The script is currently hardcoded to generate forex data for the entire month of January 2014. It uses the Python calendar library in order to ascertain business days (although I haven't excluded holidays yet) and then generates a set of files of the form BBBQQQ_YYYYMMDD.csv, where BBBQQQ will be the specified currency pair (e.g. GBPUSD) and YYYYMMDD is the specified date (e.g. 20140112). 

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An extremely important requested feature for QSForex has been the ability to backtest over multiple days. Previously the system only supported backtesting via a single file. This was not a scalable solution as such a file must be read into memory and subsequently into a Pandas DataFrame. While the tick data files produced are not huge (roughly 3.5Mb each), they do add up quickly if we consider multiple pairs over periods of months or more.
We also offer an IRA Margin account, which allows you to immediately trade on your proceeds of sales rather than waiting for your sale to settle. You can trade assets in multiple currencies and trade limited option spread combinations. IRA margin accounts have certain restrictions compared to regular margin accounts and borrowing is never allowed in an IRA account. Futures trading in an IRA margin account is subject to substantially higher margin requirements than in a non-IRA margin account. Margin rates in an IRA margin account may meet or exceed three times the overnight futures margin requirement imposed in a non-IRA margin account1.
Local Portfolio Handling - In my opinion carrying out a backtest that inflates strategy performance due to unrealistic assumptions is annoying at best and extremely unprofitable at worst! Introducing a local portfolio object that replicates the OANDA calculations means that we can check our internal calculations while carrying out practice trading, which gives us greater confidence when we later use this same portfolio object for backtesting on historical data.