Feature: Backtesting As a Service
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Written by APEXE3HQ
Updated over a week ago

The APEX:E3 backtesting service, currently in development, gives users the ability to test trading strategies based around real-world events. The events-based backtesting system will allow users to map out key events of their choosing on a timeline, including pictures, assets affected, countries affected and dated sub-events more easily than ever before.

In the above example, the recent U.S/Iran geopolitical tension has been mapped out into three sub-events, with the Digital Asset pair ‘BTC/USDT (Bitfinex)’ being tagged as the relevant asset to backtest.

Once this timeline has been established, users can then choose to take positions (buying or selling the chosen asset) around the sub-events. The backtesting platform will then use historical data to calculate the aggregated profit and loss, including exchange fees, if one had used the chosen strategy around the specified events.

The results of this backtest are then displayed in various metrics including ‘max drawdown’, ‘sharpe ratio’ & ‘return on investment’.

So why is any of this useful?

Using backtesting on the APEX:E3 platform in this way, makes it easy for a trader to assess how much of an impact each type of event has on the share price. This information then becomes useful to the trader as they decide what weighting they attribute to the importance of future events.

Although it may be impossible to predict when events will happen, it is still useful for a trader to have some idea of how a market will react after hearing reports of an event that shows similarities to the past.

Of course, it is naive to think that the future will always follow the past, but as time goes on, the Apex:E3 backtesting system will be able to build up a database of past events, which can give traders indications of the effect of incoming news.

The ties between Digital Assets and ‘real-world’ events are not-yet well-established, making it difficult to determine how much of Bitcoin’s volatility can be apportioned to specific events.

However, by performing backtests such as these, we can begin to build up a database of events that appear to affect the price of digital assets, increasing the accuracy of any future predictions.

Click HERE to try the beta version and access real-time digital asset analytics, related news and social media content

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Credit: Stuart Moore

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