Alpha Generation

Finding alphas involves a systematic approach combining automation, data sourcing, feature computation, and genetic programming.


2/16/20242 min read

person using MacBook Pro
person using MacBook Pro

Capturing Patterns in Price Developments

To understand alpha generation, it is important to first grasp the concept of capturing patterns in price developments. Formulaic alphas are specific trading signals or strategies that aim to exploit these patterns. Traders and researchers analyze historical price data to identify recurring patterns that can be used to predict future price movements. These patterns can range from simple technical indicators to complex statistical models.

The Role of Execution Algorithms

Execution algorithms play a crucial role in alpha generation. Once a trading signal or strategy has been identified, execution algorithms automate the process of executing trades based on predefined rules. These algorithms remove the emotional element from trading decisions and ensure that trades are executed efficiently and consistently. By automating the execution process, traders can take advantage of market opportunities in real-time, without the need for manual intervention.

The Process of Finding Formulaic Alphas

Finding formulaic alphas involves a systematic approach that combines automation, data sourcing, feature computation, and genetic programming. Let's explore each step in detail:

Automation using Evolutionary Algorithms

Evolutionary algorithms are computational methods inspired by the process of natural selection. These algorithms automatically search for profitable trading patterns by iteratively evolving a population of trading strategies. Each strategy is evaluated based on its performance and those with higher returns are selected to reproduce and mutate, creating new generations of strategies. This process continues until a satisfactory trading strategy is found.

Data Sourcing and Feature Computation

To find profitable trading patterns, relevant data must be gathered and analyzed. Traders and researchers source data from various market sources, such as historical price data, fundamental data, and market sentiment data. Once the data is collected, features are computed to capture relevant information for analysis. These features can include technical indicators, statistical measures, and market sentiment scores.

Generating Formulaic Alphas with Evolutionary Algorithms

Once the data is sourced and features are computed, the next step is to generate formulaic alphas using genetic programming. Genetic programming is a subset of evolutionary algorithms that uses a tree-based representation to create trading signals. The algorithm evolves a population of trading signal trees, where each tree represents a trading strategy. The trees are evaluated based on their performance, and the best-performing trees are selected to reproduce and mutate, creating new generations of trading signal trees. This process continues until a profitable trading signal is found.

You might be interested in