Margin calls are mechanisms put in place by your Forex broker in order to keep your used margin secure. Remember, your used margin is allocated by your broker as the collateral for funds borrowed from your broker. A margin call happens when your free margin falls to zero, and all you have left in your trading account is your used, or required margin. When this happens, your broker will automatically close all open positions at current market rates.
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!
Free margin in Forex is the amount of money that is not involved in any trade. You can use it to take more positions, however, that isn't all - as the free margin is the difference between equity and margin. If your open positions make you money, the more they achieve profit, the greater the equity you will have, so you will have more free margin as a result. There may be a situation when you have some open positions and also some pending orders simultaneously.
Risk Management - Many "research" backtests completely ignore risk management. Unfortunately this is generally necessary for brevity in describing the rules of a strategy. In reality we -must- use a risk overlay when trading, otherwise it is extremely likely that we will suffer a substantial loss at some stage. This is not to say that risk management can prevent this entirely, but it certainly makes it less likely!
The Federal Reserve Board and self-regulatory organizations (SROs), such as the New York Stock Exchange and FINRA, have clear rules regarding margin trading. In the United States, the Fed's Regulation T allows investors to borrow up to 50 percent of the price of the securities to be purchased on margin. The percentage of the purchase price of securities that an investor must pay for is called the initial margin. To buy securities on margin, the investor must first deposit enough cash or eligible securities with a broker to meet the initial margin requirement for that purchase.
If you sell a security short, you must have sufficient equity in your account to cover any fees associated with borrowing the security. If you borrow the security through us, we will borrow the security on your behalf and your account must have sufficient collateral to cover the margin requirements of the short sale. To cover administrative fees and stock borrowing fees, we must post 102% of the value of the security borrowed as collateral with the lender. In instances in which the security shorted is hard to borrow, borrowing fees charged by the lender may be so high (greater than the interest earned) that the short seller must pay additional interest for the privilege of borrowing a security. Customers may view the indicative short stock interest rates for a specific stock through the Short Stock (SLB) Availability tool located in the Tools section of their Account Management page. For more information concerning shorting stocks and associated fees, visit our Stock Shorting page.
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.
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.