Frontiers in Physics (Nov 2020)
Time Scales and Characteristics of Stock Markets in Different Investment Horizons
Abstract
Investors adopt varied investment strategies depending on the time scales (τ) of short-term and long-term investment time horizons (ITH). The nature of the market is very different in various investment τ. Empirical mode decomposition (EMD) based Hurst exponents (H) and normalized variance (NV) techniques have been applied to identify the τ and characteristics of the market in different time horizons. The values of H and NV have been estimated for the decomposed intrinsic mode functions (IMF) of the stock price. We obtained H1=0.5±0.04 and H1≥0.75 for the IMFs with τ ranging from a few days to 3 months and τ≥ 5 months, respectively. Based on the value of H1, two time series have been reconstructed from the IMFs: a) short-term time series [XST(t)] with H1=0.5±0.04 and τ from a few days to 3 months; b) long-term time series [XLT(t)] with H1≥0.75 and τ≥ 5 months. The XST(t) and XLT(t) show that market dynamics is random in short-term ITH and correlated in long-term ITH. We have also found that the NV is very small in the short-term ITH and gradually increases for long-term ITH. The results further show that the stock prices are correlated with the fundamental variables of the company in the long-term ITH. The finding may help the investors to design investment and trading strategies in both short-term and long-term investment horizons.
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