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Expected Time to Absorption | Markov Chains | Stochastic Processes

In this video, we explore the concept of expected time to absorption within the framework of discrete-time Markov chains, a fundamental topic in stochastic processes and quantitative finance. Building on prior understanding of state transitions and absorbing states, this session introduces methods for calculating how long it takes, on average, for a process to be absorbed.

We begin by identifying absorbing and transient states in a Markov chain, then formulate systems of linear equations based on transition probabilities to compute the expected number of steps before absorption. You'll learn how to construct the fundamental matrix, interpret its entries, and apply these tools to real-world contexts.

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Note: These are revisionary lectures meant to provide an overview before diving into the textbooks for a more in-depth understanding.

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