Return, Risk, and the Total Return  Expected Return  Unexpected Return Security Market Line Unexpected Return  Total Return - Expected Return

Total Page:16

File Type:pdf, Size:1020Kb

Return, Risk, and the Total Return  Expected Return  Unexpected Return Security Market Line Unexpected Return  Total Return - Expected Return Expected and Unexpected Returns Chapter • The return on any stock traded in a financial market is composed of two parts. – The normal, or expected, part of the return is the return that investors predict or expect. – The uncertain, or risky, part of the return comes from unexpected information revealed during the year. 12 Return, Risk, and the Total Return Expected Return Unexpected Return Security Market Line Unexpected Return Total Return - Expected Return U R - E(R) McGraw-Hill/Irwin Copyright © 2009 by The McGraw-Hill Companies, Inc. All rights reserved. 12-2 Announcements and News Systematic and Unsystematic Risk • Firms make periodic announcements about events that may significantly impact the profits of the firm. – Earnings • Systematic risk is risk that influences a large number of – Product development assets. Also called market risk. – Personnel • The impact of an announcement depends on how much of the • Unsystematic risk is risk that influences a single announcement represents new information. company or a small group of companies. Also called – When the situation is not as bad as previously thought, what seems unique risk or firm-specific risk. to be bad news is actually good news. – When the situation is not as good as previously thought, what seems to be good news is actually bad news. • News about the future is what really matters. Total risk = Systematic risk + Unsystematic risk – Market participants factor predictions about the future into the expected part of the stock return. – Announcement = Expected News + Surprise News 12-3 12-4 Diversification and Risk The Systematic Risk Principle • In a large portfolio: • What determines the size of the risk premium on a risky – Some stocks will go up in value because of positive company- asset? specific events, while – Others will go down in value because of negative company- • The systematic risk principle states: specific events. • Unsystematic risk is essentially eliminated by The expected return on an asset depends diversification, so a portfolio with many assets has almost only on its systematic risk. no unsystematic risk. • So, no matter how much total risk an asset has, only the • Unsystematic risk is also called diversifiable risk. systematic portion is relevant in determining the expected return (and the risk premium) on that asset. • Systematic risk is also called non-diversifiable risk. 12-5 12-6 Portfolio Expected Returns Measuring Systematic Risk and Betas for Asset A • To be compensated for risk, the risk has to be special. – Unsystematic risk is not special. – Systematic risk is special. • The Beta coefficient () measures the relative systematic risk of an asset. – Assets with Betas larger than 1.0 have more systematic risk than average. – Assets with Betas smaller than 1.0 have less systematic risk than average. • Because assets with larger betas have greater systematic risks, they will have greater expected returns. Note that not all Betas are created equally. 12-7 12-8 The Reward-to-Risk Ratio The Fundamental Result • Notice that all the combinations of portfolio expected returns and In general … betas fall on a straight line. • Slope (Rise over Run): • The reward-to-risk ratio must be the same for all assets in a competitive financial market. ER R 16% 4% A f 7.50% βA 1.6 • If one asset has twice as much systematic risk as another asset, its risk premium will simply be twice as large. • What this tells us is that asset A offers a reward-to-risk ratio of • Because the reward-to-risk ratio must be the same, all 7.50%. In other words, asset A has a risk premium of 7.50% per assets in the market must plot on the same line. “unit” of systematic risk. 12-9 12-10 The Security Market Line (SML) The Security Market Line, II. • The term E(RM) – Rf is often called the market risk • The Security market line (SML) is a graphical premium because it is the risk premium on a market representation of the linear relationship between portfolio. systematic risk and expected return in financial markets. ERi Rf • For any asset i in the market: ERM Rf • For a market portfolio, βi ERM Rf ERM Rf ERi Rf ERM Rf βi βM 1 ERM Rf • Setting the reward-to-risk ratio for all assets equal to the market risk premium results in an equation known as the capital asset pricing model. 12-11 12-12 The Security Market Line, III. The Security Market Line, IV. • The Capital Asset Pricing Model (CAPM) is a theory of risk and return for securities in a competitive capital market. ERi Rf ERM Rf βi • The CAPM shows that E(Ri) depends on: – Rf, the pure time value of money. – E(RM) – Rf, the reward for bearing systematic risk. – i, the amount of systematic risk. 12-13 12-14 Risk and Return Summary, I. Risk and Return Summary, II. 12-15 12-16 A Closer Look at Beta Where Do Betas Come From? • R – E(R) = m + , where m is the systematic portion of • A security’s Beta depends on: the unexpected return. – How closely correlated the security’s return is with the overall market’s return, and • m = [RM – E(RM)] – How volatile the security is relative to the market. • So, R – E(R) = [RM – E(RM)] + • A security’s Beta is equal to the correlation multiplied by the ratio of the standard deviations. • In other words: – A high-Beta security is simply one that is relatively sensitive to σ β CorrR ,R i overall market movements i i M σ – A low-Beta security is one that is relatively insensitive to overall m market movements. 12-17 12-18 Why Do Betas Differ? Extending CAPM • Betas are estimated from actual data. Different sources • The CAPM has a stunning implication: estimate differently, possibly using different data. – What you earn on your portfolio depends only on the level of – For data, the most common choices are three to five years of systematic risk that you bear monthly data, or a single year of weekly data. – As a diversified investor, you do not need to worry about total – To measure the overall market, the S&P 500 stock market index risk, only systematic risk. is commonly used. – The calculated betas may be adjusted for various statistical • But, does expected return depend only on Beta? Or, do reasons. other factors come into play? • The above bullet point is a hotly debated question. 12-19 12-20 Important General Risk-Return Principles The Fama-French Three-Factor Model • Investing has two dimensions: risk and return. • Professors Gene Fama and Ken French argue that two additional factors should be added. • It is inappropriate to look at the total risk of an individual security. • In addition to beta, two other factors appear to be useful in explaining the relationship between risk and return. • It is appropriate to look at how an individual security – Size, as measured by market capitalization contributes to the risk of the overall portfolio – The book value to market value ratio, i.e., B/M • Risk can be decomposed into nonsystematic and • Whether these two additional factors are truly sources of systematic risk. systematic risk is still being debated. • Investors will be compensated only for systematic risk. 12-21 12-22.
Recommended publications
  • The Effect of Systematic Risk Factors on the Performance of the Malaysia Stock Market
    57 Proceedings of International Conference on Economics 2017 (ICE 2017) PROCEEDINGS ICE 2017 P57 – P68 ISBN 978-967-0521-99-2 THE EFFECT OF SYSTEMATIC RISK FACTORS ON THE PERFORMANCE OF THE MALAYSIA STOCK MARKET Shameer Fahmi, Caroline Geetha, Rosle Mohidin Faculty of Business, Economics and Accountancy, Universiti Malaysia Sabah ABSTRACT Malaysia has undergone a tremendous transformation in its economic due to the New Economic This has created instability on the changes in the macroeconomic fundamental, called systematic risk. The study aims to determine the effect of the systematic risk towards the performance of the stock returns. The paper aims to use the arbitrage pricing theory (APT) framework to relate the systematic risk with the performance of stock return. The variables chosen to represent the systematic risk were variables that were in line with the transformation policy implemented. The independent variables chosen were interest rate, inflation rate due to the removal of fuel subsidy and the implementation of good and service tax, exchange rate which is influenced by the inflow of foreign direct investment, crude oil price that determines the revenue of the country being an oil exporter and industrial production index that reflect political as well as business news meanwhile the dependent variable is stock returns. All the macroeconomic variables will be regressed with the lagged 2 of its own variable to obtain the residuals. The residuals will be powered by two to obtain the variance which represents the risk of each variable. The variables were run for unit root to determine the level of stationarity. This was followed by the establishment of long run relationship using Johansen Cointegration and short run relationship using Vector Error Correction Modeling.
    [Show full text]
  • Systematic Risk of Cdos and CDO Arbitrage
    Systematic risk of CDOs and CDO arbitrage Alfred Hamerle (University of Regensburg) Thilo Liebig (Deutsche Bundesbank) Hans-Jochen Schropp (University of Regensburg) Discussion Paper Series 2: Banking and Financial Studies No 13/2009 Discussion Papers represent the authors’ personal opinions and do not necessarily reflect the views of the Deutsche Bundesbank or its staff. Editorial Board: Heinz Herrmann Thilo Liebig Karl-Heinz Tödter Deutsche Bundesbank, Wilhelm-Epstein-Strasse 14, 60431 Frankfurt am Main, Postfach 10 06 02, 60006 Frankfurt am Main Tel +49 69 9566-0 Telex within Germany 41227, telex from abroad 414431 Please address all orders in writing to: Deutsche Bundesbank, Press and Public Relations Division, at the above address or via fax +49 69 9566-3077 Internet http://www.bundesbank.de Reproduction permitted only if source is stated. ISBN 978-3–86558–570–7 (Printversion) ISBN 978-3–86558–571–4 (Internetversion) Abstract “Arbitrage CDOs” have recorded an explosive growth during the years before the outbreak of the financial crisis. In the present paper we discuss potential sources of such arbitrage opportunities, in particular arbitrage gains due to mispricing. For this purpose we examine the risk profiles of Collateralized Debt Obligations (CDOs) in some detail. The analyses reveal significant differences in the risk profile between CDO tranches and corporate bonds, in particular concerning the considerably increased sensitivity to systematic risks. This has far- reaching consequences for risk management, pricing and regulatory capital requirements. A simple analytical valuation model based on the CAPM and the single-factor Merton model is used in order to keep the model framework simple.
    [Show full text]
  • Is the Insurance Industry Systemically Risky?
    Is the Insurance Industry Systemically Risky? Viral V Acharya and Matthew Richardson1 1 Authors are at New York University Stern School of Business. E-mail: [email protected], [email protected]. Some of this essay is based on “Systemic Risk and the Regulation of Insurance Companies”, by Viral V Acharya, John Biggs, Hanh Le, Matthew Richardson and Stephen Ryan, published as Chapter 9 in Regulating Wall Street: The Dodd-Frank Act and the Architecture of Global Finance, edited by Viral V Acharya, Thomas Cooley, Matthew Richardson and Ingo Walter, John Wiley & Sons, November 2010. [Type text] Is the Insurance Industry Systemically Risky? i VIRAL V ACHARYA AND MATTHEW RICHARDSON I. Introduction As a result of the financial crisis, the Congress passed the Dodd-Frank Wall Street Reform and Consumer Protection Act and it was signed into law by President Obama on July 21, 2010. The Dodd-Frank Act did not create a new direct regulator of insurance but did impose on non-bank holding companies, possibly insurance entities, a major new and unknown form of regulation for those deemed “Systemically Important Financial Institutions” (SIFI) (sometimes denoted “Too Big To Fail” (TBTF)) or, presumably any entity which regulators believe represents a “contingent liability” for the federal government, in the event of severe stress or failure. In light of the financial crisis, and the somewhat benign changes to insurance regulation contained in the Dodd-Frank Act (regulation of SIFIs aside), how should a modern insurance regulatory structure be designed to deal with systemic risk? The economic theory of regulation is very clear.
    [Show full text]
  • Multi-Factor Models and the Arbitrage Pricing Theory (APT)
    Multi-Factor Models and the Arbitrage Pricing Theory (APT) Econ 471/571, F19 - Bollerslev APT 1 Introduction The empirical failures of the CAPM is not really that surprising ,! We had to make a number of strong and pretty unrealistic assumptions to arrive at the CAPM ,! All investors are rational, only care about mean and variance, have the same expectations, ... ,! Also, identifying and measuring the return on the market portfolio of all risky assets is difficult, if not impossible (Roll Critique) In this lecture series we will study an alternative approach to asset pricing called the Arbitrage Pricing Theory, or APT ,! The APT was originally developed in 1976 by Stephen A. Ross ,! The APT starts out by specifying a number of “systematic” risk factors ,! The only risk factor in the CAPM is the “market” Econ 471/571, F19 - Bollerslev APT 2 Introduction: Multiple Risk Factors Stocks in the same industry tend to move more closely together than stocks in different industries ,! European Banks (some old data): Source: BARRA Econ 471/571, F19 - Bollerslev APT 3 Introduction: Multiple Risk Factors Other common factors might also affect stocks within the same industry ,! The size effect at work within the banking industry (some old data): Source: BARRA ,! How does this compare to the CAPM tests that we just talked about? Econ 471/571, F19 - Bollerslev APT 4 Multiple Factors and the CAPM Suppose that there are only two fundamental sources of systematic risks, “technology” and “interest rate” risks Suppose that the return on asset i follows the
    [Show full text]
  • Systematic Risk Influences a Large Number of Assets. a Significant Political Event, for Example, Could Affect Several of the Assets in Your Portfolio
    Let's take a look at the two basic types of risk: Systematic Risk - Systematic risk influences a large number of assets. A significant political event, for example, could affect several of the assets in your portfolio. It is virtually impossible to protect yourself against this type of risk. Unsystematic Risk - Unsystematic risk is sometimes referred to as "specific risk". This kind of risk affects a very small number of assets. An example is news that affects a specific stock such as a sudden strike by employees. Diversification is the only way to protect yourself from unsystematic risk. What is 'Systematic Risk'? The risk inherent to the entire market or an entire market segment. Systematic risk, also known as “undiversifiable risk,” “volatility” or “market risk,” affects the overall market, not just a particular stock or industry. This type of risk is both unpredictable and impossible to completely avoid. It cannot be mitigated through diversification, only through hedging or by using the right asset allocation strategy. For example, putting some assets in bonds and other assets in stocks can mitigate systematic risk because an interest rate shift that makes bonds less valuable will tend to make stocks more valuable, and vice versa, thus limiting the overall change in the portfolio’s value from systematic changes. Interest rate changes, inflation, recessions and wars all represent sources of systematic risk because they affect the entire market. Systematic risk underlies all other investment risks. The Great Recession provides a prime example of systematic risk. Anyone who was invested in the market in 2008 saw the values of their investments change because of this market-wide economic event, regardless of what types of securities they held.
    [Show full text]
  • The Volatility of Industrial Stock Returns and an Empirical Test of Arbitrage Pricing Theory
    Rev. Integr. Bus. Econ. Res. Vol 4(2) 254 The Volatility of Industrial Stock Returns and An Empirical Test of Arbitrage Pricing Theory Bahri Accounting Department of Politeknik Negeri Ujung Pandang ABSTRACT This study focused on the investigation of the sensitivity of industrial stock returns and empirical test of the model of arbitrage pricing theory (APT). Three issues were the basis of this study. The first issue was the difference in industrial stock returns volatility. The second issue was concerning the validity and robustness of CAPM as well as APT models. And, the third issue was the time-varying volatility with the phenomenon of structural breaks. This study used a nested model approach with the second-pass regression. Method of estimation using ordinary least squares method, ARCH/GARCH method, and the dummy variable method. This study used secondary data for the observation period January 2003 to December 2010 in the Indonesian stock market. This investigation produced three empirical findings. First, there was no difference in sensitivity of industrial stock returns among sectors, based on systematic risk factors. Second, the testing of CAPM and APT multifactor models revealed inconsistent results in testing industrial stocks. But the model of CAPM seemed more valid and robust than APT multifactor was. Finally, there were differences in the risk premium for systematic risks caused by the structural break during the financial crisis in 2008. Keywords: Arbitrage pricing theory, industrial stock return volatility, systematic risk factors, structural-breaks 1. INTRODUCTION Investments are current expenditures of investors to expect a return in the future. There is a variety of investment options for investors; one of them is an investment in common stock.
    [Show full text]
  • Modern Portfolio Theory
    Modern portfolio theory “Portfolio analysis” redirects here. For theorems about where Rp is the return on the port- the mean-variance efficient frontier, see Mutual fund folio, Ri is the return on asset i and separation theorem. For non-mean-variance portfolio wi is the weighting of component analysis, see Marginal conditional stochastic dominance. asset i (that is, the proportion of as- set “i” in the portfolio). Modern portfolio theory (MPT), or mean-variance • Portfolio return variance: analysis, is a mathematical framework for assembling a P σ2 = w2σ2 + portfolio of assets such that the expected return is maxi- Pp P i i i w w σ σ ρ , mized for a given level of risk, defined as variance. Its key i j=6 i i j i j ij insight is that an asset’s risk and return should not be as- where σ is the (sample) standard sessed by itself, but by how it contributes to a portfolio’s deviation of the periodic returns on overall risk and return. an asset, and ρij is the correlation coefficient between the returns on Economist Harry Markowitz introduced MPT in a 1952 [1] assets i and j. Alternatively the ex- essay, for which he was later awarded a Nobel Prize in pression can be written as: economics. P P 2 σp = i j wiwjσiσjρij , where ρij = 1 for i = j , or P P 1 Mathematical model 2 σp = i j wiwjσij , where σij = σiσjρij is the (sam- 1.1 Risk and expected return ple) covariance of the periodic re- turns on the two assets, or alterna- MPT assumes that investors are risk averse, meaning that tively denoted as σ(i; j) , covij or given two portfolios that offer the same expected return, cov(i; j) .
    [Show full text]
  • Types of Risk - Systematic and Unsystematic Risk in Finance Post: Gaurav Akrani
    Types of Risk - Systematic and Unsystematic Risk in Finance Post: Gaurav Akrani. Date: 1/25/2012. Comments (3). Label: Finance. Types of risk First let's revise the simple meaning of two words, viz., types and risk. In general and in context of this finance article, 1. Types mean different classes or various forms / kinds of something or someone. 2. Risk implies the extent to which any chosen action or an inaction that may lead to a loss or some unwanted outcome. The notion implies that a choice may have an influence on the outcome that exists or has existed. However, in financial management, risk relates to any material loss attached to the project that may affect the productivity, tenure, legal issues, etc. of the project. In finance, different types of risk can be classified under two main groups, viz., The meaning of systematic and unsystematic risk in finance: 1. Systematic risk is uncontrollable by an organization and macro in nature. 2. Unsystematic risk is controllable by an organization and micro in nature. A. Systematic Risk Systematic risk is due to the influence of external factors on an organization. Such factors are normally uncontrollable from an organization's point of view. It is a macro in nature as it affects a large number of organizations operating under a similar stream or same domain. It cannot be planned by the organization. The types of systematic risk are depicted and listed below. 1. Interest rate risk Interest-rate risk arises due to variability in the interest rates from time to time. It particularly affects debt securities as they carry the fixed rate of interest.
    [Show full text]
  • Ratings‐Based Regulation and Systematic Risk Incentives
    Comments Welcome Ratings-Based Regulation and Systematic Risk Incentives by Giuliano Iannotta Department of Economics and Business Administration Universitá Cattolica Email: [email protected] and George Pennacchi Department of Finance University of Illinois Email: [email protected] First Draft: August 2011 This Draft: September 2014 Abstract When capital regulation is based on credit ratings, our model shows that a financial institution raises its shareholder value by selecting similarly-rated loans and bonds with the highest systematic risk. This moral hazard occurs if loan and bond credit spreads incorporate systematic risk premia not reflected in credit ratings. Our empirical evidence confirms that similarly-rated bonds have significantly greater credit spreads when their issuers have a higher systematic risk or “debt beta.” Moreover if a financial institution chooses higher-yielding, but equivalently-rated, bonds, its systematic risk and fair capital requirements rise by an economically significant amount. Our theory provides an explanation for prior research documenting that banks and insurance companies took excessive systematic risks. An earlier version of this paper was titled “Bank Regulation, Credit Ratings, and Systematic Risk.” Valuable comments were provided by Tobias Berg, Timotej Homar, Christine Parlour, Andrea Resti, Francesco Saita, João Santos, Andrea Sironi, René Stulz, Andrew Winton and participants of the 2011 International Risk Management Conference, the 2011 Bank of Finland Future of Risk Management
    [Show full text]
  • Systemic Risk and Insurance Regulation †
    risks Article Systemic Risk and Insurance Regulation † Fabiana Gómez 1,* and Jorge Ponce 2 1 Department of Accounting and Finance, University of Bristol, Bristol BS8 1TH, UK 2 Banco Central del Uruguay, Montevideo 11100, Uruguay; [email protected] * Correspondence: [email protected]; Tel.: +44-117-39-41485 † The views in this paper are those of the authors and not of the Institutions to which they are affiliated. Received: 25 June 2018; Accepted: 25 July 2018; Published: 27 July 2018 Abstract: This paper provides a rationale for the macro-prudential regulation of insurance companies, where capital requirements increase in their contribution to systemic risk. In the absence of systemic risk, the formal model in this paper predicts that optimal regulation may be implemented by capital regulation (similar to that observed in practice, e.g., Solvency II ) and by actuarially fair technical reserve. However, these instruments are not sufficient when insurance companies are exposed to systemic risk: prudential regulation should also add a systemic component to capital requirements that is non-decreasing in the firm’s exposure to systemic risk. Implementing the optimal policy implies separating insurance firms into two categories according to their exposure to systemic risk: those with relatively low exposure should be eligible for bailouts, while those with high exposure should not benefit from public support if a systemic event occurs. Keywords: insurance companies; systemic risk; optimal regulation JEL Classification: G22, G28 1. Introduction Insurance firms play an important role in the economy as providers of protection against financial and economic risks. In recent years, their contribution to systemic risk has increased.
    [Show full text]
  • Regulating Systemic Risk: Towards an Analytical Framework
    ARTICLES REGULATING SYSTEMIC RISK: TOWARDS AN ANALYTICAL FRAMEWORK Iman Anabtawi* & Steven L. Schwarczt The global financial crisis demonstrated the inability and unwillingness offinancial market participantsto safeguard the stability of the financialsys- tem. It also highlighted the enormous direct and indirect costs of addressing systemic crises after they have occurred, as opposed to attempting to prevent them from arising. Governments and internationalorganizations are respond- ing with measures intended to make the financial system more resilient to eco- nomic shocks, many of which will be implemented by regulatory bodies over time. These measures suffer, however, from the lack of a theoretical account of how systemic risk propagates within the financial system and why regulatory intervention is needed to disrupt it. In this Article, we address this deficiency by examining how systemic risk is transmitted. We then proceed to explain why, © 2011 Iman Anabtawi & Steven L. Schwarcz. Individuals and nonprofit institutions may reproduce and distribute copies of this Article in any format, at or below cost, for educational purposes, so long as each copy identifies the authors, provides a citation to the Notre Dame Law Review, and includes this provision and copyright notice. * Professor of Law, UCLA School of Law. E-mail: [email protected]. t Stanley A. Star Professor of Law & Business, Duke University School of Law; Founding/Co-Academic Director, Duke Global Capital Markets Center; and Leverhulme Visiting Professor, University of
    [Show full text]
  • Report on Asset Securitisation Incentives
    Basel Committee on Banking Supervision The Joint Forum Report on asset securitisation incentives July 2011 Copies of publications are available from: Bank for International Settlements Communications CH-4002 Basel, Switzerland E-mail: [email protected] Fax: +41 61 280 9100 and +41 61 280 8100 This publication is available on the BIS website (www.bis.org). © Bank for International Settlements 2011. All rights reserved. Brief excerpts may be reproduced or translated provided the source is cited. ISBN 92-9131-878-7 (print) ISBN 92-9197-878-7 (online) THE JOINT FORUM BASEL COMMITTEE ON BANKING SUPERVISION INTERNATIONAL ORGANIZATION OF SECURITIES COMMISSIONS INTERNATIONAL ASSOCIATION OF INSURANCE SUPERVISORS C/O BANK FOR INTERNATIONAL SETTLEMENTS CH-4002 BASEL, SWITZERLAND Report on asset securitisation incentives July 2011 Contents Chapter 1 – Introduction ...........................................................................................................1 1.1 Background ............................................................................................................1 1.2 Mandate .................................................................................................................2 1.3 The macrofinancial context for the growth of securitisation ...................................3 1.4 Future prospects for securitisation .........................................................................7 Chapter 2 – Securitisation incentives: misalignments and conflicts of interest.........................9 2.1 Originator/sponsor
    [Show full text]