Slippage Handling - The system is currently generating a lot of slippage due to the high-frequency nature of the tick data provided from OANDA. This means that the portfolio balance calculated locally is not reflecting the balance calculated by OANDA. Until correct event-handling and slippage adjustment is carried out, this will mean that a backtest will not correctly reflect reality.
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.
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 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.
If you believe that a currency pair such as the Australian dollar will rise against the US Dollar you can place a buy trade on AUD/USD. If the prices rises, you will make a profit for every point that AUD appreciates against the USD. If the market falls, then you will make a loss for every point the price moves against you. Our trading platform tells you in real-time how much profit or loss you are making.
Borrowing money to purchase securities is known as "buying on margin". When an investor borrows money from his broker to buy a stock, he must open a margin account with his broker, sign a related agreement and abide by the broker's margin requirements. The loan in the account is collateralized by investor's securities and cash. If the value of the stock drops too much, the investor must deposit more cash in his account, or sell a portion of the stock.
Trading on margin refers to trading on money borrowed from your broker in order to substantially increase your market exposure. When opening a margin trade, your broker lends you a certain sum of money depending on the leverage ratio used, and allocates a small portion of your trading account as the collateral, or margin for that trade. The remaining funds in your trading account will act as your free margin, which can be used to withstand negative price fluctuations from your existing leveraged positions, or to open new leveraged trades. The relation between your free margin and other important elements of your trading account, such as your balance and equity, will be explained later. For now, it’s important to understand the meaning of margin in Forex.