PEMODELAN HARGA SAHAM DENGAN GEOMETRIC BROWNIAN MOTION DAN VALUE AT RISK PT CIPUTRA DEVELOPMENT Tbk - Trimono Trimono; Di Asih I Maruddani; Dwi Ispriyanti (Jurnal Gaussian, 2017)
Financial sector investment is an activity that attracts a lot of public interest. One of them is investing funds in purchasing company’s shares. Profit received from stock investment activity can be seen from the value of stock returns. While, if the previous stock returns Normal distribution, the future stock price can be predicted by Geometric Brownian Motion Method. Based on the stock price prediction, can also be measured an estimated value of the investment risk. The result of data processing shows that the stock price prediction of PT. Ciputra Development Tbk period December 1, 2016 untuk January 31, 2017, has very good accuracy, based on the value of MAPE 1.98191%. Further, Value at Risk Method of Monte Carlo Simulation with α = 5% significance level was used to measure the share investment risk of PT.Ciputra Development Tbk. Thus, this method is only useful if it can be used to predict accurately. Therefore, backtesting is needed. Based on the processing obtained data, backtesting generates the value of violation ratio at 0, it means that at significance level α = 5%, Value at Risk Method of Monte Carlo Simulation can be used at all levels of probability violation.. Keywords : Geometric Brownian Motion, Risk, Value at Risk, Backtesting