Time scales in stock markets

Abstract

Different investment strategies are adopted in short-term and long-term depending on the time scales, even though time scales are adhoc in nature. Empirical mode decomposition based Hurst exponent analysis and variance technique have been applied to identify the time scales for short-term and long-term investment from the decomposed intrinsic mode functions(IMF). Hurst exponent ($H$) is around 0.5 for the IMFs with time scales from few days to 3 months, and $H\ge 0.75$ for the IMFs with the time scales $\ge 5$ months. Short term time series [$X_{ST}(t)$] with time scales from few days to 3 months and $H0.5$ and long term time series [$X_{LT}(t)$] with time scales $\ge 5$ and $H\ge 0.75$, which represent the dynamics of the market, are constructed from the IMFs. The $X_{ST}(t)$ and $X_{LT}(t)$ show that the market is random in short-term and correlated in long term. The study also show that the $X_{LT}(t)$ is correlated with fundamentals of the company. The analysis will be useful for investors to design the investment and trading strategy.

References in corpus (2)

• Realization of SOC behavior in a dc glow discharge plasma
• Identification of short-term and long-term time scales in stock markets and effect of structural break

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