Predicting Stock Market Movements with a Markov‑Chain State‑Transition Model

This article explains how to model short‑term stock market dynamics using a Markov‑chain framework, covering the theory of memoryless state transitions, construction of a transition matrix, multi‑step probability forecasts, steady‑state analysis, a full Python implementation, and a real‑world case study with its limitations.

Markov chainPythonTime Series

0 likes · 18 min read

Predicting Stock Market Movements with a Markov‑Chain State‑Transition Model

Liangxu Linux

Aug 11, 2024 · Fundamentals

Mastering C State Machines: Switch‑Case, Table‑Driven, and Function‑Pointer Techniques

This article explains how to implement finite state machines in C using three classic approaches—switch‑case, table‑driven, and function‑pointer—detailing their structures, code examples, trade‑offs, and safety considerations for embedded and general‑purpose software development.

CFinite State MachineFunction Pointer

0 likes · 18 min read

Mastering C State Machines: Switch‑Case, Table‑Driven, and Function‑Pointer Techniques

Model Perspective

Mar 24, 2024 · Fundamentals

Can a Markov Chain Predict Your Mood? A Simple Model Explained

This article explains how a Markov chain—a memoryless stochastic model—can be used to define, construct, and analyze a simple three‑state mental‑state transition matrix, demonstrating both short‑term predictions and long‑term steady‑state distributions with concrete probability examples.

Markov chainPsychologymood prediction

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Can a Markov Chain Predict Your Mood? A Simple Model Explained