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).
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.
Trading foreign exchange on margin carries a high level of risk, and may not be suitable for everyone. Before deciding to trade foreign exchange you should carefully consider your investment objectives, level of experience, and risk appetite. Remember, you could sustain a loss of some or all of your initial investment, which means that you should not invest money that you cannot afford to lose. If you have any doubts, it is advisable to seek advice from an independent financial advisor.
If traders are positive on the prospects for the Yen, they would expect the number on the right to go down – i.e. the Yen would be getting stronger against the Dollar. Traders would be buying less Yen with a Dollar as the Yen got stronger. Similarly, if the Yen was expected to weaken, forex traders would expect the Yen number to go up, reflecting the fact that the dollar could buy more yen.
Trading on margin can be a profitable Forex strategy, but it is important to understand all the possible risks. You should make sure you know how your margin account operates, and be sure to read the margin agreement between you and your selected broker. If there is anything you are unclear about in your agreement, ask questions and make sure everything is clear.
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.

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).


An extremely important requested feature for QSForex has been the ability to backtest over multiple days. Previously the system only supported backtesting via a single file. This was not a scalable solution as such a file must be read into memory and subsequently into a Pandas DataFrame. While the tick data files produced are not huge (roughly 3.5Mb each), they do add up quickly if we consider multiple pairs over periods of months or more.
The majority of the volume in currency trading is confined to only 18 currency pairs compared to the thousands of stocks that are available in the global equity markets. Although there are other traded pairs outside of the 18, the eight currencies most often traded are the U.S. dollar (USD), Canadian dollar (CAD), euro (EUR), British pound (GBP), Swiss franc (CHF), New Zealand dollar (NZD), Australian dollar (AUD) and the Japanese yen (JPY). Although nobody would say that currency trading is easy, having far fewer trading options makes trade and portfolio management an easier task.
Risk Management - Many "research" backtests completely ignore risk management. Unfortunately this is generally necessary for brevity in describing the rules of a strategy. In reality we -must- use a risk overlay when trading, otherwise it is extremely likely that we will suffer a substantial loss at some stage. This is not to say that risk management can prevent this entirely, but it certainly makes it less likely!
The market values/prices used to compute the equity or margin requirement in an Interactive account may differ from the price disseminated by exchanges or other market data sources, and may represent Interactive's valuation of the product. Among other things, Interactive may calculate its own index values, Exchange Traded Fund values or derivatives values, and Interactive may value securities or futures or other investment products based on bid price, offer price, last sale price, midpoint or using some other method. Interactive may use a valuation methodology that is more conservative than the marketplace as a whole.
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.
An extremely important requested feature for QSForex has been the ability to backtest over multiple days. Previously the system only supported backtesting via a single file. This was not a scalable solution as such a file must be read into memory and subsequently into a Pandas DataFrame. While the tick data files produced are not huge (roughly 3.5Mb each), they do add up quickly if we consider multiple pairs over periods of months or more.
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.
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.
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