When investors are selling, the exchange rate of the foreign currency tells them how many units of the quote currency they will get for one unit of the base currency. Traders make decisions to buy if they think that the value of the base currency might increase. In the example, traders would purchase the US dollar with the Euro if they expect the value of the US dollar to increase to $1.31. The change that takes place is how the investor makes a profit.
Not all securities can be bought on margin. Buying on margin is a double-edged sword that can translate into bigger gains or bigger losses. In volatile markets, investors who borrowed from their brokers may need to provide additional cash if the price of a stock drops too much for those who bought on margin or rallies too much for those who shorted a stock. In such cases, brokers are also allowed to liquidate a position, even without informing the investor. Real-time position monitoring is a crucial tool when buying on margin or shorting a stock.
If it was this easy to earn money utilising robots, nobody would ever go to work. It is possible that robots can make money for a restricted time period, but they could start losing after awhile - and the money earned by the 'best Forex robot' with one position may disappear before you can claim it. In addition, the vast majority of robots are scalpers. They make just a few pips with every position they take - and they can set a considerably tight target. The chances of surviving with such a strategy are quite limited for a trader.
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If the robots they sell could actually make a huge amount of money through trading the currencies, then what is the point in selling them to others and not utilising them on their own Forex accounts? The answer is logical - robots can barely make money for a Forex trader. Can a $99 FX robot or a free Forex robot really make hundreds or thousands of dollars every month? If it could, you have to ask yourself - would it really be sold for such a relatively low price?
Trading on margin refers to trading on money borrowed from your broker in order to substantially increase your market exposure. When opening a margin trade, your broker lends you a certain sum of money depending on the leverage ratio used, and allocates a small portion of your trading account as the collateral, or margin for that trade. The remaining funds in your trading account will act as your free margin, which can be used to withstand negative price fluctuations from your existing leveraged positions, or to open new leveraged trades. The relation between your free margin and other important elements of your trading account, such as your balance and equity, will be explained later. For now, it’s important to understand the meaning of margin in Forex.

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.


Maintenance margin for commodities is the amount that you must maintain in your account to support the futures contract and represents the lowest level to which your account can drop before you must deposit additional funds. Commodities positions are marked to market daily, with your account adjusted for any profit or loss that occurs. Because the price of underlying commodities fluctuates, it is possible that the value of the commodity may decline to the point at which your account balance falls below the required maintenance margin. If this happens, brokers typically make a margin call, which means you must deposit additional funds to meet the margin requirement.
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.
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).

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.
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.
As we've already stated, trading on margin is trading on money borrowed from your broker. Each time you open a trade on margin, your broker automatically allocates the required margin from your existing funds in the trading account in order to back the margin trade. The precise amount of allocated funds depends on the leverage ratio used on your account.

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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