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).

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.


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.

Monitoring and High Availability - Since we are considering a high-frequency intraday system, we must put comprehensive monitoring and high availability redundancy in place. This means reporting on CPU usage, disk usage, network I/O, latency and checking that any periodic scripts are set to keep running. In addition we need a backup and restore strategy. Ask yourself what backup plans you would have in place if you had large open positions, in a volatile market, and your server suddenly died. Believe me, it happens!
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.
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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.
In particular we will need strategy level metrics, including common risk/reward ratios such as the Sharpe Ratio, Information Ratio and Sortino Ratio. We will also need drawdown statistics including the distribution of the drawdowns, as well as descriptive stats such as maximum drawdown. Other useful metrics include the Compound Annual Growth Rate (CAGR) and total return.

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.
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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