Week 8 slides in PowerPoint format

University at Albany School of Business

Fall 2005 Professor Ross Miller

Copyright 2005 by Ross M. Miller. All rights reserved

Fin 603 Week 8

Common Stock: Returns and Volatility

Professor Ross Miller • Fall 2005 2

Grade Conversion Table (“The Curve”) for the Midterm Exam

Points convert to GPA equivalent number according to the following formula:

GPA equivalent = 4.33 – (90 – Test score)/18

For example,• 84 = 4.00 = A 81 = 3.83 = lowest A• 75 = 3.50 = lowest A- 69 = 3.16 = lowest B+

Mean and median grade were both roughly 75

C:\Program Files\Internet Explorer\IEXPLORE.EXE

C:\Program Files\Mozilla Firefox\firefox.exe


Weeks 8 through 11

Week 8: Stocks

Week 9: Portfolio material required for the Google exercise

Week 10: Advanced portfolio material

Week 11: Options




A Quick Guide to Bodie/Kane/Marcus

Chapter 2• Section 2.3 introduces stock as a financial

instrument• Section 2.4 discusses how stocks index are

constructed

Chapter 3: Stock trading, including short selling

Chapter 4: Mutual funds, including ETFs




A Quick Guide to Bodie/Kane/Marcus (cont.)

Chapter 5: Stocks are risky and have higher returns than fixed-income securities

Chapter 6: Risk aversion means people require higher returns to hold more volatile assets

Chapter 7: Tracing out the CAL/CML and maximizing utility relative to it

Chapter 8: Portfolios of risky assets





Chapters 9 and 10: CAPM and implementing a version of it with index models

Chapter 11: Multi-factor models

Chapter 12: Efficient markets

Chapter 13: Problems with everything you are learning in the previous chapters

Chapters 17-19: The cash flow approach to valuing securities





Chapters 24-27: Useful info for building portfolios• Performance measures (Ch. 24)• International diversification (Ch. 25)• Improving on index performance (Ch. 26 and 27)




Common Stock

A share in the ownership of a company (equity) and a right to share of its profits

Stock holders have the last claim on the assets of a company (a residual interest)

Ownership of stock has limited liability, you lose at most what you paid for the stock

Common stock includes not only profits, but also voting rights (sometimes limited, as in the case of Google)




Two Special Kinds of “Stock”

ADRs (or ADSs)• Shares of international companies that trade on

U.S. exchanges • For example, Sony (SNE) & Nokia (NOK).

ETFs (Exchange-Traded Funds)• Shares in portfolios that usually track specific

stock indexes• For example, SPDRs (SPY) & Quads (QQQQ)

http://finance.yahoo.com/q?s=sne

http://finance.yahoo.com/q?s=nok




Key Stock Info for Microsoft (from Yahoo!)

http://finance.yahoo.com/q?s=msft



Professor Ross Miller • Fall 2005 E=mcE=mc2211

The Concept of Efficiency

Technical economic definition: No way to make anyone better off without making someone else worse off

For an individual: Doing the best you can do with what you have

For portfolios: No way to rearrange things to get more return without taking on more risk

For financial markets: No way to use market data and information to “beat the market”




Conditions that Promote Efficiency

No single dominant player or cartel of dominant players

Easy substitution of items (limited product differentiation)

Free flow of information

Low barriers to trade• Low commissions• Low taxes• Minimal regulation




Efficient-Market Hypothesis (EMH) andTechnical Analysis

The efficient-market hypothesis (which comes in three forms) states basically that there is no way to make “excess profits” by looking at any past public information about a company

In particular, this means that “technical analysis” (look at stock graphs, etc.) does not work

It also means that whatever “behavioral anomalies” exist in financial markets are too small and fleeting to exploit profitably




Consequences of the EMH

Stock prices are efficient aggregators of information about a company

Returns that appear excessive can be interpreted as the return for bearing risk (we will see that only certain risks are rewarded)

The path of a stock’s price may not allow us to predict the future, but they can tell us a lot about the company and its risk




Consequences of the EMH (continued) Prices are a more reliable source of information

than accounting-based data• Stock prices are extremely rarely falsified or

restated• Stock prices are difficult, but not impossible, to

manipulate• Severely misstated accounting numbers can still

work their way into stock prices (Enron, Worldcom, Refco, etc.)




Consequences of the EMH (continued) EMH supports investing in index funds rather

than trying to pick individual stocks• Greatly reduces management fees• Provides cheap diversification (we will see that

diversification is a good thing)• Low-turnover indexes generate low capital gains

taxes




Consequences of the EMH (continued) EMH supports investments that go beyond

traded U.S. stocks• Despite increasing globalization of U.S.

company, adding international companies to a portfolio aids diversification

• Prudent venture capital investments provide opportunities not available in traded stocks with much higher risk

• Real estate can also enter into the mix




The Two Sources of Returns from Stock

Dividends• Quarterly payments by established companies• Stock yields used to be higher than bond yields• The price of a stock drops by the amount of its

dividend the day it goes “ex-dividend”

Capital Gains• Appreciation in the price of the stock• Not guaranteed• Usually taxed at a lower rate than dividends• Aided by companies buying back their own shares




Discounted Dividend Model (DDM)

Notice that if one holds a stock indefinitely, dividends are the only cash flow that one receives

Basic Idea: Value(stock) = NPV(future dividends) For a constant discount rate and dividend growth

rate, this is just a growing perpetuity Hence, Value(stock) = Next dividend/(r-g),

where r = stock discount rate, g = dividend growth rate

The main problem is knowing r and g




Warren Buffett: Sage of Omaha

Chairman of Berkshire Hathaway(BRKa)

Protégé of Benjamin Graham:The father of fundamental analysis

Proponent of “value investing,” skeptical of paying for growth and technology




Fundamental Stock Valuation

Stocks are valued based on their ability to generate future cash flows

Higher cash flows are good

The most popular measure (but not always the best) measure of the relative cash flow generated by a company is its P/E (Price/Earnings) ratio

Published “Book Values” are rarely used in fundamental analysis




Fundamental Stock Valuation (continued)

Fundamental valuation methods are not limited to the discounted dividend model

Free cash flows can also be discounted• This makes the most sense for a company that

is an acquisitions target• Valuation is still very dependent on growth rates• This article, which later paints a grim picture of

the prospects for the stock market, presents an argument that Google is vastly overpriced based on expected future cash flows




Size Matters

A standard measure of a stock’s “size” is the dollar value of its shares, known as market capitalization

Large companies are different from small companies

• Usually less volatile• Usually more closely linked to overall market

conditions, if only because they constitute a larger share of “the market”




The Style Matrix




Holding-Period Return (HPR)

PriceBeginningDividendPriceBeginningPriceEnding

ReturnPeriodHolding




Getting Data Historical stock data is available on Yahoo!

Finance (here is Google)

Reuters Investor has some good additional data

GoogleStats.xls has weekly HPRs for fed funds (a proxy for the “risk-free” rate of return) and the seven stocks involved in the Google exercise

Notice that your professor has used a clever trick to deal with dividend payments; however, this trick does not deal with stock splits




Holding-Period Return Example:MSFT between August 10 and 17, 2005

Closing price on August 10: $27.05

August 15 dividend: $0.08

Closing price on August 17: $26.72

HPR = ($26.72 – $27.05 + $0.08)/$27.05 = –$0.25/$27.05 = –.00924 = –0.924%




Annualizing HPRs

With few exceptions, everything to do with stock returns is reported as an annualized figure

Weekly returns are annualized by compounding them up 52 times (we usually ignore the extra day or two), so:

Annual return = (1+Weekly Return)52 – 1

In the previous example, Annual return =(1 – 0.00924) 52 – 1 = – 38.28%




More On HPR

A single week’s HPR can be misleading• HPRs can change a lot from week to week

More useful info is the mean and standard deviation of the weekly return (daily and monthly returns can also be used, depending on the purpose) over many (at least 30) observations

Finally, one may want to consider only the excess return relative to a benchmark rate; usually, “cash” or an indexed investment




The Standard Deviation of Returns

This is also known as the stock’s volatility; however, there are other methods of measuring volatility

Volatility is a standard measure of the stock’s risk—higher volatility means more risk

Annualizing volatility is somewhat tricky:

yearperPeriodsVolatilityPeriodicVolatilityAnnual

For weekly returns, we multiply by 52 to annualize




Some Numbers from the Last 60 Weeks

Fed Funds GOOG SPY QQQQ YHOOMean Return 2.654% 158.736% 8.957% 12.044% 18.548%Std Dev Return 0.094% 41.073% 9.852% 13.224% 25.991%Mean Excess Return 0 152.163% 6.143% 9.152% 15.491%Sharpe Ratio 3.704696 0.623579 0.692107 0.596035




Volatility and Risk Aversion

Chapter 6 of BKM is about quantifying risk aversion

The standard method is to create a utility function that rewards higher returns and punishes higher risk

The utility function that BKM favor is:

2005.)( ArEU




Some Comments about BKM Chapter 6

BKM use “scenarios” to illustrate “risky” situations

• Scenarios can be useful and are frequently used by financial planners, rating agencies, etc.

• Scenarios do not naturally present themselves in the real world

In recent years, a value of A much greater than BKM would suggest is required to get reasonable results




The Normal Distribution

Knowing a mean and a standard deviation is all you need to plot a normal distribution

It is often convenient to assume that HPRs for stocks are normally distributed

In reality, they are not, but sometimes this assumption is not too dangerous




What Does the Past Have to Do with the Future?

Not as much as we would like it to have

Historical rates of returns are not the best estimates of future returns

Historical volatilities are more accurate, but for many stocks there is an even better number—implied volatility, which is computed from option prices




Looking up the Implied Volatility

Visit ivolatility.com and enter stock symbol for “Basic Options”

• Here is Google• Here is Microsoft

A good estimate of annual volatility is the average of the IV Index Call” and “IV Index Put” for a stock (the value of options depends mainly on a stock’s volatility)




The Most Popular Measure of Volatility:VIX (^VIX)

VIX stands for “volatility index”

It is the implied volatility of the S&P 500, computed a collection of prices on S&P 500 options

Both futures and options on VIX are traded on the CBOE

Variants have appeared (VXN and VXD)




For Next Time

Read Chapters 5-10 of BKM

Think about what possible use the data in GoogleStats.xls could be for the Google exercise

Specifically, use GoogleStats.xls to compute useful statistics for portfolios created from Google and the six other stocks if you had held them in the past



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