Asset Securitization
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Short Sellers and Financial Misconduct 6 7 ∗ 8 JONATHAN M
jofi˙1597 jofi2009v2.cls (1994/07/13 v1.2u Standard LaTeX document class) June 25, 2010 19:56 JOFI jofi˙1597 Dispatch: June 25, 2010 CE: AFL Journal MSP No. No. of pages: 35 PE: Beetna 1 THE JOURNAL OF FINANCE • VOL. LXV, NO. 5 • OCTOBER 2010 2 3 4 5 Short Sellers and Financial Misconduct 6 7 ∗ 8 JONATHAN M. KARPOFF and XIAOXIA LOU 9 10 ABSTRACT 11 12 We examine whether short sellers detect firms that misrepresent their financial state- ments, and whether their trading conveys external costs or benefits to other investors. 13 Abnormal short interest increases steadily in the 19 months before the misrepresen- 14 tation is publicly revealed, particularly when the misconduct is severe. Short selling 15 is associated with a faster time-to-discovery, and it dampens the share price inflation 16 that occurs when firms misstate their earnings. These results indicate that short sell- 17 ers anticipate the eventual discovery and severity of financial misconduct. They also convey external benefits, helping to uncover misconduct and keeping prices closer to 18 fundamental values. 19 20 21 22 SHORT SELLING IS A CONTROVERSIAL ACTIVITY. Detractors claim that short sell- 23 ers undermine investors’ confidence in financial markets and decrease market 24 liquidity. For example, a short seller can spread false rumors about a firm 25 in which he has a short position and profit from the resulting decline in the 1 26 stock price. Advocates, in contrast, argue that short selling facilitates market 27 efficiency and the price discovery process. Investors who identify overpriced 28 firms can sell short, thereby incorporating their unfavorable information into 29 market prices. -
Analysis of Securitized Asset Liquidity June 2017 an He and Bruce Mizrach1
Analysis of Securitized Asset Liquidity June 2017 An He and Bruce Mizrach1 1. Introduction This research note extends our prior analysis2 of corporate bond liquidity to the structured products markets. We analyze data from the TRACE3 system, which began collecting secondary market trading activity on structured products in 2011. We explore two general categories of structured products: (1) real estate securities, including mortgage-backed securities in residential housing (MBS) and commercial building (CMBS), collateralized mortgage products (CMO) and to-be-announced forward mortgages (TBA); and (2) asset-backed securities (ABS) in credit cards, autos, student loans and other miscellaneous categories. Consistent with others,4 we find that the new issue market for securitized assets decreased sharply after the financial crisis and has not yet rebounded to pre-crisis levels. Issuance is below 2007 levels in CMBS, CMOs and ABS. MBS issuance had recovered by 2012 but has declined over the last four years. By contrast, 2016 issuance in the corporate bond market was at a record high for the fifth consecutive year, exceeding $1.5 trillion. Consistent with the new issue volume decline, the median age of securities being traded in non-agency CMO are more than ten years old. In student loans, the average security is over seven years old. Over the last four years, secondary market trading volumes in CMOs and TBA are down from 14 to 27%. Overall ABS volumes are down 16%. Student loan and other miscellaneous ABS declines balance increases in automobiles and credit cards. By contrast, daily trading volume in the most active corporate bonds is up nearly 28%. -
Financial Literacy and Portfolio Diversification
WORKING PAPER NO. 212 Financial Literacy and Portfolio Diversification Luigi Guiso and Tullio Jappelli January 2009 University of Naples Federico II University of Salerno Bocconi University, Milan CSEF - Centre for Studies in Economics and Finance DEPARTMENT OF ECONOMICS – UNIVERSITY OF NAPLES 80126 NAPLES - ITALY Tel. and fax +39 081 675372 – e-mail: [email protected] WORKING PAPER NO. 212 Financial Literacy and Portfolio Diversification Luigi Guiso and Tullio Jappelli Abstract In this paper we focus on poor financial literacy as one potential factor explaining lack of portfolio diversification. We use the 2007 Unicredit Customers’ Survey, which has indicators of portfolio choice, financial literacy and many demographic characteristics of investors. We first propose test-based indicators of financial literacy and document the extent of portfolio under-diversification. We find that measures of financial literacy are strongly correlated with the degree of portfolio diversification. We also compare the test-based degree of financial literacy with investors’ self-assessment of their financial knowledge, and find only a weak relation between the two measures, an issue that has gained importance after the EU Markets in Financial Instruments Directive (MIFID) has required financial institutions to rate investors’ financial sophistication through questionnaires. JEL classification: E2, D8, G1 Keywords: Financial literacy, Portfolio diversification. Acknowledgements: We are grateful to the Unicredit Group, and particularly to Daniele Fano and Laura Marzorati, for letting us contribute to the design and use of the UCS survey. European University Institute and CEPR. Università di Napoli Federico II, CSEF and CEPR. Table of contents 1. Introduction 2. The portfolio diversification puzzle 3. The data 4. -
Understanding Securitization
Understanding Securitization It is important to have a general familiarity with mortgage securitization in order to understand the foreclosure process. Securitization involves a series of conveyances of the note evidencing the residential loan and assignment of the mortgage or trust deed securing it. Therefore, chain of title and beneficial interest issues frequently turn on the securitization trajectories. Securitization is the process pooling loans into “mortgage‐ backed securities” or “MBS” for sale to investors. MBS is an investment instrument backed by an undivided interest in a pool of mortgages or trust deeds. Income from the underlying mortgages is used to pay interest and principal on the securities. Figure A below is a simplified schematic depicting the general securitization process and some of the parties involved. The process begins with Originators, which are the lenders (such as banks or finance companies) that initially make the loans to homeowners. Sponsor/Sellers (or “sponsors”) purchase these loans from one or more Originators to form the pool of assets to be securitized. (Most large financial institutions are both Originators and Sponsor/Sellers.) A Depositor creates a Securitization Trust, a special‐purpose entity, for the securitized transaction. The depositor acquires the pooled assets from the Sponsor/Seller and in turn deposits them into the Securitization Trust. An Issuer acquires the Securitization Trust and issues certificates to eventually be sold to investors. However, the Issuer does not directly offer the certificates for sale to the investors. Instead, the Issuer conveys the certificate to the Depositor in exchange for the pooled assets. An Underwriter, usually an investment bank, purchases all of the certificates from the Depositor with the responsibility of offering to them for sale to the ultimate investors. -
Auction Rate Securities 1
Auction Rate Securities 1 Auction Rate Securities (ARS) were marketed by broker-dealers to investors, including individuals, corporations and charitable foundations as liquid, short-term, cash-equivalent investments similar to traditional commercial paper. The securities, however, were long-term floating rate bonds or preferred stock with floating rate coupons which gave them a superficial similarity to short-term investments. ARS’s liquidity and similarity to short-term investments were entirely dependent on the presence of sufficient orders to buy outstanding ARS at periodic auctions in which they were bought and sold subject to a contractual ceiling on the interest rate the issuer would have to pay. If the interest rate that would clear the market was greater than this maximum rate, the auctions “failed” and existing holders of the securities were forced to hold securities they wanted to sell and had previously thought were liquid. If the demand for an ARS was too low to clear the market, broker dealers sponsoring the auction could place bids just below the maximum interest rate to clear the auction. The lower the public demand for an issue, the larger the quantity broker dealers had to buy to avoid a failed auction. Participating broker dealers had better information than public investors about the creditworthiness of the ARS issuers and were the only parties with information about the broker dealers’ holdings and inclination to abandon their support of the auctions. In addition, brokerage firms involved in the auctions knew of temporary maximum rate waivers negotiated with the issuers and the ratings agencies that allowed auctions that would have failed in late 2007 to continue to clear. -
Auction Rate Securities Issue Brief
C ALIFORNIA DEBT AND ISSUE BRIEF INVESTMENT ADVISORY California Debt and Investment Advisory Commission August 2004 C OMMISSION AUCTION RATE SECURITIES Douglas Skarr CDIAC Policy Research Unit The Auction Rate Securities market has Securities must carefully evaluate the current expanded significantly in the public finance environment, their objectives, and consider how sector since 2001. Nationwide, issuance of this debt will be managed over the long term. auction rate securities, including the public finance area, grew from $100 billion in the This Issue Brief provides an overview of the first quarter of 2002 to $200 billion by the end market, mechanics, costs, benefits and risks of the fourth quarter of 2003. Public finance associated with Auction Rate Securities. has become the fastest-growing sector to use auction rate securities, with total issuance I. DEFINITION AND PURPOSE projected to grow at double-digit rates in the Auction Rate Securities (ARS) are long term, future (see Figure 1). variable rate bonds tied to short term interest rates. ARS have a long term nominal maturity Figure 1 – ARS Issues Outstanding with interest rates reset through a modified ARS Outstanding 2002-2003 Dutch auction, at predetermined short term 250 intervals, usually 7, 28, or 35 days. They trade 200 at par and are callable at par on any interest payment date at the option of the issuer. 150 Interest is paid at the current period based on 100 the interest rate determined in the prior auction ($)In Billions period. 50 0 Although ARS are issued and rated as long term Q1- Q2- Q3- Q4- Q1- Q2- Q3- Q4- 2002 2002 2002 2002 2003 2003 2003 2003 bonds (20 to 30 years), they are priced and Total Municipal traded as short term instruments because of the liquidity provided through the interest rate reset The use of auction rate financing is becoming mechanism. -
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...................................................................................................................................... -
Private Mortgage Securitization and Loan Origination Quality - New Evidence from Loan Losses
Private Mortgage Securitization and Loan Origination Quality - New Evidence from Loan Losses Abdullah Yavas Robert E. Wangard Chair School of Business University of Wisconsin - Madison Madison, WI 53706 [email protected] and Shuang Zhu Associate Professor Department of Finance Kansas State University Manhattan, KS 66506 [email protected] December 11, 2018 1 Private Mortgage Securitization and Loan Origination Quality - New Evidence from Loan Losses Abstract Due to data constraints, earlier studies of the impact of securitization on loan quality have used default probability as a proxy for loan quality. In this paper, we utilize a unique data set that allows us to use loan losses, which incorporate both probability of default and loss given default, to proxy for mortgage quality. Our analysis of prime loans shows that higher expected loan losses are associated with higher probability of securitization. Lenders sell prime loans with lower observable quality and keep higher observable quality loans on their books. For subprime loans, we observe opposite results that lenders sell better quality loans and keep lower quality loans on their book. We then use the cutoff FICO score of 620 to infer the lender’s screening effort with respect to unobservable loan quality. We find that securitized prime loans exhibit no significant difference in default losses for 620- versus 620+ loans. However, securitized subprime loans with a 620- score incur significantly lower loan losses than securitized subprime loans with a 620+ score. By using loan losses as the proxy of loan quality, separating the analysis into prime and subprime samples, and distinguishing between observable and unobservable risk characteristics, this study sheds additional light on the potential channels that the securitization affects loan quality. -
Asset Pricing with Liquidity Risk∗
Asset Pricing with Liquidity Risk∗ Viral V. Acharyay and Lasse Heje Pedersenz First Version: July 10, 2000 Current Version: September 24, 2004 Abstract This paper solves explicitly an equilibrium asset pricing model with liq- uidity risk — the risk arising from unpredictable changes in liquidity over time. In our liquidity-adjusted capital asset pricing model, a security's re- quired return depends on its expected liquidity as well as on the covariances of its own return and liquidity with market return and market liquidity. In addition, the model shows how a negative shock to a security's liquidity, if it is persistent, results in low contemporaneous returns and high predicted future returns. The model provides a simple, unified framework for under- standing the various channels through which liquidity risk may affect asset prices. Our empirical results shed light on the total and relative economic significance of these channels. ∗We are grateful for conversations with Andrew Ang, Joseph Chen, Sergei Davydenko, Fran- cisco Gomes, Joel Hasbrouck, Andrew Jackson, Tim Johnson, Martin Lettau, Anthony Lynch, Stefan Nagel, Lubos Pastor, Tano Santos, Dimitri Vayanos, Luis Viceira, Jeff Wurgler, and semi- nar participants at London Business School, London School of Economics, New York University, the National Bureau of Economic Research (NBER) Summer Institute 2002, the Five Star Confer- ence 2002, Western Finance Association Meetings 2003, and the Texas Finance Festival 2004. We are especially indebted to Yakov Amihud and to an anonymous referee for help and many valuable suggestions. All errors remain our own. yAcharya is at London Business School and is a Research Affiliate of the Centre for Eco- nomic Policy Research (CEPR). -
Arbitrage Pricing Theory
Federal Reserve Bank of New York Staff Reports Arbitrage Pricing Theory Gur Huberman Zhenyu Wang Staff Report no. 216 August 2005 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 the paper are those of the authors and are not necessarily reflective of views at the Federal Reserve Bank of New York or the Federal Reserve System. Any errors or omissions are the responsibility of the authors. Arbitrage Pricing Theory Gur Huberman and Zhenyu Wang Federal Reserve Bank of New York Staff Reports, no. 216 August 2005 JEL classification: G12 Abstract Focusing on capital asset returns governed by a factor structure, the Arbitrage Pricing Theory (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 is contradictory to 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. Key words: arbitrage, asset pricing model, factor model Huberman: Columbia University Graduate School of Business (e-mail: [email protected]). Wang: Federal Reserve Bank of New York and University of Texas at Austin McCombs School of Business (e-mail: [email protected]). This review of the arbitrage pricing theory was written for the forthcoming second edition of The New Palgrave Dictionary of Economics, edited by Lawrence Blume and Steven Durlauf (London: Palgrave Macmillan). -
Liquidity Risk Management
BASEL III FRAMEWORK Liquidity Risk Management Rules and Guidelines November 2018 Table of Contents TABLE OF CONTENTS ...................................................................................................................................... 2 LIST OF ACRONYMS ......................................................................................................................................... 4 PART I – LIQUIDITY RISK MANAGEMENT FRAMEWORK ............................................................... 5 1. BACKGROUND AND OVERVIEW ............................................................................................................................ 5 2. SCOPE OF APPLICATION ...................................................................................................................................... 5 3. STATEMENT OF OBJECTIVES ................................................................................................................................ 5 4. ONGOING LIQUIDITY MANAGEMENT ................................................................................................................... 5 5. MEASURING AND MONITORING LIQUIDITY REQUIREMENTS ............................................................................. 7 6. MANAGING MARKET ACCESS .............................................................................................................................. 9 7. CONTINGENCY PLANNING ................................................................................................................................... -
Options and the Bubble
Options and the Bubble ROBERT BATTALIO and PAUL SCHULTZ* ABSTRACT Many believe that a bubble existed in Internet stocks in the 1999 to 2000 period, and that short-sale restrictions prevented rational investors from driving Internet stock prices to reasonable levels. In the presence of such short-sale constraints, option and stock prices could decouple during a bubble. Using intraday options data from the peak of the Internet bubble, we find almost no evidence that synthetic stock prices diverged from actual stock prices. We also show that the general public could cheaply short synthetically using options. In summary, we find no evidence that short-sale restrictions affected Internet stock prices. *Both authors, Mendoza College of Business, University of Notre Dame. We thank Morgan Stanley & Co., Inc. for financial support. The views expressed herein are solely those of the authors and not those of any other person or entity including Morgan Stanley. We thank an anonymous firm for providing the option data used in our analysis. We gratefully acknowledge comments from seminar participants at the University of North Carolina, the University of Notre Dame, the 2005 American Finance Association meetings, the 2005 Morgan Stanley Equity Microstructure Conference, the 2005 Western Finance Association meetings, Marcus Brunnermeier, Shane Corwin, Tim Loughran, Stewart Mayhew, Allen Poteshman, Matthew Richardson, Robert Whitelaw, and an anonymous referee. Prices of Nasdaq-listed technology stocks rose dramatically in the late 1990s, peaked in March 2000, and then lost more than two-thirds of their value over the next two years. Many of the largest price run-ups and subsequent collapses were associated with Internet stocks.