In recent years, several trading platforms have appeared that provide a backtest engine to calculate the historic performance of self-designed trading strategies on underlying candle data. The construction of an accurate backtest engine is, however, a subtle task, as shown in previous work by Maier-Paape and Platen. Several platforms are struggling to achieve accuracy. We discuss how the accuracy of backtest engines can be verified and provide models for candles and intra-period prices, which may be applied to conduct a “proof of correctness” for a given backtest engine when our tests on specific model candles are successful. Further, we suggest algorithmic considerations in order to allow a fast implementation of the tests necessary for the proof of correctness.