  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 $H\geq0.75$ for the IMFs with the time scales $\geq5$ months. Short
term time series [$X_{ST}(t)$] with time scales from few days to 3 months and
$H~0.5$ and long term time series [$X_{LT}(t)$] with time scales $\geq5$ and
$H\geq0.75$, 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.
