This study proposed to develop a stock indicator that can forecast the value of a share by considering the daily closing price or opening price with the different parameter of Holt’s method. Most of the indicator which is existing in most of the stock market which forecasted value is based on a long period forecast. But, Holt’s method will be easy to analyze the price of an individual company with maximum accuracy for short period forecasting. The daily data, the closing price of the different company, are collected from the Dhaka Stock Exchange (DSE) for the period of 2016. The variables: level, trend, forecast as well as smoothing constant (α, β) are used for quick reaction to systematic changes in the time series. By using Holt’s method, a buyer can predict, how much of a share price will be the next day. The research finds that Holt’s method forecasting is better for short time then long time as evidence shows that the fourth day predicted value is closer to the actual value. In addition, the analysis discovers that for prediction the forecast value, the fifteen and seven days’ data of any company are more accurate than 30 days’ data. This study notices that different smoothing constant is the big factor for forecasting and suggests to use smoothing constant α = 0.5, β = 0.1.