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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.
Leveraged trading in foreign currency or off-exchange products on margin carries significant risk and may not be suitable for all investors. We advise you to carefully consider whether trading is appropriate for you based on your personal circumstances. Forex trading involves risk. Losses can exceed deposits. We recommend that you seek independent advice and ensure you fully understand the risks involved before trading.
The market then wants to trigger one of your pending orders but you may not have enough Forex free margin in your account. That pending order will either not be triggered or will be cancelled automatically. This can cause some traders to think that their broker failed to carry out their orders. Of course in this instance, this just isn't true. It's simply because the trader didn't have enough free margin in their trading account.
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.
If traders are positive on the prospects for the Yen, they would expect the number on the right to go down – i.e. the Yen would be getting stronger against the Dollar. Traders would be buying less Yen with a Dollar as the Yen got stronger. Similarly, if the Yen was expected to weaken, forex traders would expect the Yen number to go up, reflecting the fact that the dollar could buy more yen.
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.
Each time you open a new trade, calculate how much free margin you would need to use if the trade drops to its stop loss level. In other words, if your free margin is currently $500, but your potential losses of a trade are $700 (if the trade hits stop loss), you could be in trouble. In these situations, either close some of your open positions, or decrease your position sizes in order to free up additional free margin.
Once an investor has started buying a stock on margin, the NYSE and FINRA require that a minimum amount of equity be maintained in the investor's margin account. These rules require investors to have at least 25% of the total market value of the securities they own in their margin account. This is called the maintenance margin. For market participants identified as pattern day traders, the maintenance margin requirement is a minimum of $25,000 (or 25% of the total market value of the securities, whichever is higher).
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.