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.
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.
There is one unpleasant fact for you to take into consideration about the margin call Forex. You might not even receive the margin call before your positions are liquidated. If the money in your account falls under the margin requirements, your broker will close some or all positions, as we have specified earlier in this article. This can actually help prevent your account from falling into a negative balance.
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).

(Note that the leverage shown in Trades 2 and 3 is available for Professional clients only. A Professional client is a client who possesses the experience, knowledge and expertise to make their own investment decisions and properly assess the risks that these incur. In order to be considered to be Professional client, the client must comply with MiFID ll 2014/65/EU Annex ll requirements.)


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.
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.
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.

Margin requirements for futures and futures options are established by each exchange through a calculation algorithm known as SPAN margining. SPAN (Standard Portfolio Analysis of Risk) evaluates overall portfolio risk by calculating the worst possible loss that a portfolio of derivative and physical instruments might reasonably incur over a specified time period (typically one trading day.) This is done by computing the gains and losses that the portfolio would incur under different market conditions. The most important part of the SPAN methodology is the SPAN risk array, a set of numeric values that indicate how a particular contract will gain or lose value under various conditions. Each condition is called a risk scenario. The numeric value for each risk scenario represents the gain or loss that that particular contract will experience for a particular combination of price (or underlying price) change, volatility change, and decrease in time to expiration.
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).
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.
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. 

In particular I would like to make the system a lot faster, since it will allow parameter searches to be carried out in a reasonable time. While Python is a great tool, it's one drawback is that it is relatively slow when compared to C/C++. Hence I will be carrying out a lot of profiling to try and improve the execution speed of both the backtest and the performance calculations.
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.
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