CAPM. Does it help to forecast stock market?


Junior member
10 0
CAPM. Does it help to forecast stock market?
There are so many discussions about this model. So many people argue how effective this model could be. The discussions about it have been going on over the entire lifetime of the model - from the very moment of its development. So many people predict the end of the model, but in spite of this fact the model is still alive.
In this article we’ll point out some CAPM features and try to find answer to this question.
First of all, let stop on definition. CAPM abbreviation means Capital Asset Pricing Model. Capital Asset Pricing Model (CAPM) is an equilibrium model that estimates the return of financial assets. This regression model compares the risk of exact asset and stock market. CAPM states on assumption that investors make their investment decisions base on risk and return. CAPM is a well-known model; companies such as Merrill Lynch use it.
This model was developed by Nobel Prize winner William Sharpe, John Lintner, Jack Trainor, and Jan Mossin.
This model they divided risk on systematic and non-systematic. Systematic risk stipulated by economic and stock market conditions that affect all market securities. Non-systematic risk depends on the concrete issuer.
It’s important to mention that it’s impossible to decrease the systematic risk. We can estimate the influence of stock market to exact security. As a measure of systematic risk CAPM use beta coefficient.
It’s possible to influence on non-systematic risk. Non-systematic risk can be decreased by diversification on stock portfolio. Portfolio should consist of different assets. Stocks should be originated from different sectors of economy and have different prices.
There are two important CAPM parameters describing a concrete asset, are:
· "Beta" parameter. Beta is an asset market risk parameter. Beta is the ratio of the average stock yield relative to the overall market portfolio or a stock market index such as the S&P500. It is calculated using historical data taken over a year or more. Once beta is calculated, it is considered to be a predictor of future market behavior. If the stock market goes up (or down) by a particular percentage, the theory is that there is a tendency for the stock itself to go up (or down) by the same percentage multiplied by beta. Stocks with a beta greater than 1 are considered riskier; when the stock market fluctuates, the high-beta stocks fluctuate even more. The more is beta the riskier the stock. The exact calculations are necessary for managers to select the assets that best fit their investment strategy. Managers can form different types of portfolios, conservative, aggressive, balanced etc. according to beta coefficient.
· E parameter corresponds to "residual" yield dependent on specificity of a concrete asset. It is matched with non-systematic risk, which could be reduced by creation of asset portfolio.

CAPM says that if you know a security's beta then you know the value of return that investors expect it to have.

r is the rate of a "risk-free" investment, i.e. cash;
Ep is the return rate of the appropriate portfolio.

CAPM, as any other model, has its area of applicability. This area is defined by simplifications, accepted during model creation. Such assumptions filter out unnecessary complexities and allow effective application of mathematical core, which translates empirical observations from area of sensation to the area of knowledge. Therefore, when creating CAPM, the following assumptions have been made:
· Investor is guided by only two factors - yield and risk;
· Investors operate rationally - with the same expected yield they prefer an asset with the minimal risk
· All investors have the same investment timeframe;
· Investors evaluate asset key parameters in identical manner;
· Individual investor behavior does not influence equal prices of an asset;
· There are no operational costs or hindrances, preventing free supply and demand of assets.
Let’s take a look on CAPM figure

CAPM model.
Beta an asset market risk parameter represents straight-line inclination degree.
E is average "residual" yield, describing an average asset yield deviation from "fair" yield as shown by the central line.

To create a graphic interpretation of the model, plot on a plane points, whose horizontal coordinates represent a market portfolio yield, while the vertical ones are the appropriate asset yield. One of the major stock indices, for example S&P500, is taken as market portfolio. Viewing the formed cloud of points closely, one can note that it is extended along some straight line - that of characteristic line of the given security.
The main assertion of the model is that price yield of a selected asset (or portfolio) is directly proportional to price yield of the market portfolio.
As were mentioned before, the 2 main parameters are Beta coefficient and, describing angle of straight line inclination and E parameter, describing degree of cloud concentration along the straight line.
"Beta" is a parameter of asset sensitivity to changes in market portfolio price. If, for example, "beta" is equal to 1.5, it means that when the market portfolio changes by +1%, the asset price will change by +1.5%. Assets that are more sensitive to the market are matched with greater "beta" values. This parameter is responsible for systematic (or market) asset risk, which is impossible to diversify.
To analyze stocks traded at NYSE, NASDAQ, and AMEX you can use products based on CAPM model. Such products are executed at top mathematical level. They can help you to calculated values of "beta" parameter, estimate when asset overvaluated or undervaluated and carry out asset yield forecast based on market portfolio yield.
Maybe CAPM model is not the best one but it can help traders and investors a lot!

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Veteren member
4,106 11
just an academics wet dream.

the basic premises are all flawed.
and no carpet for a soft landing.

(pun in there somewhere)


Junior member
17 1

...can´t analyze price moves. 100% guaranteed.

Rhody Trader

Senior member
2,620 266

CAPM may still have some adherents in the portfolio management arena. Volatility, however, has become more the course of academic discussion these days. Concepts such as Value At Risk (VAR) and high frequency data analysis are starting to dominate. The old linear models are falling by the wayside.
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