+1 (315) 557-6473 

We offer the best stochastic processes homework help service at an affordable price.

Are you looking for a credible and reliable team of experts to guarantee you the best stochastic processes assignment help? You found us. We a big squad of online stochastic processes tutors who work day and night to ensure that students have access to the best solutions. Our services are rooted in originality, accountability, and affordability. What is more, by using our services, you will also enjoy massive discounts. Contact us today and get a free quotation on your assignment. We are here to ensure that you do not spend sleepless nights on your assignments.

The exhaustive list of topics in Stochastic Processes in which we provide Help with Homework Assignment and Help with Project is as follows:

  • Probability Theory Refresher: Axiomatic construction of probability spaces, random variables and vectors, probability distributions, functions of random variables; mathematical expectations, transforms and generating functions, modes of convergence of sequences of random variables, laws of large numbers, central limit theorem.
  • Introduction to Stochastic Processes (SPs): Definition and examples of SPs, classification of random processes according to state space and parameter space, types of SPs, elementary problems.
  • Discrete-time Markov Chains (MCs): Definition and examples of MCs, transition probability matrix, Chapman-Kolmogorov equations; calculation of n-step transition probabilities, limiting probabilities, classification of states, ergodicity, stationary distribution, transient MC; random walk and gambler’s ruin problem, applications.
  • Continuous-time Markov Chains (MCs): Kolmogorov- Feller differential equations, infinitesimal generator, Poisson process, birth-death process, Applications to queueing theory, inventory analysis, communication networks, finance and biology.
  • Brownian Motion: Wiener process as a limit of random walk; first -passage time and other problems, applications to finance.
  • Branching Processes: Definition and examples branching processes, probability generating function, mean and variance, Galton-Watson branching process, probability of extinction.
  • Renewal Processes: Renewal function and its properties, elementary and key renewal theorems, cost/rewards associated with renewals, Markov renewal and regenerative processes, applications.
  • Stationary Processes: Weakly stationary and strongly stationary processes, moving average and auto regressive processes.
  • Martingales: Conditional expectations, definition and examples of martingales, inequality, convergence and smoothing properties, applications in finance.