Leverage and the Beta Anomaly
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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. -
Understanding the Risks of Smart Beta and the Need for Smart Alpha
UNDERSTANDING THE RISKS OF SMART BETA, AND THE NEED FOR SMART ALPHA February 2015 UNCORRELATED ANSWERS® Key Ideas Richard Yasenchak, CFA Senior Managing Director, Head of Client Portfolio Management There has been a proliferation of smart-beta strategies the past several years. According to Morningstar, asset flows into smart-beta offerings have been considerable and there are now literally thousands of such products, all offering Phillip Whitman, PhD a systematic but ‘different’ equity exposure from that offered by traditional capitalization-weighted indices. During the five years ending December 31, 2014 assets under management (AUM) of smart-beta ETFs grew by 320%; for the same period, index funds experienced AUM growth of 235% (Figure 1 on the following page). Smart beta has also become the media darling of the financial press, who often position these strategies as the answer to every investor’s investing prayers. So what is smart beta; what are its risks; and why should it matter to investors? Is there an alternative strategy that might help investors meet their investing objectives over time? These questions and more will be answered in this paper. This page is intentionally left blank. Defining smart beta and its smart-beta strategies is that they do not hold the cap-weighted market index; instead they re-weight the index based on different intended use factors such as those mentioned previously, and are therefore not The intended use of smart-beta strategies is to mitigate exposure buy-and-hold strategies like a cap-weighted index. to undesirable risk factors or to gain a potential benefit by increasing exposure to desirable risk factors resulting from a Exposure risk tactical or strategic view on the market. -
Low-Beta Strategies
A Service of Leibniz-Informationszentrum econstor Wirtschaft Leibniz Information Centre Make Your Publications Visible. zbw for Economics Korn, Olaf; Kuntz, Laura-Chloé Working Paper Low-beta strategies CFR Working Paper, No. 15-17 [rev.] Provided in Cooperation with: Centre for Financial Research (CFR), University of Cologne Suggested Citation: Korn, Olaf; Kuntz, Laura-Chloé (2017) : Low-beta strategies, CFR Working Paper, No. 15-17 [rev.], University of Cologne, Centre for Financial Research (CFR), Cologne This Version is available at: http://hdl.handle.net/10419/158007 Standard-Nutzungsbedingungen: Terms of use: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Documents in EconStor may be saved and copied for your Zwecken und zum Privatgebrauch gespeichert und kopiert werden. personal and scholarly purposes. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle You are not to copy documents for public or commercial Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich purposes, to exhibit the documents publicly, to make them machen, vertreiben oder anderweitig nutzen. publicly available on the internet, or to distribute or otherwise use the documents in public. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, If the documents have been made available under an Open gelten abweichend von diesen Nutzungsbedingungen die in der dort Content Licence (especially Creative Commons Licences), you genannten Lizenz gewährten -
Arbitrage Pricing Theory∗
ARBITRAGE PRICING THEORY∗ Gur Huberman Zhenyu Wang† August 15, 2005 Abstract Focusing on asset returns governed by a factor structure, the APT is a one-period model, in which preclusion of arbitrage over static portfolios of these assets leads to a linear relation between the expected return and its covariance with the factors. The APT, however, does not preclude arbitrage over dynamic portfolios. Consequently, applying the model to evaluate managed portfolios contradicts the no-arbitrage spirit of the model. An empirical test of the APT entails a procedure to identify features of the underlying factor structure rather than merely a collection of mean-variance efficient factor portfolios that satisfies the linear relation. Keywords: arbitrage; asset pricing model; factor model. ∗S. N. Durlauf and L. E. Blume, The New Palgrave Dictionary of Economics, forthcoming, Palgrave Macmillan, reproduced with permission of Palgrave Macmillan. This article is taken from the authors’ original manuscript and has not been reviewed or edited. The definitive published version of this extract may be found in the complete The New Palgrave Dictionary of Economics in print and online, forthcoming. †Huberman is at Columbia University. Wang is at the Federal Reserve Bank of New York and the McCombs School of Business in the University of Texas at Austin. The views stated here are those of the authors and do not necessarily reflect the views of the Federal Reserve Bank of New York or the Federal Reserve System. Introduction The Arbitrage Pricing Theory (APT) was developed primarily by Ross (1976a, 1976b). It is a one-period model in which every investor believes that the stochastic properties of returns of capital assets are consistent with a factor structure. -
Understanding Alpha Versus Beta in High Yield Bond Investing
PERITUS ASSET MANAGEMENT, LLC Market Commentary Independent Credit Research – Leveraged Finance – July 2012 Understanding Alpha versus Beta in High Yield Bond Investing Investors have come to recognize that there is a secular change occurring in financial markets. After the 2008 meltdown, we have watched equities stage an impressive rally off the bottom, only to peter out. There is no conviction and valuations are once again stretched given the lack of growth as the world economy remains on shaky ground. In another one of our writings (“High Yield Bonds versus Equities”), we discussed our belief that U.S. businesses would plod along, but valuations would continue their march toward the lower end of their historical range. So far, this looks like the correct call. Europe still hasn’t been fixed, the China miracle is slowing and, perhaps, the commodity supercycle is also in the later innings. The amount of debt assumed by the developed world is unsustainable so deleveraging began a few years ago. These are not short or pleasant cycles and both governments and individuals will be grumpy participants in this event. It simply means that economic growth will be subdued for years to come. I have never really been able to understand economic growth rates that are significantly ahead of the population growth anyway…oh yeah, the productivity miracle. I have written chapter and verse on the history of financial markets and where returns have come from: yield. Anyone with access to the internet can verify that dividends, dividend growth and dividend re-investment are what have driven stock returns over the decades. -
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 -
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. -
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. -
The Capital Asset Pricing Model (Capm)
THE CAPITAL ASSET PRICING MODEL (CAPM) Investment and Valuation of Firms Juan Jose Garcia Machado WS 2012/2013 November 12, 2012 Fanck Leonard Basiliki Loli Blaž Kralj Vasileios Vlachos Contents 1. CAPM............................................................................................................................................... 3 2. Risk and return trade off ............................................................................................................... 4 Risk ................................................................................................................................................... 4 Correlation....................................................................................................................................... 5 Assumptions Underlying the CAPM ............................................................................................. 5 3. Market portfolio .............................................................................................................................. 5 Portfolio Choice in the CAPM World ........................................................................................... 7 4. CAPITAL MARKET LINE ........................................................................................................... 7 Sharpe ratio & Alpha ................................................................................................................... 10 5. SECURITY MARKET LINE ................................................................................................... -
The Memory of Beta Factors∗
The Memory of Beta Factors∗ Janis Beckery, Fabian Hollsteiny, Marcel Prokopczuky,z, and Philipp Sibbertseny September 24, 2019 Abstract Researchers and practitioners employ a variety of time-series pro- cesses to forecast betas, using either short-memory models or implic- itly imposing infinite memory. We find that both approaches are inadequate: beta factors show consistent long-memory properties. For the vast majority of stocks, we reject both the short-memory and difference-stationary (random walk) alternatives. A pure long- memory model reliably provides superior beta forecasts compared to all alternatives. Finally, we document the relation of firm characteris- tics with the forecast error differentials that result from inadequately imposing short-memory or random walk instead of long-memory pro- cesses. JEL classification: C58, G15, G12, G11 Keywords: Long memory, beta, persistence, forecasting, predictability ∗Contact: [email protected] (J. Becker), [email protected] (F. Holl- stein), [email protected] (M. Prokopczuk), and [email protected] (P. Sibbertsen). ySchool of Economics and Management, Leibniz University Hannover, Koenigsworther Platz 1, 30167 Hannover, Germany. zICMA Centre, Henley Business School, University of Reading, Reading, RG6 6BA, UK. 1 Introduction In factor pricing models like the Capital Asset Pricing Model (CAPM) (Sharpe, 1964; Lintner, 1965; Mossin, 1966) or the arbitrage pricing theory (APT) (Ross, 1976) the drivers of expected returns are the stock's sensitivities to risk factors, i.e., beta factors. For many applications such as asset pricing, portfolio choice, capital budgeting, or risk management, the market beta is still the single most important factor. Indeed, Graham & Harvey(2001) document that chief financial officers of large U.S.