Normality assumption for the log-return of the stock prices

• Autorzy: Pedro P. Mota
• Języki publikacji: EN

Abstrakty

EN

The normality of the log-returns for the price of the stocks is one of the most important assumptions in mathematical finance. Usually is assumed that the price dynamics of the stocks are driven by geometric Brownian motion and, in that case, the log-return of the prices are independent and normally distributed. For instance, for the Black-Scholes model and for the Black-Scholes pricing formula [4] this is one of the main assumptions. In this paper we will investigate if this assumption is verified in the real world, that is, for a large number of company stock prices we will test the normality assumption for the log-return of their prices. We will apply the Kolmogorov-Smirnov [10, 5], the Shapiro-Wilks [17, 16] and the Anderson-Darling [1, 2] tests for normality to a wide number of company prices from companies quoted in the Nasdaq composite index.

Słowa kluczowe

EN

Anderson-Darling; Black-Scholes; Geometric Brownian motion; Kolmogorov-Smirnov; Log-return; Normality test; Shapiro-Wilks

Kategorie tematyczne

• 62F03: Hypothesis testing
• 62Q05: Statistical tables
• 62G30: Order statistics; empirical distribution functions
• 62F10: Point estimation

• Wydawca: Faculty of Mathematics, Computer Science and Econometrics, University of Zielona Góra
• Czasopismo: Discussiones Mathematicae Probability and Statistics
• Rocznik: 2012
• Tom: 32
• Numer: 1-2
• Strony: 47-58

Daty

wydano

2012

otrzymano

2012-05-18

Twórcy

autor

Pedro P. Mota

• Department of Mathematics, CMA of FCT/UNL

Bibliografia

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Identyfikatory

DOI

10.7151/dmps1143