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.
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How can you avoid this unanticipated surprise? Margin calls can be effectively avoided by carefully monitoring your account balance on a regular basis, and by using stop-loss orders on every position to minimise the risk. Another smart action to consider is to implement risk management within your trading. By managing your the potential risks effectively, you will be more aware of them, and you should also be able to anticipate them and potentially avoid them altogether.
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.
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 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.
These articles, on the other hand, discuss currency trading as buying and selling currency on the foreign exchange (or "Forex") market with the intent to make money, often called "speculative forex trading". XE does not offer speculative forex trading, nor do we recommend any firms that offer this service. These articles are provided for general information only.
Borrowing money to purchase securities is known as "buying on margin". When an investor borrows money from his broker to buy a stock, he must open a margin account with his broker, sign a related agreement and abide by the broker's margin requirements. The loan in the account is collateralized by investor's securities and cash. If the value of the stock drops too much, the investor must deposit more cash in his account, or sell a portion of the stock.
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!
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).
The script is currently hardcoded to generate forex data for the entire month of January 2014. It uses the Python calendar library in order to ascertain business days (although I haven't excluded holidays yet) and then generates a set of files of the form BBBQQQ_YYYYMMDD.csv, where BBBQQQ will be the specified currency pair (e.g. GBPUSD) and YYYYMMDD is the specified date (e.g. 20140112).
What’s new in version 3.2? New features A vertical view of the instruments panel has been added called Charts view Fancy new splash screen 🙂 Import modules Degiro importer Westpac importer Light Speed importer Interactive Brokers importer update due to cash transaction format change Bug fixes Fixed Gantt chart save issue Fixed layout restore problems […]
Currency markets are important to a broad range of participants, from banks, brokers, hedge funds and investor traders who trade FX. Any company that operates or has customers overseas will need to trade currency. Central banks can also be active in currency markets, as they seek to keep the currency they are responsible for trading within a specific range.
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.
Margins are a hotly debated topic. Some traders argue that too much margin is very dangerous, however it all depends on trading style and the amount of trading experience one has. If you are going to trade on a margin account, it is important that you know what your broker's policies are on margin accounts, and that you fully understand and are comfortable with the risks involved. Be careful to avoid a Forex margin call.
In particular we need to modify -every- value that appears in a Position calculation to a Decimal data-type. This includes the units, exposure, pips, profit and percentage profit. This ensures we are in full control of how rounding issues are handled when dealing with currency representations that have two decimal places of precision. In particular we need to choose the method of rounding. Python supports a few different types, but we are going to go with ROUND_HALF_DOWN, which rounds to the nearest integer with ties going towards zero.
Often, closing one losing position will take the margin level Forex higher than 5%, as it will release the margin of that position, so the total used margin will decrease and consequently the margin level will increase. The system often takes the margin level higher than 5%, by closing the biggest position first. If your other losing positions continue losing and the margin level reaches 5% once more, the system will just close another losing position.
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.