Arbitrage Pricing Theory and Multifactor Models of Risk and Return
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Credit Derivatives: Macro-Risk Issues
Credit Derivatives: Macro-Risk Issues Credit Derivatives, Macro Risks, and Systemic Risks by Tim Weithers University of Chicago April 20, 2007 Abstract In this paper, some of the “bigger picture” risks associated with credit derivatives are explored. After drawing a distinction between the market’s perception of credit and “real credit” as reflected in the formal definition of a “credit event”, an examination of the macro drivers of credit generally (which might then prove to be one of the catalysts for larger scale concerns with credit derivatives) is undertaken; these have been fairly well researched and documented. Next, the most frequently cited concerns with the modern credit derivative marketplace are enumerated: the exceedingly large notional traded in credit default swaps alone relative to (i.e., integer multiples of) the outstanding supply of debt (bonds and loans) in any single name, the increasing involvement of the hedge fund community in these products, and the operational concerns (lack of timely confirmations,…) which have come to light (and been publicly and roundly criticized) in the last year or two. The possibilities of associated systemic risk are subsequently considered. Credit derivatives deal with risk, involve the transfer of risk, and are, potentially, risky in and of themselves. As in any “new”market, there have been some “glitches”; some of these issues have already been addressed by the market participants and some of these entail the evolving modelling of these instruments. A brief look at the auto downgrade in March 2005 resulted in some “surprises”; part of the concern with these new (and sometimes complex) credit derivative instruments is their proper hedging, risk management, and valuation. -
11.50 Margin Constraints and the Security Market Line
Margin Constraints and the Security Market Line Petri Jylh¨a∗ June 9, 2016 Abstract Between the years 1934 and 1974, the Federal Reserve frequently changed the initial margin requirement for the U.S. stock market. I use this variation in margin requirements to test whether leverage constraints affect the security market line, i.e. the relation between betas and expected returns. Consistent with the theoretical predictions of Frazzini and Ped- ersen (2014), but somewhat contrary to their empirical findings, I find that tighter leverage constraints result in a flatter security market line. My results provide strong empirical sup- port for the idea that funding constraints faced by investors may, at least partially, help explain the empirical failure of the capital asset pricing model. JEL Classification: G12, G14, N22. Keywords: Leverage constraints, Security market line, Margin regulations. ∗Imperial College Business School. Imperial College London, South Kensington Campus, SW7 2AZ, London, UK; [email protected]. I thank St´ephaneChr´etien,Darrell Duffie, Samuli Kn¨upfer,Ralph Koijen, Lubos Pastor, Lasse Pedersen, Joshua Pollet, Oleg Rytchkov, Mungo Wilson, and the participants at American Economic Association 2015, Financial Intermediation Research Society 2014, Aalto University, Copenhagen Business School, Imperial College London, Luxembourg School of Finance, and Manchester Business School for helpful comments. 1 Introduction Ever since the introduction of the capital asset pricing model (CAPM) by Sharpe (1964), Lintner (1965), and Mossin (1966), finance researchers have been studying why the return difference between high and low beta stocks is smaller than predicted by the CAPM (Black, Jensen, and Scholes, 1972). One of the first explanation for this empirical flatness of the security market line is given by Black (1972) who shows that investors' inability to borrow at the risk-free rate results in a lower cross-sectional price of risk than in the CAPM. -
Portfolio Structuring and the Value of Forecasting
Research Foundation Briefs PORTFOLIO STRUCTURING AND THE VALUE OF FORECASTING Jacques Lussier, PhD, CFA, Editor In partnership with CFA Montréal Named Endowments The CFA Institute Research Foundation acknowledges with sincere gratitude the gen- erous contributions of the Named Endowment participants listed below. Gifts of at least US$100,000 qualify donors for membership in the Named Endow- ment category, which recognizes in perpetuity the commitment toward unbiased, practitioner-oriented, relevant research that these firms and individuals have expressed through their generous support of the CFA Institute Research Foundation. Ameritech Meiji Mutual Life Insurance Company Anonymous Miller Anderson & Sherrerd, LLP Robert D. Arnott Nikko Securities Co., Ltd. Theodore R. Aronson, CFA Nippon Life Insurance Company of Japan Asahi Mutual Life Nomura Securities Co., Ltd. Batterymarch Financial Management Payden & Rygel Boston Company Provident National Bank Boston Partners Asset Management, L.P. Frank K. Reilly, CFA Gary P. Brinson, CFA Salomon Brothers Brinson Partners, Inc. Sassoon Holdings Pte. Ltd. Capital Group International, Inc. Scudder Stevens & Clark Concord Capital Management Security Analysts Association of Japan Dai-Ichi Life Company Shaw Data Securities, Inc. Daiwa Securities Sit Investment Associates, Inc. Mr. and Mrs. Jeffrey Diermeier Standish, Ayer & Wood, Inc. Gifford Fong Associates State Farm Insurance Company Investment Counsel Association Sumitomo Life America, Inc. of America, Inc. T. Rowe Price Associates, Inc. Jacobs Levy Equity Management Templeton Investment Counsel Inc. John A. Gunn, CFA Frank Trainer, CFA John B. Neff Travelers Insurance Co. Jon L. Hagler Foundation USF&G Companies Long-Term Credit Bank of Japan, Ltd. Yamaichi Securities Co., Ltd. Lynch, Jones & Ryan, LLC Senior Research Fellows Financial Services Analyst Association For more on upcoming Research Foundation publications and webcasts, please visit www.cfainstitute.org/learning/foundation. -
Frictional Finance “Fricofinance”
Frictional Finance “Fricofinance” Lasse H. Pedersen NYU, CEPR, and NBER Copyright 2010 © Lasse H. Pedersen Frictional Finance: Motivation In physics, frictions are not important to certain phenomena: ……but frictions are central to other phenomena: Economists used to think financial markets are like However, as in aerodynamics, the frictions are central dropping balls to the dynamics of the financial markets: Walrasian auctioneer Frictional Finance - Lasse H. Pedersen 2 Frictional Finance: Implications ¾ Financial frictions affect – Asset prices – Macroeconomy (business cycles and allocation across sectors) – Monetary policy ¾ Parsimonious model provides unified explanation of a wide variety of phenomena ¾ Empirical evidence is very strong – Stronger than almost any other influence on the markets, including systematic risk Frictional Finance - Lasse H. Pedersen 3 Frictional Finance: Definitions ¾ Market liquidity risk: – Market liquidity = ability to trade at low cost (conversely, market illiquidity = trading cost) • Measured as bid-ask spread or as market impact – Market liquidity risk = risk that trading costs will rise • We will see there are 3 relevant liquidity betas ¾ Funding liquidity risk: – Funding liquidity for a security = ability to borrow against that security • Measured as the security’s margin requirement or haircut – Funding liquidity for an investor = investor’s availability of capital relative to his need • “Measured” as Lagrange multiplier of margin constraint – Funding liquidity risk = risk of hitting margin constraint -
Effects of Estimating Systematic Risk in Equity Stocks in the Nairobi Securities Exchange (NSE) (An Empirical Review of Systematic Risks Estimation)
International Journal of Academic Research in Accounting, Finance and Management Sciences Vol. 4, No.4, October 2014, pp. 228–248 E-ISSN: 2225-8329, P-ISSN: 2308-0337 © 2014 HRMARS www.hrmars.com Effects of Estimating Systematic Risk in Equity Stocks in the Nairobi Securities Exchange (NSE) (An Empirical Review of Systematic Risks Estimation) Paul Munene MUIRURI Department of Commerce and Economic Studies Jomo Kenyatta University of Agriculture and Technology Nairobi, Kenya, E-mail: [email protected] Abstract Capital Markets have become an integral part of the Kenyan economy. The manner in which securities are priced in the capital market has attracted the attention of many researchers for long. This study sought to investigate the effects of estimating of Systematic risk in equity stocks of the various sectors of the Nairobi Securities Exchange (NSE. The study will be of benefit to both policy makers and investors to identify the specific factors affecting stock prices. To the investors it will provide useful and adequate information an understanding on the relationship between risk and return as a key piece in building ones investment philosophy. To the market regulators to establish the NSE performance against investors’ perception of risks and returns and hence develop ways of building investors’ confidence, the policy makers to review and strengthening of the legal and regulatory framework. The paper examines the merged 12 sector equity securities of the companies listed at the market into 4sector namely Agricultural; Commercial and Services; Finance and Investment and Manufacturing and Allied sectors. This study Capital Asset Pricing Model (CAPM) of Sharpe (1964) to vis-à-vis the market returns. -
Essays on Empirical Asset Pricing
Essays on Empirical Asset Pricing A THESIS SUBMITTED TO THE FACULTY OF THE GRADUATE SCHOOL OF THE UNIVERSITY OF MINNESOTA BY Junyan Shen IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY JIANFENG YU, HENGJIE AI May, 2016 c Junyan Shen 2016 ALL RIGHTS RESERVED Acknowledgements I am grateful to my advisors: Hengjie Ai and Jianfeng Yu for their valuable suggestions and continuous encouragement. I would also like to thank the rest of my committee members Frederico Belo and Erzo G.J. Luttmer. i Dedication This dissertation is dedicated to my wife and my parents - for their love, care and support. ii Abstract My dissertation investigates the interaction between macroeconomy and asset prices. On one hand, asset returns can be explained by the riskiness embedded in the economic variables; on the other hand, the aggregate economy is affected by the appropriate distri- bution of productive resources, arising from firm’s financing capability. My dissertation contains two chapters which study these two questions respectively. Chapter one explores the role of investor sentiment in the pricing of a broad set of macro-related risk factors. Economic theory suggests that pervasive factors (such as market returns and consumption growth) should be priced in the cross-section of stock returns. However, when we form portfolios based directly on their exposure to macro-related factors, we find that portfolios with higher risk exposure do not earn higher returns. More important, we discover a striking two-regime pattern for all 10 macro-related factors: high-risk portfolios earn significantly higher returns than low-risk portfolios following low-sentiment periods, whereas the exact opposite occurs following high-sentiment periods. -
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 ................................................................................................... -
How Did Too Big to Fail Become Such a Problem for Broker-Dealers?
How did Too Big to Fail become such a problem for broker-dealers? Speculation by Andy Atkeson March 2014 Proximate Cause • By 2008, Broker Dealers had big balance sheets • Historical experience with rapid contraction of broker dealer balance sheets and bank runs raised unpleasant memories for central bankers • No satisfactory legal or administrative procedure for “resolving” failed broker dealers • So the Fed wrestled with the question of whether broker dealers were too big to fail Why do Central Bankers care? • Historically, deposit taking “Banks” held three main assets • Non-financial commercial paper • Government securities • Demandable collateralized loans to broker-dealers • Much like money market mutual funds (MMMF’s) today • Many historical (pre-Fed) banking crises (runs) associated with sharp changes in the volume and interest rates on loans to broker dealers • Similar to what happened with MMMF’s after Lehman? • Much discussion of directions for central bank policy and regulation • New York Clearing House 1873 • National Monetary Commission 1910 • Pecora Hearings 1933 • Friedman and Schwartz 1963 Questions I want to consider • How would you fit Broker Dealers into the growth model? • What economic function do they perform in facilitating trade of securities and financing margin and short positions in securities? • What would such a theory say about the size of broker dealer value added and balance sheets? • What would be lost (socially) if we dramatically reduced broker dealer balance sheets by regulation? • Are broker-dealer liabilities -
Return, Risk and the Security Market Line Systematic and Unsystematic
Expected and Unexpected Returns • The return on any stock traded in a Return, Risk and the Security financial market is composed of two parts. c The normal, or expected, part of the return is Market Line the return that investors predict or expect. d The uncertain, or risky, part of the return Chapter 18 comes from unexpected information revealed during the year. • Total return – Expected return = Unexpected return R – E(R) = U Systematic and Unsystematic Diversification and Risk Risk Systematic risk • In a large portfolio, some stocks will go up in value because of positive company-specific Risk that influences a large number of events, while others will go down in value assets. Also called market risk. because of negative company-specific events. Unsystematic risk • Unsystematic risk is essentially eliminated by Risk that influences a single company or diversification, so a portfolio with many assets a small group of companies. Also called has almost no unsystematic risk. unique or asset-specific risk. • Unsystematic risk is also called diversifiable risk, while systematic risk is also called nondiversifiable risk. Total risk = Systematic risk + Unsystematic risk The Systematic Risk Principle Measuring Systematic Risk • The systematic risk principle states that Beta coefficient (β) the reward for bearing risk depends only Measure of the relative systematic risk of an on the systematic risk of an investment. asset. Assets with betas larger than 1.0 • So, no matter how much total risk an asset have more systematic risk than average, has, only the systematic portion is relevant and vice versa. in determining the expected return (and • Because assets with larger betas have the risk premium) on that asset. -
Five-Minute-Mba-In-Corporate-Finance
GetPedia : Get How Stuff Works! Works! Welcome To GetPedia.com The Online Information Resource Providing You the Most Unique Content and Genuine Articles in the most Widest range categories. Browse and discover Information in each and every category. There are currently more than 500,000 articles to browse for. Business Communications Health & Fitness Advertising Broadband Internet Acne Branding Mobile & Cell Phone Aerobics & Cardio Business Management VOIP Alternative Medicine Business Ethics Video Conferencing Beauty Tips Careers, Jobs & Employment Satellite TV Depression Customer Service Diabetes Reference & Education Marketing Exercise & Fitness Networking Book Reviews Fitness Equipment Network Marketing College & University Hair Loss Pay-Per-Click Advertising Psychology Medicine Presentation Science Articles Meditation Public Relations Food & Drinks Muscle Building & Sales Bodybuilding Sales Management Coffee Nutrition Sales Telemarketing Cooking Tips Nutritional Supplements Sales Training Recipes & Food and Drink Weight Loss Small Business Wine & Spirits Yoga Strategic Planning Home & Family Entrepreneur Recreation and Sport Negotiation Tips Crafts & Hobbies Fishing Team Building Elder Care Golf Top Quick Tips Holiday Martial Arts Home Improvement Internet & Businesses Online Motorcycle Home Security Affiliate Revenue Interior Design & Decorating Self Improvement & Motivation Blogging, RSS & Feeds Landscaping & Gardening Attraction Domain Name Babies & Toddler Coaching E-Book Pets Creativity E-commerce Parenting Dealing with Grief -
Empirical Study on CAPM Model on China Stock Market
Empirical study on CAPM model on China stock market MASTER THESIS WITHIN: Business administration in finance NUMBER OF CREDITS: 15 ECTS TUTOR: Andreas Stephan PROGRAMME OF STUDY: international financial analysis AUTHOR: Taoyuan Zhou, Huarong Liu JÖNKÖPING 05/2018 Master Thesis in Business Administration Title: Empirical study on CAPM model of China stock market Authors: Taoyuan Zhou and Huarong Liu Tutor: Andreas Stephan Date: 05/2018 Key terms: CAPM model, β coefficient, empirical test Abstract Background: The capital asset pricing model (CAPM) describes the interrelationship between the expected return of risk assets and risk in the equilibrium of investment market and gives the equilibrium price of risky assets (Banz, 1981). CAPM plays a very important role in the process of establishing a portfolio (Bodie, 2009). As Chinese stock market continues to grow and expand, the scope and degree of attention of CAPM models in China will also increase day by day. Therefore, in China, such an emerging market, it is greatly necessary to test the applicability and validity of the CAPM model in the capital market. Purpose: Through the monthly data of 100 stocks from January 1, 2007 to February 1, 2018, the time series and cross-sectional data of the capital asset pricing model on Chinese stock market are tested. The main objectives are: (1) Empirical study of the relationship between risk and return using the data of Chinese stock market in recent years to test whether the CAPM model established in the developed western market is suitable for the Chinese market. (2) Through the empirical analysis of the results to analyse the characteristics and existing problems of Chinese capital market. -
Macro Risks and the Term Structure of Interest Rates∗
Macro Risks and the Term Structure of Interest Rates∗ Geert Bekaert, Columbia University and the National Bureau of Economic Research, Eric Engstrom, Board of Governors of the Federal Reserve System Andrey Ermolov, Gabelli School of Business, Fordham University May 31, 2018 Abstract We use non-Gaussian features in U.S. macroeconomic data to identify aggregate supply and demand shocks while imposing minimal economic assumptions. Recessions in the 1970s and 1980s were driven primarily by supply shocks; later recessions by demand shocks. We estimate macro risk factors that drive \bad" (negatively skewed) and \good" (positively skewed) variation for supply and demand shocks. We document that macro risks significantly contribute to the variation of yields, risk premiums and return variances for nominal bonds. While overall bond risk premiums are counter-cyclical, an increase in aggregate demand variance significantly lowers risk premiums. Keywords: macroeconomic volatility, business cycles, bond return predictability, term premium, Great Moderation JEL codes: E31, E32, E43, E44, G12, G13 ∗Contact information: Geert Bekaert - [email protected], Eric Engstrom - eric.c. [email protected], Andrey Ermolov - [email protected]. Authors thank Michael Bauer, Mikhail Chernov, Philipp Illeditsch, Andrea Vedolin, seminar participants at Baruch College, Bilkent University, University of British Columbia, Bundesbank, City University of London, Duke, Fordham, University of Illinois at Urbana-Champaign, Imperial College, Oxford, Riksbank, Sabanci Business School, Tulane, University of North Carolina at Chapel-Hill, and Stevens Institute of Technology and conference par- ticipants at 2015 Federal Reserve Bank of San Francisco and Bank of Canada Conference on Fixed Income Markets, 2016 NBER Summer Institute, 2016 Society of Financial Econometrics Meeting, 2017 European Finance Association Meeting, 2017 NBER-NSF Time Series Conference, Spring 2018 Midwest Macroeconomics Meetings, and 2018 SFS Cavalcade North America for useful comments.