The "philosophy" of the forex trading system, as with the rest of the QuantStart site, is to try and mimic real-life trading as much as possible in our backtesting. This means including the details that are often excluded from more "research oriented" backtesting situations. Latency, server outages, automation, monitoring, realistic transaction costs will all be included within the models to give us a good idea of how well a strategy is likely to perform.
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Systems that derive risk-based margin requirements deliver adequate assessments of the risk for complex derivative portfolios under small/moderate move scenarios. Such systems are less comprehensive when considering large moves in the price of the underlying stock or future. We have enhanced the basic exchange margin models with algorithms that consider the portfolio impact of larger moves up 30% (or even higher for extremely volatile stocks). This 'Extreme Margin Model' may increase the margin requirement for portfolios with net short options positions, and is particularly sensitive to short positions in far out-of-the-money options.
Now that we have discussed the longer term plan I want to present some of the changes I have made to the code since diary entry #2. In particular, I want to describe how I modified the code to handle the Decimal data-type instead of using floating point storage. This is an extremely important change as floating point representations are a substantial source of long-term error in portfolio and order management systems.
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.
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).
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.
Trading on margin is extremely popular among retail Forex traders. It allows you to open a much larger position than your initial trading account would otherwise allow, by allocating only a small portion of your trading account as the margin, or collateral for the trade. Trading on margin also carries certain risks, as both your profits and losses are magnified.
Trading on a margin can have varying consequences. It can influence your trading experience both positively and negatively, with both profits and losses potentially being seriously augmented. Your broker takes your margin deposit and then pools it with someone else's margin Forex deposits. Brokers do this in order to be able to place trades within the whole interbank network.