Investors use a variety of investing methods depending on the time scales () of their short-term and long-term investment time horizons (ITH). The nature of the market varies greatly depending on the type of investment. Hurst exponents (H) and normalised variance (NV) techniques based on empirical mode decomposition (EMD) have been used to identify key features of the market over various time horizons. For the stock price's decomposed intrinsic mode functions (IMF), the values of H and NV have been estimated. We found H1 0.5 0.04 and H1 0.75 for the IMFs with time periods ranging from a few days to 3 months and 5 months, respectively. Two time series from the IMFs have been reconstructed based on the value of H1: a) Short-term time series [XST (t)] with H1 = 0.5.b) long-term time series [XLT (t)] with H1 0.75 and a time span of 5 months. The XST (t) and XLT (t) indicators reveal that market dynamics in short-term ITH are random and connected in long-term ITH. We also discovered that the NV is very low in short-term ITH and gradually increases in long-term ITH. The results also reveal that in the long run, stock prices are connected with the company's fundamental factors. The discovery may aid investors in developing investment and trading strategies for both short-term and long-term investment goals.