A STUDY ON MONTE CARLO SIMULATION FOR STOCK PRICE FORECASTING - Singh, Thangjam Ravichandra (Digital Repository of Theses - SSBM Geneva, 2022)
The financial market may be a stochastic and sophisticated system that's challenging to model. Investors should be able to predict or simulate the probable outcomes of their portfolio or the interested investment strategy or the decision of choosing the asset class to yield the desired and expected return from the selected portfolio investments. This research project will check the feasibility and capacity of Monte Carlo Simulation to forecast the futuristic prices of equity shares of selected corporates from the India’s largest and oldest stock exchange National Stock Exchange (NSE). Five stocks of the banking sector, five stocks of the entertainment sector, and five stocks of the hotel sector were used as data set for the simulation and evaluates them over their past year data and predicted the data for the present year and further interpreted whether the business is strong for the future and what will be the forecasted present price. Monte Carlo Simulation is a very important part of the firm as it states the stock price forecasting and tells us about efficient market hypothesis. Stock price forecasting will be taken for analysis purpose as it simplifies the fundamental hypothesis with respect to stock value anticipating is the Proficient Market Theory (EMH), which declares that the cost of a stock market as all data are accessible, and everybody has some level of admittance to the information. Time arrangement investigation covers countless forecasting strategies. It also allows the management to recognize problem relates areas so they can work on them. The main parameters which determine the outcome of the simulations are the mean return of a stock, median return of the stock, standard deviation, and the percentiles returns. When these parameters were calculated and proved to be statistically significant for predictions for a month. By varying the assumptions regarding price distribution concerning the size of the current period time, the method could prove to be more accurate than what this study suggests. Monte Carlo Simulations proved to have the potential to become the best tool which will gives the accurate and effective stock price prediction model.