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.


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.
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.
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).
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.
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.
In a margin account, the broker uses the $1,000 as a security deposit of sorts. If the investor's position worsens and his or her losses approach $1,000, the broker may initiate a margin call. When this occurs, the broker will usually instruct the investor to either deposit more money into the account or to close out the position to limit the risk to both parties.

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.
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).
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).
Have you always dreamed of financial freedom? Maybe you want to start your own business and need a way to supplement the income it brings in. It doesn’t matter what your goals are – Forex trading may be the solution you have been looking for. This high-reward, high-risk market has plenty of opportunities for the patient, insightful investor. You do not need to spend all day researching and watching the market; currency trading only requires you to dedicate a small portion of each day to it, leaving you with more time to spend following your dreams!
Multiple Currency Pairs - Similarly we need to support the major currency pairs beyond "Cable" (GBP/USD). There are two aspects to this. The first is to correctly handle the calculations when neither the base or quote of a currency pair is equal to the account denomination currency. The second aspect is to support multiple positions so that we can trade a portfolio of currency pairs.
Slippage Handling - The system is currently generating a lot of slippage due to the high-frequency nature of the tick data provided from OANDA. This means that the portfolio balance calculated locally is not reflecting the balance calculated by OANDA. Until correct event-handling and slippage adjustment is carried out, this will mean that a backtest will not correctly reflect reality.
Popular leverage ratios in Forex trading include 1:10, 1:50, 1:100, 1:200, or even higher. Simply put, the leverage ratio determines the position size you’re allowed to take based on the size of your trading account. For example, a 1:100 leverage allows you to open a position 10 times higher than your trading account size, i.e., if you have $1,000 in your account, you can open a position worth $10,000. Similarly, a  leverage ratio of 1:100 allows you to open a position size 100 times larger than your trading account size. With $1,000 in your trading account, you could open a position worth $100,000!
GUI Control and Reporting - Right now the system is completely console/command line based. At the very least we will need some basic charting to display backtest results. A more sophisticated system will incorporate summary statistics of trades, strategy-level performance metrics as well as overall portfolio performance. This GUI could be implemented using a cross-platform windowing system such as Qt or Tkinter. It could also be presented using a web-based front-end, utilising a web-framework such as Django.
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.
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