Compute gambler’s ruin probabilities and hitting times
Company: Imc
Role: Data Scientist
Category: Machine Learning
Difficulty: medium
Interview Round: Onsite
A gambler plays a sequence of independent bets. Starting wealth is \(i\) dollars, with absorbing boundaries at \(0\) (ruin) and \(N\) (target).
Each round:
- With probability \(p\), wealth increases by 1.
- With probability \(q=1-p\), wealth decreases by 1.
1) Derive the probability \(u_i\) that the gambler reaches \(N\) before 0.
2) Derive the expected number of steps until absorption (hitting either 0 or \(N\)) starting from \(i\).
3) (Random walk follow-up) For the unbiased case \(p=q=1/2\), relate your results to a simple symmetric random walk hitting \(\{0,N\}\).
Quick Answer: This question evaluates understanding of stochastic processes, Markov chains, and discrete-time random walks by requiring derivation of absorption probabilities and expected hitting times in the gambler’s ruin model.