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# ADV THERMAL SCI ME 134

UCSB

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This 32 page Class Notes was uploaded by Daren Beatty Jr. on Thursday October 22, 2015. The Class Notes belongs to ME 134 at University of California Santa Barbara taught by Staff in Fall. Since its upload, it has received 50 views. For similar materials see /class/227082/me-134-university-of-california-santa-barbara in Mechanical Engineering at University of California Santa Barbara.

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Date Created: 10/22/15

Chapter 13 Market Efficiency Econ 134A Page 1 Spring 05 7 7 m A 357 no 53 a F f fL min mm 7 e56gt M f vJQDLVQNL eai bgbL Ul vdw bd WW7 b db 1 2 IL Lykjl Ub u r a W Earnr1 FD LI bllgiJuuvz fu r l Up until now we have assumed that markets correctly price investments This leads to the idea of Efficient Markets Recall our definition A market is efficient if all information is incorporated into the price of an asset Econ 134A Page 2 Spring 05 Three forms of efficiency Weak Form Prices reflect only past prices and dividends SemiStrong Prices reflect all publicly knowable information Strong Prices reflect all information Econ 134A Page 3 Spring 05 Arbitrage or a similar idea One process that makes markets efficient is arbitrage This arbitrage will move the market in a way that will incorporate the knowledgeable arbitrager s information into the stock price Charlie Plott Information experiment Econ 134A Page 4 Spring 05 a N U NW N 7 rl Sp 4 an ll 77 l 439 army M Mg m m c s 7 1 a n w quotH I s it 75gt ll Ll My cl lu u dCcu JL QJAQUF U U lyW Random Walks Each term in the sequence is equal to the previous term plus an error term These error terms have an expected value of 0 They are independent of any other term Example Flipping a coin and counting the number of heads minus the number of tails Econ 134A Page 5 Spring 05 Implications of Random Walks The random walk can be written as Pj1 Pf 8 11 Thus E PM EiPJi or P1 E PN 9141 The Efficient Market Hypothesis implies that the error term am is unpredictable Econ 134A Page 6 Spring 05 x 7 213 r f 1737777 11271757375535 rm 4 w L been u k a mu bu umLoc m ALI 57 L4 Consider a stock of Ford which pays dividends of 1 2 1 2 starting one year hence We will assume a discount factor of 10 throughout What is this stock s price This is the sum of two perpetuities one that pays 1 every year and one that pays 1 every other year The value of the first perpetuity is 101 10 The second perpetuity is worth 1021 476 Econ 134A Page 7 Spring 05 Tests of Weak Form Efficiency Trading rules based upon the past prices if a stock rises by x buy it until it has lost x from its subsequent high Fama and Blume 1966 showed that no value of x could beat a buy and hold strategy after commissions Econ 134A Page 8 Spring 05 l 4 P x F r g nr v I lt99 l 1 436 J F quot7770 W L HO 1 L 793 UZQLL W Ul Lars be 1 u a j l l l l l l l l J l l l J l l l Serial Correlations the correlation between P1f and Plf1 can be calculated If the Weak Form Efficiency Hypothesis holds the correlation should be 0 Studies of daily returns usually show a small positive correlation but it is too small of which to take advantage The conclusion is that the market is efficient in the weak form Econ 134A Page 9 Spring 05 as A r a a a s 47 C an a a M EMU mgWthm w r m if grew gm Chartists and technical analysts who try to see where the market is going based upon past pnces But I don t know many successful day traders or chartists In fact a major trading house Smith Barney recently a few year ago released it s entire technical analysis division Econ 134A Page 10 Spring 05 Tests for this form efficiency look at timing of stock price adjustments with respect to events For instance when earnings are announced new information is available about the price of the stock Almost the full adjustment 90 for increased earnings 76 for decreased earnings takes place in the first three hours of the announcement RWJ has more tests of this sort Econ 134A Page 11 Spring 05 Mutual Funds Mutual funds do not outperform the market consistently even though they have immense resources to look through all publicly available information This supports semistrong form efficiency So why do we hear about mostly good mutual funds Econ 134A Page 12 Spring 05 Buy the Sells en quot um those with only quotbuyquot or 39holq39 ratings especially in recent years Vealanvyear pmmnanoa l ks wim me must 39seII39ra ngs I lswcls with quotbuy39 ur hnlu39 mung only I I I I I l I I I 391 1994 95 95496 96quot 973993 933999 3999 3900 39W39 l 39013902 02 03 39DIP39M mbullnoe mnnmlv 5mm lads Immmem Rumm Wall Street Journal Monday April 11 2005 C1 Econ mm Pager 13 SWIG 3905 Strong Form Efficiency Strong Form Efficiency implies that ALL possible information about a stock is reflected in its price This is too extreme to hold in practice Econ 134A Page 14 Spring 05 Implications of Efficient Markets Markets have no memory There are no financial illusions Trust market prices Can t time markets This means that trying to time issuing debt or lPOs cannot create value Econ 134A Page 15 Spring 05 UCSB ECON 134A Introductory Finance Lecture 9 Risk and Return Historical Lessons Corresponds to Ch 9 in textbook Spring quarter 2009 Instructor Ragnar Arnason Basic Statistics Outcomes of projects may follow any distribution Distributions are characterized by their quotmomentsquot characteristic aspects or parameters Some distributions are simple and defined by one or two parameters These are the distributions we have studied and like to use Normal tdistribution chisquare distribution F distribution lognormal etc Basic Statistics cont Common moments used to describe distributions are The mean expected value Variance or standard deviation Some distributions are fully described by these moments Eg the normal the lognormal etc The Normal Distribution A two parameter distribution mean and variance Ifx is normal then often written XNmXvarX Probability I I I I 36 2039 1039 0 16 26 30 I I 39 483 281 79 123 325 527 729 6826 x V j 0 9544 A J 9974 MeanxEx expected value of X Va rxEx Ex2 I W 972 moo x Standard deviation SDx tVarOc Definition of returns Dollar Return Dividend Change in Market Value dollar return percentage return 2 o beginning market value dividend change in market value beginning market value dividend yield capital gains yield Returns Example Suppose you bought 100 shares of WalMart WMT one year ago today at 25 Over the last year you received 20 in dividends 20 cents per share 100 shares At the end of the year the stock sells for 30 What was your return R Div ch in market value beg market value 208 Realreturns R real dollar return beg market value divt prieet PM 1 PIt prieet 1 prieet 1 Average vs cumulative returns Average return over a period of length T T 1 2 2 r0 Arithmetic mean Average cumulative return over a T periods R 1 rm 1 T i 1 Geometric mean Average and cumulative returns Example Suppose your investment provides the following returns over a four year period Annual cumulative return 3 1 r4 4 1 11095120115 1 00958 2 958 Average Geometric vs Arithmetic Mean Arithmetic mean Best predictor for the return in any one year Geometric mean Best predictor for the annual return over a number of years Arithmetic mean deometric mean if rtrts ie returns are constant So which to use to predict returns depends on the time horizon Blume s formula to forecast rates of return Data period N Arithmetic average RA Geometric average RG Forecast period 7 TltN T R AA Real stock prices and earnings Deflated by CPI Monthly data Source Shiller Stock prices SampP 500 Stock index Real Earnings SampP composite earnings Real 2000 450 1800 7 Price 77 400 1600 7 77 350 1400 7 W 300 1200 7 AW 250 1000 7 W 200 800 7 600 a 150 400 7 Bar in rsloo mw gmwwM 1870 1890 1910 1930 1950 1970 1990 2010 Year Real returns on stocks Based on Shiller 20o 150 109 1111111411111 m 111 50 010 M IIIIIIIIIII I39MWm 1Wquot39Iquotquotquotquotquot39Iquotquotmy39I 39E39IWWV39HZ39 1871 1881 1 9 191 191 121 1 41 1 51 1961 37 191 1591 50 I39 39 100 iTotal return MA12 Historical Returns 19262004 Source Stocks Bonds Bills and Inflation 2006 Yearbook Ibbotson Associates Inc Se es Large Company Stocks Small Company Stocks LongTerm Corporate Bonds LongTerm Government Bonds US Treasury Bills Inflation Average Annual Return 123 174 62 58 38 31 Standard Deviation 202 329 85 92 31 43 Distribution II III WH JulJr u Jr I it 90 0 90 The Historical RiskReturn Tradeoff 18 SmallCompany Stocks 16 Q go 14 25 E 12 LargeCompany Stocks E 5 10 Q 4 Tc 8 a 1 j 6 4 TBllls 2 0 5 10 15 20 25 30 35 Annual Return Standard Deviation Risk premiums and RiskFree Returns The Risk Premium is the added return over and above the risk free rate for bearing risk Treasury bills are often taken to be risk free One of the most significant observations of stock market data is the long run excess of stock return over the risk free return The average excess return from large company common stocks 1926 to 2005 was 85 123 38 The average excess return from small company common stocks 1926 to 2005 was 136 174 38 The average excess return from longterm corporate bonds 1926 to 2005 was 24 62 38

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