The backtesting process involves simulating that an investment strategy is running live and then evaluating its out-of-sample performance to decide if the strategy is profitable or not. Backtesting is a common practice to test algorithmic trading strategies in a historical period, mainly for single and dual asset strategies. However, in the case of multiassets portfolios, it is not common to see backtesting exercises due to the complexity of the simulation process. This chapter explains three methodologies that can be applied to the multiassets case: the walk-forward method, the cross-validation method, and the combinatorial purged cross-validation method, and then shows examples for each one using Python code.