How deeply does Investing for Programmers cover random walk?

Explains randomness through market psychology and interconnected markets, but stops short of formal stochastic-process mathematics.

Random walk

As explained in Investing for Programmers

A random walk is a stochastic process whose successive movements are determined by random variation rather than a predictable directional pattern.

A random walk describes movement that does not follow deterministic rules. In financial markets, stock prices may show chaotic behavior and lack dependable patterns. section 8.1.3

This view limits what machine learning can infer from historical price data. Global market interactions and mass psychology make prediction more complex and can turn apparently analytical forecasts into speculation. section 8.1.3 section 8.0

Market prediction

The Mr. Market allegory illustrates emotionally unstable price movements, while irrational exuberance and tulip mania show how collective optimism can produce bubbles. section 8.1.3

How Investing for Programmers covers it

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Also explained in

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Graph Neural Networks in ActionA random walk is a stochastic traversal of a graph that repeatedly moves from a node to one of its connected neighbors according to transition probabilities.
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Graph Algorithms for Data ScienceA random walk is a stochastic graph traversal that repeatedly moves from the current node to a neighboring node according to transition probabilities.

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Related concepts

Node2Vecused by · Node2Vec is a graph representation-learning algorithm that learns node embeddings from biased random walks and their context relationships.
corpusproduces · A corpus is an organized collection of documents, texts, or other language data assembled for processing, retrieval, analysis, training, or evaluation.
encoder-decoder architectureimplements · An encoder-decoder architecture is a model design in which an encoder transforms input into an intermediate representation and a decoder uses that representation to produce output.
second-order biased random walkincludes · A second-order biased random walk chooses its next node using both the current node and the node visited immediately before it.

This explainer was generated by Manning's knowledge graph from the text of Investing for Programmers. The section links point to the parts of the book it draws on.