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.

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I post this to let you know, as the title mentions it, that I made a trading diary, with google documents tool. This a generic spreadsheet which allows any trader to manage his trading (his risk, his pnl, his opened position, the orders...) with a trding diary. Every trader,should have one, and I mad mine with google docs. At least you must have an account to acces this spreadsheet.
(Note that the leverage shown in Trades 2 and 3 is available for Professional clients only. A Professional client is a client who possesses the experience, knowledge and expertise to make their own investment decisions and properly assess the risks that these incur. In order to be considered to be Professional client, the client must comply with MiFID ll 2014/65/EU Annex ll requirements.)
To date, we've been experimenting with the OANDA Rest API in order to see how it compared to the API provided by Interactive Brokers. We've also seen how to add in a basic portfolio replication element as the first step towards a proper event-driven backtesting system. I've also had some helpful comments on both previous articles (#1 and #2), which suggests that many of you are keen on changing and extending the code yourselves.
We use real-time margining to allow you to see your trading risk at any moment of the day. Our real-time margin system applies margin requirements throughout the day to new trades and trades already on the books and enforces initial margin requirements at the end of the day, with real-time liquidation of positions instead of delayed margin calls. This system allows us to maintain our low commissions because we do not have to spread the cost of credit losses to customers in the form of higher costs.
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