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.

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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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.
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 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.
All currency trading is done in pairs. Unlike the stock market, where you can buy or sell a single stock, you have to buy one currency and sell another currency in the forex market. Next, nearly all currencies are priced out to the fourth decimal point. A pip or percentage in point is the smallest increment of trade. One pip typically equals 1/100 of 1 percent.

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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