Investigating the long memory property of the Hungarian market pig prices by using detrended fluctuation analys

Abstract

Within the scope of this study we test the Long Memory property on monthly average pig market prices including piglet, young pig, sow and slaughter pig. We also calculate the Hurst exponent using Detrended Fluctuation Analysis (DFA) method. DFA is a method for determining the statistical self-affinity of a time serie. It is a useful technique for investigating time series with long memory (diverging correlation time and power-low decaying autocorrelation function. The obtained exponent by DFA is similar to those Hurst exponents estimated by other methods such as Rescaled Range (R/S) and AutoRegressive Fractionally Integrated Moving Average (ARFIMA), except the fact that DFA may also be applied to non-stacionary time series (mean and variance is changing with time) as in our case. We study the long memory property of the market pig prices. Data consist of four time series (piglet, young pig, sow, slaughter pig) between 1991 and 2013. Before the econometric analysis all the series were seasonally adjusted by using TRAMO/SEATS method. Data preparation was followed by differencing the time series and testing the normality and stationarity of them. In the next step we divided the analysed period to four parts and determined the Hurst exponent for each sub-period with the DFA method. So as to sum it up, slaughter pig prices are random, young pig and piglet prices developed similarly and have long memory, while sow price changes have definitely short memory