Arima Model Usage in Forecasting Stock Prices of Nykaa

The accurate projection of stocks is very important as investors should make the right steps depending on the probability of the market. This research revolves around the forecast of Nykaa’s stock prices using the Autoregressive Integrated Moving Average (ARIMA) techniques. Thus, historical stock price data of Nykaa is gathered and preprocessed to find out patterns for creation of a trading model. ARIMA is used to analyze the time series characteristics and trend of stock prices to give projection for the future prices. Evaluation criteria including the MAE and Root Mean Squared Error scale the model’s predictability level. This paper shows how the adopted ARIMA model satisfies the modeling of Nykaa’s stock price fluctuations that are useful to investors and stakeholders. Thus, this research presents a valuable contribution to the improvement of the choices in the sphere of financial markets, focusing on the Nykaa’sstock employing the historical data and the ARIMA model.