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There is one unpleasant fact for you to take into consideration about the margin call Forex. You might not even receive the margin call before your positions are liquidated. If the money in your account falls under the margin requirements, your broker will close some or all positions, as we have specified earlier in this article. This can actually help prevent your account from falling into a negative balance.
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.
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.
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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.
Monitoring and High Availability - Since we are considering a high-frequency intraday system, we must put comprehensive monitoring and high availability redundancy in place. This means reporting on CPU usage, disk usage, network I/O, latency and checking that any periodic scripts are set to keep running. In addition we need a backup and restore strategy. Ask yourself what backup plans you would have in place if you had large open positions, in a volatile market, and your server suddenly died. Believe me, it happens!

Retail or beginning traders often trade currency in micro lots, because one pip in a micro lot represents only a 10-cent move in the price. This makes losses easier to manage if a trade doesn't produce the intended results. In a mini lot, one pip equals $1 and that same one pip in a standard lot equals $10. Some currencies move as much as 100 pips or more in a single trading session making the potential losses to the small investor much more manageable by trading in micro or mini lots.
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Equity – Your equity is simply the total amount of funds you have in your trading account. Your equity will change and float each time you open a new trading position, in such a way that all your unrealised profits and losses will be added to or deducted from your total equity. For example, if your trading account size is $1,000 and your open positions are $50 in profit, your equity will amount to $1,050.
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.
Whether you have assets in a securities account or in a futures account, your assets are protected by U.S. federal regulations governing how brokers must protect your property and funds. In the securities account, your assets are protected by SEC and SIPC rules. In the futures account, your assets are protected by CFTC rules requiring segregation of customer funds. You are also protected by our strong financial position and our conservative risk management philosophy. See our Strength & Security page.
Each time you open a new trade, calculate how much free margin you would need to use if the trade drops to its stop loss level. In other words, if your free margin is currently $500, but your potential losses of a trade are $700 (if the trade hits stop loss), you could be in trouble. In these situations, either close some of your open positions, or decrease your position sizes in order to free up additional free margin.
Margin requirements for futures and futures options are established by each exchange through a calculation algorithm known as SPAN margining. SPAN (Standard Portfolio Analysis of Risk) evaluates overall portfolio risk by calculating the worst possible loss that a portfolio of derivative and physical instruments might reasonably incur over a specified time period (typically one trading day.) This is done by computing the gains and losses that the portfolio would incur under different market conditions. The most important part of the SPAN methodology is the SPAN risk array, a set of numeric values that indicate how a particular contract will gain or lose value under various conditions. Each condition is called a risk scenario. The numeric value for each risk scenario represents the gain or loss that that particular contract will experience for a particular combination of price (or underlying price) change, volatility change, and decrease in time to expiration.
A Portfolio Margin account can provide lower margin requirements than a Margin account. However, for a portfolio with concentrated risk, the requirements under Portfolio Margin may be greater than those under Margin, as the true economic risk behind the portfolio may not be adequately accounted for under the static Reg T calculations used for Margin accounts. Customers can compare their current Reg T margin requirements for their portfolio with those current projected under Portfolio Margin rules by clicking the Try PM button from the Account Window in Trader Workstation (demo or customer account).
In addition, I've had some comments from people suggesting that they'd like to see more varied order types than the simple Market Order. For carrying out proper HFT strategies against OANDA we are going to need to use Limit Orders. This will probably require a reworking of how the system currently executes trades, but it will allow a much bigger universe of trading strategies to be carried out.

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.


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.

If you believe that a currency pair such as the Australian dollar will rise against the US Dollar you can place a buy trade on AUD/USD. If the prices rises, you will make a profit for every point that AUD appreciates against the USD. If the market falls, then you will make a loss for every point the price moves against you. Our trading platform tells you in real-time how much profit or loss you are making.
To date, we've been experimenting with the OANDA Rest API in order to see how it compared to the API provided by Interactive Brokers. We've also seen how to add in a basic portfolio replication element as the first step towards a proper event-driven backtesting system. I've also had some helpful comments on both previous articles (#1 and #2), which suggests that many of you are keen on changing and extending the code yourselves.
To date, we've been experimenting with the OANDA Rest API in order to see how it compared to the API provided by Interactive Brokers. We've also seen how to add in a basic portfolio replication element as the first step towards a proper event-driven backtesting system. I've also had some helpful comments on both previous articles (#1 and #2), which suggests that many of you are keen on changing and extending the code yourselves.
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.
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).
For those of you who are new to source version control you will probably want to read up on how git (and version control in general) works with the fantastic free ebook Pro Git. It is worth spending some time learning about source control as it will save you a huge amount of future headache if you spend a lot of time programming and updating projects!
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.
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