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.
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.
Margin is one of the most important concepts of Forex trading. However, a lot of people don't understand its significance, or simply misunderstand the term. A Forex margin is basically a good faith deposit that is needed to maintain open positions. A margin is not a fee or a transaction cost, but instead, a portion of your account equity set aside and assigned as a margin deposit.
Once an investor has started buying a stock on margin, the NYSE and FINRA require that a minimum amount of equity be maintained in the investor's margin account. These rules require investors to have at least 25% of the total market value of the securities they own in their margin account. This is called the maintenance margin. For market participants identified as pattern day traders, the maintenance margin requirement is a minimum of $25,000 (or 25% of the total market value of the securities, whichever is higher).
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 […]
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.
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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.
Forex margin is a good faith deposit that a trader puts up as collateral to initiate a trade. Essentially, it is the minimum amount that a trader needs in the trading account to open a new position. This is usually communicated as a percentage of the notional value (trade size) of the forex trade. The difference between the deposit and the full value of the trade is “borrowed” from the broker.
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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.
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.
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.
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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.
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.