Each time you open a new trade, calculate how much free margin you would need to use if the trade drops to its stop loss level. In other words, if your free margin is currently $500, but your potential losses of a trade are $700 (if the trade hits stop loss), you could be in trouble. In these situations, either close some of your open positions, or decrease your position sizes in order to free up additional free margin.
In particular we need to modify -every- value that appears in a Position calculation to a Decimal data-type. This includes the units, exposure, pips, profit and percentage profit. This ensures we are in full control of how rounding issues are handled when dealing with currency representations that have two decimal places of precision. In particular we need to choose the method of rounding. Python supports a few different types, but we are going to go with ROUND_HALF_DOWN, which rounds to the nearest integer with ties going towards zero.

GUI Control and Reporting - Right now the system is completely console/command line based. At the very least we will need some basic charting to display backtest results. A more sophisticated system will incorporate summary statistics of trades, strategy-level performance metrics as well as overall portfolio performance. This GUI could be implemented using a cross-platform windowing system such as Qt or Tkinter. It could also be presented using a web-based front-end, utilising a web-framework such as Django.
Unit Tests for Position/Portfolio - While I've not mentioned it directly in diary entries #1 and #2, I've actually been writing some unit tests for the Portfolio and Position objects. Since these are so crucial to the calculations of the strategy, one must be extremely confident that they perform as expected. An additional benefit of such tests is that they allow the underlying calculation to be modified, such that if all tests still pass, we can be confident that the overall system will continue to behave as expected.
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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A Portfolio Margin account can provide lower margin requirements than a Margin account. However, for a portfolio with concentrated risk, the requirements under Portfolio Margin may be greater than those under Margin, as the true economic risk behind the portfolio may not be adequately accounted for under the static Reg T calculations used for Margin accounts. Customers can compare their current Reg T margin requirements for their portfolio with those current projected under Portfolio Margin rules by clicking the Try PM button from the Account Window in Trader Workstation (demo or customer account).
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