[R-SIG-Finance] Blotter and historical options

[Frank]

Hi,

I have an interest in analyzing option data. I work with data from the CBOE
using an Access 2003 template and export it to cvs format. The analysis is
done on the cvs data using a C program. 

I am thinking of writing a simple C program to process the CBOE data
directly to the cvs format I use. You could potentially use this program as
a starting point for conversion.

CBOE introduced new symbols for options in two stages, which I think is now
complete. You may want to consider using this format.

What is the source of your data? Hopefully CBOE?

Frank
Chicago, IL

-----Original Message-----
From: r-sig-finance-bounces at r-project.org
[mailto:r-sig-finance-bounces at r-project.org] On Behalf Of Noah Silverman
Sent: Wednesday, April 16, 2014 6:52 PM
To: r-sig-finance at r-project.org; Joshua Ulrich
Subject: [R-SIG-Finance] Blotter and historical options

Hi,

I'm a bit stuck trying to figure out how to integrate historical option
data into the blotter package.

Trying to take a log of trading history and insert it all into Blotter.

I have:
    1) historical data for a bunch of options as CSV files.
    2) A log of trades

Processing the trades for equities was easy:
    1) Use quantmod to fetch the symbols (historical data)
    2) Loop through trade log and use addTxn function of blotter.

Not sure what to do with the options.  I see a function named
"getOptionChain" in the quantmod package, but that just returns a list
of puts and calls for a single date.  I have historical data for a few
years, and need to somehow munge it into a format that I can run through
blotter.

Thoughts:
    1) Lie to blotter.  Just makeup a symbol for the option.  (i.e Apple
April 15 calls at $200 becomes "AAPL_Call_0415_200")  and then set it up
in the environment to look/act like an equity.

    2) Figure out how blotter/quantmod expects to see option data,
format my data accordingly and then pass it off to blotter as a proper
option.

Can anyone provide some insight on this?

Thanks!

-- 
*Noah Silverman, PhD* | UCLA Department of Statistics
8117 Math Sciences Building, Los Angeles, CA 90095

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