Fixed-Income Arbitrage
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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. -
Fixed Income Strategies and Alternatives in a Zero-Interest Rate Environment - September 2016 - September 2016
September 2016 PROMOTION. FOR INVESTMENT PROFESSIONALS ONLY. NOT FOR PUBLIC DISTRIBUTION Insurance linked Strategies Uncorrelated risk Premia and active Management Time to Look at European Asset Backed Securities Bringing Direct Lending to the Nordics Alternative Credit: an Oasis of Yield in the NIRP Desert Fixed Income Strategies and Alternatives in a Zero-Interest Rate Environment www.hedgenordic.com - September 2016 www.hedgenordic.com - September 2016 PROMOTION. FOR INVESTMENT PROFESSIONALS ONLY. NOT FOR PUBLIC DISTRIBUTION Contents INTRODUCTION HedgeNordic is the leading media covering the Nordic alternative Viewing the Credit LAndSCApe MoMA AdViSorS roLLS expenSiVe VALuAtionS, But SupportiVe teChniCALS for investment and hedge fund universe. through An ALternAtiVe LenS out ASgArd Credit KAMeS inVeStMent grAde gLobal Bond fund The website brings daily news, research, analysis and background that is relevant StrAtegy to Nordic hedge fund professionals from the sell and buy side from all tiers. HedgeNordic publishes monthly, quarterly and annual reports on recent developments in her core market as well as special, indepth reports on “hot topics”. HedgeNordic also calculates and publishes the Nordic Hedge Index (NHX) and is host to the Nordic Hedge Award and organizes round tables and seminars. 62 20 40 the Long And Short of it - the tortoiSe & the hAre: gLobal CorporAte BondS - Targeting opportunitieS in SCAndinaviAn,independent, A DYNAMIC APPROacH TO FIXED INCOME & SRI/ESG in SeArCh of CouponS u.S. LeVerAged Credit eSg, CAt Bond inVeSting HIGH YIELD INVESTING HedgeNordic Project Team: Glenn Leaper, Pirkko Juntunen, Jonathan Furelid, Tatja Karkkainen, Kamran Ghalitschi, Jonas Wäingelin Contact: 33 76 36 48 58 Nordic Business Media AB BOX 7285 SE-103 89 Stockholm, Sweden Targeting opportunities in End of the road - How CTAs the Added intereSt Corporate Number: 556838-6170 The Editor – Faith and Fixed Income.. -
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. -
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. -
Securitization & Hedge Funds
SECURITIZATION & HEDGE FUNDS: COLLATERALIZED FUND OBLIGATIONS SECURITIZATION & HEDGE FUNDS: CREATING A MORE EFFICIENT MARKET BY CLARK CHENG, CFA Intangis Funds AUGUST 6, 2002 INTANGIS PAGE 1 SECURITIZATION & HEDGE FUNDS: COLLATERALIZED FUND OBLIGATIONS TABLE OF CONTENTS INTRODUCTION........................................................................................................................................ 3 PROBLEM.................................................................................................................................................... 4 SOLUTION................................................................................................................................................... 5 SECURITIZATION..................................................................................................................................... 5 CASH-FLOW TRANSACTIONS............................................................................................................... 6 MARKET VALUE TRANSACTIONS.......................................................................................................8 ARBITRAGE................................................................................................................................................ 8 FINANCIAL ENGINEERING.................................................................................................................... 8 TRANSPARENCY...................................................................................................................................... -
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 -
Arbitrage and Price Revelation with Asymmetric Information And
Journal of Mathematical Economics 38 (2002) 393–410 Arbitrage and price revelation with asymmetric information and incomplete markets Bernard Cornet a,∗, Lionel De Boisdeffre a,b a CERMSEM, Université de Paris 1, 106–112 boulevard de l’Hˆopital, 75647 Paris Cedex 13, France b Cambridge University, Cambridge, UK Received 5 January 2002; received in revised form 7 September 2002; accepted 10 September 2002 Abstract This paper deals with the issue of arbitrage with differential information and incomplete financial markets, with a focus on information that no-arbitrage asset prices can reveal. Time and uncertainty are represented by two periods and a finite set S of states of nature, one of which will prevail at the second period. Agents may operate limited financial transfers across periods and states via finitely many nominal assets. Each agent i has a private information about which state will prevail at the second period; this information is represented by a subset Si of S. Agents receive no wrong information in the sense that the “true state” belongs to the “pooled information” set ∩iSi, hence assumed to be non-empty. Our analysis is two-fold. We first extend the classical symmetric information analysis to the asym- metric setting, via a concept of no-arbitrage price. Second, we study how such no-arbitrage prices convey information to agents in a decentralized way. The main difference between the symmetric and the asymmetric settings stems from the fact that a classical no-arbitrage asset price (common to every agent) always exists in the first case, but no longer in the asymmetric one, thus allowing arbitrage opportunities. -
Why Convertible Arbitrage Makes Sense in 2021
For UBS marketing purposes Convertible arbitrage as a hedge fund strategy should continue to work well in 2021. (Keystone) Investment strategies Why convertible arbitrage makes sense in 2021 19 January 2021, 8:52 pm CET, written by UBS Editorial Team The current market environment is conducive for convertible arbitrage hedge funds with elevated new issuance, attractive equity volatility levels and convertible valuations all likely to support performance in 2021. Investors should consider allocating to the strategy within a diversified hedge fund portfolio. The global coronavirus pandemic resulted in significant equity market drawdowns in March last year, followed by an almost unparalleled recovery over the next few months. On balance, 2020 was a good year for hedge funds focusing on convertible arbitrage strategies which returned 12.1% for the year, according to HFR data. We believe that all drivers remain in place for a solid performance in 2021. And while current market conditions resemble those after the great financial crisis, convertible arbitrage today is a far less crowded strategy with more moderate leverage levels. The market structure is also more balanced between hedge funds and long only funds, and has after a long period of outflows, recently witnessed renewed investor interest. So we believe there are a number of reasons why convertible arbitrage remains attractive for investors in 2021 based on the following assumptions: Convertible arbitrage traditionally performs well in recovery phases. Historically, convertible arbitrage funds have generated their best returns during periods of economic recovery and expansion. Improving risk sentiment, tightening credit spreads, and attractively priced new issues are key contributors to returns in such periods. -
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. -
Hedge Fund Returns: a Study of Convertible Arbitrage
Hedge Fund Returns: A Study of Convertible Arbitrage by Chris Yurek An honors thesis submitted in partial fulfillment of the requirements for the degree of Bachelor of Science Undergraduate College Leonard N. Stern School of Business New York University May 2005 Professor Marti G. Subrahmanyam Professor Lasse Pedersen Faculty Adviser Thesis Advisor Table of Contents I Introductions…………………………………………………………….3 Related Research………………………………………………………………4 Convertible Arbitrage Returns……………………………………………....4 II. Background: Hedge Funds………………………………………….5 Backfill Bias…………………………………………………………………….7 End-of-Life Reporting Bias…………………………………………………..8 Survivorship Bias……………………………………………………………...9 Smoothing………………………………………………………………………9 III Background: Convertible Arbitrage……………………………….9 Past Performance……………………………………………………………...9 Strategy Overview……………………………………………………………10 IV Implementing a Convertible Arbitrage Strategy……………….12 Creating the Hedge…………………………………………………………..12 Implementation with No Trading Rule……………………………………13 Implementation with a Trading Rule……………………………………...14 Creating a Realistic Trade………………………………….……………....15 Constructing a Portfolio…………………………………………………….16 Data……………………………………………………………………………..16 Bond and Stock Data………………………………………………………………..16 Hedge Fund Databases……………………………………………………………..17 V Convertible Arbitrage: Risk and Return…………………….…...17 Effectiveness of the Hedge………………………………………………...17 Success of the Trading Rule……………………………………………….20 Portfolio Risk and Return…………………………………………………..22 Hedge Fund Database Returns……………………………………………23 VI -
Risk and Return in Yield Curve Arbitrage
Norwegian School of Economics Bergen, Fall 2020 Risk and Return in Yield Curve Arbitrage A Survey of the USD and EUR Interest Rate Swap Markets Brage Ager-Wick and Ngan Luong Supervisor: Petter Bjerksund Master’s Thesis, Financial Economics NORWEGIAN SCHOOL OF ECONOMICS This thesis was written as a part of the Master of Science in Economics and Business Administration at NHH. Please note that neither the institution nor the examiners are responsible – through the approval of this thesis – for the theories and methods used, or results and conclusions drawn in this work. Acknowledgements We would like to thank Petter Bjerksund for his patient guidance and valuable insights. The empirical work for this thesis was conducted in . -scripts can be shared upon request. 2 Abstract This thesis extends the research of Duarte, Longstaff and Yu (2007) by looking at the risk and return characteristics of yield curve arbitrage. Like in Duarte et al., return indexes are created by implementing a particular version of the strategy on historical data. We extend the analysis to include both USD and EUR swap markets. The sample period is from 2006-2020, which is more recent than in Duarte et al. (1988-2004). While the USD strategy produces risk-adjusted excess returns of over five percent per year, the EUR strategy underperforms, which we argue is a result of the term structure model not being well suited to describe the abnormal shape of the EUR swap curve that manifests over much of the sample period. For both USD and EUR, performance is much better over the first half of the sample (2006-2012) than over the second half (2013-2020), which coincides with a fall in swap rate volatility.