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

Kuaishou Audio & Video Technology

Oct 14, 2022 · Artificial Intelligence

How Probability-Driven Adaptive Streaming Won the ACM MM 2022 Grand Challenge

The Kuaishou audio‑video team’s PDAS algorithm, a probability‑driven adaptive streaming solution for short videos, achieved first place at ACM MM 2022 by modeling user behavior, optimizing pre‑load decisions, and delivering superior QoE while minimizing bandwidth waste.

ACM MM 2022QoE optimizationadaptive streaming

0 likes · 12 min read

How Probability-Driven Adaptive Streaming Won the ACM MM 2022 Grand Challenge