TY  - JOUR
T1  - Statistical Data Mining Approach with Asymmetric Conditionally Volatility Model in Financial Time Series Data
AU - Ilango, V. AU - Subramanian, R. AU - Vasudevan, V. 
JO  - International Journal of Soft Computing
VL  - 8
IS  - 4
SP  - 252
EP  - 260
PY  - 2013
DA  - 2001/08/19
SN  - 1816-9503
DO  - ijscomp.2013.252.260
UR  - https://makhillpublications.co/view-article.php?doi=ijscomp.2013.252.260
KW  - Returns
KW  -emerging markets
KW  -volatility
KW  -weekend anomaly
KW  -TGARCH
AB  - The objective of this study is to investigate the possible 
  existence and stability of the day of the week effect and measures the mean 
  and conditional volatility in testing the degree of market efficiency in the 
  BSE Sensitivity Index and S&P CNX Nifty Index over the period spanning from 
  July 1, 1997 to March 31, 2012 by using asymmetric TGARCH Model and introduced 
  dummy variables into the mean equation and conditional variance equation the 
  assess the distributional properties between Monday to Friday. Unit Root test, 
  Augmented Dickey Fuller (ADF) test, Phillips-Peron (PP) test, Ljung Box Q were 
  applied. The result of the study indicates the return and volatility for both 
  the index are scattered over a period of time. Apart from that the risk averse 
  investors are willing to commit huge amount of transaction with higher risk 
  appetite because the market digest the information and react immediately towards 
  news shocks. Therefore, the seasonality changes and interexchange arbitrage 
  opportunity in emerging markets makes the investors to create various trading 
  strategies in both the market. Overall, the professionals market watchers who 
  are aware of the daily return pattern should adjust the timing of their buying 
  and selling to take advantage of the effect.
ER  -