If the latter is the case then you just earn risk

Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: ins stock returns and believe the factor will rise, then they can (1) long stocks that are more sensitive to the factor, (2) short the stocks that are less sensitive to the factor, and (3) make profits from the rise of factor profits If you do not believe efficient markets, you make If profits from speculations profits If you believe efficient markets, profits will quickly If disappear, or they are related with “true” risk. If the latter is the case, then you just earn risk premium5-60 latter Speculate using factor models Suppose we want to speculate using the FX Suppose exposure (For example, we want to make profits by betting on the depreciation of US dollar) by For Excel, see “speculation” in For “Lecture2_StockPricing” “Lecture2_StockPricing” As you can see, by longing Dell and shorting GE, As we achieve: (1) a “zero-investment” portfolio (2) “neutralize” the risk exposure to market risk, so that we can eliminate other risks; (3) So, if we believe that the USD will depreciate against Euro, we will profit over 9% when USD depreciates by 1%. 5-61 The implementation of multifactor models (1) Basically speaking, you can throw in any Basically economic variables in the multifactor model You can throw in any quantitative economic quantitative variables in the multifactor model variables For qualitative variables (e.g., country risk), you For qualitative can assign number to each status (e.g, 1-least risky, 5- most risky) and thus “quantify” these variables variables Or, you can use binary distribution to present the Or, variable in regression (1 = risky countries; 0 = riskless countries) riskless 5-62 The implementation of multifactor models (2) So, how many variables should we consider? There are two stepwise approaches: There stepwise Narrow-down: First, throw in all variables in the Narrow-down First, regression; then, drop the insignificant ones and rerun the regression. Keep doing so until you find all variables appear to be significant. find Expansion: First, only include one variable that First, should be the most important one (e.g., market premium); then, throw in another variable to see if this new one is significant – (a) if not, then drop it and try another – (b) if yes, then keep it and throw in another variable until all variables have been tried. 5-63 Linking return models to dividend models 5-64 General dividend model for stocks ∞ Dt Po = ∑ t t = 1 (1+ rt) P0 = Current stock price Dt = Future cash dividends (can be fixed) Future rt = expected stock return from CAPM and other linear models (can be fixed) other The key concept here is: your future The dividend is “discounted” by expected return dividend 5-65 Example Let’s use GE as the example because it is Let’s financially solid and provides constant dividends financially We go to check GE’s dividend process since We 2000 2000 Now, we set the follows: (1) fixed r = 5% and (2) Now, dividends after 2011 remains the same dividends Let’s try to used dividend data since 2000 to Let’s estimate GE’s stock price in 2000 estimate See “GE dividend” in “Lecture2_StockPricing” The estimated price is 11.67 but the market price The was 50 at the end of December 2000, so GE was overpriced back in 2000 was 5-66 Exercise 7 See “Exercise 7” tab in “Lecture2_StockPricing” Try to compute GE stock price using data table Try function for various expected stock returns, given (1) presumed dividend process and (2) expected returns ranging from 1% to 10% Let’s try to used dividend data since 2000 to estimate GE’s stock price in 2000 estimate Plot the expected returns (in X-axis) and stock Plot price (Y-axis) price 5-67...
View Full Document

Ask a homework question - tutors are online