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.
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.
Retail or beginning traders often trade currency in micro lots, because one pip in a micro lot represents only a 10-cent move in the price. This makes losses easier to manage if a trade doesn't produce the intended results. In a mini lot, one pip equals $1 and that same one pip in a standard lot equals $10. Some currencies move as much as 100 pips or more in a single trading session making the potential losses to the small investor much more manageable by trading in micro or mini lots.

In particular I would like to make the system a lot faster, since it will allow parameter searches to be carried out in a reasonable time. While Python is a great tool, it's one drawback is that it is relatively slow when compared to C/C++. Hence I will be carrying out a lot of profiling to try and improve the execution speed of both the backtest and the performance calculations.

In particular I've made the interface for beginning a new backtest a lot simpler by encapsulating a lot of the "boilerplate" code into a new Backtest class. I've also modified the system to be fully workable with multiple currency pairs. In this article I'll describe the new interface and show the usual Moving Average Crossover example on both GBP/USD and EUR/USD.


For those of you who are new to source version control you will probably want to read up on how git (and version control in general) works with the fantastic free ebook Pro Git. It is worth spending some time learning about source control as it will save you a huge amount of future headache if you spend a lot of time programming and updating projects!
Trading on a margin can have varying consequences. It can influence your trading experience both positively and negatively, with both profits and losses potentially being seriously augmented. Your broker takes your margin deposit and then pools it with someone else's margin Forex deposits. Brokers do this in order to be able to place trades within the whole interbank network.
Trading foreign exchange on margin carries a high level of risk, and may not be suitable for everyone. Before deciding to trade foreign exchange you should carefully consider your investment objectives, level of experience, and risk appetite. Remember, you could sustain a loss of some or all of your initial investment, which means that you should not invest money that you cannot afford to lose. If you have any doubts, it is advisable to seek advice from an independent financial advisor.
For those of you who are new to source version control you will probably want to read up on how git (and version control in general) works with the fantastic free ebook Pro Git. It is worth spending some time learning about source control as it will save you a huge amount of future headache if you spend a lot of time programming and updating projects!
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.
Now that we have discussed the longer term plan I want to present some of the changes I have made to the code since diary entry #2. In particular, I want to describe how I modified the code to handle the Decimal data-type instead of using floating point storage. This is an extremely important change as floating point representations are a substantial source of long-term error in portfolio and order management systems.
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Note also that when we begin storing our trades in a relational database (as described above in the roadmap) we will need to make sure we once again use the correct data-type. PostgreSQL and MySQL support a decimal representation. It is vital that we utilise these data-types when we create our database schema, otherwise we will run into rounding errors that are extremely difficult to diagnose!
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Now, let’s say you open a trade worth $50,000 with the same trading account size and leverage ratio. Your required margin for this trade would be $500 (1% of your position size), and your free margin would now also amount to $500. In other words, you could withstand a negative price fluctuation of $500 until your free margin falls to zero and causes a margin call. Your position size of $50,000 could only fall to $49,500 – this would be the largest loss your trading account could withstand.
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© Forex Factory 2020.  All rights reserved.  The Forex Factory calendar changes frequently to reflect the latest information.  For the most up to date calendar, please visit https://www.forexfactory.com/calendar.php.  Forex Factory takes no responsibility for decisions based on this information, please see our terms of service at https://www.forexfactory.com/legal.php.
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