I am new to this field(Quantitative high frequency finance) and really would
like some guidance from senior people. Please guide me to some good
tutorials for handling dataframes and the xts package. I need to import data
(time series, tick data) for my backtesting. The problem with tick data is:-
1)It has multiple symbols, so when I'm importing the data from a file into a
dataframe, I have to again extract data into other dataframes with unique
symbols(since my backtesting strategies will work on one symbol at a time,
and for general charting purposes)
2)It does not have a date field, just the timestamp (hh:mm:ss), so I need to
add the date field from the filename and convert it to a suitable format
compatible with Quantmod/xts before starting to use the data for
backtesting.
3)It is large, around 500MB per day(all symbols), so I need to split the
file into 50000 rows per call into the dataframe. It may be a good idea to
store it in a binary format of R.

Since I'm a beginner with R, I'm having some stupid troubles handling
dataframes, for eg. adding date into the columns of timestamps and
converting it to a compatible format for quantmod/xts

Please also guide me to some backtesting links(tutorials) or packages(like
quantmod), preferably open source, for backtesting and even for implementing
my own trading platform(for eg. Marketcetera)

Thanks

Regards
Jatin

-- 
Jatin Patni
Tel: 91 9833 2180 52
jatinpatni@gmail.com
www.jatinpatni.co.nr

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