Backtesting is a standard tool in the development of trading strategies on the financial market, however, it is often underutilized in energy trading. There are good reasons for this, and yet backtesting should not be completely ignored. Why? A brief assessment.
Backtesting is carried out to evaluate and test new ideas and strategies. Wikipedia says: "Backtesting is the process of evaluating a strategy, theory, or model by applying the strategy, theory, or model to historical data."
That is to say, the strategy is provided with the data it needs from what was already available/known at a point in the past. From there, data is added for the future with respect to how it may occur in reality. From this, the strategy decides in the same way as it would have done in the corresponding historical situation. For example, orders can be executed directly or own orders can be set. The aim is to reproduce the real conditions as realistically as possible. The results of the strategy actions are then evaluated; in this way, for example, one can compare financial benchmarks with the results of other strategies.
Backtesting is based on the assumption that the future will behave similarly to the past. For individual days, this statement is obviously wrong because every day is different. Therefore, it is important to simulate as large a time period as possible when backtesting. In contrast to the financial market, the electricity market changes very quickly - be it due to changes in regulations and market conditions (examples are the introduction of xbid/sidc, sdat or the standard labour market) or due to changes in the market/the market participants (increase in renewables, shutdown of nuclear power plants, changes in strategies/digitisation). Therefore, older data quickly becomes unrepresentative. It is not always easy to find a suitable trade-off here.
Especially for the marketing of EEG quantities, it is important that the traded quantities match the corresponding day that is simulated. Since the forecast deviations are similar for all marketers, we speak of market-correlated quantities: if you have to sell, everyone else has to sell too - and vice versa. So, to test one's strategy, real forecast deviations should be simulated with the matching days.
Backtesting is a simulation with "outdated" data. This leads to the following difficulties:
So, what do I need to consider in order to benefit from the advantages of backtesting in electricity trading?
Backtesting never delivers the one truth, but it can help to validate and improve one's own strategies. At the same time, the entry hurdle is high, because in addition to the data, software is needed to synchronously merge the information and simulate the market accordingly. Therefore, in iTrade we have tried to offer our users the easiest possible access to backtesting while maintaining the necessary flexibility. Backtesting in iTrade can be fully controlled via the UI. In doing so, we offer the following parameters to ensure the most comprehensive, simple and flexible handling possible:
Those who do not want to use the UI here can create the strategies and jobs directly in the database. This provides a higher level of automation and the user can even set up automated parameter tuning. And to counteract the limitations mentioned above, iTrade also recognises iceberg orders in the order book in backtesting and is able to convert own trades into orders. In this way, one's own influence on the market is better taken into account.