The Price of Protection: Derivatives, Default Risk, and Margining∗
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Up to EUR 3,500,000.00 7% Fixed Rate Bonds Due 6 April 2026 ISIN
Up to EUR 3,500,000.00 7% Fixed Rate Bonds due 6 April 2026 ISIN IT0005440976 Terms and Conditions Executed by EPizza S.p.A. 4126-6190-7500.7 This Terms and Conditions are dated 6 April 2021. EPizza S.p.A., a company limited by shares incorporated in Italy as a società per azioni, whose registered office is at Piazza Castello n. 19, 20123 Milan, Italy, enrolled with the companies’ register of Milan-Monza-Brianza- Lodi under No. and fiscal code No. 08950850969, VAT No. 08950850969 (the “Issuer”). *** The issue of up to EUR 3,500,000.00 (three million and five hundred thousand /00) 7% (seven per cent.) fixed rate bonds due 6 April 2026 (the “Bonds”) was authorised by the Board of Directors of the Issuer, by exercising the powers conferred to it by the Articles (as defined below), through a resolution passed on 26 March 2021. The Bonds shall be issued and held subject to and with the benefit of the provisions of this Terms and Conditions. All such provisions shall be binding on the Issuer, the Bondholders (and their successors in title) and all Persons claiming through or under them and shall endure for the benefit of the Bondholders (and their successors in title). The Bondholders (and their successors in title) are deemed to have notice of all the provisions of this Terms and Conditions and the Articles. Copies of each of the Articles and this Terms and Conditions are available for inspection during normal business hours at the registered office for the time being of the Issuer being, as at the date of this Terms and Conditions, at Piazza Castello n. -
Margin Requirements Across Equity-Related Instruments: How Level Is the Playing Field?
Fortune pgs 31-50 1/6/04 8:21 PM Page 31 Margin Requirements Across Equity-Related Instruments: How Level Is the Playing Field? hen interest rates rose sharply in 1994, a number of derivatives- related failures occurred, prominent among them the bankrupt- cy of Orange County, California, which had invested heavily in W 1 structured notes called “inverse floaters.” These events led to vigorous public discussion about the links between derivative securities and finan- cial stability, as well as about the potential role of new regulation. In an effort to clarify the issues, the Federal Reserve Bank of Boston sponsored an educational forum in which the risks and risk management of deriva- tive securities were discussed by a range of interested parties: academics; lawmakers and regulators; experts from nonfinancial corporations, investment and commercial banks, and pension funds; and issuers of securities. The Bank published a summary of the presentations in Minehan and Simons (1995). In the keynote address, Harvard Business School Professor Jay Light noted that there are at least 11 ways that investors can participate in the returns on the Standard and Poor’s 500 composite index (see Box 1). Professor Light pointed out that these alternatives exist because they dif- Peter Fortune fer in a variety of important respects: Some carry higher transaction costs; others might have higher margin requirements; still others might differ in tax treatment or in regulatory restraints. The author is Senior Economist and The purpose of the present study is to assess one dimension of those Advisor to the Director of Research at differences—margin requirements. -
Predicting the Probability of Corporate Default Using Logistic Regression
UGC Approval No:40934 CASS-ISSN:2581-6403 Predicting the Probability of Corporate HEB CASS Default using Logistic Regression *Deepika Verma *Research Scholar, School of Management Science, Department of Commerce, IGNOU Address for Correspondence: [email protected] ABSTRACT This paper studies the probability of default of Indian Listed companies. Study aims to develop a model by using Logistic regression to predict the probability of default of corporate. Study has undertaken 90 Indian Companies listed in BSE; financial data is collected for the financial year 2010- 2014. Financial ratios have been considered as the independent predictors of the defaulting companies. The empirical result demonstrates that the model is best fit and well capable to predict the default on loan with 92% of accuracy. Access this Article Online http://heb-nic.in/cass-studies Quick Response Code: Received on 25/03/2019 Accepted on 11/04/2019@HEB All rights reserved April 2019 – Vol. 3, Issue- 1, Addendum 7 (Special Issue) Page-161 UGC Approval No:40934 CASS-ISSN:2581-6403 INTRODUCTION Credit risk is eternal for the banking and financial institutions, there is always an uncertainty in receiving the repayments of the loans granted to the corporate (Sirirattanaphonkun&Pattarathammas, 2012). Many models have been developed for predicting the corporate failures in advance. To run the economy on the right pace the banking system of that economy must be strong enough to gauge the failure of the corporate in the repayment of loan. Financial crisis has been witnessed across the world from Latin America, to Asia, from Nordic Countries to East and Central European countries (CIMPOERU, 2015). -
Margin Requirements and Equity Option Returns∗
Margin Requirements and Equity Option Returns∗ Steffen Hitzemann† Michael Hofmann‡ Marliese Uhrig-Homburg§ Christian Wagner¶ December 2017 Abstract In equity option markets, traders face margin requirements both for the options them- selves and for hedging-related positions in the underlying stock market. We show that these requirements carry a significant margin premium in the cross-section of equity option returns. The sign of the margin premium depends on demand pressure: If end-users are on the long side of the market, option returns decrease with margins, while they increase otherwise. Our results are statistically and economically significant and robust to different margin specifications and various control variables. We explain our findings by a model of funding-constrained derivatives dealers that require compensation for satisfying end-users’ option demand. Keywords: equity options, margins, funding liquidity, cross-section of option returns JEL Classification: G12, G13 ∗We thank Hameed Allaudeen, Mario Bellia, Jie Cao, Zhi Da, Matt Darst, Maxym Dedov, Bjørn Eraker, Andrea Frazzini, Ruslan Goyenko, Guanglian Hu, Hendrik Hülsbusch, Kris Jacobs, Stefan Kanne, Olaf Korn, Dmitriy Muravyev, Lasse Pedersen, Matthias Pelster, Oleg Rytchkov, Ivan Shaliastovich, as well as participants of the 2017 EFA Annual Meeting, the SFS Cavalcade North America 2017, the 2017 MFA Annual Meeting, the SGF Conference 2017, the Conference on the Econometrics of Financial Markets, the 2016 Annual Meeting of the German Finance Association, the Paris December 2016 Finance Meeting, and seminar participants at the Center for Financial Frictions at Copenhagen Business School, the CUHK Business School, the University of Gothenburg, and the University of Wisconsin-Madison for valuable discussions and helpful comments and suggestions. -
Margin-Based Asset Pricing and Deviations from the Law of One Price∗
Margin-Based Asset Pricing and Deviations from the Law of One Price∗ Nicolae Gˆarleanu and Lasse Heje Pedersen† Current Version: September 2009 Abstract In a model with heterogeneous-risk-aversion agents facing margin constraints, we show how securities’ required returns are characterized both by their betas and their margins. Negative shocks to fundamentals make margin constraints bind, lowering risk-free rates and raising Sharpe ratios of risky securities, especially for high-margin securities. Such a funding liquidity crisis gives rise to “bases,” that is, price gaps between securities with identical cash-flows but different margins. In the time series, bases depend on the shadow cost of capital, which can be captured through the interest- rate spread between collateralized and uncollateralized loans, and, in the cross section, they depend on relative margins. We apply the model empirically to CDS-bond bases and other deviations from the Law of One Price, and to evaluate the Fed lending facilities. ∗We are grateful for helpful comments from Markus Brunnermeier, Xavier Gabaix, Andrei Shleifer, and Wei Xiong, as well as from seminar participants at the Bank of Canada, Columbia GSB, London School of Economics, MIT Sloan, McGill University, Northwestern University Kellog, UT Austin McCombs, UC Berkeley Haas, the Yale Financial Crisis Conference, and Yale SOM. †Gˆarleanu (corresponding author) is at Haas School of Business, University of California, Berkeley, NBER, and CEPR; e-mail: [email protected]. Pedersen is at New York University, NBER, and CEPR, 44 West Fourth Street, NY 10012-1126; e-mail: [email protected], http://www.stern.nyu.edu/∼lpederse/. -
Guide for Margin Finance
Guide for Margin Finance Guide for Margin Finance Contents Margin Finance What is margin finance? How does margin finance take place? Risks of margin finance Acknowledgement 1 / 6 Guide for Margin Finance Margin Finance Investors should request copies from their financial brokers and familiarize themselves with the following: The guide issued by the Jordan Securities Commission, Margin Finance Instructions, the list of securities allowed to be margin financed, and the margin finance agreement. Investors should also sign an acknowledgement that they have familiarized themselves with the above in order to protect their rights. This guide aims to familiarize investors with the concept of margin finance and the risks related to it. It should be read thoroughly. 2 / 6 Guide for Margin Finance What is margin finance? The term “Margin Finance” shall mean the financing by a Financial Broker of a part of the value of the securities in the margin finance account by guaranteeing the securities in that account. How does margin finance take place? Say you are an investor and you buy shares worth JD 5,000 with your own money, then the value of these shares rises to JD 7,500, your profit would be 50%. But if you finance your purchase of these shares through margin finance the shares, you would pay JD 2,500 of your own money and your broker would pay JD 2,500, so your profit would be 100%. In other words, your profit is greater when you margin finance. If, on the other hand, the value of the shares drops to JD 2,500 after you had bought them with your own money, your loss would be 50%; but if you had bought them from the margin finance account, your loss would be 100% plus any interest payments and fees. -
Chapter 5 Credit Risk
Chapter 5 Credit risk 5.1 Basic definitions Credit risk is a risk of a loss resulting from the fact that a borrower or counterparty fails to fulfill its obligations under the agreed terms (because he or she either cannot or does not want to pay). Besides this definition, the credit risk also includes the following risks: Sovereign risk is the risk of a government or central bank being unwilling or • unable to meet its contractual obligations. Concentration risk is the risk resulting from the concentration of transactions with • regard to a person, a group of economically associated persons, a government, a geographic region or an economic sector. It is the risk associated with any single exposure or group of exposures with the potential to produce large enough losses to threaten a bank's core operations, mainly due to a low level of diversification of the portfolio. Settlement risk is the risk resulting from a situation when a transaction settlement • does not take place according to the agreed conditions. For example, when trading bonds, it is common that the securities are delivered two days after the trade has been agreed and the payment has been made. The risk that this delivery does not occur is called settlement risk. Counterparty risk is the credit risk resulting from the position in a trading in- • strument. As an example, this includes the case when the counterparty does not honour its obligation resulting from an in-the-money option at the time of its ma- turity. It also important to note that the credit risk is related to almost all types of financial instruments. -
EQUITY EQUITY DER- PARAMETERS METHODOLOGIES USED in MARGIN CALCULATIONS Manual
EQUITY EQUITY DER- PARAMETERS METHODOLOGIES USED IN MARGIN CALCULATIONS Manual APRIL 2021 V02.0 1 TABLE OF CONTENTS Executive summary ...................................................................................... 3 Methodologies for determining Margin Parameters used in Margin Calculations ...................................................................................................... 5 2.1 Main parameters...................................................................................... 6 2.2 Margin Interval calculation ...................................................................... 7 2.2.1 Defining Coverage Level......................................................................... 7 2.2.2 Determining the Margin Interval for Equity cash ........................................ 7 2.2.3 Determining the Margin Interval for Equity derivatives .............................. 10 2.3 Product Group Offset Factor .................................................................. 10 2.4 Futures Straddle Margin ........................................................................ 10 2.4.1 Straddle Interest Rate Methodology ........................................................ 11 2.4.2 Straddle Correlation Methodology ........................................................... 13 2.5 Minimum Initial Margin ......................................................................... 13 2.6 Margin Intervals and Additional Margin changes ................................... 14 2 EXECUTIVE SUMMARY 3 EXECUTIVE SUMMARY This -
Margin-Based Asset Pricing and Deviations from the Law of One Price
Margin-based Asset Pricing and Deviations from the Law of One Price Nicolae Garleanuˆ University of California Lasse Heje Pedersen New York University In a model with heterogeneous-risk-aversion agents facing margin constraints, we show how securities’ required returns increase in both their betas and their margin require- ments. Negative shocks to fundamentals make margin constraints bind, lowering risk-free rates and raising Sharpe ratios of risky securities, especially for high-margin securities. Such a funding-liquidity crisis gives rise to “bases,” that is, price gaps between securities with identical cash-flows but different margins. In the time series, bases depend onthe shadow cost of capital, which can be captured through the interest-rate spread between collateralized and uncollateralized loans and, in the cross-section, they depend on rela- tive margins. We test the model empirically using the credit default swap–bond bases and other deviations from the Law of One Price, and use it to evaluate central banks’ lending facilities. (JEL G01, G12, G13, E44, E50) The paramount role of funding constraints becomes particularly salient dur- ing liquidity crises, with the one that started in 2007 being an excellent case in point. Banks unable to fund their operations closed down, and the fund- ing problems spread to other investors, such as hedge funds, that relied on bank funding. Therefore, traditional liquidity providers became forced sellers, interest-rate spreads increased dramatically, Treasury rates dropped sharply, and central -
Probability of Default (PD) Is the Core Credit Product of the Credit Research Initiative (CRI)
2019 The Credit Research Initiative (CRI) National University of Singapore First version: March 2, 2017, this version: January 8, 2019 Probability of Default (PD) is the core credit product of the Credit Research Initiative (CRI). The CRI system is built on the forward intensity model developed by Duan et al. (2012, Journal of Econometrics). This white paper describes the fundamental principles and the implementation of the model. Details of the theoretical foundations and numerical realization are presented in RMI-CRI Technical Report (Version 2017). This white paper contains five sections. Among them, Sections II & III describe the methodology and performance of the model respectively, and Section IV relates to the examples of how CRI PD can be used. ........................................................................ 2 ............................................................... 3 .................................................. 8 ............................................................... 11 ................................................................. 14 .................... 15 Please cite this document in the following way: “The Credit Research Initiative of the National University of Singapore (2019), Probability of Default (PD) White Paper”, Accessible via https://www.rmicri.org/en/white_paper/. 1 | Probability of Default | White Paper Probability of Default (PD) is the core credit measure of the CRI corporate default prediction system built on the forward intensity model of Duan et al. (2012)1. This forward -
Equity Friendly Or Noteholder Friendly? the Role of Collateral Asset Managers in the Col- Lapse of the Market for ABS-Cdos
Equity friendly or noteholder friendly? The role of collateral asset managers in the col- lapse of the market for ABS-CDOs Thomas Mählmann Chair of Banking and Finance, Catholic University of Eichstaett-Ingolstadt, Auf der Schanz 49, 85049 Ingolstadt, Germany This version: April 2012 Abstract This paper shows that ABS-CDOs (i.e., collateralized debt obligations backed by asset- backed securities) managed by large market share managers have higher ex post collateral default rates. The paper also finds that (1) large manager deals, while having higher realized default rates, do not carry more default risk ex ante (at origination), as measured by the deal fraction rated AAA or the size of the equity tranche, (2) ex post, these deals have higher per- centages of home-equity loans, subprime RMBS and synthetic assets in their collateral pools, and larger asset-specific default rates and issuer concentration levels, (3) compared to smaller managers, large market share manager deals pay out higher cash flows to equity tranche in- vestors prior to the start of the subprime crisis (July 2007) but significantly lower cash flows afterwards, and (4) investors demand a (price) discount on non-equity tranches sold by large manager deals. In sum, this evidence is consistent with a conflict of interest/risk shifting ar- gument: some managers boost their market share by catering to the interests of the deals’ eq- uity sponsors. JEL classification: G21, G28 Keywords: Conflict of interest, Credit Rating, Collateralized Debt Obligation, Yield Spread Tel.: +49 841 937 1883; fax: +49 841 937 2883. E-mail address: [email protected] 1. -
Mortgage Finance and Climate Change: Securitization Dynamics in the Aftermath of Natural Disasters
NBER WORKING PAPER SERIES MORTGAGE FINANCE AND CLIMATE CHANGE: SECURITIZATION DYNAMICS IN THE AFTERMATH OF NATURAL DISASTERS Amine Ouazad Matthew E. Kahn Working Paper 26322 http://www.nber.org/papers/w26322 NATIONAL BUREAU OF ECONOMIC RESEARCH 1050 Massachusetts Avenue Cambridge, MA 02138 September 2019, Revised February 2021 We thank Jeanne Sorin for excellent research assistance in the early stages of the project. We would like to thank Asaf Bernstein, Justin Contat, Thomas Davido , Matthew Eby, Lynn Fisher, Ambika Gandhi, Richard K. Green, Jesse M. Keenan, Michael Lacour-Little, William Larson, Stephen Oliner, Ying Pan, Tsur Sommerville, Stan Veuger, James Vickery, Susan Wachter, for comments on early versions of our paper, as well as the audience of the seminar series at George Washington University, the 2018 annual meeting of the Urban Economics Association at Columbia University, Stanford University, the Canadian Urban Economics Conference, the University of Southern California, the American Enterprise Institute. The usual disclaimers apply. Amine Ouazad would like to thank the HEC Montreal Foundation for nancial support through the research professorship in Urban and Real Estate Economics. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. 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. © 2019 by Amine Ouazad and Matthew E. Kahn. 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.