Forex trading is versatile due to the different trading styles, Forex strategies, and Forex systems that can be used. In the Forex market, there are traders of all levels of proficiency, and each type of trader will have different ways of working. One of the features of Forex is the split between the traders who want to manually trade, and those who want to utilise automated trading. This article will focus on automated trading.
Just like securities, commodities have required initial and maintenance margins. These are typically set by the individual exchanges as a percentage of the current value of a futures contract, based on the volatility and price of the contract. The initial margin requirement for a futures contract is the amount of money you must put up as collateral to open position on the contract. To be able to buy a futures contract, you must meet the initial margin requirement, which means that you must deposit or already have that amount of money in your account.
However, what must be remembered is that the majority of robots trade within a certain range. They make a particular amount of pips inside the tight range, during the slowest time on the Forex market, and they regularly set a few pip targets, and may not even use a stop-loss. They can be classed as successful, as they do tend to make profits in each trade, even if it is only a few.
Popular leverage ratios in Forex trading include 1:10, 1:50, 1:100, 1:200, or even higher. Simply put, the leverage ratio determines the position size you’re allowed to take based on the size of your trading account. For example, a 1:100 leverage allows you to open a position 10 times higher than your trading account size, i.e., if you have $1,000 in your account, you can open a position worth $10,000. Similarly, a  leverage ratio of 1:100 allows you to open a position size 100 times larger than your trading account size. With $1,000 in your trading account, you could open a position worth $100,000!
If your free margin drops to zero, your broker will send you a margin call in order to protect the used margin on your account. Always monitor your free margin to prevent margin calls from happening, and calculate the potential losses of your trades (depending on their stop-loss levels) to determine their impact on your free margin. With some experience, you’ll find it significantly easier to follow your margin ratio and understand the meaning of margin in Forex trading.
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.
Now, let’s say you open a trade worth $50,000 with the same trading account size and leverage ratio. Your required margin for this trade would be $500 (1% of your position size), and your free margin would now also amount to $500. In other words, you could withstand a negative price fluctuation of $500 until your free margin falls to zero and causes a margin call. Your position size of $50,000 could only fall to $49,500 – this would be the largest loss your trading account could withstand.

Foreign exchange (forex) or FX trading involves trading the prices of global currencies, and at City Index it is possible to trade on the prices of a huge range of global currencies. Currency trading allows you to speculate on the movement of one currency against another, and is traded in pairs, for example the Euro against the US Dollar (EUR/USD).

As you may now come to understand, FX margins are one of the key aspects of Forex trading that must not be overlooked, as they can potentially lead to unpleasant outcomes. In order to avoid them, you should understand the theory concerning margins, margin levels and margin calls, and apply your trading experience to create a viable Forex strategy. Indeed a well developed approach will undoubtedly lead you to trading success in the end.


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.
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