CAPITAL ASSET PRICING MODEL

Similar documents
Models of Asset Pricing

Models of Asset Pricing

Models of Asset Pricing

Appendix 1 to Chapter 5

of Asset Pricing R e = expected return

of Asset Pricing APPENDIX 1 TO CHAPTER EXPECTED RETURN APPLICATION Expected Return

1 Random Variables and Key Statistics

r i = a i + b i f b i = Cov[r i, f] The only parameters to be estimated for this model are a i 's, b i 's, σe 2 i

Dr. Maddah ENMG 624 Financial Eng g I 03/22/06. Chapter 6 Mean-Variance Portfolio Theory

First determine the payments under the payment system

AY Term 2 Mock Examination

A random variable is a variable whose value is a numerical outcome of a random phenomenon.

CHAPTER 2 PRICING OF BONDS

Statistics for Economics & Business

Correlation possibly the most important and least understood topic in finance

Binomial Model. Stock Price Dynamics. The Key Idea Riskless Hedge

SCHOOL OF ACCOUNTING AND BUSINESS BSc. (APPLIED ACCOUNTING) GENERAL / SPECIAL DEGREE PROGRAMME

We learned: $100 cash today is preferred over $100 a year from now

BASIC STATISTICS ECOE 1323

Subject CT1 Financial Mathematics Core Technical Syllabus

FINM6900 Finance Theory How Is Asymmetric Information Reflected in Asset Prices?

Chapter 8. Confidence Interval Estimation. Copyright 2015, 2012, 2009 Pearson Education, Inc. Chapter 8, Slide 1

ELEMENTARY PORTFOLIO MATHEMATICS


point estimator a random variable (like P or X) whose values are used to estimate a population parameter

Lecture 16 Investment, Time, and Risk (Basic issues in Finance)

An Empirical Study of the Behaviour of the Sample Kurtosis in Samples from Symmetric Stable Distributions

Inferential Statistics and Probability a Holistic Approach. Inference Process. Inference Process. Chapter 8 Slides. Maurice Geraghty,

Sampling Distributions and Estimation

CAPITAL PROJECT SCREENING AND SELECTION

The Time Value of Money in Financial Management

Online appendices from Counterparty Risk and Credit Value Adjustment a continuing challenge for global financial markets by Jon Gregory

Introduction to Financial Derivatives

NPTEL DEPARTMENT OF INDUSTRIAL AND MANAGEMENT ENGINEERING IIT KANPUR QUANTITATIVE FINANCE END-TERM EXAMINATION (2015 JULY-AUG ONLINE COURSE)

Statistical techniques

Indice Comit 30 Ground Rules. Intesa Sanpaolo Research Department December 2017

Estimating Proportions with Confidence

Chapter 8: Estimation of Mean & Proportion. Introduction

DOWLING COLLEGE: School of Education Department of Educational Administration, Leadership, and Technology

1. Suppose X is a variable that follows the normal distribution with known standard deviation σ = 0.3 but unknown mean µ.

MA Lesson 11 Section 1.3. Solving Applied Problems with Linear Equations of one Variable

Introduction to Probability and Statistics Chapter 7

Estimating Volatilities and Correlations. Following Options, Futures, and Other Derivatives, 5th edition by John C. Hull. Chapter 17. m 2 2.

CD Appendix AC Index Numbers

NOTES ON ESTIMATION AND CONFIDENCE INTERVALS. 1. Estimation

ii. Interval estimation:

This article is part of a series providing

5. Best Unbiased Estimators

Monetary Economics: Problem Set #5 Solutions

How Efficient is Naive Portfolio Diversification? An Educational Note

Quantitative Analysis

This paper provides a new portfolio selection rule. The objective is to minimize the

APPLICATION OF GEOMETRIC SEQUENCES AND SERIES: COMPOUND INTEREST AND ANNUITIES

Chapter Four 1/15/2018. Learning Objectives. The Meaning of Interest Rates Future Value, Present Value, and Interest Rates Chapter 4, Part 1.

Structuring the Selling Employee/ Shareholder Transition Period Payments after a Closely Held Company Acquisition

PORTFOLIO THEORY: MANAGING BIG DATA

Online appendices from The xva Challenge by Jon Gregory. APPENDIX 10A: Exposure and swaption analogy.


CHAPTER 8 Estimating with Confidence

International Journal of Management (IJM), ISSN (Print), ISSN (Online) Volume 1, Number 2, July - Aug (2010), IAEME

These characteristics are expressed in terms of statistical properties which are estimated from the sample data.

Optimizing of the Investment Structure of the Telecommunication Sector Company

Lecture 4: Probability (continued)

Confidence Intervals. CI for a population mean (σ is known and n > 30 or the variable is normally distributed in the.

Standard Deviations for Normal Sampling Distributions are: For proportions For means _

Osborne Books Update. Financial Statements of Limited Companies Tutorial

Combining imperfect data, and an introduction to data assimilation Ross Bannister, NCEO, September 2010

Chapter 11 Appendices: Review of Topics from Foundations in Finance and Tables

Today: Finish Chapter 9 (Sections 9.6 to 9.8 and 9.9 Lesson 3)

4.5 Generalized likelihood ratio test

Predicting Market Data Using The Kalman Filter

Calculation of the Annual Equivalent Rate (AER)

Where a business has two competing investment opportunities the one with the higher NPV should be selected.

Portfolio Optimization

A point estimate is the value of a statistic that estimates the value of a parameter.

Topic-7. Large Sample Estimation

Statistics for Business and Economics

KEY INFORMATION DOCUMENT CFD s Generic

1. BANK-INVESTMENT FUND INTERCONNECTIONS AND SYSTEMICALLY IMPORTANT INSTITUTIONS IN LUXEMBOURG

Equity Instruments: Part I Discounted Cash Flow Valuation

. (The calculated sample mean is symbolized by x.)

Forecasting bad debt losses using clustering algorithms and Markov chains

An Empirical Study on the Contribution of Foreign Trade to the Economic Growth of Jiangxi Province, China

living well in retirement Adjusting Your Annuity Income Your Payment Flexibilities

Lecture 4: Parameter Estimation and Confidence Intervals. GENOME 560 Doug Fowler, GS

Lecture 5: Sampling Distribution

Investments and Financial Markets

Linear Programming for Portfolio Selection Based on Fuzzy Decision-Making Theory

IMPLICATIONS OF A FIRM S MARKET WEIGHT IN A CAPM FRAMEWORK

Anomaly Correction by Optimal Trading Frequency

Exam 2. Instructor: Cynthia Rudin TA: Dimitrios Bisias. October 25, 2011

DESCRIPTION OF MATHEMATICAL MODELS USED IN RATING ACTIVITIES

Quarterly Update First Quarter 2018

Fixed Income Securities

Driver s. 1st Gear: Determine your asset allocation strategy.

STRAND: FINANCE. Unit 3 Loans and Mortgages TEXT. Contents. Section. 3.1 Annual Percentage Rate (APR) 3.2 APR for Repayment of Loans

Basic formula for confidence intervals. Formulas for estimating population variance Normal Uniform Proportion

1 Basic Growth Models

Problem Set 1a - Oligopoly

MATH : EXAM 2 REVIEW. A = P 1 + AP R ) ny

Transcription:

CAPITAL ASSET PRICING MODEL RETURN. Retur i respect of a observatio is give by the followig formula R = (P P 0 ) + D P 0 Where R = Retur from the ivestmet durig this period P 0 = Curret market price P = Year ed market price D = Divided received durig the period. Expected Retur of a stock is the weighted average retur of the various observatios with probability of occurrece beig the assiged weight EV = Σ PxR EV = (MOV + 4 x RV + MPV) / 6 R = Value MOV = Most optimistic Value RV = Realistic Value MPV = Most pessimistic value RISK 3. Risk of a stock is the stadard deviatio of the stock ad is give by the followig formula Stadard Deviatio () = P d i i i= d = Deviatio = Number of observatios 4. If the probabilities are ot give it ca be assumed to be uiform 5. Alteratively the followig formula ca be used Stadard Deviatio () = P d i i i= d = Deviatio = Number of observatios DIVERSIFCATION 6. Diversificatio reduces risk. It does ot icrease retur. If you are lookig for retur, pick the best stock ad stay with it. If you are lookig to reduce risk, ivest i a portfolio of stocks Faculty: V PATTABHI RAM 9

PORTFOLIO 7. Risk of a two security portfolio is give by the followig formula P = ( ) ( w ) + ( ) ( w ) + ( ) ( ) ( w ) ( w ) ( Cor x x y y x y x y xy) Where ( x ) = Variace of Security X ( Y ) = Variace of Security Y (w x ) & (w y ) = Proportio of ivestmet i security X & Y (Cor xy )= Correlatio Coefficiet of security X ad Y 8. Retur of a portfolio is the weighted average retur of the securities formig the portfolio with market value of each stock beig the assiged weight Σ PxR Where P = probability R = value 9. Risk of a portfolio is NOT the weighted average risk of the security costitutig the portfolio. The oly exceptio is whe the correlatio is plus 0. Risk of a multi security portfolio is computed usig the matrix approach.. Risk reductio meas the extet to which the risk of a portfolio is less tha the weighted average risk of the securities costitutig the portfolio.. It is possible to idetify the portfolio combiatio at which risk is lowest. This is give by the followig formula - cov XY y W = x + - cov XY x y DOMINANCE 3. Security A is said to domiate Security B if a. It gives higher retur for same risk b. It carries lower risk for same retur 4. Stocks which are domiated are called iefficiet stocks. Stocks which are ot domiated are called efficiet stocks. Oly efficiet stocks are selected by a portfolio maager. 5. Although a particular stock may be domiated it could at times still form part of portfolio i such a way that the portfolio itself is ot domiated. NON DIVERSIFIABLE RISK 6. Beyod a poit diversificatio ceases to be importat. However there is o empirical evidece as to at what umber of stocks i the portfolio does diversificatio cease to be relevat 7. Risk which ca be reduced through diversificatio is called diversifiable risk or No Systematic risk Faculty: V PATTABHI RAM 30

8. Risk which caot be reduced through diversificatio is called NON diversifiable risk or Systematic risk 9. The umerator i the Beta formula is o-diversifiable risk. The differece betwee total risk ad o-diversifiable risk is diversifiable risk BETA 0. Beta is a measure of o-diversifiable risk. It is the ratio of o-diversifiable risk to variace of the market idex. There are three formulae for the computatio of Beta XY - X Y β = Y Y Covariace jm β = Variace m j β = x Corr jm m Where X = Retur (%) from stock X Y = Retur (%) from the stock market as a class = Number of observatios X = Arithmetic mea of rate of retur from the stock Y = Arithmetic mea of rate of retur from the market Covariace jm = Covariace betwee stock ad market Variace m = Variace of the market j = Stadard deviatio of stock m = Stadard deviatio of market returs corr = Correlatio betwee returs from stock ad stock market jm CAPM. The required retur from a stock is give by the followig CAPM formula R j = R f + β x (R m R f ) Where R j = CAPM retur R f = Risk free rate of retur β = Beta of the security R m = Retur from the market ALPHA 3. Alpha is the extet to which the actual retur of a stock i the past have bee greater tha the retur madated uder the capital asset pricig model Alpha (α) = Actual Retur CAPM retur Faculty: V PATTABHI RAM 3

4. The alpha of a stock is the average of the alphas of a series of observatios. CAPM AND GEARING 5. The overall beta of a compay is the weighted average beta of the assets or projects costitutig the compay 6. The overall beta of a compay is also the weighted average beta of the liabilities costitutig the compay also kow as Liability Beta 7. Hece the Asset Beta of a compay equals its liability Beta 8. The Asset Beta of all compaies operatig i the same busiess risk class is same ad hece the startig overall Asset Beta is the beta of a ulevered compay Debt β A g U + Value Where β A = Beta of asset β g = Beta geared β u = Beta ugeared Value = Debt + Equity Equity ( debt) β ( Equity) Value 9. Where taxes are ivolved D i the formula will be replaced with D*(-T). The broad formulae are as uder D (-T) Equity β + β A g U debt S+D(-T) Equity S + D( T) Where β A = Beta of asset β g = Beta geared β u = Beta ugeared ( ) ( ) LINES AND OTHER MODELS 30. The Security Market lie captures the relatioship betwee the beta of a stock ad the retur from the stock. It plots the retur of the stock for various levels of osystematic risk 3. The x-axis represets the risk (beta), ad the y-axis represets the expected retur. The market risk premium is determied from the slope of the SML. 3. The security market lie is a useful tool i determiig whether a asset beig cosidered for a portfolio offers a reasoable expected retur for risk. Idividual securities are plotted o the SML graph. If the security's risk versus expected retur is plotted above the SML, it is udervalued because the ivestor ca expect a greater retur for the iheret risk. A security plotted below the SML is overvalued because the ivestor would be acceptig less retur for the amout of risk assumed. 33. This lie graphs the systematic, or market, risk versus retur of the whole market at a certai time ad shows all risky marketable securities. It is also called the "characteristic lie" 34. The Capital Market lie captures the relatioship betwee the stadard deviatio of a stock ad the retur from the stock. Faculty: V PATTABHI RAM 3

It plots the retur of the stock for various levels of risk. The CML is used i the CAP model to illustrate the rates of retur for efficiet portfolios depedig o the risk-free rate of retur ad the level of risk (stadard deviatio) for a particular portfolio. The CML is derived by drawig a taget lie from the itercept poit o the efficiet frotier to the poit where the expected retur equals the risk-free rate of retur. 35. The CML is cosidered superior to the efficiet frotier sice it takes ito accout the iclusio of a risk-free asset i the portfolio. The CAPM demostrates that the market portfolio is essetially the efficiet frotier. 36. The CML replaces Beta i the CAP Model with the ratio of SD of portfolio to SD of market. 37. Risk retur ratio is the ratio of risk premium o a stock to beta of a stock. I a equilibrium market this should be same for all securities 38. Idividual securities do ot lie o CML They have some usystematic risk. 39. CML assumes o usystematic risk. All of that is take care of by diversificatio 40. The Characteristic Lie: A lie formed usig regressio aalysis that summarizes a particular security or portfolio's systematic risk ad rate of retur. The rate of retur is depedet o the stadard deviatio of the asset's returs ad the slope of the characteristic lie, which is represeted by the asset's beta. A characteristic lie of a stock is the same as the security market lie. The slope of the lie, which is a measure of systematic risk, determies the risk-retur trade-off. 4. Idividual securities as also portfolio of securities will lie i the SML because of the EMH which says that all securities will yield retur commesurate with their risk. 4. Market Model α + β x Risk premium from Idex a. There is o risk free rate b. Market risk affects the etire retur of a security ot just risk premium Expected Retur = α + (β x R m ) c. Sice there is o risk free rate, the SML formula is reduced to β x R m. To this we add the historical α to get a estimate of the rate of retur 43. Excess Retur Model a. Expected retur cosiderig risk free retur α R f x (-Port β) + CAPM retur + Error estimate 44. Multi factor model a. More tha oe factor ca drive the retur of a stock Expected retur = R f + β of GNP x (GNP R f ) + β of Iflatio x (Iflatio R f ) Faculty: V PATTABHI RAM 33