Fin 603 Week 8

1. Fin 603 Week 8 Common Stock: Returns and Volatility

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 Professor Ross Miller • Fall 2005

3. Weeks 8 through 11 • Week 8: Stocks • Week 9: Portfolio material required for the Google exercise • Week 10: Advanced portfolio material • Week 11: Options Professor Ross Miller • Fall 2005

4. 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 Professor Ross Miller • Fall 2005

5. 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 Professor Ross Miller • Fall 2005

6. A Quick Guide to Bodie/Kane/Marcus (cont.) • 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 Professor Ross Miller • Fall 2005

7. A Quick Guide to Bodie/Kane/Marcus (cont.) • Chapters 24-27: Useful info for building portfolios • Performance measures (Ch. 24) • International diversification (Ch. 25) • Improving on index performance (Ch. 26 and 27) Professor Ross Miller • Fall 2005

8. 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) Professor Ross Miller • Fall 2005

9. 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) Professor Ross Miller • Fall 2005

10. Key Stock Info for Microsoft (from Yahoo!) Professor Ross Miller • Fall 2005

11. 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” Professor Ross Miller • Fall 2005

12. 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 Professor Ross Miller • Fall 2005

13. 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 Professor Ross Miller • Fall 2005

14. 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 Professor Ross Miller • Fall 2005

15. 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.) Professor Ross Miller • Fall 2005

16. 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 Professor Ross Miller • Fall 2005

17. 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 Professor Ross Miller • Fall 2005

18. 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 Professor Ross Miller • Fall 2005

19. 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 Professor Ross Miller • Fall 2005

20. 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 Professor Ross Miller • Fall 2005

21. 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 Professor Ross Miller • Fall 2005

22. 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 Professor Ross Miller • Fall 2005

23. 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” Professor Ross Miller • Fall 2005

24. The Style Matrix Professor Ross Miller • Fall 2005

25. Holding-Period Return (HPR) Professor Ross Miller • Fall 2005

26. 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 Professor Ross Miller • Fall 2005

27. 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% Professor Ross Miller • Fall 2005

28. 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% Professor Ross Miller • Fall 2005

29. 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 Professor Ross Miller • Fall 2005

30. 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: For weekly returns, we multiply by 52 to annualize Professor Ross Miller • Fall 2005

31. Some Numbers from the Last 60 Weeks Professor Ross Miller • Fall 2005

32. 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: Professor Ross Miller • Fall 2005

33. 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 Professor Ross Miller • Fall 2005

34. 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 Professor Ross Miller • Fall 2005

35. 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 Professor Ross Miller • Fall 2005

36. 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) Professor Ross Miller • Fall 2005

37. 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) Professor Ross Miller • Fall 2005

38. 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 Professor Ross Miller • Fall 2005