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.
So, for an investor who wants to trade $100,000, a 1% margin would mean that $1,000 needs to be deposited into the account. The remaining 99% is provided by the broker. No interest is paid directly on this borrowed amount, but if the investor does not close their position before the delivery date, it will have to be rolled over. In that case, interest may be charged depending on the investor's position (long or short) and the short-term interest rates of the underlying currencies.
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.
You could ask yourself, why wouldn’t you use the highest leverage ratio available in order to decrease your margin requirements and get an extremely high market exposure? The answer is rather simple and deals with Forex risk management. While leverage magnifies your potential profits, it also magnifies your potential losses. Trading on high leverage increases your risk in trading.
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.