Stock Prices: Predictable Patterns or Pure Chance?
Author(s): Shenggang Li
Originally published on Towards AI.
Statistical Analysis of Stock Market Trends Across Bull and Bear Phases, Uncovering When and How Market Conditions Shape Predictability
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Are stock prices truly random, or do hidden patterns surface under certain conditions? Traditional finance says stock prices follow a random walk — unpredictable and tough to forecast. But does this randomness hold in every scenario? Could specific conditions reveal trends?
I’ll dig into stock data from the health, energy, and tech sectors, examining randomness across various market phases — from bear to bull. Does a tech stock act differently in a bull market than energy in a downturn? And can we measure that?
This isn’t just theory. Knowing when stocks show patterns can give traders and analysts a real edge, showing when to rely on trends versus randomness. Using statistical tests and data segmentation, I’ll work to pinpoint where stocks deviate from a random walk, offering insights for strategies across investment and arbitrage.
A “random walk” is a sequence where each step is independent of the last. Imagine a stock price that takes a step up, down, or stays level purely by chance — there’s no pattern. In the simplest form, we can define this as:
where S_t is the stock price at time t, and ϵ_t… Read the full blog for free on Medium.
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Note: Article content contains the views of the contributing authors and not Towards AI.
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