Stochastic Processes Cycle Review
Stochastic processes cycle review for quant interviews, covering Markov chains, random walks, Poisson processes, martingales, and hitting problems.
Candidates consolidating stochastic process interview basics.
Review process setup
For any stochastic process prompt, define state, time index, transition or update rule, starting condition, and target quantity before doing algebra.
Review Markov and arrival models
Markov chains, transition matrices, stationary distributions, absorbing states, Poisson processes, exponential waits, and queues are common interview patterns.
Review hitting and stopping problems
Random walks, gambler’s ruin, first passage times, hitting probabilities, and stopping times all reward clean boundary conditions and careful information timing.
Concrete final drill
Take one bounded random walk and identify states, boundaries, transition probabilities, absorption probability, expected time, and how you would simulate it.
Common mistakes
Candidates often start with formulas. The better interview habit is setup first: state space, assumptions, boundary conditions, and then the calculation.
Practice the pattern
Use the LeetQuidity curriculum and calibration to turn this topic into a focused practice plan.