Ten considerations for a backtesting model
In the previous section, we performed one replication of a backtest. Our result looks pretty optimistic. However, is this sufficient to deduce that this is a good model? The truth is that backtesting involves a lot of research that stems a literature on its own. The following list briefly covers some thoughts that you might want to consider when implementing your backtests.
Resources restricting your model
The resources that are available to your backtesting system limits how well you can implement your backtest. A financial model that generates signals using only the last closing price needs a set of historical data of closing prices. A trading system that requires reading from the order book requires all levels of the order book data to be available on every tick. This adds up the storage complexity. Other resources, such as exchange data, estimation techniques, and computer resources pose a limitation on the nature of model that can be used.
