Paolucci-Giacobini Method

The Paolucci-Giacobini method is a mathematical method that is used to forecast financial time series. This method was developed in 1967 by two Italian scientists, Francesco Paolovich and Ezio Giacobini.

The main advantage of the Paolucci-Jacobian method is its flexibility, allowing it to be applied to different types of time series and situations. When using the method, both long-term trends and short-term fluctuations are taken into account. It is important to note that the forecast accuracy when using the Paolursi-Dhakobinian method is higher than when using other forecasting methods.

The process of using the Paulucci-Jacobilian method consists of several steps:

defining the initial period of a time series, used to identify general trends and characteristics of the time series. considering the noise level in a time series and dividing it into two parts. constructing a smoothed curve and comparing it with the original time series. determining the segments in which the further development of time series is predicted by calculating the average balance for past periods. calculating a trial value for a future period based on the predicted values ​​of the previous curve, including both residual values ​​in this period. comparing the forecast curve (matching the detrended curve) with the original time series to determine how good the forecast is