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).
Systems that derive risk-based margin requirements deliver adequate assessments of the risk for complex derivative portfolios under small/moderate move scenarios. Such systems are less comprehensive when considering large moves in the price of the underlying stock or future. We have enhanced the basic exchange margin models with algorithms that consider the portfolio impact of larger moves up 30% (or even higher for extremely volatile stocks). This 'Extreme Margin Model' may increase the margin requirement for portfolios with net short options positions, and is particularly sensitive to short positions in far out-of-the-money options.
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.
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