Algorithmic trading strategies are driven by signals that indicate when to buy or sell assets to generate positive returns relative to a benchmark. The portion of an asset's return that is not explained by exposure to the benchmark is called alpha, and hence these signals are also called alpha factors.
Alpha factors aim to predict the price movements of assets in the investment universe based on the available market, fundamental, or alternative data. A factor may combine one or several input variables, but assumes a single value for each asset every time the strategy evaluates the factor. Trade decisions typically rely on relative values across assets. Trading strategies are often based on signals emitted by multiple factors, and we will see that machine learning (ML) models are particularly well suited to integrate the various signals efficiently to...
