Feedback trading behavior in Dhaka Stock Exchange (DSE ...

do not have statistically significant effect on index returns and thus investors are
not compensated, in the CAPM framework, with higher return for taking higher
risk in DSE. When the expected volatility rises, rational investors influence prices
negatively, and in such a case
0
would be negative. Our results reveal just the
opposite. Statistically significant positive
0
for both the returen series in our
analysis would, therefore, suggest the lack of rational traders’ influence on prices
during volatility changes.
Table 3: Parameter estimations of Koutmos version of SSW- GARCH (1,1)
model for testing feedback trading hypothesis
Parameters DSE Gen DSE 20
R t = α+
0 (σ 2 t) - (
1 +
2 σ 2 t) R t -1 +
3
R
t 1
+є t
α -0.0001 -0.0011***
p-value 0.5590 0.0001
0
3.3981 1.3803
p-value 0.3764 0.7669
1
0.2425*** 0.2846***
p-value 0.0000 0.0000
2
-365.1448** -389.6968***
p-value 0.0212 0.0002
3
0.0538 0.1538***
p-value 0.1825 0.0007
2
2
2
t = + 0
t 1
+ 1
t 1
+ t
1.03E-06*** 8.66E-06***
p-value 0.0000 0.0000
0
0.1726*** 0.2221***
p-value 0.0000 0.0000
1
0.8368**** 0.7195***
p-value 0.0000 0.0000
Durbin-Watson stat. 1.9672 1.9789
F statistics 7.2836 12.1344
Log likelihood 5217.439 5923.475
Akaike info criterion -6.5594 -6.4702
Schwarz criterion -6.5332 -6.4536
***Significant at 1 % level; **Significant at 5% level.
Taking the complex behavior in stock markets into account, it is more robust than
the traditional stochastic approach to model the observed data by a nonlinear
chaotic model disturbed by dynamic noise (Kyrtsou, C. and M. Terraza , 2003 ).
Following Kyrtsou (2005) and Kyrtsou and Serletis (2006) we employ a Mackey-
Glass-GARCH (MG-GARCH) process model to reconfirm the existence of
feedback trading. The model has either negligible or zero autocorrelations in the
conditional mean, and a rich structure in the conditional variance. This model
also permits to capture volatility-clustering phenomena which is treated as an
endogenous process . The optimal c and τ are chosen on the basis of Log
Likelihood and Schwarz criteria. In this case c=2 and τ=1 are selected. The main
characteristic of the non-linear trading strategy in the mean equation of the above
model is that it can take into account dynamics produced by both positive and