Monitoring and High Availability - Since we are considering a high-frequency intraday system, we must put comprehensive monitoring and high availability redundancy in place. This means reporting on CPU usage, disk usage, network I/O, latency and checking that any periodic scripts are set to keep running. In addition we need a backup and restore strategy. Ask yourself what backup plans you would have in place if you had large open positions, in a volatile market, and your server suddenly died. Believe me, it happens!
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.
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.