to -7.5%, we expect deleveraging to curtail commercial bank 5% credit by $646bn and $687bn per year for 2009-2010 0% -5% Trends in deleveraging and commercial banking over time Leverage Growth -10% 2004 -15% 1946 Deleveraging is the process whereby commercial banks reduce their ratio of -20% assets to equity capital, thus bringing down their aggregate exposure to the 0% 5% -5% 10% 15% 20% 25% 30% economy. Many commentators point to this process as an eventual destination -10% Asset Growth for the US commercial banking system, but few have described where or how Source: FDIC we arrive at a more deleveraged commercial banking system. Commercial Bank Assets and Equity Adjusted for Inflation by CPI, $tr Over the past seventy years, the commercial banking sector’s aggregate 0.6 6 balance sheet has demonstrated a strong positive correlation between leverage and asset growth. For the banking industry, 2004 was an 0.5 5 S&L Crisis, 1989-1991 exceptionally unusual year, with equity increasing yoy by 22%. -
Leverage and the Beta Anomaly
Downloaded from https://doi.org/10.1017/S0022109019000322 JOURNAL OF FINANCIAL AND QUANTITATIVE ANALYSIS COPYRIGHT 2019, MICHAEL G. FOSTER SCHOOL OF BUSINESS, UNIVERSITY OF WASHINGTON, SEATTLE, WA 98195 doi:10.1017/S0022109019000322 https://www.cambridge.org/core Leverage and the Beta Anomaly Malcolm Baker, Mathias F. Hoeyer, and Jeffrey Wurgler * . IP address: 199.94.10.45 Abstract , on 13 Dec 2019 at 20:01:41 The well-known weak empirical relationship between beta risk and the cost of equity (the beta anomaly) generates a simple tradeoff theory: As firms lever up, the overall cost of cap- ital falls as leverage increases equity beta, but as debt becomes riskier the marginal benefit of increasing equity beta declines. As a simple theoretical framework predicts, we find that leverage is inversely related to asset beta, including upside asset beta, which is hard to ex- plain by the traditional leverage tradeoff with financial distress that emphasizes downside risk. The results are robust to a variety of specification choices and control variables. , subject to the Cambridge Core terms of use, available at I. Introduction Millions of students have been taught corporate finance under the assump- tion of the capital asset pricing model (CAPM) and integrated equity and debt markets. Yet, it is well known that the link between textbook measures of risk and realized returns in the stock market is weak, or even backward. For example, a dollar invested in a low beta portfolio of U.S. stocks in 1968 grows to $70.50 by 2011, while a dollar in a high beta portfolio grows to just $7.61 (see Baker, Bradley, and Taliaferro (2014)). -
Chapter 13 Lecture: Leverage
CHAPTERCHAPTER 13:13: LEVERAGE.LEVERAGE. (The use of debt) 1 The analogy of physical leverage & financial leverage... A Physical Lever... 500 lbs 2 feet 5 feet 200 lbs LIFTS "Leverage Ratio" = 500/200 = 2.5 “Give me a place to stand, and I will move the earth.” - Archimedes (287-212 BC) 2 Financial Leverage... $4,000,000 EQUITY BUYS INVESTMENT $10,000,000 PROPERTY "Leverage Ratio" = $10,000,000 / $4,000,000 = 2.5 Equity = $4,000,000 Debt = $6,000,000 3 Terminology... “Leverage” “Debt Value”, “Loan Value” (L) (or “D”). “Equity Value” (E) “Underlying Asset Value” (V = E+L): "Leverage Ratio“ = LR = V / E = V / (V-L) = 1/(1-L/V) (Not the same as the “Loan/Value Ratio”: L / V,or “LTV” .) “Risk” The RISK that matters to investors is the risk in their total return, related to the standard deviation (or range or spread) in that return. 4 Leverage Ratio & Loan-to-Value Ratio 25 20 1 LR = 1−LTV 15 LR 10 5 0 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% LTV 5 Leverage Ratio & Loan-to-Value Ratio 100% 90% 80% 70% 1 60% LTV =1− LR 50% LTV 40% 30% 20% 10% 0% 0.00 2.00 4.00 6.00 8.00 10.00 12.00 14.00 16.00 18.00 20.00 LR 6 Effect of Leverage on Risk & Return (Numerical Example)… Example Property & Scenario Characteristics: Current (t=0) values (known for certain): E0[CF1] = $800,000 V0 = $10,000,000 Possible Future Outcomes are risky (next year, t=1): "Pessimistic" scenario (1/2 chance): $11.2M CF1 = $700,000; V1 = $9,200,000. -
Facts and Challenges from the Great Recession for Forecasting and Macroeconomic Modeling
NBER WORKING PAPER SERIES FACTS AND CHALLENGES FROM THE GREAT RECESSION FOR FORECASTING AND MACROECONOMIC MODELING Serena Ng Jonathan H. Wright Working Paper 19469 http://www.nber.org/papers/w19469 NATIONAL BUREAU OF ECONOMIC RESEARCH 1050 Massachusetts Avenue Cambridge, MA 02138 September 2013 We are grateful to Frank Diebold and two anonymous referees for very helpful comments on earlier versions of this paper. Kyle Jurado provided excellent research assistance. The first author acknowledges financial support from the National Science Foundation (SES-0962431). All errors are our sole responsibility. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. At least one co-author has disclosed a financial relationship of potential relevance for this research. Further information is available online at http://www.nber.org/papers/w19469.ack NBER working papers are circulated for discussion and comment purposes. They have not been peer- reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications. © 2013 by Serena Ng and Jonathan H. Wright. All rights reserved. Short sections of text, not to exceed two paragraphs, may be quoted without explicit permission provided that full credit, including © notice, is given to the source. Facts and Challenges from the Great Recession for Forecasting and Macroeconomic Modeling Serena Ng and Jonathan H. Wright NBER Working Paper No. 19469 September 2013 JEL No. C22,C32,E32,E37 ABSTRACT This paper provides a survey of business cycle facts, updated to take account of recent data. Emphasis is given to the Great Recession which was unlike most other post-war recessions in the US in being driven by deleveraging and financial market factors. -
The Great Leverage 2.0? a Tale of Different Indicators of Corporate Leverage Falk Bräuning and J
Research Department April 2, 2020 Current Policy Perspectives The Great Leverage 2.0? A Tale of Different Indicators of Corporate Leverage Falk Bräuning and J. Christina Wang Many policymakers have expressed concerns about the rise in nonfinancial corporate leverage and the risks this poses to financial stability, since (1) high leverage raises the odds of firms becoming a source of adverse shocks, and (2) high leverage amplifies the role of firms in propagating other adverse shocks. This policy brief examines alternative indicators of leverage, focusing especially on the somewhat disparate signals they send regarding the current state of indebtedness of nonfinancial corporate businesses. Even though the aggregate nonfinancial corporate debt-to-income ratio is at a historical high, these firms’ ability to service the debt, as measured by the interest coverage ratio, looks healthy. A simple model shows that this pattern can be consistent with firms’ optimal choice of leverage in response to an exogenous decline in interest rates. On the other hand, the model also reveals that the fall in the interest coverage ratio due to a given yield increase is magnified when interest rates are at low levels. The implication is that the elevated nonfinancial corporate debt-to-income ratio that has been present in recent years raises the downside risk of firms becoming unable to service their debt following any adverse shock, such as a decline in income or an increase in risk premia. 1. Introduction In recent years, US policymakers have repeatedly expressed concerns about the rising leverage of nonfinancial corporate businesses and the risks this poses to financial stability and the real economy. -
1 Solving the Present Crisis and Managing the Leverage Cycle John Geanakoplos We Are at the Acute Crisis Stage of a Leverage
Solving the Present Crisis and Managing the Leverage Cycle John Geanakoplos1 We are at the acute crisis stage of a leverage cycle, a very big cycle. I write to propose a plan with concrete steps that the government could take to address the severe financial condition that we now find ourselves in. It is critical that any rescue plan be clear and transparent, implementable and not subject to fraud, and comprehensive enough to succeed and to convince the public it will succeed. The law already enacted by Congress was admittedly an emergency measure designed to staunch further immediate hemorrhaging. What to do next is the question; understanding how we got here will help us find the right set of answers. The leverage cycle is a recurring phenomenon in American financial history. Most recently, one ended in the derivatives crisis in 1994 that bankrupted Orange County, and another ended in the Emerging Markets-mortgage crisis of 1998 that bankrupted Long Term Capital. A proper understanding of the origins of the cycle shows the way to manage it and to deal with the final crisis stage. A critical aspect of the leverage cycle is that collateral margin rates change. Two years ago a home buyer could make a 5% downpayment on a house, and borrow the other 95%. Now he must put 25% down. Two years ago a mortgage security buyer could put 3% or 10% down, borrowing the rest. Now he must pay 100% in cash. All leverage cycles end with (1) bad news creating more uncertainty and disagreement, (2) sharply increasing collateral margin rates, and (3) losses and bankruptcies among the leveraged optimists. -
Pacer Metaurus Dividend Multiplier Series
FAQ Pacer Metaurus Dividend Multiplier Series What are the Pacer Metaurus US Large Cap Dividend Multiplier 300 ETF (Ticker: TRPL) & Pacer Metaurus US Large Cap Dividend Multiplier 400 ETF (Ticker: QDPL) funds? A series of passive ETFs designed to provide exposure to approximately 300% or 400%, respectively, of the dividends these funds would normally have received from a direct investment in the S&P 500’s constituent companies, while also providing uncapped, long-term Index price appreciation potential. Dividend distributions are paid quarterly. TRPL QDPL is designed to provide approximately “triple” (~300%) of the ordinary is designed to provide approximately “quadruple” (~400%) of the dividend yield of the S&P 500 Index in exchange for reduced exposure ordinary dividend yield of the S&P 500 Index in exchange for reduced to the price appreciation/depreciation of the S&P 500 Index exposure to the price appreciation/depreciation of the S&P 500 Index (~92%1 S&P 500 price exposure). (~88%1 S&P 500 price exposure). (1)As of June 1, 2021. The ETFs are driven by the Dividend Multiplier Strategy–how does that work? The Dividend Multiplier Strategy first separates the S&P 500 into two components: (1) a Dividend Component comprised of the next three years of expected ordinary dividends, and (2) a Price Component representing exposure to the SPX Index (S&P 500 Price Return Index). The Strategy then determines the relative weightings of the two components, the Dividend Component and the Price Component, aiming to deliver a multiple (triple or quadruple) of the S&P 500 ordinary dividend yield in exchange for reduced exposure to the price return of the S&P 500 Index. -
When Credit Bites Back: Leverage, Business Cycles, and Crises∗
February 2012 When Credit Bites Back: Leverage, Business Cycles, and Crises∗ Abstract This paper studies the role of leverage in the business cycle. Based on a study of nearly 200 recession episodes in 14 advanced countries between 1870 and 2008, we document a new stylized fact of the modern business cycle: more credit-intensive booms tend to be followed by deeper recessions and slower recoveries. We find a close relationship between the rate of credit growth relative to GDP in the expansion phase and the severity of the subsequent recession. We use local projection methods to study how leverage impacts the behavior of key macroeconomic variables such as investment, lending, interest rates, and inflation. The effects of leverage are particularly pronounced in recessions that coincide with financial crises, but are also distinctly present in normal cycles. The stylized facts we uncover lend support to the idea that financial factors play an important role in the modern business cycle. Keywords: leverage, financial crises, business cycles, local projections. JEL Codes: C14, C52, E51, F32, F42, N10, N20. Oscar` Jord`a(Federal Reserve Bank of San Francisco and University of California, Davis) e-mail: [email protected]; [email protected] Moritz Schularick (Free University of Berlin) e-mail: [email protected] Alan M. Taylor (University of Virginia, NBER, and CEPR) e-mail: [email protected] ∗The authors gratefully acknowledge financial support through a grant of the Institute for New Economic Thinking (INET) administered by the University of Virginia. Part of this research was undertaken when Schularick was a visitor at the Economics Department, Stern School of Business, New York University.