资产定价asset pricing.docx

1、资产定价asset pricingA Multifactor Approach in Understanding Asset Pricing AnomaliesAn empirical study of the factor model in the Budapest Stock MarketNaffa HelenaSpring 2009BudapestTable of ContentsTable of Figures 3Tables 31 Introduction 32 The Efficient Market Hypothesis 32.1 Theory 32.1.1 Weak Form

2、of Efficiency 32.1.2 Semi-Strong Form of Efficiency 32.1.3 Strong Form of Efficiency 32.2 The Hypothesis Defied 32.3 Capital Asset Pricing Model 32.4 An Alternative Theory: Arbitrage Pricing Theory 32.5 Relationship between the CAPM and APT 32.6 When Theories Fail, Anomalies Prevail 32.6.1 The Calen

3、dar Effect 32.6.2 Earnings on Book Equity 32.6.3 P/E Effect 32.6.4 Small-Firm Effect 32.6.5 Over and Under Reaction to Earnings 32.6.6 Mean Reversion 32.6.7 The Momentum Effect 32.6.8 Other Anomalies 32.7 Causes of the Anomalies 33 Behavioural Finance 34 Anomalies: Premium or Inefficiency 34.1 A Tes

4、t to the CAPM 34.2 Multiple Factors 34.2.1 Market Capitalisation and the Value Premium 34.3 Three Factor Model of Fama and French 34.4 Characteristics Model of Daniel and Titman 35 Empirical Findings of the Budapest Stock Exchange 35.1.1 Calculating beta and mean return 35.1.2 Forming Portfolios 35.

5、1.3 The Factors: Market Premium, SMB and HML 35.1.4 Famas model tested on the Budapest Stock Exchange 36 Limitations of the Study 37 Conclusion 3References 3Appendix 1 3Appendix 2 3Table of FiguresFigure 1: Haugens monthly returns for years 1927-2001 3Figure 2 Mean reverting and non-mean reverting b

6、ehaviour 3Figure 3: CAPM mean excess returns plotted against beta. 3Figure 6: Empirical beta for BUX components 3Figure 7: Reuters beta for BUX components, calculation period 5 years 3Figure 8: Empirical beta (x axis) graphed against stock return (y axis) 3Figure 9: Reuters beta (x axis) graphed aga

7、inst stock return (y axis) 3Figure 10: Mean excess returns vs. market beta, varying size and book/market ratio 3Figure 11: Varying size within book-to-market equity ratio groups. 3Figure 12: Varying book-to-market equity ratio within size groups 3Figure 13: BUX yearly return and the 3 month governme

8、nt bond yield 3Figure 14: Market premium is shown by the excess return over the risk free rate. 3TablesTable 1: The first periods regression January 1991- December 1997 3Table 2: The second periods regression January 1998 December 2004 3Table 3: Summary Statistics for Monthly Percent Three-Factor Ex

9、planatory Returns 3Table 4: Regression Results for the Characteristic-Balanced Portfolios 3Table 5. Returns of the 16 BUX constituent stocks 3Table 6: Stock returns, betas 3Table 7: Correlation matrix of the factors HML and SMB 3Table 8: Granger causality test for the factors HML and SMB 3Table 9: S

10、ummary table of regression of the 3 factors on the 23 Hungarian shares 3“What is a cynic? A man who knows the price of everything, and the value of nothing.”Oscar Wilde Lady Windermeres Fan1 IntroductionAn anomaly is usually a disorder, a deviation from the norm. In natural science, it has induced r

11、esearchers to formulate new theories. In finance however, what could not be explained by traditional asset pricing theories was hastily arbitrated, and later labelled an anomaly. The multifactor model devised by Fama and French on the other hand, is quite successful in explaining these anomalies, an

12、d therefore, the new theory is able to incorporate them in their asset pricing formula. In my thesis, I introduce the topic of observed abnormal market returns as being justifiable premiums versus signifying market inefficiencies. The phenomenon of anomalies is best explained by an amalgam of availa

13、ble financial literature. In such an explanation, the Efficient Market Hypothesis plays a central role in defining a standard for asset pricing in an ideal world. I will introduce the capital asset pricing model approach. In contrast with this, I discuss an extended model devised by Fama of asset pr

14、icing that incorporates factors relating to the anomalies discussed. This will familiarise the reader with the methodologies applied by different theorists to test the new model against traditional approaches. The critics of the new Fama model rebuke with an apparent rationale: the new model is spec

15、ific to the set of data examined by Fama; therefore its high precision in forecasting asset returns is not a coincidence. I shall attempt to reveal the relevance of the model to the Hungarian market. My approach will apply the formula to the emerging Budapest Stock Exchange shares using an un-ambiti

16、ous time series from September 2003 till September, 2008. Id be a bum in the street with a tin cup if the markets were efficient. Warren Buffett2 The Efficient Market HypothesisDespite the above quote from Warren Buffett, I with to study informational efficiency in stock markets. When markets are ef

17、ficient, they work smoothly whereby the possession of new information causes no added-value. From this stems the assumption in financial models that additional information should come at no cost, as it is already reflected in prices. It is much ore likely to have transparent pricing for financial in

18、struments traded on stock markets e.g. stocks, bonds, commodities. But the matter of fact is that the efficient market hypothesis fails in practice. Investments traded on the stock market by far do not represent to complete investment portfolio available to investors. Other financial products are av

19、ailable on different platforms, most of which are less transparent than stock markets. The efficient market hypothesis (EMH), however, makes assumptions that limit its validity to a theoretical market. Amongst these assumptions is that all transactions are transparent, which makes pricing fair (unbi

20、ased), as they incorporate all available information including the expectations of the market participants of the future shaping of the market. Information, as defined by the theory, is anything that affects prices in a way unknown in the present appearing randomly in the future. For this reason, it

21、 is not possible to consistently outperform the market by taking advantage of news the market already knows, except when an investor is lucky.The efficient market hypothesis was first coined by Louis Bachelier, a French mathematician. In his 1900 dissertation “Thorie de la Spculation” he “begins the

22、 mathematical modelling of stock price movements and formulates the principle that the expectation of the speculator is zero. Obviously, he understands here by expectation the conditional expectation given the past information. In other words, he implicitly accepts as an axiom that the market evalua

23、tes assets using a martingale measure.” (Courtault et al. 2000 p. 343) Yet his work was overlooked for decades until the mid 1960s when Paul Samuelson stumbled upon the dissertation and soon it became a hot topic for financial economists. However, the efficient market theory owes its refined details

24、 to Professor Eugene Fama of the University of Chicago Graduate School of Business. Fama started the formation of the theory as a PhD. dissertation and ended up as a life-long research. In 1970 he published a review of both the theory and the evidence for the hypothesis. The paper extended and fine-

25、tuned the theory; in addition, it included the definitions for three forms of market efficiency: the weak, the semi-strong and the strong form of market efficiency.2.1 TheoryThe theory assumes that market participants apart from being utility maximising, also have rational expectations. This include

26、s the assumption that even though individuals may be wrong, the population as a whole is correct; and that people adjust their expectations according to new information. When faced with new information, some investors will overreact and others will under react. In summery, reactions will be random,

27、but will have a constant volatility, and a known distribution function. Thus, the net effect does not allow for abnormal profit to be realised especially when considering transaction costs and spreads.Fama says that an efficient market is one that quickly adjusts to new information. It prevails in m

28、arkets where prices “fully reflect” available data. This constitutes the impossibility of attainting extra profits by trading on the basis of knowledge of information already incorporated. It means that in its strongest form, there should be no cost of information. We know that this in untrue, and t

29、hat a whole industry is based on selling information. This is why the need arises to further define efficiency of the markets. This has taken the form 3 levels of information integration; the weak form of efficiency, the semi-strong form of efficiency and the strong form of efficiency are discussed

30、below.2.1.1 Weak Form of EfficiencyIn its weakest form, the efficient market hypothesis assumes that all historical share prices are already incorporated into the pricing of assets. Therefore, no excess profits can be earned by basing investment strategies on past returns. This implies that technica

31、l analysis, which studies formations in past returns, is useless in predicting the future. Since past performance is already known to the market, the current situation remains unknown. This is where fundamental analysis gains attention and may be rewarding for those keen investors who do their homew

32、ork on companies financial statements. Tests for the weak form of efficiency engage in historical data analysis using statistical and econometrical methods. Analyses concerning market value, P/E, DIV/P, and book-equity-to-market-equity influences on past data, as well as technical analysis are prevalent in such testing.2.1.2 Semi-Strong Form of EfficiencyThe levels of efficiency gradually increase their restrictions, so it is natural for the next level to include the previou