[R] how to analyze time series structures?

[ensark]

hı,  I am preparing undergraduate thesis If you help me this would make me
feel good. 
   First  I need to analyze effect of Dow Jones Industrial average(DJIA)'s
return on Istanbul Stock Exchange(ISE). I want to use Markov-Switching
Bayesian Vector Autoregression Models (MSBVAR) that is used to examine the
effect of a large economy’s stock exchange movement on a small economy’s
stock exchange movement. The foreign stock  exchange index follows its own
dynamics (an AR process is used as a proxy).
Turkish stock exchange movements are affected by its own lag and movements
of the foreign stock exchange. Therefore, the foreign stock exchange can be
thought to have an exogenous affect on the Turkish stock exchange. None of
the lag variables of the Turkish stock exchange determine foreign stock
exchange; however, lag values and spot values of the foreign stock exchange
affect Turkish stock exchange movement.
    To calculate the standard errors of the impulse response functions, I
should use the modified error bands of Bernanke, Hall, Leeper, Sims and Zha
(1996) for the maximum likelihood estimation (MLE).

Data structure(time series);
for ISE and DJIA
daily closing prices from 01.01.1989 to 01.01.2008 in excel format.

Also I should provide following spec.;
*should fill the missing variables.
*the lag order of the identified VAR model is 5 as suggested by Bayesian
information criteria. 
*All error bands for  this paper should generated with 2000 Monto Carlo
draws. The corresponding impulse responses should reported in the
figures(use one-standard deviation shock in order to see impulses.). 

and I need these outputs;
*plot impluse-response figures and should define level of confidence bonds
in the figures for every sub-periods
*t values of responses from ISE to DJIA.(for 10 days)

Finally, I am not good at R statistics(inexperienced) so I need explanations
in detailed also need resources and ready-made codes. How I use MSBVAR model
in R and Can you prepare me toDo list? thank you  

 
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