Elham Danesh - Ph.D. Candidate in Accounting, Department of Accounting, North Tehran Branch, Islamic Azad University, Tehran, Iran.
Ali Saeedi - Associate Professor, Department of Management, North Tehran Branch, Islamic Azad University, Tehran, Iran.
Ehsan Rahmani nia - Assistant Prof, Department of Accounting, North Tehran Branch, Islamic Azad University, Tehran, Iran.
Amir Gholami - Assistant Prof, Department of Accounting, North Tehran Branch, Islamic Azad University, Tehran, Iran.

The purpose of this study is a new understanding behaviour and net cash flow forecasting. The data of this research contains the daily trial balance for one year, which has been received from ۴۸ bank branches. For this purpose, the optimal model out of ۴ models; Geometric Brownie, Arithmetic Brownie, Vasicek and Modified Square Root at three levels of microscopic, mesoscopic and macroscopic have been investigated and the Geometric Brownie model has been approved as the optimal model in microscopic level . The results show that Geometric Brownian Motion model can simulate the net cash flow highly accurate in accordance with the criteria of mean absolute percentage error. also forecasting net cash flow for each under study time series has been done in various forecasting horizons involved ۷, ۱۴, ۲۱, ۳۰, ۶۰, ۹۰ and ۱۸۰ day time period accordance with the criteria of mean absolute percentage error. Also The other results obtained from this study is that according to ۸ different prediction accuracy criteria, By increasing the forecast hori-zon, ability of the GBM model in simulation and forecasting the net cash flow de-creases.

Net cash flow, Geometric Brown Motion, Arithmetic Brownian Motion, Vasicek, Modified Square Root