Due Diligence for Fixed Income and Credit Strategies
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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.. -
2017 Financial Services Industry Outlook
NEW YORK 535 Madison Avenue, 19th Floor New York, NY 10022 +1 212 207 1000 SAN FRANCISCO One Market Street, Spear Tower, Suite 3600 San Francisco, CA 94105 +1 415 293 8426 DENVER 999 Eighteenth Street, Suite 3000 2017 Denver, CO 80202 FINANCIAL SERVICES +1 303 893 2899 INDUSTRY REVIEW MEMBER, FINRA / SIPC SYDNEY Level 2, 9 Castlereagh Street Sydney, NSW, 2000 +61 419 460 509 BERKSHIRE CAPITAL SECURITIES LLC (ARBN 146 206 859) IS A LIMITED LIABILITY COMPANY INCORPORATED IN THE UNITED STATES AND REGISTERED AS A FOREIGN COMPANY IN AUSTRALIA UNDER THE CORPORATIONS ACT 2001. BERKSHIRE CAPITAL IS EXEMPT FROM THE REQUIREMENTS TO HOLD AN AUSTRALIAN FINANCIAL SERVICES LICENCE UNDER THE AUSTRALIAN CORPORATIONS ACT IN RESPECT OF THE FINANCIAL SERVICES IT PROVIDES. BERKSHIRE CAPITAL IS REGULATED BY THE SEC UNDER US LAWS, WHICH DIFFER FROM AUSTRALIAN LAWS. LONDON 11 Haymarket, 2nd Floor London, SW1Y 4BP United Kingdom +44 20 7828 2828 BERKSHIRE CAPITAL SECURITIES LIMITED IS AUTHORISED AND REGULATED BY THE FINANCIAL CONDUCT AUTHORITY (REGISTRATION NUMBER 188637). www.berkcap.com CONTENTS ABOUT BERKSHIRE CAPITAL Summary 1 Berkshire Capital is an independent employee-owned investment bank specializing in M&A in the financial services sector. With more completed transactions in this space than any Traditional Investment Management 6 other investment bank, we help clients find successful, long-lasting partnerships. Wealth Management 9 Founded in 1983, Berkshire Capital is headquartered in New York with partners located in Cross Border 13 London, Sydney, San Francisco, Denver and Philadelphia. Our partners have been with the firm an average of 14 years. We are recognized as a leading expert in the asset management, Real Estate 17 wealth management, alternatives, real estate and broker/dealer industries. -
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...................................................................................................................................... -
Dynamic Strategic Arbitrage∗
Dynamic Strategic Arbitrage∗ Vincent Fardeauy Frankfurt School of Finance and Managment This version: June 11, 2014 Abstract Asset prices do not adjust instantaneously following uninformative demand or supply shocks. This paper offers a theory based on arbitrageurs' price impact to explain these slow-moving cap- ital dynamics. Arbitrageurs recognizing their price impact break up trades, leading to gradual price adjustments. When shocks are anticipated, prices exhibit a V-shaped pattern, with a peak at the realization of the shocks. The dynamics of market depth and price adjustments depend on the degree of competition between arbitrageurs. When shocks are uncertain, price dynamics depend on the interaction between arbitrageurs' competition and the total risk-bearing capacity of the market. JEL codes: G12, G20, L12; Keywords: Strategic arbitrage, liquidity, price impact, limits of arbitrage. ∗I benefited from comments from Miguel Ant´on,Bruno Biais, Maria-Cecilia Bustamante, Amil Dasgupta, Michael Gordy, Martin Oehmke (discussant), Matt Pritsker, Jean-Charles Rochet, Yuki Sato, Kostas Zachariadis, Jean-Pierre Zigrand and seminar and conference participants at LSE, INSEAD, FRB, the University of Zurich and the 2013 AFA meetings in San Diego. I am grateful to Dimitri Vayanos and Denis Gromb for supervision and insights. Jay Im provided excellent research assistance. This paper is the first part of a paper previously circulated as \Strategic Arbitrage with Entry". All remaining errors are my own. yDepartment of Finance, Frankfurt School of Finance and Management, Sonnemannstrasse 9-11, 60314 Frankfurt am Main, Germany. Email: [email protected]. 1 1 Introduction Empirical evidence shows that prices recover slowly from demand or supply shocks that are unre- lated to future earnings and that these patterns are due to imperfections in the supply of capital. -
Optimal Convergence Trading with Unobservable Pricing Errors
OPTIMAL CONVERGENCE TRADING WITH UNOBSERVABLE PRICING ERRORS SÜHAN ALTAY, KATIA COLANERI, AND ZEHRA EKSI Abstract. We study a dynamic portfolio optimization problem related to convergence trading, which is an investment strategy that exploits temporary mispricing by simultane- ously buying relatively underpriced assets and selling short relatively overpriced ones with the expectation that their prices converge in the future. We build on the model of Liu and Timmermann [22] and extend it by incorporating unobservable Markov-modulated pricing errors into the price dynamics of two co-integrated assets. We characterize the optimal portfolio strategies in full and partial information settings both under the assumption of unrestricted and beta-neutral strategies. By using the innovations approach, we provide the filtering equation that is essential for solving the optimization problem under partial information. Finally, in order to illustrate the model capabilities, we provide an example with a two-state Markov chain. 1. Introduction Convergence-type trading strategies have become one of the most popular trading strate- gies that are used to capitalize on market inefficiencies, or deviations from “equilibrium,” especially with the rapid developments in algorithmic and high-frequency trading. For a typical convergence trade, temporary mispricing is exploited by simultaneously buying rel- atively underpriced assets and selling short relatively overpriced assets in anticipation that at some future date their prices will have become closer. Thus one can profit by the extent of the convergence. A prime example of a convergence trade is a pairs trading strategy that involves a long position and a short position in a pair of similar stocks that have moved together historically and hence an investor can profit from the relative value trade arising arXiv:1910.01438v2 [q-fin.PM] 7 Oct 2019 from the cointegration between asset price dynamics involved in the trade. -
Europe's Largest Single Managers Ranked by a Um
2013 IN ASSOCIATION WITH IN ASSOCIATION 5O EUROPEEUROPE’S LARGEST SINGLE MANAGERS RANKED BY AUM EUROPE50 01 02 03 04 Brevan Howard Man BlueCrest Capital Blackrock Management 1 1 1 1 Total AUM (as at 30.06.13) Total AUM (as at 30.06.13) Total AUM (as at 01.04.13) Total AUM (as at 30.06.13) $40.0bn $35.6bn $34.22bn $28.7bn 2 2 2 2 2012 ranking 2012 ranking 2012 ranking 2012 ranking 2 1 3 6 3 3 3 3 Founded Founded Founded Founded 2002 1783 (as a cooperage) 2000 1988 4 4 4 4 Founders/principals Founders/principals Founders/principals Founders/principals Alan Howard Manny Roman (CEO), Luke Ellis (President), Mike Platt, Leda Braga Larry Fink Jonathan Sorrell (CFO) 5 5 5 Hedge fund(s) 5 Hedge fund(s) Hedge fund(s) Fund name: Brevan Howard Master Fund Hedge fund(s) Fund name: BlueCrest Capital International Fund name: UK Emerging Companies Hedge Limited Fund name: Man AHL Diversified plc Inception date: 12/2000 Fund Inception date: 04/2003 Inception date:03/1996 AUM: $13.5bn Inception date: Not disclosed AUM: $27.4bn AUM: $7.9bn Portfolio manager: Mike Platt AUM: Not disclosed Portfolio manager: Multiple portfolio Portfolio manager: Tim Wong, Matthew Strategy: Global macro Portfolio manager: Not disclosed managers Sargaison Asset classes: Not disclosed Strategy: Equity long/short Strategy: Global macro, relative value Strategy: Managed futures Domicile: Not disclosed Asset classes: Not disclosed Asset classes: Fixed income and FX Asset classes: Cross asset Domicile: Not disclosed Domicile: Cayman Islands Domicile: Ireland Fund name: BlueTrend -
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. -
Optimal Convergence Trade Strategies*
Optimal Convergence Trade Strategies∗ Jun Liu† Allan Timmermann‡ UC San Diego and SAIF UC San Diego and CREATES October4,2012 Abstract Convergence trades exploit temporary mispricing by simultaneously buying relatively un- derpriced assets and selling short relatively overpriced assets. This paper studies optimal con- vergence trades under both recurring and non-recurring arbitrage opportunities represented by continuing and ‘stopped’ cointegrated price processes and considers both fixed and stochastic (Poisson) horizons. We demonstrate that conventional long-short delta neutral strategies are generally suboptimal and show that it can be optimal to simultaneously go long (or short) in two mispriced assets. We also find that the optimal portfolio holdings critically depend on whether the risky asset position is liquidated when prices converge. Our theoretical results are illustrated using parameters estimated on pairs of Chinese bank shares that are traded on both the Hong Kong and China stock exchanges. We find that the optimal convergence trade strategy can yield economically large gains compared to a delta neutral strategy. Key words: convergence trades; risky arbitrage; delta neutrality; optimal portfolio choice ∗The paper was previously circulated under the title Optimal Arbitrage Strategies. We thank the Editor, Pietro Veronesi, and an anonymous referee for detailed and constructive comments on the paper. We also thank Alberto Jurij Plazzi, Jun Pan, seminar participants at the CREATES workshop on Dynamic Asset Allocation, Blackrock, Shanghai Advanced Institute of Finance, and Remin University of China for helpful discussions and comments. Antonio Gargano provided excellent research assistance. Timmermann acknowledges support from CREATES, funded by the Danish National Research Foundation. †UCSD and Shanghai Advanced Institute of Finance (SAIF). -
Hedge Fund Strategies
Andrea Frazzini Principal AQR Capital Management Two Greenwich Plaza Greenwich, CT 06830 [email protected] Ronen Israel Principal AQR Capital Management Two Greenwich Plaza Greenwich, CT 06830 [email protected] Hedge Fund Strategies Prof. Andrea Frazzini Prof. Ronen Israel Course Description The class describes some of the main strategies used by hedge funds and proprietary traders and provides a methodology to analyze them. In class and through exercises and projects (see below), the strategies are illustrated using real data and students learn to use “backtesting” to evaluate a strategy. The class also covers institutional issues related to liquidity, margin requirements, risk management, and performance measurement. The class is highly quantitative. As a result of the advanced techniques used in state-of- the-art hedge funds, the class requires the students to work independently, analyze and manipulate real data, and use mathematical modeling. Group Projects The students must form groups of 4-5 members and analyze either (i) a hedge fund strategy or (ii) a hedge fund case study. Below you will find ideas for strategies or case studies, but the students are encouraged to come up with their own ideas. Each group must document its findings in a written report to be handed in on the last day of class. The report is evaluated based on quality, not quantity. It should be a maximum of 5 pages of text, double spaced, 1 inch margins everywhere, 12 point Times New Roman, Hedge Fund Strategies – Syllabus – Frazzini including references and everything else except tables and figures (each table and figure must be discussed in the text). -
Asset Pricing with Arbitrage Activity∗
Asset pricing with arbitrage activity∗ Julien Hugonniery Rodolfo Prietoz Forthcoming: Journal of Financial Economics Abstract We study an economy populated by three groups of myopic agents: Constrained agents subject to a portfolio constraint that limits their risk-taking, unconstrained agents subject to a standard nonnegative wealth constraint, and arbitrageurs with access to a credit facility. Such credit is valuable as it allows arbitrageurs to exploit the limited arbitrage opportunities that emerge endogenously in reaction to the demand imbalance generated by the portfolio constraint. The model is solved in closed-form and we show that, in contrast to existing models with frictions and logarithmic agents, arbitrage activity has an impact on the price level and generates both excess volatility and the leverage effect. We show that these results are due to the fact that arbitrageurs amplify fundamental shocks by levering up in good times and deleveraging in bad times. Keywords: Limits of arbitrage; Rational bubbles; Wealth constraints; Excess volatility; Leverage effect. JEL Classification: D51, D52, G11, G12. ∗A previous draft of this paper was circulated under the title \Arbitrageurs, bubbles and credit conditions". For helpful comments we thank Hengjie Ai, Rui Albuquerque, Harjoat Bhamra, Pablo Casta~neda,Pierre Collin Dufresne, J´er^omeDetemple, Bernard Dumas, Phil Dybvig, Zhiguo He, Leonid Kogan, Mark Loewenstein, Marcel Rindisbacher, and seminar participants at the 2013 AMS meetings at Boston College, the Bank of Canada, Boston University, the 8th Cowles Conference, the 2012 FIRS Conference, the Southwestern University of Finance and Economics, the 4th Finance UC Conference, Universidad Adolfo Ib´a~nez,University of Geneva and University of Lugano. -
Hedgeweek Awards 2013 LEADING the WAY UNRIVALLED in CHOICE, QUALITY and EXPERIENCE
March 2013 Hedgeweek Awards 2013 LEADING THE WAY UNRIVALLED IN CHOICE, QUALITY AND EXPERIENCE LYXOR MANAGED ACCOUNT PLATFORM, INNOVATING SINCE 1998 With $11bn assets under management*, only Lyxor’s Managed Account Platform gives access to over 100 managers, selected among the best in the industry. With the addition of weekly liquidity**, unrivalled transparency and sophisticated monitoring features, you can invest with confidence. We offer investors much more than a platform, we offer our unrivalled experience. Think Managed Accounts, Think Lyxor. HedgeWeek Best Managed Account Platform 2012 • HFMWeek Most Innovative Managed Account Platform 2012 • The Hedge Fund Journal The Leading Managed Account Platform 2012 • Hedge Funds Review #1 Managed Account Platform from Hedge Fund/FoHF viewpoint Dec 2011 For more information visit www.lyxor.com or email [email protected] * As at 31st December 2012. ** 95% of the funds on Lyxor MAP offer weekly liquidity. This material is not intended for use by or targeted at retail customers. It is neither an offer, nor a solicitation, advice or recommendation for the purchase or sale of any securities, financial instruments or investment solutions in any jurisdiction, including the United States, or to enter into any transaction. Securities or financial instruments may not be offered or sold in any jurisdiction, including the United States, absent registration or an exemption from registration under applicable regulations. This material is issued by Lyxor Asset Management S.A., 17 cours Valmy, 92987 Paris -
Speed of Trade and Arbitrage Ariel Lohr, September 2018 Abstract: We
Speed Of Trade And Arbitrage Ariel Lohr, September 2018 Abstract: We employ a theoretical microstructue model with overconfident traders (Kyle, Obizhaeva, Wang 2017) to demonstrate how market differences effect an arbitrageurs abil- ity/willingness to engage in price correcting trades. The markets differ in the rates at which traders adjust their inventories towards their target levels, "trading speeds". The extent to which trading speed differences across markets effect the degree of price convergence or diver- gence depends on the arbitrageur's preexisting positions in each market. If the arbitrageur trades towards their target in each market at the same prevailing speed the prices converge. Trading speeds are found to be time invariant and the effect of a financial constraint on the arbitrageur increases in the difference between market speeds. 1 1 Introduction This paper contemplates how differences in markets effects an arbitrageurs ability or will- ingness to engage in price correcting trading, enforcing the law of one price. Theoretically if we take some arbitrary return r multiply it by the stochastic dis- count factor m and take the expectation of the product we should recover the fundamental pricing equation 1 = hmri (Cochrane 2009). Any asset pricing model, H : returns ! prices, amounts to an estimation of the homomorphism hm · i which maps elements of a return space to some price space with any r2 = ker(H) being seen as a mispricing in the eyes of the model. Since prices effect returns, asset pricing models amount to restrictions on the price gener- ating process. In reality prices are the results of trading games (i.e.