Financial markets are often described as random. Millions of participants, different strategies, emotions and unexpected information make the next price movement inherently uncertain. But random does not necessarily mean independent.
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More than a century ago, mathematician Andrey Markov demonstrated that random events can depend on previous states while still following measurable statistical patterns. This idea became the foundation of Markov chains.
In our new video, we take this concept from its origins in probability theory to modern financial markets. We explore market memory, transition probabilities and market regimes — and ask whether knowing the current state of the market can tell us something about the probabilities of what comes next.
The objective is not to predict the next move. It is to understand how the odds change when the market regime changes.