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Determinácia systematického rizika kmeňovej akcie v modeli časovo-premenlivého fundamentálneho beta


Finance

Determinácia systematického rizika kmeňovej akcie v modeli časovo-premenlivého fundamentálneho beta

Name and surname of author:

Jozef Glova

Year:
2013
Volume:
16
Issue:
2
Keywords:
Systematic Risk, Capital Asset Pricing Model, Time-Varying Beta, Equity Risk Premium
DOI (& full text):
Anotation:
The current paper explores CAPM as a static model expressing relationships between excess return on the market portfolio often proxied by capital market indices, where beta is a measure of the volatility or systematic risk. We discuss background to the CAPM and derive the equations of the capital market line and security market line. To become more dynamic in the model we suggest apply the equations (12) and (13) expressing the time varying measure of the systematic risk of equity – fundamental beta. To demonstrate the applicability of the general model we apply financial econometrics involving three key steps – model selection, estimation and testing. We suggest a variety of factors (quite 24 variables) that potentially influence equity risk of Dell. In an efficient financial market we expect only stock market reaction to the unanticipated component of the fundamental variables. Thus we focus on the unanticipated or unexpected components, which we find as the residuals from ARIMA models fitted to the fundamental data. These ARIMA models were identified from the autocorrelation and partial autocorrelation functions of the data. The outcome of our modelling shows that only the multiplying the residuals from ARIMA model fitted to 6-month treasury bills yield data by the excess return on the market portfolio data and the excess return on the market portfolio data are linked to variations in Dell’s equity risk. The results of estimating the most comprehensive specification of the economic variable market model of equation (17) are reported in Tab. 1. Tests are indicating an absence of autocorrelation and heteroskedasticity in the model. The applied model can be used to determination of equity costs within a discounted cash flow approach to assess of the business value of equity or intrinsic value of stock.  
The current paper explores CAPM as a static model expressing relationships between excess return on the market portfolio often proxied by capital market indices, where beta is a measure of the volatility or systematic risk. We discuss background to the CAPM and derive the equations of the capital market line and security market line. To become more dynamic in the model we suggest apply the equations (12) and (13) expressing the time varying measure of the systematic risk of equity – fundamental beta.

To demonstrate the applicability of the general model we apply financial econometrics involving three key steps – model selection, estimation and testing. We suggest a variety of factors (quite 24 variables) that potentially influence equity risk of Dell. In an efficient financial market we expect only stock market reaction to the unanticipated component of the fundamental variables. Thus we focus on the unanticipated or unexpected components, which we find as the residuals from ARIMA models fitted to the fundamental data. These ARIMA models were identified from the autocorrelation and partial autocorrelation functions of the data. The outcome of our modelling shows that only the multiplying the residuals from ARIMA model fitted to 6-month treasury bills yield data by the excess return on the market portfolio data and the excess return on the market portfolio data are linked to variations in Dell’s equity risk. The results of estimating the most comprehensive specification of the economic variable market model of equation (17) are reported in Tab. 1. Tests are indicating an absence of autocorrelation and heteroskedasticity in the model.
The applied model can be used to determination of equity costs within a discounted cash flow approach to assess of the business value of equity or intrinsic value of stock.
 
Section:
Finance

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