Let's presume that the market keeps on going against you. In this case, the broker will simply have no choice but to shut down all your losing positions. This limit is referred to as a stop out level. For example, when the stop out level is established at 5% by a broker, the trading platform will start closing your losing positions automatically if your margin level reaches 5%. It is important to note that it starts closing from the biggest losing position.
In particular we will need strategy level metrics, including common risk/reward ratios such as the Sharpe Ratio, Information Ratio and Sortino Ratio. We will also need drawdown statistics including the distribution of the drawdowns, as well as descriptive stats such as maximum drawdown. Other useful metrics include the Compound Annual Growth Rate (CAGR) and total return.
Let’s cover this with an example. If you have $1,000 in your trading account and use a leverage of 1:100 you could theoretically open a position size of $100,000. However, by doing so, your entire trading account would be allocated as the required margin for the trade, and even a single price tick against you would lead to a margin call. There would be no free margin to withstand any negative price fluctuation.
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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