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).
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!
Risk warning: Trading Forex (foreign exchange) or CFDs (contracts for difference) on margin carries a high level of risk and may not be suitable for all investors. There is a possibility that you may sustain a loss equal to or greater than your entire investment. Therefore, you should not invest or risk money that you cannot afford to lose. Before using Admiral Markets UK Ltd, Admiral Markets Cyprus Ltd or Admiral Markets PTY Ltd services, please acknowledge all of the risks associated with trading.

This material does not contain and should not be construed as containing investment advice, investment recommendations, an offer of or solicitation for any transactions in financial instruments. Please note that such trading analysis is not a reliable indicator for any current or future performance, as circumstances may change over time. Before making any investment decisions, you should seek advice from independent financial advisors to ensure you understand the risks.

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.
Just like securities, commodities have required initial and maintenance margins. These are typically set by the individual exchanges as a percentage of the current value of a futures contract, based on the volatility and price of the contract. The initial margin requirement for a futures contract is the amount of money you must put up as collateral to open position on the contract. To be able to buy a futures contract, you must meet the initial margin requirement, which means that you must deposit or already have that amount of money in your account.

Not all securities can be bought on margin. Buying on margin is a double-edged sword that can translate into bigger gains or bigger losses. In volatile markets, investors who borrowed from their brokers may need to provide additional cash if the price of a stock drops too much for those who bought on margin or rallies too much for those who shorted a stock. In such cases, brokers are also allowed to liquidate a position, even without informing the investor. Real-time position monitoring is a crucial tool when buying on margin or shorting a stock.


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.
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I post this to let you know, as the title mentions it, that I made a trading diary, with google documents tool. This a generic spreadsheet which allows any trader to manage his trading (his risk, his pnl, his opened position, the orders...) with a trding diary. Every trader,should have one, and I mad mine with google docs. At least you must have an account to acces this spreadsheet.
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