AUTOREGRESSIVE CONDITIONAL DURATION MODEL WITH WEIBULL DISTRIBUTION

Jurnal Akuntansi Prima, Volume VI, Nomor II, Juli 2016

Rabu, 13 September 2017 15:37 | Sudah dibaca 810 kali

Analysis oftime series dataisthe typeof data that consists ofvariables where it is collectedin chronological order with in a certain time frame foracate goryor aspecific individual. ACD (Autoregressive Conditional Duration) modelisone of themodel thatcanbe used fortime series data. ACD (Autoregressive ConditionalDuration) modelisa modelthat usesthe data lengthwhichis the goal of the ACD (Autoregressive Conditional Duration) modelisto model thedurationo data between transactions with narrow interval sandi rregular. The distribution of the error is weibull distribution. weibull distribution has shape parameter and it can describe the dynamic of the duration. Parametersinthe ACD (Autoregressive Conditional Duration) modelare estimated by using Maximum Like lihood method and also Estimating Function. The method of Estimating Function is using numerica liter ation method. The Method is called NewtonRaphson method. That method is usedto estimate the parametersofthe model ACD (Autoregressive Conditional Duration). Estimating Functionis a good method for the Unilever stock data and it has a smaller variance than the Maximum Likelihood method

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